diff --git a/apis.json b/apis.json index 0073c5d2ef..e54c1a83d0 100644 --- a/apis.json +++ b/apis.json @@ -2,6 +2,36 @@ "kind": "discovery#directoryList", "discoveryVersion": "v1", "items": [ + { + "kind": "discovery#directoryItem", + "id": "aiplatform:v1", + "name": "aiplatform", + "version": "v1", + "title": "Vertex AI API", + "description": "Train high-quality custom machine learning models with minimal machine learning expertise and effort.", + "discoveryRestUrl": "https://aiplatform.googleapis.com/$discovery/rest?version=v1", + "icons": { + "x16": "http://www.google.com/images/icons/product/search-16.gif", + "x32": "http://www.google.com/images/icons/product/search-32.gif" + }, + "documentationLink": "https://cloud.google.com/vertex-ai/", + "preferred": true + }, + { + "kind": "discovery#directoryItem", + "id": "aiplatform:v1beta1", + "name": "aiplatform", + "version": "v1", + "title": "Vertex AI API", + "description": "Train high-quality custom machine learning models with minimal machine learning expertise and effort.", + "discoveryRestUrl": "https://aiplatform.googleapis.com/$discovery/rest?version=v1beta1", + "icons": { + "x16": "http://www.google.com/images/icons/product/search-16.gif", + "x32": "http://www.google.com/images/icons/product/search-32.gif" + }, + "documentationLink": "https://cloud.google.com/vertex-ai/", + "preferred": false + }, { "kind": "discovery#directoryItem", "id": "walletobjects:v1", diff --git a/etc/api/aiplatform/v1/aiplatform-api.json b/etc/api/aiplatform/v1/aiplatform-api.json new file mode 100644 index 0000000000..99940c2b89 --- /dev/null +++ b/etc/api/aiplatform/v1/aiplatform-api.json @@ -0,0 +1,38926 @@ +{ + "description": "Train high-quality custom machine learning models with minimal machine learning expertise and effort.", + "canonicalName": "Aiplatform", + "servicePath": "", + "batchPath": "batch", + "kind": "discovery#restDescription", + "ownerName": "Google", + "id": "aiplatform:v1", + "rootUrl": "https://aiplatform.googleapis.com/", + "basePath": "", + "resources": { + "projects": { + "resources": { + "locations": { + "methods": { + "list": { + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleCloudLocationListLocationsResponse" + }, + "description": "Lists information about the supported locations for this service.", + "path": "v1/{+name}/locations", + "id": "aiplatform.projects.locations.list", + "flatPath": "v1/projects/{projectsId}/locations", + "httpMethod": "GET", + "parameters": { + "pageSize": { + "type": "integer", + "location": "query", + "description": "The maximum number of results to return. If not set, the service selects a default.", + "format": "int32" + }, + "pageToken": { + "type": "string", + "description": "A page token received from the `next_page_token` field in the response. Send that page token to receive the subsequent page.", + "location": "query" + }, + "filter": { + "location": "query", + "description": "A filter to narrow down results to a preferred subset. The filtering language accepts strings like `\"displayName=tokyo\"`, and is documented in more detail in [AIP-160](https://google.aip.dev/160).", + "type": "string" + }, + "name": { + "description": "The resource that owns the locations collection, if applicable.", + "pattern": "^projects/[^/]+$", + "required": true, + "type": "string", + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "get": { + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "description": "Resource name for the location.", + "required": true + } + }, + "description": "Gets information about a location.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}", + "path": "v1/{+name}", + "response": { + "$ref": "GoogleCloudLocationLocation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "id": "aiplatform.projects.locations.get", + "parameterOrder": [ + "name" + ] + }, + "evaluateInstances": { + "id": "aiplatform.projects.locations.evaluateInstances", + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1EvaluateInstancesRequest" + }, + "path": "v1/{+location}:evaluateInstances", + "response": { + "$ref": "GoogleCloudAiplatformV1EvaluateInstancesResponse" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}:evaluateInstances", + "parameterOrder": [ + "location" + ], + "parameters": { + "location": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location to evaluate the instances. Format: `projects/{project}/locations/{location}`", + "required": true, + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Evaluates instances based on a given metric." + } + }, + "resources": { + "dataLabelingJobs": { + "resources": { + "operations": { + "methods": { + "delete": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string", + "required": true, + "description": "The name of the operation resource to be deleted." + } + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.dataLabelingJobs.operations.delete", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}" + }, + "wait": { + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}:wait", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string", + "location": "query", + "format": "google-duration" + }, + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string", + "description": "The name of the operation resource to wait on." + } + }, + "id": "aiplatform.projects.locations.dataLabelingJobs.operations.wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}:wait" + }, + "cancel": { + "httpMethod": "POST", + "path": "v1/{+name}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}:cancel", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+/operations/[^/]+$", + "type": "string", + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "required": true + } + }, + "id": "aiplatform.projects.locations.dataLabelingJobs.operations.cancel" + }, + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "filter": { + "description": "The standard list filter.", + "location": "query", + "type": "string" + }, + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+$", + "description": "The name of the operation's parent resource.", + "required": true, + "location": "path" + }, + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + }, + "pageSize": { + "format": "int32", + "description": "The standard list page size.", + "location": "query", + "type": "integer" + } + }, + "id": "aiplatform.projects.locations.dataLabelingJobs.operations.list", + "httpMethod": "GET", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}/operations", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + } + }, + "get": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "type": "string", + "description": "The name of the operation resource." + } + }, + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "httpMethod": "GET", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.dataLabelingJobs.operations.get" + } + } + } + }, + "methods": { + "delete": { + "parameterOrder": [ + "name" + ], + "description": "Deletes a DataLabelingJob.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}", + "httpMethod": "DELETE", + "path": "v1/{+name}", + "parameters": { + "name": { + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+$", + "description": "Required. The name of the DataLabelingJob to be deleted. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}`", + "location": "path" + } + }, + "id": "aiplatform.projects.locations.dataLabelingJobs.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "list": { + "id": "aiplatform.projects.locations.dataLabelingJobs.list", + "path": "v1/{+parent}/dataLabelingJobs", + "httpMethod": "GET", + "description": "Lists DataLabelingJobs in a Location.", + "parameterOrder": [ + "parent" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs", + "parameters": { + "filter": { + "location": "query", + "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`", + "type": "string" + }, + "parent": { + "required": true, + "location": "path", + "type": "string", + "description": "Required. The parent of the DataLabelingJob. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$" + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token." + }, + "orderBy": { + "location": "query", + "type": "string", + "description": "A comma-separated list of fields to order by, sorted in ascending order by default. Use `desc` after a field name for descending." + }, + "pageSize": { + "format": "int32", + "location": "query", + "type": "integer", + "description": "The standard list page size." + }, + "readMask": { + "type": "string", + "location": "query", + "description": "Mask specifying which fields to read. FieldMask represents a set of symbolic field paths. For example, the mask can be `paths: \"name\"`. The \"name\" here is a field in DataLabelingJob. If this field is not set, all fields of the DataLabelingJob are returned.", + "format": "google-fieldmask" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1ListDataLabelingJobsResponse" + } + }, + "get": { + "parameters": { + "name": { + "description": "Required. The name of the DataLabelingJob. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}`", + "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+$", + "location": "path", + "required": true, + "type": "string" + } + }, + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}", + "description": "Gets a DataLabelingJob.", + "id": "aiplatform.projects.locations.dataLabelingJobs.get", + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1DataLabelingJob" + } + }, + "cancel": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}:cancel", + "parameters": { + "name": { + "location": "path", + "required": true, + "description": "Required. The name of the DataLabelingJob. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+$" + } + }, + "path": "v1/{+name}:cancel", + "id": "aiplatform.projects.locations.dataLabelingJobs.cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1CancelDataLabelingJobRequest" + }, + "description": "Cancels a DataLabelingJob. Success of cancellation is not guaranteed.", + "parameterOrder": [ + "name" + ], + "httpMethod": "POST" + }, + "create": { + "id": "aiplatform.projects.locations.dataLabelingJobs.create", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "response": { + "$ref": "GoogleCloudAiplatformV1DataLabelingJob" + }, + "parameters": { + "parent": { + "description": "Required. The parent of the DataLabelingJob. Format: `projects/{project}/locations/{location}`", + "required": true, + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs", + "request": { + "$ref": "GoogleCloudAiplatformV1DataLabelingJob" + }, + "parameterOrder": [ + "parent" + ], + "path": "v1/{+parent}/dataLabelingJobs", + "description": "Creates a DataLabelingJob." + } + } + }, + "notebookExecutionJobs": { + "methods": { + "create": { + "path": "v1/{+parent}/notebookExecutionJobs", + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs", + "id": "aiplatform.projects.locations.notebookExecutionJobs.create", + "parameters": { + "parent": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "required": true, + "description": "Required. The resource name of the Location to create the NotebookExecutionJob. Format: `projects/{project}/locations/{location}`" + }, + "notebookExecutionJobId": { + "type": "string", + "location": "query", + "description": "Optional. User specified ID for the NotebookExecutionJob." + } + }, + "description": "Creates a NotebookExecutionJob.", + "request": { + "$ref": "GoogleCloudAiplatformV1NotebookExecutionJob" + }, + "httpMethod": "POST" + }, + "delete": { + "description": "Deletes a NotebookExecutionJob.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.notebookExecutionJobs.delete", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "DELETE", + "path": "v1/{+name}", + "parameters": { + "name": { + "description": "Required. The name of the NotebookExecutionJob resource to be deleted.", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+$", + "location": "path" + } + } + }, + "list": { + "response": { + "$ref": "GoogleCloudAiplatformV1ListNotebookExecutionJobsResponse" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs", + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "path": "v1/{+parent}/notebookExecutionJobs", + "parameters": { + "view": { + "location": "query", + "enum": [ + "NOTEBOOK_EXECUTION_JOB_VIEW_UNSPECIFIED", + "NOTEBOOK_EXECUTION_JOB_VIEW_BASIC", + "NOTEBOOK_EXECUTION_JOB_VIEW_FULL" + ], + "enumDescriptions": [ + "When unspecified, the API defaults to the BASIC view.", + "Includes all fields except for direct notebook inputs.", + "Includes all fields." + ], + "description": "Optional. The NotebookExecutionJob view. Defaults to BASIC.", + "type": "string" + }, + "filter": { + "location": "query", + "type": "string", + "description": "Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `notebookExecutionJob` supports = and !=. `notebookExecutionJob` represents the NotebookExecutionJob ID. * `displayName` supports = and != and regex. * `schedule` supports = and != and regex. Some examples: * `notebookExecutionJob=\"123\"` * `notebookExecutionJob=\"my-execution-job\"` * `displayName=\"myDisplayName\"` and `displayName=~\"myDisplayNameRegex\"`" + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "description": "Required. The resource name of the Location from which to list the NotebookExecutionJobs. Format: `projects/{project}/locations/{location}`", + "required": true, + "type": "string" + }, + "pageSize": { + "location": "query", + "type": "integer", + "description": "Optional. The standard list page size.", + "format": "int32" + }, + "orderBy": { + "type": "string", + "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`.", + "location": "query" + }, + "pageToken": { + "description": "Optional. The standard list page token. Typically obtained via ListNotebookExecutionJobs.next_page_token of the previous NotebookService.ListNotebookExecutionJobs call.", + "location": "query", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.notebookExecutionJobs.list", + "description": "Lists NotebookExecutionJobs in a Location." + }, + "get": { + "id": "aiplatform.projects.locations.notebookExecutionJobs.get", + "description": "Gets a NotebookExecutionJob.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}", + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "httpMethod": "GET", + "parameters": { + "name": { + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+$", + "description": "Required. The name of the NotebookExecutionJob resource." + }, + "view": { + "enum": [ + "NOTEBOOK_EXECUTION_JOB_VIEW_UNSPECIFIED", + "NOTEBOOK_EXECUTION_JOB_VIEW_BASIC", + "NOTEBOOK_EXECUTION_JOB_VIEW_FULL" + ], + "description": "Optional. The NotebookExecutionJob view. Defaults to BASIC.", + "enumDescriptions": [ + "When unspecified, the API defaults to the BASIC view.", + "Includes all fields except for direct notebook inputs.", + "Includes all fields." + ], + "type": "string", + "location": "query" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1NotebookExecutionJob" + } + } + }, + "resources": { + "operations": { + "methods": { + "cancel": { + "path": "v1/{+name}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}:cancel", + "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.cancel", + "httpMethod": "POST", + "parameters": { + "name": { + "required": true, + "type": "string", + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+/operations/[^/]+$", + "location": "path" + } + }, + "parameterOrder": [ + "name" + ] + }, + "wait": { + "path": "v1/{+name}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.wait", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}:wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "parameters": { + "name": { + "location": "path", + "description": "The name of the operation resource to wait on.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+/operations/[^/]+$", + "required": true + }, + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "type": "string", + "format": "google-duration" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "delete": { + "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "description": "The name of the operation resource to be deleted.", + "type": "string", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+/operations/[^/]+$" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." + }, + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations", + "httpMethod": "GET", + "path": "v1/{+name}/operations", + "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.list", + "parameters": { + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "name": { + "required": true, + "type": "string", + "description": "The name of the operation's parent resource.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+$" + }, + "pageToken": { + "description": "The standard list page token.", + "location": "query", + "type": "string" + }, + "pageSize": { + "location": "query", + "format": "int32", + "description": "The standard list page size.", + "type": "integer" + } + }, + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." + }, + "get": { + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "httpMethod": "GET", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+/operations/[^/]+$", + "type": "string", + "description": "The name of the operation resource.", + "required": true, + "location": "path" + } + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.get" + } + } + } + } + }, + "trainingPipelines": { + "resources": { + "operations": { + "methods": { + "cancel": { + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+/operations/[^/]+$" + } + }, + "httpMethod": "POST", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.trainingPipelines.operations.cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "path": "v1/{+name}:cancel" + }, + "list": { + "id": "aiplatform.projects.locations.trainingPipelines.operations.list", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}/operations", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations", + "httpMethod": "GET", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "parameters": { + "name": { + "type": "string", + "description": "The name of the operation's parent resource.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+$", + "required": true + }, + "pageSize": { + "location": "query", + "type": "integer", + "format": "int32", + "description": "The standard list page size." + }, + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + }, + "filter": { + "description": "The standard list filter.", + "location": "query", + "type": "string" + } + }, + "parameterOrder": [ + "name" + ] + }, + "wait": { + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string", + "format": "google-duration", + "location": "query" + }, + "name": { + "description": "The name of the operation resource to wait on.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+/operations/[^/]+$", + "required": true, + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}:wait", + "id": "aiplatform.projects.locations.trainingPipelines.operations.wait", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}:wait" + }, + "get": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.trainingPipelines.operations.get", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameters": { + "name": { + "description": "The name of the operation resource.", + "required": true, + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+/operations/[^/]+$" + } + } + }, + "delete": { + "httpMethod": "DELETE", + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.trainingPipelines.operations.delete", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "required": true, + "location": "path", + "type": "string", + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+/operations/[^/]+$" + } + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." + } + } + } + }, + "methods": { + "create": { + "response": { + "$ref": "GoogleCloudAiplatformV1TrainingPipeline" + }, + "path": "v1/{+parent}/trainingPipelines", + "request": { + "$ref": "GoogleCloudAiplatformV1TrainingPipeline" + }, + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.trainingPipelines.create", + "parameterOrder": [ + "parent" + ], + "parameters": { + "parent": { + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string", + "description": "Required. The resource name of the Location to create the TrainingPipeline in. Format: `projects/{project}/locations/{location}`" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines", + "description": "Creates a TrainingPipeline. A created TrainingPipeline right away will be attempted to be run." + }, + "cancel": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}:cancel", + "description": "Cancels a TrainingPipeline. Starts asynchronous cancellation on the TrainingPipeline. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use PipelineService.GetTrainingPipeline or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the TrainingPipeline is not deleted; instead it becomes a pipeline with a TrainingPipeline.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and TrainingPipeline.state is set to `CANCELLED`.", + "request": { + "$ref": "GoogleCloudAiplatformV1CancelTrainingPipelineRequest" + }, + "httpMethod": "POST", + "parameters": { + "name": { + "type": "string", + "description": "Required. The name of the TrainingPipeline to cancel. Format: `projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}`", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+$" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.trainingPipelines.cancel", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}:cancel" + }, + "get": { + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.trainingPipelines.get", + "response": { + "$ref": "GoogleCloudAiplatformV1TrainingPipeline" + }, + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+$", + "location": "path", + "required": true, + "type": "string", + "description": "Required. The name of the TrainingPipeline resource. Format: `projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}`" + } + }, + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets a TrainingPipeline.", + "httpMethod": "GET" + }, + "delete": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}", + "description": "Deletes a TrainingPipeline.", + "path": "v1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.trainingPipelines.delete", + "parameters": { + "name": { + "description": "Required. The name of the TrainingPipeline resource to be deleted. Format: `projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+$", + "type": "string", + "location": "path" + } + } + }, + "list": { + "id": "aiplatform.projects.locations.trainingPipelines.list", + "description": "Lists TrainingPipelines in a Location.", + "parameterOrder": [ + "parent" + ], + "httpMethod": "GET", + "path": "v1/{+parent}/trainingPipelines", + "parameters": { + "readMask": { + "format": "google-fieldmask", + "location": "query", + "description": "Mask specifying which fields to read.", + "type": "string" + }, + "pageSize": { + "type": "integer", + "location": "query", + "format": "int32", + "description": "The standard list page size." + }, + "parent": { + "description": "Required. The resource name of the Location to list the TrainingPipelines from. Format: `projects/{project}/locations/{location}`", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path" + }, + "filter": { + "type": "string", + "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `training_task_definition` `=`, `!=` comparisons, and `:` wildcard. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"PIPELINE_STATE_SUCCEEDED\" AND display_name:\"my_pipeline_*\"` * `state!=\"PIPELINE_STATE_FAILED\" OR display_name=\"my_pipeline\"` * `NOT display_name=\"my_pipeline\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `training_task_definition:\"*automl_text_classification*\"`", + "location": "query" + }, + "pageToken": { + "description": "The standard list page token. Typically obtained via ListTrainingPipelinesResponse.next_page_token of the previous PipelineService.ListTrainingPipelines call.", + "location": "query", + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines", + "response": { + "$ref": "GoogleCloudAiplatformV1ListTrainingPipelinesResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + } + } + }, + "indexes": { + "resources": { + "operations": { + "methods": { + "get": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameters": { + "name": { + "type": "string", + "description": "The name of the operation resource.", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+/operations/[^/]+$" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.indexes.operations.get", + "httpMethod": "GET", + "parameterOrder": [ + "name" + ] + }, + "cancel": { + "path": "v1/{+name}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations/{operationsId}:cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.indexes.operations.cancel", + "httpMethod": "POST", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+/operations/[^/]+$", + "type": "string", + "required": true, + "location": "path", + "description": "The name of the operation resource to be cancelled." + } + } + }, + "list": { + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "path": "v1/{+name}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + }, + "name": { + "type": "string", + "location": "path", + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", + "required": true + }, + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter." + }, + "pageSize": { + "format": "int32", + "location": "query", + "type": "integer", + "description": "The standard list page size." + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations", + "id": "aiplatform.projects.locations.indexes.operations.list", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "GET" + }, + "wait": { + "parameters": { + "timeout": { + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string", + "format": "google-duration" + }, + "name": { + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource to wait on." + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations/{operationsId}:wait", + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.indexes.operations.wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}:wait" + }, + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+/operations/[^/]+$", + "required": true, + "type": "string", + "description": "The name of the operation resource to be deleted.", + "location": "path" + } + }, + "id": "aiplatform.projects.locations.indexes.operations.delete", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations/{operationsId}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." + } + } + } + }, + "methods": { + "delete": { + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "parameters": { + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", + "description": "Required. The name of the Index resource to be deleted. Format: `projects/{project}/locations/{location}/indexes/{index}`", + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.indexes.delete", + "description": "Deletes an Index. An Index can only be deleted when all its DeployedIndexes had been undeployed." + }, + "upsertDatapoints": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Add/update Datapoints into an Index.", + "httpMethod": "POST", + "path": "v1/{+index}:upsertDatapoints", + "request": { + "$ref": "GoogleCloudAiplatformV1UpsertDatapointsRequest" + }, + "parameterOrder": [ + "index" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}:upsertDatapoints", + "id": "aiplatform.projects.locations.indexes.upsertDatapoints", + "parameters": { + "index": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", + "type": "string", + "description": "Required. The name of the Index resource to be updated. Format: `projects/{project}/locations/{location}/indexes/{index}`", + "location": "path" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1UpsertDatapointsResponse" + } + }, + "patch": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1Index" + }, + "id": "aiplatform.projects.locations.indexes.patch", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}", + "parameters": { + "updateMask": { + "format": "google-fieldmask", + "location": "query", + "description": "The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask.", + "type": "string" + }, + "name": { + "type": "string", + "location": "path", + "description": "Output only. The resource name of the Index.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$" + } + }, + "path": "v1/{+name}", + "description": "Updates an Index.", + "parameterOrder": [ + "name" + ], + "httpMethod": "PATCH", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "removeDatapoints": { + "path": "v1/{+index}:removeDatapoints", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}:removeDatapoints", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "index" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1RemoveDatapointsRequest" + }, + "response": { + "$ref": "GoogleCloudAiplatformV1RemoveDatapointsResponse" + }, + "description": "Remove Datapoints from an Index.", + "parameters": { + "index": { + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", + "required": true, + "description": "Required. The name of the Index resource to be updated. Format: `projects/{project}/locations/{location}/indexes/{index}`", + "type": "string", + "location": "path" + } + }, + "id": "aiplatform.projects.locations.indexes.removeDatapoints", + "httpMethod": "POST" + }, + "create": { + "description": "Creates an Index.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1Index" + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.indexes.create", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes", + "path": "v1/{+parent}/indexes", + "httpMethod": "POST", + "parameters": { + "parent": { + "description": "Required. The resource name of the Location to create the Index in. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string", + "location": "path", + "required": true + } + } + }, + "get": { + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", + "type": "string", + "description": "Required. The name of the Index resource. Format: `projects/{project}/locations/{location}/indexes/{index}`", + "required": true + } + }, + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1Index" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}", + "description": "Gets an Index.", + "id": "aiplatform.projects.locations.indexes.get" + }, + "list": { + "parameterOrder": [ + "parent" + ], + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1ListIndexesResponse" + }, + "description": "Lists Indexes in a Location.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes", + "path": "v1/{+parent}/indexes", + "parameters": { + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + }, + "pageSize": { + "type": "integer", + "description": "The standard list page size.", + "format": "int32", + "location": "query" + }, + "parent": { + "required": true, + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location from which to list the Indexes. Format: `projects/{project}/locations/{location}`" + }, + "readMask": { + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask", + "type": "string", + "location": "query" + }, + "pageToken": { + "location": "query", + "description": "The standard list page token. Typically obtained via ListIndexesResponse.next_page_token of the previous IndexService.ListIndexes call.", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.indexes.list" + } + } + }, + "studies": { + "resources": { + "trials": { + "methods": { + "listOptimalTrials": { + "id": "aiplatform.projects.locations.studies.trials.listOptimalTrials", + "description": "Lists the pareto-optimal Trials for multi-objective Study or the optimal Trials for single-objective Study. The definition of pareto-optimal can be checked in wiki page. https://en.wikipedia.org/wiki/Pareto_efficiency", + "parameterOrder": [ + "parent" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1ListOptimalTrialsResponse" + }, + "path": "v1/{+parent}/trials:listOptimalTrials", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials:listOptimalTrials", + "request": { + "$ref": "GoogleCloudAiplatformV1ListOptimalTrialsRequest" + }, + "parameters": { + "parent": { + "type": "string", + "location": "path", + "description": "Required. The name of the Study that the optimal Trial belongs to.", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", + "required": true + } + } + }, + "stop": { + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1StopTrialRequest" + }, + "id": "aiplatform.projects.locations.studies.trials.stop", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}:stop", + "path": "v1/{+name}:stop", + "response": { + "$ref": "GoogleCloudAiplatformV1Trial" + }, + "description": "Stops a Trial.", + "parameters": { + "name": { + "required": true, + "type": "string", + "description": "Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "addTrialMeasurement": { + "parameters": { + "trialName": { + "location": "path", + "description": "Required. The name of the trial to add measurement. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Adds a measurement of the objective metrics to a Trial. This measurement is assumed to have been taken before the Trial is complete.", + "httpMethod": "POST", + "id": "aiplatform.projects.locations.studies.trials.addTrialMeasurement", + "path": "v1/{+trialName}:addTrialMeasurement", + "response": { + "$ref": "GoogleCloudAiplatformV1Trial" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}:addTrialMeasurement", + "request": { + "$ref": "GoogleCloudAiplatformV1AddTrialMeasurementRequest" + }, + "parameterOrder": [ + "trialName" + ] + }, + "get": { + "response": { + "$ref": "GoogleCloudAiplatformV1Trial" + }, + "description": "Gets a Trial.", + "id": "aiplatform.projects.locations.studies.trials.get", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", + "description": "Required. The name of the Trial resource. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", + "type": "string", + "required": true, + "location": "path" + } + }, + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "create": { + "path": "v1/{+parent}/trials", + "description": "Adds a user provided Trial to a Study.", + "request": { + "$ref": "GoogleCloudAiplatformV1Trial" + }, + "id": "aiplatform.projects.locations.studies.trials.create", + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials", + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", + "description": "Required. The resource name of the Study to create the Trial in. Format: `projects/{project}/locations/{location}/studies/{study}`", + "location": "path", + "required": true, + "type": "string" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1Trial" + } + }, + "checkTrialEarlyStoppingState": { + "parameterOrder": [ + "trialName" + ], + "id": "aiplatform.projects.locations.studies.trials.checkTrialEarlyStoppingState", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Checks whether a Trial should stop or not. Returns a long-running operation. When the operation is successful, it will contain a CheckTrialEarlyStoppingStateResponse.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}:checkTrialEarlyStoppingState", + "parameters": { + "trialName": { + "location": "path", + "type": "string", + "required": true, + "description": "Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1CheckTrialEarlyStoppingStateRequest" + }, + "path": "v1/{+trialName}:checkTrialEarlyStoppingState" + }, + "complete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Marks a Trial as complete.", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.studies.trials.complete", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}:complete", + "parameters": { + "name": { + "description": "Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", + "type": "string", + "location": "path", + "required": true + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1Trial" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1CompleteTrialRequest" + }, + "httpMethod": "POST", + "path": "v1/{+name}:complete" + }, + "list": { + "description": "Lists the Trials associated with a Study.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1ListTrialsResponse" + }, + "parameters": { + "pageSize": { + "type": "integer", + "location": "query", + "format": "int32", + "description": "Optional. The number of Trials to retrieve per \"page\" of results. If unspecified, the service will pick an appropriate default." + }, + "parent": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", + "location": "path", + "description": "Required. The resource name of the Study to list the Trial from. Format: `projects/{project}/locations/{location}/studies/{study}`", + "required": true + }, + "pageToken": { + "description": "Optional. A page token to request the next page of results. If unspecified, there are no subsequent pages.", + "type": "string", + "location": "query" + } + }, + "id": "aiplatform.projects.locations.studies.trials.list", + "parameterOrder": [ + "parent" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials", + "path": "v1/{+parent}/trials", + "httpMethod": "GET" + }, + "suggest": { + "parameterOrder": [ + "parent" + ], + "parameters": { + "parent": { + "description": "Required. The project and location that the Study belongs to. Format: `projects/{project}/locations/{location}/studies/{study}`", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", + "location": "path", + "required": true, + "type": "string" + } + }, + "description": "Adds one or more Trials to a Study, with parameter values suggested by Vertex AI Vizier. Returns a long-running operation associated with the generation of Trial suggestions. When this long-running operation succeeds, it will contain a SuggestTrialsResponse.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+parent}/trials:suggest", + "request": { + "$ref": "GoogleCloudAiplatformV1SuggestTrialsRequest" + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.studies.trials.suggest", + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials:suggest" + }, + "delete": { + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", + "location": "path", + "description": "Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", + "required": true + } + }, + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.studies.trials.delete", + "description": "Deletes a Trial.", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}", + "path": "v1/{+name}" + } + }, + "resources": { + "operations": { + "methods": { + "cancel": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}:cancel", + "parameterOrder": [ + "name" + ], + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "path": "v1/{+name}:cancel", + "id": "aiplatform.projects.locations.studies.trials.operations.cancel", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "location": "path", + "type": "string", + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+/operations/[^/]+$", + "required": true + } + } + }, + "delete": { + "id": "aiplatform.projects.locations.studies.trials.operations.delete", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+/operations/[^/]+$", + "location": "path", + "required": true, + "type": "string", + "description": "The name of the operation resource to be deleted." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}", + "path": "v1/{+name}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "httpMethod": "DELETE" + }, + "get": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "GET", + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.studies.trials.operations.get", + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string", + "description": "The name of the operation resource." + } + } + }, + "wait": { + "id": "aiplatform.projects.locations.studies.trials.operations.wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "parameters": { + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+/operations/[^/]+$", + "type": "string", + "description": "The name of the operation resource to wait on." + }, + "timeout": { + "format": "google-duration", + "location": "query", + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + } + }, + "path": "v1/{+name}:wait", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}:wait", + "httpMethod": "POST" + }, + "list": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations", + "path": "v1/{+name}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.studies.trials.operations.list", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameterOrder": [ + "name" + ], + "parameters": { + "pageSize": { + "location": "query", + "type": "integer", + "format": "int32", + "description": "The standard list page size." + }, + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + }, + "filter": { + "type": "string", + "description": "The standard list filter.", + "location": "query" + }, + "name": { + "type": "string", + "required": true, + "description": "The name of the operation's parent resource.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$" + } + }, + "httpMethod": "GET" + } + } + } + } + }, + "operations": { + "methods": { + "delete": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.studies.operations.delete", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "httpMethod": "DELETE", + "parameters": { + "name": { + "location": "path", + "type": "string", + "required": true, + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/operations/[^/]+$" + } + } + }, + "wait": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations/{operationsId}:wait", + "path": "v1/{+name}:wait", + "id": "aiplatform.projects.locations.studies.operations.wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "type": "string", + "location": "query" + }, + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/operations/[^/]+$", + "required": true, + "type": "string", + "description": "The name of the operation resource to wait on." + } + }, + "httpMethod": "POST" + }, + "cancel": { + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "id": "aiplatform.projects.locations.studies.operations.cancel", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be cancelled.", + "type": "string", + "location": "path", + "required": true + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1/{+name}:cancel", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations/{operationsId}:cancel", + "parameterOrder": [ + "name" + ] + }, + "get": { + "id": "aiplatform.projects.locations.studies.operations.get", + "parameters": { + "name": { + "location": "path", + "required": true, + "type": "string", + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/operations/[^/]+$" + } + }, + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations/{operationsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." + }, + "list": { + "path": "v1/{+name}/operations", + "id": "aiplatform.projects.locations.studies.operations.list", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "parameters": { + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + }, + "pageSize": { + "format": "int32", + "location": "query", + "description": "The standard list page size.", + "type": "integer" + }, + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "name": { + "type": "string", + "description": "The name of the operation's parent resource.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", + "location": "path" + } + }, + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + } + } + } + }, + "methods": { + "create": { + "path": "v1/{+parent}/studies", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies", + "id": "aiplatform.projects.locations.studies.create", + "response": { + "$ref": "GoogleCloudAiplatformV1Study" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1Study" + }, + "parameters": { + "parent": { + "description": "Required. The resource name of the Location to create the CustomJob in. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true, + "location": "path", + "type": "string" + } + }, + "description": "Creates a Study. A resource name will be generated after creation of the Study.", + "parameterOrder": [ + "parent" + ], + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "delete": { + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "parameters": { + "name": { + "type": "string", + "description": "Required. The name of the Study resource to be deleted. Format: `projects/{project}/locations/{location}/studies/{study}`", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", + "location": "path", + "required": true + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Deletes a Study.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}", + "id": "aiplatform.projects.locations.studies.delete", + "httpMethod": "DELETE" + }, + "lookup": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies:lookup", + "path": "v1/{+parent}/studies:lookup", + "parameterOrder": [ + "parent" + ], + "description": "Looks a study up using the user-defined display_name field instead of the fully qualified resource name.", + "id": "aiplatform.projects.locations.studies.lookup", + "request": { + "$ref": "GoogleCloudAiplatformV1LookupStudyRequest" + }, + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location to get the Study from. Format: `projects/{project}/locations/{location}`", + "required": true, + "type": "string", + "location": "path" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1Study" + } + }, + "list": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies", + "path": "v1/{+parent}/studies", + "parameterOrder": [ + "parent" + ], + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "pageSize": { + "format": "int32", + "description": "Optional. The maximum number of studies to return per \"page\" of results. If unspecified, service will pick an appropriate default.", + "location": "query", + "type": "integer" + }, + "pageToken": { + "description": "Optional. A page token to request the next page of results. If unspecified, there are no subsequent pages.", + "location": "query", + "type": "string" + }, + "parent": { + "description": "Required. The resource name of the Location to list the Study from. Format: `projects/{project}/locations/{location}`", + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1ListStudiesResponse" + }, + "description": "Lists all the studies in a region for an associated project.", + "id": "aiplatform.projects.locations.studies.list" + }, + "get": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}", + "response": { + "$ref": "GoogleCloudAiplatformV1Study" + }, + "id": "aiplatform.projects.locations.studies.get", + "parameters": { + "name": { + "type": "string", + "description": "Required. The name of the Study resource. Format: `projects/{project}/locations/{location}/studies/{study}`", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$" + } + }, + "description": "Gets a Study by name.", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "path": "v1/{+name}" + } + } + }, + "migratableResources": { + "methods": { + "batchMigrate": { + "description": "Batch migrates resources from ml.googleapis.com, automl.googleapis.com, and datalabeling.googleapis.com to Vertex AI.", + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "parent": { + "location": "path", + "description": "Required. The location of the migrated resource will live in. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true, + "type": "string" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1BatchMigrateResourcesRequest" + }, + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/migratableResources:batchMigrate", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.migratableResources.batchMigrate", + "path": "v1/{+parent}/migratableResources:batchMigrate" + }, + "search": { + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true, + "description": "Required. The location that the migratable resources should be searched from. It's the Vertex AI location that the resources can be migrated to, not the resources' original location. Format: `projects/{project}/locations/{location}`", + "type": "string", + "location": "path" + } + }, + "parameterOrder": [ + "parent" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/migratableResources:search", + "request": { + "$ref": "GoogleCloudAiplatformV1SearchMigratableResourcesRequest" + }, + "response": { + "$ref": "GoogleCloudAiplatformV1SearchMigratableResourcesResponse" + }, + "id": "aiplatform.projects.locations.migratableResources.search", + "description": "Searches all of the resources in automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com that can be migrated to Vertex AI's given location.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+parent}/migratableResources:search", + "httpMethod": "POST" + } + }, + "resources": { + "operations": { + "methods": { + "delete": { + "parameters": { + "name": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+/operations/[^/]+$", + "required": true, + "description": "The name of the operation resource to be deleted." + } + }, + "id": "aiplatform.projects.locations.migratableResources.operations.delete", + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "httpMethod": "DELETE", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations/{operationsId}", + "response": { + "$ref": "GoogleProtobufEmpty" + } + }, + "cancel": { + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations/{operationsId}:cancel", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.migratableResources.operations.cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}:cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "httpMethod": "POST", + "parameters": { + "name": { + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+/operations/[^/]+$" + } + } + }, + "list": { + "parameterOrder": [ + "name" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "httpMethod": "GET", + "id": "aiplatform.projects.locations.migratableResources.operations.list", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations", + "path": "v1/{+name}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "pageToken": { + "location": "query", + "description": "The standard list page token.", + "type": "string" + }, + "pageSize": { + "description": "The standard list page size.", + "type": "integer", + "location": "query", + "format": "int32" + }, + "name": { + "type": "string", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+$", + "description": "The name of the operation's parent resource." + }, + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "wait": { + "id": "aiplatform.projects.locations.migratableResources.operations.wait", + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+/operations/[^/]+$", + "required": true, + "description": "The name of the operation resource to wait on.", + "location": "path" + }, + "timeout": { + "format": "google-duration", + "type": "string", + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + } + }, + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations/{operationsId}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}:wait", + "httpMethod": "POST" + }, + "get": { + "httpMethod": "GET", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.migratableResources.operations.get", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+/operations/[^/]+$", + "required": true, + "type": "string", + "description": "The name of the operation resource." + } + }, + "path": "v1/{+name}" + } + } + } + } + }, + "nasJobs": { + "methods": { + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.nasJobs.delete", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+$", + "description": "Required. The name of the NasJob resource to be deleted. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}`", + "required": true + } + }, + "description": "Deletes a NasJob.", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}", + "path": "v1/{+name}" + }, + "get": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+$", + "description": "Required. The name of the NasJob resource. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}`", + "location": "path", + "required": true + } + }, + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.nasJobs.get", + "response": { + "$ref": "GoogleCloudAiplatformV1NasJob" + }, + "parameterOrder": [ + "name" + ], + "description": "Gets a NasJob", + "httpMethod": "GET" + }, + "list": { + "description": "Lists NasJobs in a Location.", + "parameterOrder": [ + "parent" + ], + "path": "v1/{+parent}/nasJobs", + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/nasJobs", + "id": "aiplatform.projects.locations.nasJobs.list", + "response": { + "$ref": "GoogleCloudAiplatformV1ListNasJobsResponse" + }, + "parameters": { + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`" + }, + "parent": { + "type": "string", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location to list the NasJobs from. Format: `projects/{project}/locations/{location}`" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token. Typically obtained via ListNasJobsResponse.next_page_token of the previous JobService.ListNasJobs call." + }, + "pageSize": { + "location": "query", + "type": "integer", + "format": "int32", + "description": "The standard list page size." + }, + "readMask": { + "format": "google-fieldmask", + "type": "string", + "description": "Mask specifying which fields to read.", + "location": "query" + } + } + }, + "create": { + "parameters": { + "parent": { + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true, + "description": "Required. The resource name of the Location to create the NasJob in. Format: `projects/{project}/locations/{location}`" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1NasJob" + }, + "response": { + "$ref": "GoogleCloudAiplatformV1NasJob" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/nasJobs", + "id": "aiplatform.projects.locations.nasJobs.create", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+parent}/nasJobs", + "description": "Creates a NasJob", + "parameterOrder": [ + "parent" + ] + }, + "cancel": { + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+$", + "location": "path", + "description": "Required. The name of the NasJob to cancel. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}`", + "type": "string" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1CancelNasJobRequest" + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1/{+name}:cancel", + "description": "Cancels a NasJob. Starts asynchronous cancellation on the NasJob. The server makes a best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetNasJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On successful cancellation, the NasJob is not deleted; instead it becomes a job with a NasJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and NasJob.state is set to `CANCELLED`.", + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}:cancel", + "id": "aiplatform.projects.locations.nasJobs.cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + } + }, + "resources": { + "nasTrialDetails": { + "methods": { + "list": { + "description": "List top NasTrialDetails of a NasJob.", + "path": "v1/{+parent}/nasTrialDetails", + "response": { + "$ref": "GoogleCloudAiplatformV1ListNasTrialDetailsResponse" + }, + "id": "aiplatform.projects.locations.nasJobs.nasTrialDetails.list", + "parameters": { + "pageSize": { + "description": "The standard list page size.", + "type": "integer", + "format": "int32", + "location": "query" + }, + "parent": { + "required": true, + "location": "path", + "type": "string", + "description": "Required. The name of the NasJob resource. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}`", + "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+$" + }, + "pageToken": { + "description": "The standard list page token. Typically obtained via ListNasTrialDetailsResponse.next_page_token of the previous JobService.ListNasTrialDetails call.", + "location": "query", + "type": "string" + } + }, + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}/nasTrialDetails", + "parameterOrder": [ + "parent" + ] + }, + "get": { + "response": { + "$ref": "GoogleCloudAiplatformV1NasTrialDetail" + }, + "description": "Gets a NasTrialDetail.", + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.nasJobs.nasTrialDetails.get", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+/nasTrialDetails/[^/]+$", + "description": "Required. The name of the NasTrialDetail resource. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}/nasTrialDetails/{nas_trial_detail}`", + "type": "string", + "required": true + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}/nasTrialDetails/{nasTrialDetailsId}" + } + } + } + } + }, + "schedules": { + "methods": { + "list": { + "id": "aiplatform.projects.locations.schedules.list", + "path": "v1/{+parent}/schedules", + "httpMethod": "GET", + "parameterOrder": [ + "parent" + ], + "parameters": { + "filter": { + "description": "Lists the Schedules that match the filter expression. The following fields are supported: * `display_name`: Supports `=`, `!=` comparisons, and `:` wildcard. * `state`: Supports `=` and `!=` comparisons. * `request`: Supports existence of the check. (e.g. `create_pipeline_job_request:*` --\u003e Schedule has create_pipeline_job_request). * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `start_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `end_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, `\u003e=` comparisons and `:*` existence check. Values must be in RFC 3339 format. * `next_run_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. Filter expressions can be combined together using logical operators (`NOT`, `AND` & `OR`). The syntax to define filter expression is based on https://google.aip.dev/160. Examples: * `state=\"ACTIVE\" AND display_name:\"my_schedule_*\"` * `NOT display_name=\"my_schedule\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `end_time\u003e\"2021-05-18T00:00:00Z\" OR NOT end_time:*` * `create_pipeline_job_request:*`", + "type": "string", + "location": "query" + }, + "parent": { + "description": "Required. The resource name of the Location to list the Schedules from. Format: `projects/{project}/locations/{location}`", + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$" + }, + "pageToken": { + "type": "string", + "description": "The standard list page token. Typically obtained via ListSchedulesResponse.next_page_token of the previous ScheduleService.ListSchedules call.", + "location": "query" + }, + "pageSize": { + "type": "integer", + "description": "The standard list page size. Default to 100 if not specified.", + "format": "int32", + "location": "query" + }, + "orderBy": { + "location": "query", + "description": "A comma-separated list of fields to order by. The default sort order is in ascending order. Use \"desc\" after a field name for descending. You can have multiple order_by fields provided. For example, using \"create_time desc, end_time\" will order results by create time in descending order, and if there are multiple schedules having the same create time, order them by the end time in ascending order. If order_by is not specified, it will order by default with create_time in descending order. Supported fields: * `create_time` * `start_time` * `end_time` * `next_run_time`", + "type": "string" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1ListSchedulesResponse" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules", + "description": "Lists Schedules in a Location.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "pause": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", + "type": "string", + "location": "path", + "description": "Required. The name of the Schedule resource to be paused. Format: `projects/{project}/locations/{location}/schedules/{schedule}`", + "required": true + } + }, + "description": "Pauses a Schedule. Will mark Schedule.state to 'PAUSED'. If the schedule is paused, no new runs will be created. Already created runs will NOT be paused or canceled.", + "request": { + "$ref": "GoogleCloudAiplatformV1PauseScheduleRequest" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.schedules.pause", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1/{+name}:pause", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}:pause" + }, + "create": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+parent}/schedules", + "request": { + "$ref": "GoogleCloudAiplatformV1Schedule" + }, + "httpMethod": "POST", + "parameterOrder": [ + "parent" + ], + "description": "Creates a Schedule.", + "parameters": { + "parent": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true, + "description": "Required. The resource name of the Location to create the Schedule in. Format: `projects/{project}/locations/{location}`" + } + }, + "id": "aiplatform.projects.locations.schedules.create", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules", + "response": { + "$ref": "GoogleCloudAiplatformV1Schedule" + } + }, + "get": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "required": true, + "type": "string", + "location": "path", + "description": "Required. The name of the Schedule resource. Format: `projects/{project}/locations/{location}/schedules/{schedule}`", + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$" + } + }, + "description": "Gets a Schedule.", + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1Schedule" + }, + "id": "aiplatform.projects.locations.schedules.get", + "httpMethod": "GET" + }, + "delete": { + "parameters": { + "name": { + "location": "path", + "description": "Required. The name of the Schedule resource to be deleted. Format: `projects/{project}/locations/{location}/schedules/{schedule}`", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$" + } + }, + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.schedules.delete", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "DELETE", + "description": "Deletes a Schedule." + }, + "resume": { + "request": { + "$ref": "GoogleCloudAiplatformV1ResumeScheduleRequest" + }, + "parameters": { + "name": { + "required": true, + "description": "Required. The name of the Schedule resource to be resumed. Format: `projects/{project}/locations/{location}/schedules/{schedule}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", + "location": "path" + } + }, + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}:resume", + "httpMethod": "POST", + "path": "v1/{+name}:resume", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Resumes a paused Schedule to start scheduling new runs. Will mark Schedule.state to 'ACTIVE'. Only paused Schedule can be resumed. When the Schedule is resumed, new runs will be scheduled starting from the next execution time after the current time based on the time_specification in the Schedule. If Schedule.catchUp is set up true, all missed runs will be scheduled for backfill first.", + "id": "aiplatform.projects.locations.schedules.resume" + }, + "patch": { + "description": "Updates an active or paused Schedule. When the Schedule is updated, new runs will be scheduled starting from the updated next execution time after the update time based on the time_specification in the updated Schedule. All unstarted runs before the update time will be skipped while already created runs will NOT be paused or canceled.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1Schedule" + }, + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.schedules.patch", + "parameters": { + "updateMask": { + "location": "query", + "format": "google-fieldmask", + "type": "string", + "description": "Required. The update mask applies to the resource. See google.protobuf.FieldMask." + }, + "name": { + "description": "Immutable. The resource name of the Schedule.", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", + "location": "path" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1Schedule" + }, + "httpMethod": "PATCH", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}", + "parameterOrder": [ + "name" + ] + } + }, + "resources": { + "operations": { + "methods": { + "delete": { + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "description": "The name of the operation resource to be deleted." + } + }, + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations/{operationsId}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.schedules.operations.delete", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "httpMethod": "DELETE", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "path": "v1/{+name}/operations", + "parameters": { + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + }, + "pageSize": { + "format": "int32", + "type": "integer", + "description": "The standard list page size.", + "location": "query" + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", + "required": true, + "description": "The name of the operation's parent resource.", + "location": "path", + "type": "string" + }, + "filter": { + "location": "query", + "description": "The standard list filter.", + "type": "string" + } + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "id": "aiplatform.projects.locations.schedules.operations.list", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations" + }, + "get": { + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.schedules.operations.get", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameters": { + "name": { + "description": "The name of the operation resource.", + "type": "string", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+/operations/[^/]+$" + } + }, + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "cancel": { + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "path": "v1/{+name}:cancel", + "httpMethod": "POST", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.schedules.operations.cancel", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations/{operationsId}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "type": "string", + "required": true, + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+/operations/[^/]+$" + } + } + }, + "wait": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.schedules.operations.wait", + "parameterOrder": [ + "name" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations/{operationsId}:wait", + "httpMethod": "POST", + "path": "v1/{+name}:wait", + "parameters": { + "name": { + "type": "string", + "required": true, + "location": "path", + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+/operations/[^/]+$" + }, + "timeout": { + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "location": "query" + } + } + } + } + } + } + }, + "tensorboards": { + "resources": { + "operations": { + "methods": { + "cancel": { + "parameters": { + "name": { + "location": "path", + "required": true, + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.tensorboards.operations.cancel", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations/{operationsId}:cancel", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}:cancel" + }, + "list": { + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + }, + "name": { + "type": "string", + "required": true, + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", + "location": "path" + }, + "pageSize": { + "location": "query", + "type": "integer", + "description": "The standard list page size.", + "format": "int32" + } + }, + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}/operations", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "id": "aiplatform.projects.locations.tensorboards.operations.list", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations" + }, + "delete": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/operations/[^/]+$", + "location": "path", + "required": true, + "type": "string", + "description": "The name of the operation resource to be deleted." + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.tensorboards.operations.delete", + "parameterOrder": [ + "name" + ], + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "httpMethod": "DELETE" + }, + "wait": { + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations/{operationsId}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.tensorboards.operations.wait", + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "location": "query", + "type": "string" + }, + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "required": true, + "type": "string" + } + }, + "path": "v1/{+name}:wait" + }, + "get": { + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource.", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.tensorboards.operations.get", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations/{operationsId}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "parameterOrder": [ + "name" + ] + } + } + }, + "experiments": { + "methods": { + "get": { + "parameterOrder": [ + "name" + ], + "description": "Gets a TensorboardExperiment.", + "response": { + "$ref": "GoogleCloudAiplatformV1TensorboardExperiment" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}", + "httpMethod": "GET", + "parameters": { + "name": { + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", + "description": "Required. The name of the TensorboardExperiment resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", + "location": "path" + } + }, + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "id": "aiplatform.projects.locations.tensorboards.experiments.get" + }, + "patch": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", + "type": "string", + "required": true, + "description": "Output only. Name of the TensorboardExperiment. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", + "location": "path" + }, + "updateMask": { + "type": "string", + "location": "query", + "description": "Required. Field mask is used to specify the fields to be overwritten in the TensorboardExperiment resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified.", + "format": "google-fieldmask" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1TensorboardExperiment" + }, + "httpMethod": "PATCH", + "id": "aiplatform.projects.locations.tensorboards.experiments.patch", + "response": { + "$ref": "GoogleCloudAiplatformV1TensorboardExperiment" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "description": "Updates a TensorboardExperiment.", + "parameterOrder": [ + "name" + ] + }, + "delete": { + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.tensorboards.experiments.delete", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", + "location": "path", + "required": true, + "type": "string", + "description": "Required. The name of the TensorboardExperiment to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ], + "description": "Deletes a TensorboardExperiment." + }, + "list": { + "description": "Lists TensorboardExperiments in a Location.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1ListTensorboardExperimentsResponse" + }, + "path": "v1/{+parent}/experiments", + "id": "aiplatform.projects.locations.tensorboards.experiments.list", + "parameterOrder": [ + "parent" + ], + "httpMethod": "GET", + "parameters": { + "orderBy": { + "description": "Field to use to sort the list.", + "location": "query", + "type": "string" + }, + "pageToken": { + "description": "A page token, received from a previous TensorboardService.ListTensorboardExperiments call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboardExperiments must match the call that provided the page token.", + "type": "string", + "location": "query" + }, + "filter": { + "type": "string", + "location": "query", + "description": "Lists the TensorboardExperiments that match the filter expression." + }, + "readMask": { + "description": "Mask specifying which fields to read.", + "type": "string", + "format": "google-fieldmask", + "location": "query" + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", + "type": "string", + "location": "path", + "required": true, + "description": "Required. The resource name of the Tensorboard to list TensorboardExperiments. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`" + }, + "pageSize": { + "location": "query", + "description": "The maximum number of TensorboardExperiments to return. The service may return fewer than this value. If unspecified, at most 50 TensorboardExperiments are returned. The maximum value is 1000; values above 1000 are coerced to 1000.", + "type": "integer", + "format": "int32" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments" + }, + "write": { + "id": "aiplatform.projects.locations.tensorboards.experiments.write", + "description": "Write time series data points of multiple TensorboardTimeSeries in multiple TensorboardRun's. If any data fail to be ingested, an error is returned.", + "request": { + "$ref": "GoogleCloudAiplatformV1WriteTensorboardExperimentDataRequest" + }, + "parameters": { + "tensorboardExperiment": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", + "required": true, + "description": "Required. The resource name of the TensorboardExperiment to write data to. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", + "location": "path", + "type": "string" + } + }, + "parameterOrder": [ + "tensorboardExperiment" + ], + "path": "v1/{+tensorboardExperiment}:write", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}:write", + "response": { + "$ref": "GoogleCloudAiplatformV1WriteTensorboardExperimentDataResponse" + } + }, + "create": { + "httpMethod": "POST", + "description": "Creates a TensorboardExperiment.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.tensorboards.experiments.create", + "path": "v1/{+parent}/experiments", + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", + "location": "path", + "type": "string", + "description": "Required. The resource name of the Tensorboard to create the TensorboardExperiment in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", + "required": true + }, + "tensorboardExperimentId": { + "location": "query", + "description": "Required. The ID to use for the Tensorboard experiment, which becomes the final component of the Tensorboard experiment's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`.", + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments", + "response": { + "$ref": "GoogleCloudAiplatformV1TensorboardExperiment" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1TensorboardExperiment" + } + }, + "batchCreate": { + "description": "Batch create TensorboardTimeSeries that belong to a TensorboardExperiment.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}:batchCreate", + "id": "aiplatform.projects.locations.tensorboards.experiments.batchCreate", + "parameters": { + "parent": { + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", + "description": "Required. The resource name of the TensorboardExperiment to create the TensorboardTimeSeries in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}` The TensorboardRuns referenced by the parent fields in the CreateTensorboardTimeSeriesRequest messages must be sub resources of this TensorboardExperiment.", + "required": true + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1BatchCreateTensorboardTimeSeriesResponse" + }, + "parameterOrder": [ + "parent" + ], + "httpMethod": "POST", + "path": "v1/{+parent}:batchCreate", + "request": { + "$ref": "GoogleCloudAiplatformV1BatchCreateTensorboardTimeSeriesRequest" + } + } + }, + "resources": { + "runs": { + "resources": { + "timeSeries": { + "methods": { + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}", + "httpMethod": "DELETE", + "description": "Deletes a TensorboardTimeSeries.", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", + "location": "path", + "required": true, + "type": "string", + "description": "Required. The name of the TensorboardTimeSeries to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`" + } + }, + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.delete", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "exportTensorboardTimeSeries": { + "description": "Exports a TensorboardTimeSeries' data. Data is returned in paginated responses.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "tensorboardTimeSeries" + ], + "httpMethod": "POST", + "path": "v1/{+tensorboardTimeSeries}:exportTensorboardTimeSeries", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.exportTensorboardTimeSeries", + "parameters": { + "tensorboardTimeSeries": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", + "description": "Required. The resource name of the TensorboardTimeSeries to export data from. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`", + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}:exportTensorboardTimeSeries", + "response": { + "$ref": "GoogleCloudAiplatformV1ExportTensorboardTimeSeriesDataResponse" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1ExportTensorboardTimeSeriesDataRequest" + } + }, + "get": { + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.get", + "path": "v1/{+name}", + "description": "Gets a TensorboardTimeSeries.", + "httpMethod": "GET", + "parameters": { + "name": { + "type": "string", + "description": "Required. The name of the TensorboardTimeSeries resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1TensorboardTimeSeries" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}" + }, + "create": { + "parameterOrder": [ + "parent" + ], + "description": "Creates a TensorboardTimeSeries.", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.create", + "response": { + "$ref": "GoogleCloudAiplatformV1TensorboardTimeSeries" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "tensorboardTimeSeriesId": { + "location": "query", + "type": "string", + "description": "Optional. The user specified unique ID to use for the TensorboardTimeSeries, which becomes the final component of the TensorboardTimeSeries's resource name. This value should match \"a-z0-9{0, 127}\"" + }, + "parent": { + "type": "string", + "required": true, + "description": "Required. The resource name of the TensorboardRun to create the TensorboardTimeSeries in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$" + } + }, + "path": "v1/{+parent}/timeSeries", + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1TensorboardTimeSeries" + } + }, + "readBlobData": { + "parameterOrder": [ + "timeSeries" + ], + "description": "Gets bytes of TensorboardBlobs. This is to allow reading blob data stored in consumer project's Cloud Storage bucket without users having to obtain Cloud Storage access permission.", + "parameters": { + "blobIds": { + "location": "query", + "description": "IDs of the blobs to read.", + "type": "string", + "repeated": true + }, + "timeSeries": { + "description": "Required. The resource name of the TensorboardTimeSeries to list Blobs. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", + "type": "string", + "location": "path", + "required": true + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1ReadTensorboardBlobDataResponse" + }, + "httpMethod": "GET", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}:readBlobData", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.readBlobData", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "path": "v1/{+timeSeries}:readBlobData" + }, + "read": { + "httpMethod": "GET", + "path": "v1/{+tensorboardTimeSeries}:read", + "description": "Reads a TensorboardTimeSeries' data. By default, if the number of data points stored is less than 1000, all data is returned. Otherwise, 1000 data points is randomly selected from this time series and returned. This value can be changed by changing max_data_points, which can't be greater than 10k.", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.read", + "parameterOrder": [ + "tensorboardTimeSeries" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1ReadTensorboardTimeSeriesDataResponse" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}:read", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "parameters": { + "tensorboardTimeSeries": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", + "location": "path", + "description": "Required. The resource name of the TensorboardTimeSeries to read data from. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`", + "required": true + }, + "filter": { + "location": "query", + "type": "string", + "description": "Reads the TensorboardTimeSeries' data that match the filter expression." + }, + "maxDataPoints": { + "type": "integer", + "description": "The maximum number of TensorboardTimeSeries' data to return. This value should be a positive integer. This value can be set to -1 to return all data.", + "format": "int32", + "location": "query" + } + } + }, + "list": { + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.list", + "httpMethod": "GET", + "description": "Lists TensorboardTimeSeries in a Location.", + "parameterOrder": [ + "parent" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1ListTensorboardTimeSeriesResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries", + "path": "v1/{+parent}/timeSeries", + "parameters": { + "filter": { + "location": "query", + "description": "Lists the TensorboardTimeSeries that match the filter expression.", + "type": "string" + }, + "orderBy": { + "description": "Field to use to sort the list.", + "location": "query", + "type": "string" + }, + "pageSize": { + "format": "int32", + "description": "The maximum number of TensorboardTimeSeries to return. The service may return fewer than this value. If unspecified, at most 50 TensorboardTimeSeries are returned. The maximum value is 1000; values above 1000 are coerced to 1000.", + "location": "query", + "type": "integer" + }, + "readMask": { + "format": "google-fieldmask", + "location": "query", + "description": "Mask specifying which fields to read.", + "type": "string" + }, + "pageToken": { + "location": "query", + "description": "A page token, received from a previous TensorboardService.ListTensorboardTimeSeries call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboardTimeSeries must match the call that provided the page token.", + "type": "string" + }, + "parent": { + "location": "path", + "required": true, + "description": "Required. The resource name of the TensorboardRun to list TensorboardTimeSeries. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$" + } + } + }, + "patch": { + "response": { + "$ref": "GoogleCloudAiplatformV1TensorboardTimeSeries" + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.patch", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}", + "parameters": { + "updateMask": { + "format": "google-fieldmask", + "description": "Required. Field mask is used to specify the fields to be overwritten in the TensorboardTimeSeries resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified.", + "location": "query", + "type": "string" + }, + "name": { + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", + "description": "Output only. Name of the TensorboardTimeSeries." + } + }, + "description": "Updates a TensorboardTimeSeries.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "PATCH", + "path": "v1/{+name}", + "request": { + "$ref": "GoogleCloudAiplatformV1TensorboardTimeSeries" + } + } + }, + "resources": { + "operations": { + "methods": { + "wait": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}:wait", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}:wait", + "parameters": { + "timeout": { + "location": "query", + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration" + }, + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "type": "string", + "location": "path" + } + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "POST" + }, + "delete": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.delete", + "path": "v1/{+name}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be deleted.", + "location": "path", + "required": true, + "type": "string" + } + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}" + }, + "list": { + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "pageToken": { + "location": "query", + "description": "The standard list page token.", + "type": "string" + }, + "name": { + "location": "path", + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", + "required": true, + "type": "string" + }, + "pageSize": { + "location": "query", + "description": "The standard list page size.", + "format": "int32", + "type": "integer" + } + }, + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.list", + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "path": "v1/{+name}/operations" + }, + "cancel": { + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "required": true, + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$" + } + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "path": "v1/{+name}:cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}:cancel", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.cancel", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "get": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource.", + "required": true, + "type": "string", + "location": "path" + } + }, + "parameterOrder": [ + "name" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.get", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}", + "httpMethod": "GET" + } + } + } + } + }, + "operations": { + "methods": { + "cancel": { + "path": "v1/{+name}:cancel", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string", + "required": true + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "httpMethod": "POST" + }, + "delete": { + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be deleted.", + "location": "path", + "type": "string" + } + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.delete", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "httpMethod": "DELETE" + }, + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.list", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "path": "v1/{+name}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "pageSize": { + "format": "int32", + "type": "integer", + "location": "query", + "description": "The standard list page size." + }, + "name": { + "description": "The name of the operation's parent resource.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", + "required": true, + "type": "string" + }, + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + } + } + }, + "get": { + "parameters": { + "name": { + "description": "The name of the operation resource.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", + "type": "string", + "required": true + } + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.get", + "path": "v1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "wait": { + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.wait", + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}:wait", + "parameters": { + "timeout": { + "format": "google-duration", + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query" + }, + "name": { + "location": "path", + "required": true, + "description": "The name of the operation resource to wait on.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}:wait" + } + } + } + }, + "methods": { + "list": { + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.list", + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1ListTensorboardRunsResponse" + }, + "parameters": { + "pageToken": { + "location": "query", + "type": "string", + "description": "A page token, received from a previous TensorboardService.ListTensorboardRuns call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboardRuns must match the call that provided the page token." + }, + "pageSize": { + "format": "int32", + "description": "The maximum number of TensorboardRuns to return. The service may return fewer than this value. If unspecified, at most 50 TensorboardRuns are returned. The maximum value is 1000; values above 1000 are coerced to 1000.", + "location": "query", + "type": "integer" + }, + "filter": { + "description": "Lists the TensorboardRuns that match the filter expression.", + "location": "query", + "type": "string" + }, + "orderBy": { + "description": "Field to use to sort the list.", + "location": "query", + "type": "string" + }, + "readMask": { + "format": "google-fieldmask", + "location": "query", + "description": "Mask specifying which fields to read.", + "type": "string" + }, + "parent": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", + "type": "string", + "description": "Required. The resource name of the TensorboardExperiment to list TensorboardRuns. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`" + } + }, + "path": "v1/{+parent}/runs", + "httpMethod": "GET", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs", + "description": "Lists TensorboardRuns in a Location." + }, + "get": { + "parameters": { + "name": { + "required": true, + "description": "Required. The name of the TensorboardRun resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$" + } + }, + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.get", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "description": "Gets a TensorboardRun.", + "response": { + "$ref": "GoogleCloudAiplatformV1TensorboardRun" + } + }, + "create": { + "httpMethod": "POST", + "path": "v1/{+parent}/runs", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "parameters": { + "tensorboardRunId": { + "description": "Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`.", + "type": "string", + "location": "query" + }, + "parent": { + "description": "Required. The resource name of the TensorboardExperiment to create the TensorboardRun in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", + "required": true + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs", + "request": { + "$ref": "GoogleCloudAiplatformV1TensorboardRun" + }, + "response": { + "$ref": "GoogleCloudAiplatformV1TensorboardRun" + }, + "description": "Creates a TensorboardRun.", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.create" + }, + "write": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}:write", + "path": "v1/{+tensorboardRun}:write", + "httpMethod": "POST", + "description": "Write time series data points into multiple TensorboardTimeSeries under a TensorboardRun. If any data fail to be ingested, an error is returned.", + "response": { + "$ref": "GoogleCloudAiplatformV1WriteTensorboardRunDataResponse" + }, + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.write", + "parameterOrder": [ + "tensorboardRun" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1WriteTensorboardRunDataRequest" + }, + "parameters": { + "tensorboardRun": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", + "location": "path", + "required": true, + "description": "Required. The resource name of the TensorboardRun to write data to. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", + "type": "string" + } + } + }, + "patch": { + "response": { + "$ref": "GoogleCloudAiplatformV1TensorboardRun" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}", + "description": "Updates a TensorboardRun.", + "parameters": { + "updateMask": { + "type": "string", + "description": "Required. Field mask is used to specify the fields to be overwritten in the TensorboardRun resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified.", + "format": "google-fieldmask", + "location": "query" + }, + "name": { + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", + "required": true, + "description": "Output only. Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`" + } + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "PATCH", + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.patch", + "request": { + "$ref": "GoogleCloudAiplatformV1TensorboardRun" + } + }, + "batchCreate": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1BatchCreateTensorboardRunsResponse" + }, + "parameterOrder": [ + "parent" + ], + "description": "Batch create TensorboardRuns.", + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", + "required": true, + "location": "path", + "type": "string", + "description": "Required. The resource name of the TensorboardExperiment to create the TensorboardRuns in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}` The parent field in the CreateTensorboardRunRequest messages must match this field." + } + }, + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.batchCreate", + "httpMethod": "POST", + "path": "v1/{+parent}/runs:batchCreate", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs:batchCreate", + "request": { + "$ref": "GoogleCloudAiplatformV1BatchCreateTensorboardRunsRequest" + } + }, + "delete": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}", + "parameters": { + "name": { + "required": true, + "description": "Required. The name of the TensorboardRun to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.delete", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "description": "Deletes a TensorboardRun.", + "httpMethod": "DELETE" + } + } + }, + "operations": { + "methods": { + "get": { + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.tensorboards.experiments.operations.get", + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource.", + "type": "string", + "required": true, + "location": "path" + } + } + }, + "delete": { + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", + "type": "string", + "description": "The name of the operation resource to be deleted.", + "required": true + } + }, + "path": "v1/{+name}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "id": "aiplatform.projects.locations.tensorboards.experiments.operations.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE" + }, + "wait": { + "id": "aiplatform.projects.locations.tensorboards.experiments.operations.wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "parameters": { + "timeout": { + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "location": "query" + }, + "name": { + "type": "string", + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", + "required": true, + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}:wait", + "httpMethod": "POST", + "path": "v1/{+name}:wait" + }, + "list": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "id": "aiplatform.projects.locations.tensorboards.experiments.operations.list", + "path": "v1/{+name}/operations", + "parameters": { + "filter": { + "type": "string", + "description": "The standard list filter.", + "location": "query" + }, + "pageToken": { + "description": "The standard list page token.", + "location": "query", + "type": "string" + }, + "name": { + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", + "description": "The name of the operation's parent resource.", + "location": "path" + }, + "pageSize": { + "type": "integer", + "description": "The standard list page size.", + "format": "int32", + "location": "query" + } + } + }, + "cancel": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.tensorboards.experiments.operations.cancel", + "parameters": { + "name": { + "type": "string", + "description": "The name of the operation resource to be cancelled.", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$" + } + }, + "httpMethod": "POST", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}:cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1/{+name}:cancel" + } + } + } + } + } + }, + "methods": { + "batchRead": { + "response": { + "$ref": "GoogleCloudAiplatformV1BatchReadTensorboardTimeSeriesDataResponse" + }, + "parameterOrder": [ + "tensorboard" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}:batchRead", + "path": "v1/{+tensorboard}:batchRead", + "parameters": { + "tensorboard": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", + "type": "string", + "location": "path", + "description": "Required. The resource name of the Tensorboard containing TensorboardTimeSeries to read data from. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`. The TensorboardTimeSeries referenced by time_series must be sub resources of this Tensorboard.", + "required": true + }, + "timeSeries": { + "description": "Required. The resource names of the TensorboardTimeSeries to read data from. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`", + "location": "query", + "type": "string", + "repeated": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Reads multiple TensorboardTimeSeries' data. The data point number limit is 1000 for scalars, 100 for tensors and blob references. If the number of data points stored is less than the limit, all data is returned. Otherwise, the number limit of data points is randomly selected from this time series and returned.", + "httpMethod": "GET", + "id": "aiplatform.projects.locations.tensorboards.batchRead" + }, + "delete": { + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", + "description": "Required. The name of the Tensorboard to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", + "required": true, + "location": "path" + } + }, + "httpMethod": "DELETE", + "description": "Deletes a Tensorboard.", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.tensorboards.delete", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "readUsage": { + "parameterOrder": [ + "tensorboard" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}:readUsage", + "path": "v1/{+tensorboard}:readUsage", + "response": { + "$ref": "GoogleCloudAiplatformV1ReadTensorboardUsageResponse" + }, + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Returns a list of monthly active users for a given TensorBoard instance.", + "id": "aiplatform.projects.locations.tensorboards.readUsage", + "parameters": { + "tensorboard": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", + "required": true, + "description": "Required. The name of the Tensorboard resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", + "type": "string", + "location": "path" + } + } + }, + "readSize": { + "parameterOrder": [ + "tensorboard" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+tensorboard}:readSize", + "id": "aiplatform.projects.locations.tensorboards.readSize", + "description": "Returns the storage size for a given TensorBoard instance.", + "response": { + "$ref": "GoogleCloudAiplatformV1ReadTensorboardSizeResponse" + }, + "httpMethod": "GET", + "parameters": { + "tensorboard": { + "location": "path", + "type": "string", + "required": true, + "description": "Required. The name of the Tensorboard resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}:readSize" + }, + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "id": "aiplatform.projects.locations.tensorboards.list", + "description": "Lists Tensorboards in a Location.", + "parameters": { + "filter": { + "description": "Lists the Tensorboards that match the filter expression.", + "location": "query", + "type": "string" + }, + "pageSize": { + "type": "integer", + "description": "The maximum number of Tensorboards to return. The service may return fewer than this value. If unspecified, at most 100 Tensorboards are returned. The maximum value is 100; values above 100 are coerced to 100.", + "format": "int32", + "location": "query" + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "type": "string", + "description": "Required. The resource name of the Location to list Tensorboards. Format: `projects/{project}/locations/{location}`", + "required": true + }, + "orderBy": { + "type": "string", + "description": "Field to use to sort the list.", + "location": "query" + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "A page token, received from a previous TensorboardService.ListTensorboards call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboards must match the call that provided the page token." + }, + "readMask": { + "type": "string", + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask", + "location": "query" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards", + "response": { + "$ref": "GoogleCloudAiplatformV1ListTensorboardsResponse" + }, + "httpMethod": "GET", + "path": "v1/{+parent}/tensorboards", + "parameterOrder": [ + "parent" + ] + }, + "create": { + "path": "v1/{+parent}/tensorboards", + "description": "Creates a Tensorboard.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "parent" + ], + "parameters": { + "parent": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "description": "Required. The resource name of the Location to create the Tensorboard in. Format: `projects/{project}/locations/{location}`", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.tensorboards.create", + "request": { + "$ref": "GoogleCloudAiplatformV1Tensorboard" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "get": { + "path": "v1/{+name}", + "description": "Gets a Tensorboard.", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "id": "aiplatform.projects.locations.tensorboards.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}", + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", + "location": "path", + "description": "Required. The name of the Tensorboard resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", + "type": "string" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1Tensorboard" + } + }, + "patch": { + "path": "v1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "updateMask": { + "description": "Required. Field mask is used to specify the fields to be overwritten in the Tensorboard resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified.", + "location": "query", + "format": "google-fieldmask", + "type": "string" + }, + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", + "type": "string", + "description": "Output only. Name of the Tensorboard. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`" + } + }, + "parameterOrder": [ + "name" + ], + "description": "Updates a Tensorboard.", + "httpMethod": "PATCH", + "id": "aiplatform.projects.locations.tensorboards.patch", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1Tensorboard" + } + } + } + }, + "featureGroups": { + "resources": { + "operations": { + "methods": { + "wait": { + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "POST", + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "format": "google-duration", + "type": "string" + }, + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "type": "string" + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.featureGroups.operations.wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/operations/{operationsId}:wait", + "path": "v1/{+name}:wait" + }, + "listWait": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/operations/{operationsId}:wait", + "id": "aiplatform.projects.locations.featureGroups.operations.listWait", + "parameters": { + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + }, + "pageSize": { + "description": "The standard list page size.", + "location": "query", + "type": "integer", + "format": "int32" + }, + "name": { + "required": true, + "description": "The name of the operation's parent resource.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/operations/[^/]+$", + "type": "string" + }, + "filter": { + "location": "query", + "description": "The standard list filter.", + "type": "string" + } + }, + "path": "v1/{+name}:wait", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + } + }, + "get": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/operations/[^/]+$", + "location": "path", + "required": true, + "description": "The name of the operation resource.", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.featureGroups.operations.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "path": "v1/{+name}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/operations/{operationsId}" + }, + "delete": { + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/operations/{operationsId}", + "parameters": { + "name": { + "location": "path", + "type": "string", + "description": "The name of the operation resource to be deleted.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/operations/[^/]+$" + } + }, + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.featureGroups.operations.delete" + } + } + }, + "features": { + "methods": { + "get": { + "id": "aiplatform.projects.locations.featureGroups.features.get", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}", + "path": "v1/{+name}", + "description": "Gets details of a single Feature.", + "parameters": { + "name": { + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+$", + "description": "Required. The name of the Feature resource. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", + "required": true + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1Feature" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "httpMethod": "GET", + "parameters": { + "readMask": { + "type": "string", + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask", + "location": "query" + }, + "pageSize": { + "location": "query", + "format": "int32", + "type": "integer", + "description": "The maximum number of Features to return. The service may return fewer than this value. If unspecified, at most 1000 Features will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000." + }, + "parent": { + "location": "path", + "type": "string", + "description": "Required. The resource name of the Location to list Features. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$" + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "A page token, received from a previous FeaturestoreService.ListFeatures call or FeatureRegistryService.ListFeatures call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.ListFeatures or FeatureRegistryService.ListFeatures must match the call that provided the page token." + }, + "filter": { + "type": "string", + "description": "Lists the Features that match the filter expression. The following filters are supported: * `value_type`: Supports = and != comparisons. * `create_time`: Supports =, !=, \u003c, \u003e, \u003e=, and \u003c= comparisons. Values must be in RFC 3339 format. * `update_time`: Supports =, !=, \u003c, \u003e, \u003e=, and \u003c= comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality as well as key presence. Examples: * `value_type = DOUBLE` --\u003e Features whose type is DOUBLE. * `create_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\" OR update_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\"` --\u003e EntityTypes created or updated after 2020-01-31T15:30:00.000000Z. * `labels.active = yes AND labels.env = prod` --\u003e Features having both (active: yes) and (env: prod) labels. * `labels.env: *` --\u003e Any Feature which has a label with 'env' as the key.", + "location": "query" + }, + "orderBy": { + "location": "query", + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `feature_id` * `value_type` (Not supported for FeatureRegistry Feature) * `create_time` * `update_time`", + "type": "string" + }, + "latestStatsCount": { + "location": "query", + "description": "Only applicable for Vertex AI Feature Store (Legacy). If set, return the most recent ListFeaturesRequest.latest_stats_count of stats for each Feature in response. Valid value is [0, 10]. If number of stats exists \u003c ListFeaturesRequest.latest_stats_count, return all existing stats.", + "format": "int32", + "type": "integer" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features", + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.featureGroups.features.list", + "path": "v1/{+parent}/features", + "description": "Lists Features in a given FeatureGroup.", + "response": { + "$ref": "GoogleCloudAiplatformV1ListFeaturesResponse" + } + }, + "patch": { + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}", + "request": { + "$ref": "GoogleCloudAiplatformV1Feature" + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "PATCH", + "parameters": { + "updateMask": { + "format": "google-fieldmask", + "location": "query", + "description": "Field mask is used to specify the fields to be overwritten in the Features resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `description` * `labels` * `disable_monitoring` (Not supported for FeatureRegistryService Feature) * `point_of_contact` (Not supported for FeaturestoreService FeatureStore)", + "type": "string" + }, + "name": { + "description": "Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.", + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+$" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Updates the parameters of a single Feature.", + "id": "aiplatform.projects.locations.featureGroups.features.patch", + "parameterOrder": [ + "name" + ] + }, + "create": { + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.featureGroups.features.create", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1Feature" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features", + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", + "required": true, + "location": "path", + "type": "string", + "description": "Required. The resource name of the EntityType or FeatureGroup to create a Feature. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`" + }, + "featureId": { + "type": "string", + "description": "Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.", + "location": "query" + } + }, + "httpMethod": "POST", + "path": "v1/{+parent}/features", + "description": "Creates a new Feature in a given FeatureGroup." + }, + "delete": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+$", + "required": true, + "description": "Required. The name of the Features to be deleted. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}`", + "type": "string", + "location": "path" + } + }, + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}", + "path": "v1/{+name}", + "description": "Deletes a single Feature.", + "id": "aiplatform.projects.locations.featureGroups.features.delete", + "httpMethod": "DELETE" + } + }, + "resources": { + "operations": { + "methods": { + "delete": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "type": "string", + "description": "The name of the operation resource to be deleted." + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}", + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.featureGroups.features.operations.delete", + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "wait": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+/operations/[^/]+$", + "location": "path", + "required": true, + "type": "string", + "description": "The name of the operation resource to wait on." + }, + "timeout": { + "type": "string", + "location": "query", + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "path": "v1/{+name}:wait", + "id": "aiplatform.projects.locations.featureGroups.features.operations.wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." + }, + "get": { + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameters": { + "name": { + "location": "path", + "required": true, + "description": "The name of the operation resource.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+/operations/[^/]+$" + } + }, + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.featureGroups.features.operations.get", + "httpMethod": "GET", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ] + }, + "listWait": { + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}:wait", + "parameters": { + "pageSize": { + "type": "integer", + "description": "The standard list page size.", + "location": "query", + "format": "int32" + }, + "pageToken": { + "description": "The standard list page token.", + "location": "query", + "type": "string" + }, + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+/operations/[^/]+$", + "type": "string", + "location": "path", + "description": "The name of the operation's parent resource." + }, + "filter": { + "location": "query", + "description": "The standard list filter.", + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}:wait", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "id": "aiplatform.projects.locations.featureGroups.features.operations.listWait" + } + } + } + } + } + }, + "methods": { + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "DELETE", + "description": "Deletes a single FeatureGroup.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}", + "path": "v1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.featureGroups.delete", + "parameters": { + "force": { + "description": "If set to true, any Features under this FeatureGroup will also be deleted. (Otherwise, the request will only work if the FeatureGroup has no Features.)", + "location": "query", + "type": "boolean" + }, + "name": { + "location": "path", + "description": "Required. The name of the FeatureGroup to be deleted. Format: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", + "required": true, + "type": "string" + } + } + }, + "patch": { + "parameters": { + "updateMask": { + "description": "Field mask is used to specify the fields to be overwritten in the FeatureGroup resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `description` * `big_query` * `big_query.entity_id_columns`", + "format": "google-fieldmask", + "location": "query", + "type": "string" + }, + "name": { + "required": true, + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", + "description": "Identifier. Name of the FeatureGroup. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}`" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1FeatureGroup" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}", + "path": "v1/{+name}", + "description": "Updates the parameters of a single FeatureGroup.", + "httpMethod": "PATCH", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.featureGroups.patch" + }, + "get": { + "path": "v1/{+name}", + "description": "Gets details of a single FeatureGroup.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}", + "id": "aiplatform.projects.locations.featureGroups.get", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "description": "Required. The name of the FeatureGroup resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", + "type": "string", + "location": "path", + "required": true + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1FeatureGroup" + } + }, + "list": { + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+parent}/featureGroups", + "description": "Lists FeatureGroups in a given project and location.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups", + "id": "aiplatform.projects.locations.featureGroups.list", + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1ListFeatureGroupsResponse" + }, + "parameters": { + "pageSize": { + "type": "integer", + "location": "query", + "description": "The maximum number of FeatureGroups to return. The service may return fewer than this value. If unspecified, at most 100 FeatureGroups will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100.", + "format": "int32" + }, + "orderBy": { + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported Fields: * `create_time` * `update_time`", + "location": "query", + "type": "string" + }, + "parent": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string", + "description": "Required. The resource name of the Location to list FeatureGroups. Format: `projects/{project}/locations/{location}`", + "location": "path" + }, + "pageToken": { + "description": "A page token, received from a previous FeatureGroupAdminService.ListFeatureGroups call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureGroupAdminService.ListFeatureGroups must match the call that provided the page token.", + "type": "string", + "location": "query" + }, + "filter": { + "location": "query", + "type": "string", + "description": "Lists the FeatureGroups that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality and key presence. Examples: * `create_time \u003e \"2020-01-01\" OR update_time \u003e \"2020-01-01\"` FeatureGroups created or updated after 2020-01-01. * `labels.env = \"prod\"` FeatureGroups with label \"env\" set to \"prod\"." + } + } + }, + "create": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.featureGroups.create", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "featureGroupId": { + "location": "query", + "description": "Required. The ID to use for this FeatureGroup, which will become the final component of the FeatureGroup's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location.", + "type": "string" + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location to create FeatureGroups. Format: `projects/{project}/locations/{location}`", + "location": "path", + "type": "string", + "required": true + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups", + "request": { + "$ref": "GoogleCloudAiplatformV1FeatureGroup" + }, + "path": "v1/{+parent}/featureGroups", + "description": "Creates a new FeatureGroup in a given project and location.", + "httpMethod": "POST", + "parameterOrder": [ + "parent" + ] + } + } + }, + "featureOnlineStores": { + "resources": { + "featureViews": { + "methods": { + "patch": { + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "parameters": { + "updateMask": { + "format": "google-fieldmask", + "location": "query", + "description": "Field mask is used to specify the fields to be overwritten in the FeatureView resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `service_agent_type` * `big_query_source` * `big_query_source.uri` * `big_query_source.entity_id_columns` * `feature_registry_source` * `feature_registry_source.feature_groups` * `sync_config` * `sync_config.cron`", + "type": "string" + }, + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", + "required": true, + "description": "Identifier. Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`", + "type": "string" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.patch", + "request": { + "$ref": "GoogleCloudAiplatformV1FeatureView" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}", + "httpMethod": "PATCH", + "description": "Updates the parameters of a single FeatureView." + }, + "searchNearestEntities": { + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.searchNearestEntities", + "response": { + "$ref": "GoogleCloudAiplatformV1SearchNearestEntitiesResponse" + }, + "description": "Search the nearest entities under a FeatureView. Search only works for indexable feature view; if a feature view isn't indexable, returns Invalid argument response.", + "parameters": { + "featureView": { + "description": "Required. FeatureView resource format `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/{featureView}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", + "location": "path", + "required": true + } + }, + "path": "v1/{+featureView}:searchNearestEntities", + "parameterOrder": [ + "featureView" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1SearchNearestEntitiesRequest" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:searchNearestEntities", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST" + }, + "create": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+parent}/featureViews", + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.create", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews", + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Creates a new FeatureView in a given FeatureOnlineStore.", + "parameters": { + "featureViewId": { + "location": "query", + "description": "Required. The ID to use for the FeatureView, which will become the final component of the FeatureView's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within a FeatureOnlineStore.", + "type": "string" + }, + "parent": { + "type": "string", + "description": "Required. The resource name of the FeatureOnlineStore to create FeatureViews. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}`", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", + "location": "path", + "required": true + }, + "runSyncImmediately": { + "location": "query", + "description": "Immutable. If set to true, one on demand sync will be run immediately, regardless whether the FeatureView.sync_config is configured or not.", + "type": "boolean" + } + }, + "parameterOrder": [ + "parent" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1FeatureView" + } + }, + "list": { + "response": { + "$ref": "GoogleCloudAiplatformV1ListFeatureViewsResponse" + }, + "path": "v1/{+parent}/featureViews", + "httpMethod": "GET", + "description": "Lists FeatureViews in a given FeatureOnlineStore.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.list", + "parameters": { + "orderBy": { + "type": "string", + "location": "query", + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `feature_view_id` * `create_time` * `update_time`" + }, + "pageSize": { + "description": "The maximum number of FeatureViews to return. The service may return fewer than this value. If unspecified, at most 1000 FeatureViews will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000.", + "format": "int32", + "type": "integer", + "location": "query" + }, + "filter": { + "description": "Lists the FeatureViews that match the filter expression. The following filters are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003e=`, and `\u003c=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003e=`, and `\u003c=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality as well as key presence. Examples: * `create_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\" OR update_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\"` --\u003e FeatureViews created or updated after 2020-01-31T15:30:00.000000Z. * `labels.active = yes AND labels.env = prod` --\u003e FeatureViews having both (active: yes) and (env: prod) labels. * `labels.env: *` --\u003e Any FeatureView which has a label with 'env' as the key.", + "location": "query", + "type": "string" + }, + "parent": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", + "location": "path", + "description": "Required. The resource name of the FeatureOnlineStore to list FeatureViews. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}`", + "required": true + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "A page token, received from a previous FeatureOnlineStoreAdminService.ListFeatureViews call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureOnlineStoreAdminService.ListFeatureViews must match the call that provided the page token." + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews" + }, + "get": { + "response": { + "$ref": "GoogleCloudAiplatformV1FeatureView" + }, + "httpMethod": "GET", + "parameters": { + "name": { + "type": "string", + "location": "path", + "description": "Required. The name of the FeatureView resource. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "description": "Gets details of a single FeatureView.", + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.get", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}" + }, + "sync": { + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.sync", + "request": { + "$ref": "GoogleCloudAiplatformV1SyncFeatureViewRequest" + }, + "parameters": { + "featureView": { + "type": "string", + "location": "path", + "description": "Required. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "parameterOrder": [ + "featureView" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1SyncFeatureViewResponse" + }, + "path": "v1/{+featureView}:sync", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:sync", + "description": "Triggers on-demand sync for the FeatureView." + }, + "fetchFeatureValues": { + "parameterOrder": [ + "featureView" + ], + "httpMethod": "POST", + "response": { + "$ref": "GoogleCloudAiplatformV1FetchFeatureValuesResponse" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1FetchFeatureValuesRequest" + }, + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.fetchFeatureValues", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Fetch feature values under a FeatureView.", + "path": "v1/{+featureView}:fetchFeatureValues", + "parameters": { + "featureView": { + "location": "path", + "required": true, + "description": "Required. FeatureView resource format `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/{featureView}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:fetchFeatureValues" + }, + "delete": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a single FeatureView.", + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.delete", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}", + "path": "v1/{+name}", + "httpMethod": "DELETE", + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", + "location": "path", + "required": true, + "description": "Required. The name of the FeatureView to be deleted. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`" + } + } + } + }, + "resources": { + "featureViewSyncs": { + "methods": { + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+parent}/featureViewSyncs", + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.featureViewSyncs.list", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/featureViewSyncs", + "parameterOrder": [ + "parent" + ], + "httpMethod": "GET", + "description": "Lists FeatureViewSyncs in a given FeatureView.", + "parameters": { + "pageToken": { + "description": "A page token, received from a previous FeatureOnlineStoreAdminService.ListFeatureViewSyncs call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureOnlineStoreAdminService.ListFeatureViewSyncs must match the call that provided the page token.", + "type": "string", + "location": "query" + }, + "pageSize": { + "location": "query", + "type": "integer", + "format": "int32", + "description": "The maximum number of FeatureViewSyncs to return. The service may return fewer than this value. If unspecified, at most 1000 FeatureViewSyncs will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000." + }, + "filter": { + "type": "string", + "location": "query", + "description": "Lists the FeatureViewSyncs that match the filter expression. The following filters are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003e=`, and `\u003c=` comparisons. Values must be in RFC 3339 format. Examples: * `create_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\"` --\u003e FeatureViewSyncs created after 2020-01-31T15:30:00.000000Z." + }, + "orderBy": { + "location": "query", + "type": "string", + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `create_time`" + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", + "required": true, + "type": "string", + "location": "path", + "description": "Required. The resource name of the FeatureView to list FeatureViewSyncs. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1ListFeatureViewSyncsResponse" + } + }, + "get": { + "parameters": { + "name": { + "location": "path", + "type": "string", + "description": "Required. The name of the FeatureViewSync resource. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}/featureViewSyncs/{feature_view_sync}`", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+/featureViewSyncs/[^/]+$", + "required": true + } + }, + "path": "v1/{+name}", + "response": { + "$ref": "GoogleCloudAiplatformV1FeatureViewSync" + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.featureViewSyncs.get", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/featureViewSyncs/{featureViewSyncsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets details of a single FeatureViewSync.", + "httpMethod": "GET" + } + } + }, + "operations": { + "methods": { + "get": { + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}", + "path": "v1/{+name}", + "parameters": { + "name": { + "required": true, + "description": "The name of the operation resource.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.operations.get", + "httpMethod": "GET" + }, + "listWait": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.operations.listWait", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "filter": { + "description": "The standard list filter.", + "location": "query", + "type": "string" + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token." + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", + "description": "The name of the operation's parent resource.", + "location": "path", + "required": true, + "type": "string" + }, + "pageSize": { + "type": "integer", + "location": "query", + "format": "int32", + "description": "The standard list page size." + } + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "path": "v1/{+name}:wait", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}:wait" + }, + "wait": { + "parameters": { + "name": { + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", + "type": "string", + "required": true, + "location": "path" + }, + "timeout": { + "location": "query", + "format": "google-duration", + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "path": "v1/{+name}:wait", + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.operations.wait", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." + }, + "delete": { + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.operations.delete", + "path": "v1/{+name}", + "httpMethod": "DELETE", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be deleted." + } + } + } + } + } + } + }, + "operations": { + "methods": { + "get": { + "path": "v1/{+name}", + "parameters": { + "name": { + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/operations/[^/]+$", + "required": true, + "type": "string", + "location": "path" + } + }, + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.featureOnlineStores.operations.get", + "parameterOrder": [ + "name" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "listWait": { + "id": "aiplatform.projects.locations.featureOnlineStores.operations.listWait", + "path": "v1/{+name}:wait", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}:wait", + "parameters": { + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + }, + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation's parent resource.", + "required": true + }, + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "pageSize": { + "type": "integer", + "description": "The standard list page size.", + "format": "int32", + "location": "query" + } + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ] + }, + "delete": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/operations/[^/]+$", + "required": true, + "description": "The name of the operation resource to be deleted." + } + }, + "httpMethod": "DELETE", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.featureOnlineStores.operations.delete" + }, + "wait": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}:wait", + "parameters": { + "timeout": { + "format": "google-duration", + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string" + }, + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "type": "string" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.featureOnlineStores.operations.wait", + "path": "v1/{+name}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "httpMethod": "POST", + "parameterOrder": [ + "name" + ] + } + } + } + }, + "methods": { + "patch": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.featureOnlineStores.patch", + "httpMethod": "PATCH", + "parameters": { + "name": { + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", + "description": "Identifier. Name of the FeatureOnlineStore. Format: `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}`", + "type": "string" + }, + "updateMask": { + "location": "query", + "description": "Field mask is used to specify the fields to be overwritten in the FeatureOnlineStore resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `description` * `bigtable` * `bigtable.auto_scaling` * `bigtable.enable_multi_region_replica`", + "format": "google-fieldmask", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1FeatureOnlineStore" + }, + "description": "Updates the parameters of a single FeatureOnlineStore.", + "path": "v1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "get": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1FeatureOnlineStore" + }, + "id": "aiplatform.projects.locations.featureOnlineStores.get", + "description": "Gets details of a single FeatureOnlineStore.", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "path": "v1/{+name}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", + "location": "path", + "required": true, + "description": "Required. The name of the FeatureOnlineStore resource.", + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}" + }, + "list": { + "id": "aiplatform.projects.locations.featureOnlineStores.list", + "response": { + "$ref": "GoogleCloudAiplatformV1ListFeatureOnlineStoresResponse" + }, + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "description": "Lists FeatureOnlineStores in a given project and location.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores", + "path": "v1/{+parent}/featureOnlineStores", + "parameters": { + "pageToken": { + "type": "string", + "description": "A page token, received from a previous FeatureOnlineStoreAdminService.ListFeatureOnlineStores call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureOnlineStoreAdminService.ListFeatureOnlineStores must match the call that provided the page token.", + "location": "query" + }, + "parent": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "description": "Required. The resource name of the Location to list FeatureOnlineStores. Format: `projects/{project}/locations/{location}`", + "required": true + }, + "pageSize": { + "description": "The maximum number of FeatureOnlineStores to return. The service may return fewer than this value. If unspecified, at most 100 FeatureOnlineStores will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100.", + "type": "integer", + "location": "query", + "format": "int32" + }, + "filter": { + "description": "Lists the FeatureOnlineStores that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality and key presence. Examples: * `create_time \u003e \"2020-01-01\" OR update_time \u003e \"2020-01-01\"` FeatureOnlineStores created or updated after 2020-01-01. * `labels.env = \"prod\"` FeatureOnlineStores with label \"env\" set to \"prod\".", + "type": "string", + "location": "query" + }, + "orderBy": { + "type": "string", + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported Fields: * `create_time` * `update_time`", + "location": "query" + } + } + }, + "create": { + "parameters": { + "featureOnlineStoreId": { + "location": "query", + "type": "string", + "description": "Required. The ID to use for this FeatureOnlineStore, which will become the final component of the FeatureOnlineStore's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location." + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "description": "Required. The resource name of the Location to create FeatureOnlineStores. Format: `projects/{project}/locations/{location}`", + "required": true, + "type": "string" + } + }, + "description": "Creates a new FeatureOnlineStore in a given project and location.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores", + "id": "aiplatform.projects.locations.featureOnlineStores.create", + "parameterOrder": [ + "parent" + ], + "path": "v1/{+parent}/featureOnlineStores", + "request": { + "$ref": "GoogleCloudAiplatformV1FeatureOnlineStore" + }, + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "delete": { + "description": "Deletes a single FeatureOnlineStore. The FeatureOnlineStore must not contain any FeatureViews.", + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", + "description": "Required. The name of the FeatureOnlineStore to be deleted. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}`", + "required": true, + "type": "string", + "location": "path" + }, + "force": { + "type": "boolean", + "location": "query", + "description": "If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted. (Otherwise, the request will only work if the FeatureOnlineStore has no FeatureViews.)" + } + }, + "id": "aiplatform.projects.locations.featureOnlineStores.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}", + "httpMethod": "DELETE" + } + } + }, + "indexEndpoints": { + "resources": { + "operations": { + "methods": { + "delete": { + "path": "v1/{+name}", + "parameters": { + "name": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+/operations/[^/]+$", + "required": true, + "description": "The name of the operation resource to be deleted." + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.indexEndpoints.operations.delete", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations/{operationsId}", + "httpMethod": "DELETE", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." + }, + "cancel": { + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations/{operationsId}:cancel", + "parameters": { + "name": { + "required": true, + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.indexEndpoints.operations.cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1/{+name}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`." + }, + "get": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.indexEndpoints.operations.get", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET" + }, + "list": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations", + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "id": "aiplatform.projects.locations.indexEndpoints.operations.list", + "httpMethod": "GET", + "parameters": { + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter." + }, + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + }, + "pageSize": { + "type": "integer", + "location": "query", + "format": "int32", + "description": "The standard list page size." + }, + "name": { + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", + "type": "string", + "location": "path", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." + }, + "wait": { + "httpMethod": "POST", + "id": "aiplatform.projects.locations.indexEndpoints.operations.wait", + "parameters": { + "timeout": { + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "type": "string" + }, + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "type": "string" + } + }, + "path": "v1/{+name}:wait", + "parameterOrder": [ + "name" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations/{operationsId}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + } + } + } + } + }, + "methods": { + "findNeighbors": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:findNeighbors", + "path": "v1/{+indexEndpoint}:findNeighbors", + "id": "aiplatform.projects.locations.indexEndpoints.findNeighbors", + "response": { + "$ref": "GoogleCloudAiplatformV1FindNeighborsResponse" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1FindNeighborsRequest" + }, + "description": "Finds the nearest neighbors of each vector within the request.", + "parameters": { + "indexEndpoint": { + "type": "string", + "required": true, + "description": "Required. The name of the index endpoint. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "indexEndpoint" + ], + "httpMethod": "POST" + }, + "mutateDeployedIndex": { + "parameters": { + "indexEndpoint": { + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", + "type": "string", + "required": true, + "location": "path", + "description": "Required. The name of the IndexEndpoint resource into which to deploy an Index. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.indexEndpoints.mutateDeployedIndex", + "request": { + "$ref": "GoogleCloudAiplatformV1DeployedIndex" + }, + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:mutateDeployedIndex", + "description": "Update an existing DeployedIndex under an IndexEndpoint.", + "path": "v1/{+indexEndpoint}:mutateDeployedIndex", + "parameterOrder": [ + "indexEndpoint" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "patch": { + "response": { + "$ref": "GoogleCloudAiplatformV1IndexEndpoint" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "parameters": { + "name": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", + "description": "Output only. The resource name of the IndexEndpoint.", + "required": true + }, + "updateMask": { + "location": "query", + "format": "google-fieldmask", + "description": "Required. The update mask applies to the resource. See google.protobuf.FieldMask.", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.indexEndpoints.patch", + "request": { + "$ref": "GoogleCloudAiplatformV1IndexEndpoint" + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "PATCH", + "description": "Updates an IndexEndpoint.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}" + }, + "undeployIndex": { + "request": { + "$ref": "GoogleCloudAiplatformV1UndeployIndexRequest" + }, + "path": "v1/{+indexEndpoint}:undeployIndex", + "description": "Undeploys an Index from an IndexEndpoint, removing a DeployedIndex from it, and freeing all resources it's using.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:undeployIndex", + "parameters": { + "indexEndpoint": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", + "type": "string", + "description": "Required. The name of the IndexEndpoint resource from which to undeploy an Index. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", + "location": "path" + } + }, + "httpMethod": "POST", + "parameterOrder": [ + "indexEndpoint" + ], + "id": "aiplatform.projects.locations.indexEndpoints.undeployIndex", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "get": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}", + "description": "Gets an IndexEndpoint.", + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", + "location": "path", + "type": "string", + "description": "Required. The name of the IndexEndpoint resource. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`" + } + }, + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.indexEndpoints.get", + "response": { + "$ref": "GoogleCloudAiplatformV1IndexEndpoint" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET" + }, + "deployIndex": { + "httpMethod": "POST", + "path": "v1/{+indexEndpoint}:deployIndex", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deploys an Index into this IndexEndpoint, creating a DeployedIndex within it. Only non-empty Indexes can be deployed.", + "request": { + "$ref": "GoogleCloudAiplatformV1DeployIndexRequest" + }, + "parameterOrder": [ + "indexEndpoint" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.indexEndpoints.deployIndex", + "parameters": { + "indexEndpoint": { + "description": "Required. The name of the IndexEndpoint resource into which to deploy an Index. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", + "required": true + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:deployIndex" + }, + "readIndexDatapoints": { + "request": { + "$ref": "GoogleCloudAiplatformV1ReadIndexDatapointsRequest" + }, + "path": "v1/{+indexEndpoint}:readIndexDatapoints", + "id": "aiplatform.projects.locations.indexEndpoints.readIndexDatapoints", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "indexEndpoint": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", + "type": "string", + "location": "path", + "description": "Required. The name of the index endpoint. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`" + } + }, + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:readIndexDatapoints", + "parameterOrder": [ + "indexEndpoint" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1ReadIndexDatapointsResponse" + }, + "description": "Reads the datapoints/vectors of the given IDs. A maximum of 1000 datapoints can be retrieved in a batch." + }, + "delete": { + "httpMethod": "DELETE", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.indexEndpoints.delete", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "description": "Deletes an IndexEndpoint.", + "parameters": { + "name": { + "description": "Required. The name of the IndexEndpoint resource to be deleted. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", + "type": "string" + } + } + }, + "create": { + "id": "aiplatform.projects.locations.indexEndpoints.create", + "path": "v1/{+parent}/indexEndpoints", + "description": "Creates an IndexEndpoint.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1IndexEndpoint" + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints", + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "required": true, + "type": "string", + "description": "Required. The resource name of the Location to create the IndexEndpoint in. Format: `projects/{project}/locations/{location}`" + } + }, + "httpMethod": "POST", + "parameterOrder": [ + "parent" + ] + }, + "list": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints", + "description": "Lists IndexEndpoints in a Location.", + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.indexEndpoints.list", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "parameters": { + "pageSize": { + "description": "Optional. The standard list page size.", + "location": "query", + "type": "integer", + "format": "int32" + }, + "readMask": { + "type": "string", + "format": "google-fieldmask", + "description": "Optional. Mask specifying which fields to read.", + "location": "query" + }, + "filter": { + "type": "string", + "location": "query", + "description": "Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `index_endpoint` supports = and !=. `index_endpoint` represents the IndexEndpoint ID, ie. the last segment of the IndexEndpoint's resourcename. * `display_name` supports =, != and regex() (uses [re2](https://github.com/google/re2/wiki/Syntax) syntax) * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* or labels:key - key existence A key including a space must be quoted. `labels.\"a key\"`. Some examples: * `index_endpoint=\"1\"` * `display_name=\"myDisplayName\"` * `regex(display_name, \"^A\") -\u003e The display name starts with an A. * `labels.myKey=\"myValue\"`" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "Optional. The standard list page token. Typically obtained via ListIndexEndpointsResponse.next_page_token of the previous IndexEndpointService.ListIndexEndpoints call." + }, + "parent": { + "location": "path", + "description": "Required. The resource name of the Location from which to list the IndexEndpoints. Format: `projects/{project}/locations/{location}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1ListIndexEndpointsResponse" + }, + "path": "v1/{+parent}/indexEndpoints" + } + } + }, + "endpoints": { + "resources": { + "operations": { + "methods": { + "get": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+/operations/[^/]+$", + "location": "path", + "required": true, + "description": "The name of the operation resource." + } + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.endpoints.operations.get" + }, + "cancel": { + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string", + "required": true, + "description": "The name of the operation resource to be cancelled." + } + }, + "path": "v1/{+name}:cancel", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations/{operationsId}:cancel", + "id": "aiplatform.projects.locations.endpoints.operations.cancel" + }, + "wait": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.endpoints.operations.wait", + "parameterOrder": [ + "name" + ], + "parameters": { + "timeout": { + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "type": "string" + }, + "name": { + "location": "path", + "description": "The name of the operation resource to wait on.", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+/operations/[^/]+$" + } + }, + "httpMethod": "POST", + "path": "v1/{+name}:wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations/{operationsId}:wait" + }, + "delete": { + "httpMethod": "DELETE", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations/{operationsId}", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string", + "description": "The name of the operation resource to be deleted.", + "required": true + } + }, + "id": "aiplatform.projects.locations.endpoints.operations.delete", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + } + }, + "list": { + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "pageToken": { + "description": "The standard list page token.", + "location": "query", + "type": "string" + }, + "pageSize": { + "type": "integer", + "description": "The standard list page size.", + "format": "int32", + "location": "query" + }, + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "name": { + "required": true, + "description": "The name of the operation's parent resource.", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$" + } + }, + "httpMethod": "GET", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "id": "aiplatform.projects.locations.endpoints.operations.list", + "path": "v1/{+name}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations" + } + } + } + }, + "methods": { + "serverStreamingPredict": { + "httpMethod": "POST", + "response": { + "$ref": "GoogleCloudAiplatformV1StreamingPredictResponse" + }, + "parameters": { + "endpoint": { + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "location": "path", + "required": true, + "type": "string" + } + }, + "description": "Perform a server-side streaming online prediction request for Vertex LLM streaming.", + "id": "aiplatform.projects.locations.endpoints.serverStreamingPredict", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:serverStreamingPredict", + "request": { + "$ref": "GoogleCloudAiplatformV1StreamingPredictRequest" + }, + "path": "v1/{+endpoint}:serverStreamingPredict", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "parameterOrder": [ + "endpoint" + ] + }, + "rawPredict": { + "response": { + "$ref": "GoogleApiHttpBody" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "parameterOrder": [ + "endpoint" + ], + "description": "Perform an online prediction with an arbitrary HTTP payload. The response includes the following HTTP headers: * `X-Vertex-AI-Endpoint-Id`: ID of the Endpoint that served this prediction. * `X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's DeployedModel that served this prediction.", + "parameters": { + "endpoint": { + "type": "string", + "location": "path", + "required": true, + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:rawPredict", + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1RawPredictRequest" + }, + "id": "aiplatform.projects.locations.endpoints.rawPredict", + "path": "v1/{+endpoint}:rawPredict" + }, + "undeployModel": { + "path": "v1/{+endpoint}:undeployModel", + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1UndeployModelRequest" + }, + "parameters": { + "endpoint": { + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "description": "Required. The name of the Endpoint resource from which to undeploy a Model. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "endpoint" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:undeployModel", + "description": "Undeploys a Model from an Endpoint, removing a DeployedModel from it, and freeing all resources it's using.", + "id": "aiplatform.projects.locations.endpoints.undeployModel" + }, + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "parameters": { + "filter": { + "description": "Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `endpoint` supports `=` and `!=`. `endpoint` represents the Endpoint ID, i.e. the last segment of the Endpoint's resource name. * `display_name` supports `=` and `!=`. * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:*` or `labels:key` - key existence * A key including a space must be quoted. `labels.\"a key\"`. * `base_model_name` only supports `=`. Some examples: * `endpoint=1` * `displayName=\"myDisplayName\"` * `labels.myKey=\"myValue\"` * `baseModelName=\"text-bison\"`", + "location": "query", + "type": "string" + }, + "orderBy": { + "location": "query", + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`.", + "type": "string" + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "description": "Required. The resource name of the Location from which to list the Endpoints. Format: `projects/{project}/locations/{location}`", + "required": true, + "type": "string" + }, + "pageToken": { + "type": "string", + "description": "Optional. The standard list page token. Typically obtained via ListEndpointsResponse.next_page_token of the previous EndpointService.ListEndpoints call.", + "location": "query" + }, + "readMask": { + "description": "Optional. Mask specifying which fields to read.", + "location": "query", + "format": "google-fieldmask", + "type": "string" + }, + "pageSize": { + "format": "int32", + "type": "integer", + "description": "Optional. The standard list page size.", + "location": "query" + } + }, + "id": "aiplatform.projects.locations.endpoints.list", + "response": { + "$ref": "GoogleCloudAiplatformV1ListEndpointsResponse" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints", + "httpMethod": "GET", + "description": "Lists Endpoints in a Location.", + "path": "v1/{+parent}/endpoints" + }, + "directPredict": { + "id": "aiplatform.projects.locations.endpoints.directPredict", + "parameterOrder": [ + "endpoint" + ], + "path": "v1/{+endpoint}:directPredict", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:directPredict", + "parameters": { + "endpoint": { + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "required": true, + "location": "path", + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "type": "string" + } + }, + "httpMethod": "POST", + "response": { + "$ref": "GoogleCloudAiplatformV1DirectPredictResponse" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1DirectPredictRequest" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "description": "Perform an unary online prediction request to a gRPC model server for Vertex first-party products and frameworks." + }, + "get": { + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.endpoints.get", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}", + "parameters": { + "name": { + "description": "Required. The name of the Endpoint resource. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "location": "path", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "description": "Gets an Endpoint.", + "response": { + "$ref": "GoogleCloudAiplatformV1Endpoint" + } + }, + "computeTokens": { + "parameters": { + "endpoint": { + "description": "Required. The name of the Endpoint requested to get lists of tokens and token ids.", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "location": "path" + } + }, + "description": "Return a list of tokens based on the input text.", + "request": { + "$ref": "GoogleCloudAiplatformV1ComputeTokensRequest" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:computeTokens", + "parameterOrder": [ + "endpoint" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1ComputeTokensResponse" + }, + "id": "aiplatform.projects.locations.endpoints.computeTokens", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+endpoint}:computeTokens", + "httpMethod": "POST" + }, + "countTokens": { + "parameterOrder": [ + "endpoint" + ], + "id": "aiplatform.projects.locations.endpoints.countTokens", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:countTokens", + "path": "v1/{+endpoint}:countTokens", + "parameters": { + "endpoint": { + "description": "Required. The name of the Endpoint requested to perform token counting. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "required": true, + "location": "path" + } + }, + "httpMethod": "POST", + "response": { + "$ref": "GoogleCloudAiplatformV1CountTokensResponse" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1CountTokensRequest" + }, + "description": "Perform a token counting." + }, + "directRawPredict": { + "response": { + "$ref": "GoogleCloudAiplatformV1DirectRawPredictResponse" + }, + "id": "aiplatform.projects.locations.endpoints.directRawPredict", + "request": { + "$ref": "GoogleCloudAiplatformV1DirectRawPredictRequest" + }, + "parameterOrder": [ + "endpoint" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:directRawPredict", + "path": "v1/{+endpoint}:directRawPredict", + "description": "Perform an unary online prediction request to a gRPC model server for custom containers.", + "httpMethod": "POST", + "parameters": { + "endpoint": { + "location": "path", + "required": true, + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ] + }, + "generateContent": { + "request": { + "$ref": "GoogleCloudAiplatformV1GenerateContentRequest" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "path": "v1/{+model}:generateContent", + "id": "aiplatform.projects.locations.endpoints.generateContent", + "description": "Generate content with multimodal inputs.", + "httpMethod": "POST", + "parameterOrder": [ + "model" + ], + "parameters": { + "model": { + "type": "string", + "location": "path", + "required": true, + "description": "Required. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1GenerateContentResponse" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:generateContent" + }, + "explain": { + "request": { + "$ref": "GoogleCloudAiplatformV1ExplainRequest" + }, + "httpMethod": "POST", + "parameterOrder": [ + "endpoint" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:explain", + "path": "v1/{+endpoint}:explain", + "description": "Perform an online explanation. If deployed_model_id is specified, the corresponding DeployModel must have explanation_spec populated. If deployed_model_id is not specified, all DeployedModels must have explanation_spec populated.", + "parameters": { + "endpoint": { + "description": "Required. The name of the Endpoint requested to serve the explanation. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1ExplainResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "id": "aiplatform.projects.locations.endpoints.explain" + }, + "deployModel": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:deployModel", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "endpoint" + ], + "id": "aiplatform.projects.locations.endpoints.deployModel", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Deploys a Model into this Endpoint, creating a DeployedModel within it.", + "parameters": { + "endpoint": { + "type": "string", + "location": "path", + "required": true, + "description": "Required. The name of the Endpoint resource into which to deploy a Model. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$" + } + }, + "path": "v1/{+endpoint}:deployModel", + "request": { + "$ref": "GoogleCloudAiplatformV1DeployModelRequest" + } + }, + "delete": { + "httpMethod": "DELETE", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "description": "Required. The name of the Endpoint resource to be deleted. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$" + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.endpoints.delete", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}", + "path": "v1/{+name}", + "description": "Deletes an Endpoint.", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "predict": { + "description": "Perform an online prediction.", + "response": { + "$ref": "GoogleCloudAiplatformV1PredictResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "id": "aiplatform.projects.locations.endpoints.predict", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:predict", + "path": "v1/{+endpoint}:predict", + "parameterOrder": [ + "endpoint" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1PredictRequest" + }, + "parameters": { + "endpoint": { + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "type": "string", + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" + } + }, + "httpMethod": "POST" + }, + "mutateDeployedModel": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "parameters": { + "endpoint": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "description": "Required. The name of the Endpoint resource into which to mutate a DeployedModel. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "required": true, + "type": "string" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1MutateDeployedModelRequest" + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.endpoints.mutateDeployedModel", + "path": "v1/{+endpoint}:mutateDeployedModel", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:mutateDeployedModel", + "description": "Updates an existing deployed model. Updatable fields include `min_replica_count`, `max_replica_count`, `autoscaling_metric_specs`, `disable_container_logging` (v1 only), and `enable_container_logging` (v1beta1 only).", + "parameterOrder": [ + "endpoint" + ] + }, + "patch": { + "description": "Updates an Endpoint.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}", + "parameters": { + "updateMask": { + "format": "google-fieldmask", + "type": "string", + "location": "query", + "description": "Required. The update mask applies to the resource. See google.protobuf.FieldMask." + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "type": "string", + "location": "path", + "required": true, + "description": "Output only. The resource name of the Endpoint." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1Endpoint" + }, + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.endpoints.patch", + "httpMethod": "PATCH", + "response": { + "$ref": "GoogleCloudAiplatformV1Endpoint" + } + }, + "create": { + "parameterOrder": [ + "parent" + ], + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1Endpoint" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+parent}/endpoints", + "parameters": { + "endpointId": { + "description": "Immutable. The ID to use for endpoint, which will become the final component of the endpoint resource name. If not provided, Vertex AI will generate a value for this ID. If the first character is a letter, this value may be up to 63 characters, and valid characters are `[a-z0-9-]`. The last character must be a letter or number. If the first character is a number, this value may be up to 9 characters, and valid characters are `[0-9]` with no leading zeros. When using HTTP/JSON, this field is populated based on a query string argument, such as `?endpoint_id=12345`. This is the fallback for fields that are not included in either the URI or the body.", + "location": "query", + "type": "string" + }, + "parent": { + "location": "path", + "required": true, + "description": "Required. The resource name of the Location to create the Endpoint in. Format: `projects/{project}/locations/{location}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Creates an Endpoint.", + "id": "aiplatform.projects.locations.endpoints.create" + }, + "streamRawPredict": { + "id": "aiplatform.projects.locations.endpoints.streamRawPredict", + "request": { + "$ref": "GoogleCloudAiplatformV1StreamRawPredictRequest" + }, + "path": "v1/{+endpoint}:streamRawPredict", + "response": { + "$ref": "GoogleApiHttpBody" + }, + "httpMethod": "POST", + "parameters": { + "endpoint": { + "required": true, + "type": "string", + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$" + } + }, + "parameterOrder": [ + "endpoint" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:streamRawPredict", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "description": "Perform a streaming online prediction with an arbitrary HTTP payload." + }, + "streamGenerateContent": { + "parameterOrder": [ + "model" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "path": "v1/{+model}:streamGenerateContent", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:streamGenerateContent", + "httpMethod": "POST", + "parameters": { + "model": { + "required": true, + "description": "Required. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.endpoints.streamGenerateContent", + "request": { + "$ref": "GoogleCloudAiplatformV1GenerateContentRequest" + }, + "response": { + "$ref": "GoogleCloudAiplatformV1GenerateContentResponse" + }, + "description": "Generate content with multimodal inputs with streaming support." + } + } + }, + "specialistPools": { + "resources": { + "operations": { + "methods": { + "list": { + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "id": "aiplatform.projects.locations.specialistPools.operations.list", + "parameterOrder": [ + "name" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "parameters": { + "pageSize": { + "description": "The standard list page size.", + "location": "query", + "format": "int32", + "type": "integer" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + }, + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter." + }, + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+$", + "type": "string", + "required": true, + "description": "The name of the operation's parent resource." + } + }, + "path": "v1/{+name}/operations" + }, + "get": { + "id": "aiplatform.projects.locations.specialistPools.operations.get", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations/{operationsId}", + "path": "v1/{+name}", + "parameters": { + "name": { + "description": "The name of the operation resource.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+/operations/[^/]+$", + "type": "string", + "required": true + } + }, + "parameterOrder": [ + "name" + ] + }, + "cancel": { + "parameters": { + "name": { + "required": true, + "description": "The name of the operation resource to be cancelled.", + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+/operations/[^/]+$" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations/{operationsId}:cancel", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "id": "aiplatform.projects.locations.specialistPools.operations.cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "path": "v1/{+name}:cancel" + }, + "delete": { + "id": "aiplatform.projects.locations.specialistPools.operations.delete", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE", + "parameters": { + "name": { + "type": "string", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be deleted." + } + }, + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + } + }, + "wait": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}:wait", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations/{operationsId}:wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "parameters": { + "timeout": { + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string", + "location": "query" + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+/operations/[^/]+$", + "required": true, + "description": "The name of the operation resource to wait on.", + "location": "path", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.specialistPools.operations.wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST" + } + } + } + }, + "methods": { + "patch": { + "id": "aiplatform.projects.locations.specialistPools.patch", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Updates a SpecialistPool.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}", + "request": { + "$ref": "GoogleCloudAiplatformV1SpecialistPool" + }, + "path": "v1/{+name}", + "httpMethod": "PATCH", + "parameters": { + "updateMask": { + "location": "query", + "description": "Required. The update mask applies to the resource.", + "type": "string", + "format": "google-fieldmask" + }, + "name": { + "required": true, + "description": "Required. The resource name of the SpecialistPool.", + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+$" + } + } + }, + "delete": { + "httpMethod": "DELETE", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a SpecialistPool as well as all Specialists in the pool.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.specialistPools.delete", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "location": "path", + "description": "Required. The resource name of the SpecialistPool to delete. Format: `projects/{project}/locations/{location}/specialistPools/{specialist_pool}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+$", + "required": true + }, + "force": { + "type": "boolean", + "description": "If set to true, any specialist managers in this SpecialistPool will also be deleted. (Otherwise, the request will only work if the SpecialistPool has no specialist managers.)", + "location": "query" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}", + "path": "v1/{+name}" + }, + "get": { + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets a SpecialistPool.", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+$", + "required": true, + "type": "string", + "description": "Required. The name of the SpecialistPool resource. The form is `projects/{project}/locations/{location}/specialistPools/{specialist_pool}`.", + "location": "path" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}", + "response": { + "$ref": "GoogleCloudAiplatformV1SpecialistPool" + }, + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.specialistPools.get", + "httpMethod": "GET" + }, + "create": { + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1SpecialistPool" + }, + "description": "Creates a SpecialistPool.", + "parameters": { + "parent": { + "description": "Required. The parent Project name for the new SpecialistPool. The form is `projects/{project}/locations/{location}`.", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true, + "location": "path", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.specialistPools.create", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools", + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+parent}/specialistPools" + }, + "list": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools", + "description": "Lists SpecialistPools in a Location.", + "response": { + "$ref": "GoogleCloudAiplatformV1ListSpecialistPoolsResponse" + }, + "parameters": { + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token. Typically obtained by ListSpecialistPoolsResponse.next_page_token of the previous SpecialistPoolService.ListSpecialistPools call. Return first page if empty." + }, + "pageSize": { + "location": "query", + "description": "The standard list page size.", + "type": "integer", + "format": "int32" + }, + "readMask": { + "description": "Mask specifying which fields to read. FieldMask represents a set of", + "type": "string", + "format": "google-fieldmask", + "location": "query" + }, + "parent": { + "type": "string", + "description": "Required. The name of the SpecialistPool's parent resource. Format: `projects/{project}/locations/{location}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path" + } + }, + "id": "aiplatform.projects.locations.specialistPools.list", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "httpMethod": "GET", + "path": "v1/{+parent}/specialistPools" + } + } + }, + "customJobs": { + "resources": { + "operations": { + "methods": { + "get": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "parameters": { + "name": { + "type": "string", + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+/operations/[^/]+$", + "location": "path", + "required": true + } + }, + "id": "aiplatform.projects.locations.customJobs.operations.get", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations/{operationsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "GET" + }, + "wait": { + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "type": "string", + "location": "query" + }, + "name": { + "required": true, + "description": "The name of the operation resource to wait on.", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+/operations/[^/]+$" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations/{operationsId}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}:wait", + "id": "aiplatform.projects.locations.customJobs.operations.wait", + "httpMethod": "POST", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "path": "v1/{+name}/operations", + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+$", + "location": "path", + "type": "string", + "description": "The name of the operation's parent resource." + }, + "filter": { + "type": "string", + "description": "The standard list filter.", + "location": "query" + }, + "pageSize": { + "description": "The standard list page size.", + "type": "integer", + "location": "query", + "format": "int32" + }, + "pageToken": { + "description": "The standard list page token.", + "location": "query", + "type": "string" + } + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "id": "aiplatform.projects.locations.customJobs.operations.list" + }, + "cancel": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations/{operationsId}:cancel", + "parameters": { + "name": { + "required": true, + "type": "string", + "description": "The name of the operation resource to be cancelled.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+/operations/[^/]+$" + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "httpMethod": "POST", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "id": "aiplatform.projects.locations.customJobs.operations.cancel", + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}:cancel" + }, + "delete": { + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource to be deleted.", + "type": "string", + "required": true + } + }, + "httpMethod": "DELETE", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.customJobs.operations.delete", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." + } + } + } + }, + "methods": { + "get": { + "response": { + "$ref": "GoogleCloudAiplatformV1CustomJob" + }, + "description": "Gets a CustomJob.", + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "description": "Required. The name of the CustomJob resource. Format: `projects/{project}/locations/{location}/customJobs/{custom_job}`", + "type": "string", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+$" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}", + "id": "aiplatform.projects.locations.customJobs.get" + }, + "cancel": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1CancelCustomJobRequest" + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}:cancel", + "description": "Cancels a CustomJob. Starts asynchronous cancellation on the CustomJob. The server makes a best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetCustomJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On successful cancellation, the CustomJob is not deleted; instead it becomes a job with a CustomJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and CustomJob.state is set to `CANCELLED`.", + "path": "v1/{+name}:cancel", + "parameters": { + "name": { + "required": true, + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+$", + "description": "Required. The name of the CustomJob to cancel. Format: `projects/{project}/locations/{location}/customJobs/{custom_job}`" + } + }, + "id": "aiplatform.projects.locations.customJobs.cancel" + }, + "delete": { + "description": "Deletes a CustomJob.", + "parameters": { + "name": { + "type": "string", + "description": "Required. The name of the CustomJob resource to be deleted. Format: `projects/{project}/locations/{location}/customJobs/{custom_job}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+$", + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.customJobs.delete", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "DELETE", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}" + }, + "list": { + "description": "Lists CustomJobs in a Location.", + "parameterOrder": [ + "parent" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.customJobs.list", + "parameters": { + "parent": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "required": true, + "description": "Required. The resource name of the Location to list the CustomJobs from. Format: `projects/{project}/locations/{location}`" + }, + "filter": { + "location": "query", + "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`", + "type": "string" + }, + "readMask": { + "type": "string", + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask", + "location": "query" + }, + "pageSize": { + "format": "int32", + "location": "query", + "type": "integer", + "description": "The standard list page size." + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token. Typically obtained via ListCustomJobsResponse.next_page_token of the previous JobService.ListCustomJobs call." + } + }, + "path": "v1/{+parent}/customJobs", + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1ListCustomJobsResponse" + } + }, + "create": { + "parameters": { + "parent": { + "type": "string", + "description": "Required. The resource name of the Location to create the CustomJob in. Format: `projects/{project}/locations/{location}`", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1CustomJob" + }, + "parameterOrder": [ + "parent" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1CustomJob" + }, + "id": "aiplatform.projects.locations.customJobs.create", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+parent}/customJobs", + "description": "Creates a CustomJob. A created CustomJob right away will be attempted to be run.", + "httpMethod": "POST" + } + } + }, + "modelDeploymentMonitoringJobs": { + "resources": { + "operations": { + "methods": { + "cancel": { + "parameters": { + "name": { + "required": true, + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.cancel", + "httpMethod": "POST", + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}:cancel", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + } + }, + "get": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.get", + "path": "v1/{+name}", + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}", + "parameters": { + "name": { + "description": "The name of the operation resource.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", + "location": "path", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "wait": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}:wait", + "parameters": { + "name": { + "description": "The name of the operation resource to wait on.", + "required": true, + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$" + }, + "timeout": { + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "location": "query" + } + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." + }, + "list": { + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "required": true, + "type": "string", + "description": "The name of the operation's parent resource.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$" + }, + "pageToken": { + "location": "query", + "description": "The standard list page token.", + "type": "string" + }, + "pageSize": { + "description": "The standard list page size.", + "type": "integer", + "location": "query", + "format": "int32" + }, + "filter": { + "location": "query", + "description": "The standard list filter.", + "type": "string" + } + }, + "httpMethod": "GET", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "path": "v1/{+name}/operations", + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.list" + }, + "delete": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}", + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ], + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "description": "The name of the operation resource to be deleted.", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", + "required": true + } + }, + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.delete" + } + } + } + }, + "methods": { + "patch": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.patch", + "path": "v1/{+name}", + "parameters": { + "updateMask": { + "description": "Required. The update mask is used to specify the fields to be overwritten in the ModelDeploymentMonitoringJob resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. For the objective config, the user can either provide the update mask for model_deployment_monitoring_objective_configs or any combination of its nested fields, such as: model_deployment_monitoring_objective_configs.objective_config.training_dataset. Updatable fields: * `display_name` * `model_deployment_monitoring_schedule_config` * `model_monitoring_alert_config` * `logging_sampling_strategy` * `labels` * `log_ttl` * `enable_monitoring_pipeline_logs` . and * `model_deployment_monitoring_objective_configs` . or * `model_deployment_monitoring_objective_configs.objective_config.training_dataset` * `model_deployment_monitoring_objective_configs.objective_config.training_prediction_skew_detection_config` * `model_deployment_monitoring_objective_configs.objective_config.prediction_drift_detection_config`", + "format": "google-fieldmask", + "location": "query", + "type": "string" + }, + "name": { + "required": true, + "type": "string", + "description": "Output only. Resource name of a ModelDeploymentMonitoringJob.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1ModelDeploymentMonitoringJob" + }, + "parameterOrder": [ + "name" + ], + "description": "Updates a ModelDeploymentMonitoringJob.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "PATCH" + }, + "resume": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}:resume", + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.resume", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "location": "path", + "type": "string", + "description": "Required. The resource name of the ModelDeploymentMonitoringJob to resume. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`", + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", + "required": true + } + }, + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1ResumeModelDeploymentMonitoringJobRequest" + }, + "parameterOrder": [ + "name" + ], + "description": "Resumes a paused ModelDeploymentMonitoringJob. It will start to run from next scheduled time. A deleted ModelDeploymentMonitoringJob can't be resumed.", + "path": "v1/{+name}:resume" + }, + "get": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}", + "parameters": { + "name": { + "description": "Required. The resource name of the ModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.get", + "response": { + "$ref": "GoogleCloudAiplatformV1ModelDeploymentMonitoringJob" + }, + "description": "Gets a ModelDeploymentMonitoringJob.", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}" + }, + "pause": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1PauseModelDeploymentMonitoringJobRequest" + }, + "description": "Pauses a ModelDeploymentMonitoringJob. If the job is running, the server makes a best effort to cancel the job. Will mark ModelDeploymentMonitoringJob.state to 'PAUSED'.", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", + "description": "Required. The resource name of the ModelDeploymentMonitoringJob to pause. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`", + "required": true, + "location": "path" + } + }, + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.pause", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}:pause", + "path": "v1/{+name}:pause", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "delete": { + "httpMethod": "DELETE", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "required": true, + "description": "Required. The resource name of the model monitoring job to delete. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`", + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$" + } + }, + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.delete", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a ModelDeploymentMonitoringJob." + }, + "searchModelDeploymentMonitoringStatsAnomalies": { + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.searchModelDeploymentMonitoringStatsAnomalies", + "parameterOrder": [ + "modelDeploymentMonitoringJob" + ], + "parameters": { + "modelDeploymentMonitoringJob": { + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", + "description": "Required. ModelDeploymentMonitoring Job resource name. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`", + "type": "string" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1SearchModelDeploymentMonitoringStatsAnomaliesRequest" + }, + "response": { + "$ref": "GoogleCloudAiplatformV1SearchModelDeploymentMonitoringStatsAnomaliesResponse" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}:searchModelDeploymentMonitoringStatsAnomalies", + "httpMethod": "POST", + "path": "v1/{+modelDeploymentMonitoringJob}:searchModelDeploymentMonitoringStatsAnomalies", + "description": "Searches Model Monitoring Statistics generated within a given time window.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "description": "Lists ModelDeploymentMonitoringJobs in a Location.", + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1ListModelDeploymentMonitoringJobsResponse" + }, + "path": "v1/{+parent}/modelDeploymentMonitoringJobs", + "httpMethod": "GET", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs", + "parameters": { + "readMask": { + "description": "Mask specifying which fields to read", + "format": "google-fieldmask", + "type": "string", + "location": "query" + }, + "pageSize": { + "location": "query", + "description": "The standard list page size.", + "type": "integer", + "format": "int32" + }, + "pageToken": { + "location": "query", + "description": "The standard list page token.", + "type": "string" + }, + "parent": { + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string", + "description": "Required. The parent of the ModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}`" + }, + "filter": { + "location": "query", + "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.list" + }, + "create": { + "request": { + "$ref": "GoogleCloudAiplatformV1ModelDeploymentMonitoringJob" + }, + "parameters": { + "parent": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The parent of the ModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}`", + "type": "string" + } + }, + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.create", + "path": "v1/{+parent}/modelDeploymentMonitoringJobs", + "response": { + "$ref": "GoogleCloudAiplatformV1ModelDeploymentMonitoringJob" + }, + "parameterOrder": [ + "parent" + ], + "description": "Creates a ModelDeploymentMonitoringJob. It will run periodically on a configured interval.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs" + } + } + }, + "datasets": { + "resources": { + "dataItems": { + "resources": { + "operations": { + "methods": { + "cancel": { + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}:cancel", + "path": "v1/{+name}:cancel", + "id": "aiplatform.projects.locations.datasets.dataItems.operations.cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", + "location": "path", + "required": true + } + }, + "parameterOrder": [ + "name" + ] + }, + "delete": { + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.datasets.dataItems.operations.delete", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}", + "path": "v1/{+name}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", + "type": "string", + "location": "path", + "required": true, + "description": "The name of the operation resource to be deleted." + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + } + }, + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "path": "v1/{+name}/operations", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations", + "parameters": { + "name": { + "location": "path", + "description": "The name of the operation's parent resource.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+$", + "required": true + }, + "filter": { + "description": "The standard list filter.", + "location": "query", + "type": "string" + }, + "pageSize": { + "format": "int32", + "location": "query", + "type": "integer", + "description": "The standard list page size." + }, + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + } + }, + "id": "aiplatform.projects.locations.datasets.dataItems.operations.list" + }, + "wait": { + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string", + "format": "google-duration", + "location": "query" + }, + "name": { + "description": "The name of the operation resource to wait on.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", + "required": true, + "location": "path" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.datasets.dataItems.operations.wait", + "path": "v1/{+name}:wait", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}:wait" + }, + "get": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "description": "The name of the operation resource.", + "required": true, + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$" + } + }, + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "httpMethod": "GET", + "id": "aiplatform.projects.locations.datasets.dataItems.operations.get" + } + } + }, + "annotations": { + "resources": { + "operations": { + "methods": { + "list": { + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "path": "v1/{+name}/operations", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations", + "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.list", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "httpMethod": "GET", + "parameters": { + "name": { + "description": "The name of the operation's parent resource.", + "type": "string", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+$" + }, + "filter": { + "location": "query", + "description": "The standard list filter.", + "type": "string" + }, + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + }, + "pageSize": { + "type": "integer", + "location": "query", + "format": "int32", + "description": "The standard list page size." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "get": { + "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.get", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", + "required": true, + "type": "string", + "description": "The name of the operation resource." + } + }, + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", + "type": "string", + "description": "The name of the operation resource to be deleted.", + "location": "path" + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.delete", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}", + "httpMethod": "DELETE", + "path": "v1/{+name}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." + }, + "wait": { + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.wait", + "parameterOrder": [ + "name" + ], + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "location": "query", + "type": "string" + }, + "name": { + "location": "path", + "required": true, + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}:wait", + "path": "v1/{+name}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST" + }, + "cancel": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "httpMethod": "POST", + "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "required": true, + "description": "The name of the operation resource to be cancelled.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}:cancel", + "path": "v1/{+name}:cancel", + "parameterOrder": [ + "name" + ] + } + } + } + }, + "methods": { + "list": { + "parameters": { + "parent": { + "type": "string", + "description": "Required. The resource name of the DataItem to list Annotations from. Format: `projects/{project}/locations/{location}/datasets/{dataset}/dataItems/{data_item}`", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+$" + }, + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter." + }, + "pageSize": { + "format": "int32", + "type": "integer", + "location": "query", + "description": "The standard list page size." + }, + "orderBy": { + "location": "query", + "type": "string", + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending." + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token." + }, + "readMask": { + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask", + "location": "query", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1ListAnnotationsResponse" + }, + "id": "aiplatform.projects.locations.datasets.dataItems.annotations.list", + "description": "Lists Annotations belongs to a dataitem", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations", + "httpMethod": "GET", + "path": "v1/{+parent}/annotations", + "parameterOrder": [ + "parent" + ] + } + } + } + }, + "methods": { + "list": { + "path": "v1/{+parent}/dataItems", + "description": "Lists DataItems in a Dataset.", + "response": { + "$ref": "GoogleCloudAiplatformV1ListDataItemsResponse" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.datasets.dataItems.list", + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", + "description": "Required. The resource name of the Dataset to list DataItems from. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", + "required": true, + "location": "path", + "type": "string" + }, + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + }, + "orderBy": { + "type": "string", + "location": "query", + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending." + }, + "pageSize": { + "description": "The standard list page size.", + "location": "query", + "format": "int32", + "type": "integer" + }, + "readMask": { + "format": "google-fieldmask", + "location": "query", + "type": "string", + "description": "Mask specifying which fields to read." + }, + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + } + }, + "httpMethod": "GET" + } + } + }, + "annotationSpecs": { + "methods": { + "get": { + "id": "aiplatform.projects.locations.datasets.annotationSpecs.get", + "response": { + "$ref": "GoogleCloudAiplatformV1AnnotationSpec" + }, + "description": "Gets an AnnotationSpec.", + "path": "v1/{+name}", + "parameters": { + "readMask": { + "type": "string", + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask", + "location": "query" + }, + "name": { + "required": true, + "description": "Required. The name of the AnnotationSpec resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}/annotationSpecs/{annotation_spec}`", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+$", + "location": "path", + "type": "string" + } + }, + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}", + "httpMethod": "GET" + } + }, + "resources": { + "operations": { + "methods": { + "wait": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "parameters": { + "timeout": { + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string", + "location": "query" + }, + "name": { + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "location": "path" + } + }, + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "POST", + "path": "v1/{+name}:wait" + }, + "cancel": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}:cancel", + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "parameters": { + "name": { + "type": "string", + "description": "The name of the operation resource to be cancelled.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", + "location": "path" + } + }, + "path": "v1/{+name}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.cancel" + }, + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "description": "The name of the operation resource to be deleted.", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", + "required": true + } + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.delete", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}", + "path": "v1/{+name}" + }, + "list": { + "httpMethod": "GET", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations", + "parameters": { + "name": { + "description": "The name of the operation's parent resource.", + "required": true, + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+$" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + }, + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "pageSize": { + "format": "int32", + "location": "query", + "description": "The standard list page size.", + "type": "integer" + } + }, + "path": "v1/{+name}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.list", + "parameterOrder": [ + "name" + ] + }, + "get": { + "parameters": { + "name": { + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource." + } + }, + "httpMethod": "GET", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.get", + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}" + } + } + } + } + }, + "datasetVersions": { + "methods": { + "patch": { + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "description": "Updates a DatasetVersion.", + "httpMethod": "PATCH", + "parameters": { + "name": { + "description": "Output only. Identifier. The resource name of the DatasetVersion.", + "type": "string", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/datasetVersions/[^/]+$" + }, + "updateMask": { + "location": "query", + "format": "google-fieldmask", + "type": "string", + "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Updatable fields: * `display_name`" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1DatasetVersion" + }, + "id": "aiplatform.projects.locations.datasets.datasetVersions.patch", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}", + "request": { + "$ref": "GoogleCloudAiplatformV1DatasetVersion" + } + }, + "list": { + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+parent}/datasetVersions", + "parameterOrder": [ + "parent" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions", + "parameters": { + "pageToken": { + "type": "string", + "description": "Optional. The standard list page token.", + "location": "query" + }, + "readMask": { + "format": "google-fieldmask", + "description": "Optional. Mask specifying which fields to read.", + "type": "string", + "location": "query" + }, + "orderBy": { + "location": "query", + "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending.", + "type": "string" + }, + "filter": { + "location": "query", + "type": "string", + "description": "Optional. The standard list filter." + }, + "pageSize": { + "type": "integer", + "location": "query", + "description": "Optional. The standard list page size.", + "format": "int32" + }, + "parent": { + "type": "string", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", + "description": "Required. The resource name of the Dataset to list DatasetVersions from. Format: `projects/{project}/locations/{location}/datasets/{dataset}`" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1ListDatasetVersionsResponse" + }, + "id": "aiplatform.projects.locations.datasets.datasetVersions.list", + "description": "Lists DatasetVersions in a Dataset." + }, + "get": { + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.datasets.datasetVersions.get", + "parameters": { + "readMask": { + "type": "string", + "location": "query", + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask" + }, + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/datasetVersions/[^/]+$", + "description": "Required. The resource name of the Dataset version to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", + "required": true, + "location": "path" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1DatasetVersion" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}", + "httpMethod": "GET", + "description": "Gets a Dataset version.", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.datasets.datasetVersions.delete", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}", + "description": "Deletes a Dataset version.", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/datasetVersions/[^/]+$", + "type": "string", + "description": "Required. The resource name of the Dataset version to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", + "required": true, + "location": "path" + } + }, + "parameterOrder": [ + "name" + ] + }, + "create": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.datasets.datasetVersions.create", + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", + "required": true, + "location": "path", + "type": "string", + "description": "Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}`" + } + }, + "parameterOrder": [ + "parent" + ], + "path": "v1/{+parent}/datasetVersions", + "description": "Create a version from a Dataset.", + "request": { + "$ref": "GoogleCloudAiplatformV1DatasetVersion" + }, + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions" + }, + "restore": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.datasets.datasetVersions.restore", + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/datasetVersions/[^/]+$", + "location": "path", + "description": "Required. The name of the DatasetVersion resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", + "required": true + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}:restore", + "parameterOrder": [ + "name" + ], + "description": "Restores a dataset version.", + "httpMethod": "GET", + "path": "v1/{+name}:restore", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + } + } + }, + "savedQueries": { + "resources": { + "operations": { + "methods": { + "cancel": { + "httpMethod": "POST", + "id": "aiplatform.projects.locations.datasets.savedQueries.operations.cancel", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1/{+name}:cancel", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "type": "string", + "required": true + } + } + }, + "wait": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}:wait", + "parameters": { + "timeout": { + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string", + "format": "google-duration" + }, + "name": { + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "location": "path" + } + }, + "id": "aiplatform.projects.locations.datasets.savedQueries.operations.wait", + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." + }, + "list": { + "httpMethod": "GET", + "id": "aiplatform.projects.locations.datasets.savedQueries.operations.list", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations", + "path": "v1/{+name}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "parameters": { + "pageSize": { + "description": "The standard list page size.", + "location": "query", + "format": "int32", + "type": "integer" + }, + "filter": { + "location": "query", + "description": "The standard list filter.", + "type": "string" + }, + "name": { + "type": "string", + "location": "path", + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+$", + "required": true + }, + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + } + }, + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + } + }, + "get": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "path": "v1/{+name}", + "parameters": { + "name": { + "location": "path", + "description": "The name of the operation resource.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.datasets.savedQueries.operations.get" + }, + "delete": { + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "type": "string", + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", + "location": "path", + "required": true + } + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.datasets.savedQueries.operations.delete" + } + } + } + }, + "methods": { + "list": { + "description": "Lists SavedQueries in a Dataset.", + "path": "v1/{+parent}/savedQueries", + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1ListSavedQueriesResponse" + }, + "parameters": { + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + }, + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter." + }, + "pageSize": { + "location": "query", + "description": "The standard list page size.", + "type": "integer", + "format": "int32" + }, + "readMask": { + "type": "string", + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask", + "location": "query" + }, + "orderBy": { + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending.", + "type": "string", + "location": "query" + }, + "parent": { + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", + "description": "Required. The resource name of the Dataset to list SavedQueries from. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.datasets.savedQueries.list", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries" + }, + "delete": { + "id": "aiplatform.projects.locations.datasets.savedQueries.delete", + "parameterOrder": [ + "name" + ], + "description": "Deletes a SavedQuery.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}", + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "DELETE", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+$", + "description": "Required. The resource name of the SavedQuery to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/savedQueries/{saved_query}`", + "type": "string", + "location": "path", + "required": true + } + } + } + } + }, + "operations": { + "methods": { + "cancel": { + "httpMethod": "POST", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "required": true, + "type": "string", + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/operations/[^/]+$" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations/{operationsId}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "path": "v1/{+name}:cancel", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.datasets.operations.cancel" + }, + "wait": { + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations/{operationsId}:wait", + "path": "v1/{+name}:wait", + "id": "aiplatform.projects.locations.datasets.operations.wait", + "parameters": { + "timeout": { + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string", + "format": "google-duration" + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "required": true, + "location": "path", + "type": "string" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ] + }, + "list": { + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "httpMethod": "GET", + "parameters": { + "name": { + "required": true, + "type": "string", + "description": "The name of the operation's parent resource.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$" + }, + "pageSize": { + "description": "The standard list page size.", + "format": "int32", + "type": "integer", + "location": "query" + }, + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter." + }, + "pageToken": { + "location": "query", + "description": "The standard list page token.", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.datasets.operations.list", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}/operations", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + } + }, + "delete": { + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be deleted.", + "type": "string", + "location": "path", + "required": true + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.datasets.operations.delete", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}" + }, + "get": { + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.datasets.operations.get", + "httpMethod": "GET", + "parameters": { + "name": { + "type": "string", + "location": "path", + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/operations/[^/]+$", + "required": true + } + } + } + } + } + }, + "methods": { + "patch": { + "path": "v1/{+name}", + "description": "Updates a Dataset.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", + "description": "Output only. Identifier. The resource name of the Dataset.", + "type": "string", + "required": true + }, + "updateMask": { + "format": "google-fieldmask", + "location": "query", + "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Updatable fields: * `display_name` * `description` * `labels`", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.datasets.patch", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1Dataset" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1Dataset" + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "PATCH" + }, + "list": { + "description": "Lists Datasets in a Location.", + "id": "aiplatform.projects.locations.datasets.list", + "response": { + "$ref": "GoogleCloudAiplatformV1ListDatasetsResponse" + }, + "path": "v1/{+parent}/datasets", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets", + "parameters": { + "pageSize": { + "format": "int32", + "type": "integer", + "location": "query", + "description": "The standard list page size." + }, + "filter": { + "description": "An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `display_name`: supports = and != * `metadata_schema_uri`: supports = and != * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels.\"a key\"`. Some examples: * `displayName=\"myDisplayName\"` * `labels.myKey=\"myValue\"`", + "location": "query", + "type": "string" + }, + "parent": { + "required": true, + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The name of the Dataset's parent resource. Format: `projects/{project}/locations/{location}`" + }, + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + }, + "orderBy": { + "location": "query", + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time`", + "type": "string" + }, + "readMask": { + "description": "Mask specifying which fields to read.", + "type": "string", + "format": "google-fieldmask", + "location": "query" + } + }, + "parameterOrder": [ + "parent" + ], + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "delete": { + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.datasets.delete", + "description": "Deletes a Dataset.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", + "description": "Required. The resource name of the Dataset to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", + "type": "string", + "location": "path", + "required": true + } + }, + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}" + }, + "get": { + "parameters": { + "readMask": { + "type": "string", + "location": "query", + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask" + }, + "name": { + "type": "string", + "location": "path", + "description": "Required. The name of the Dataset resource.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$" + } + }, + "description": "Gets a Dataset.", + "path": "v1/{+name}", + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.datasets.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}", + "response": { + "$ref": "GoogleCloudAiplatformV1Dataset" + } + }, + "export": { + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.datasets.export", + "path": "v1/{+name}:export", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "required": true, + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", + "description": "Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}`" + } + }, + "parameterOrder": [ + "name" + ], + "description": "Exports data from a Dataset.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:export", + "request": { + "$ref": "GoogleCloudAiplatformV1ExportDataRequest" + } + }, + "import": { + "description": "Imports data into a Dataset.", + "request": { + "$ref": "GoogleCloudAiplatformV1ImportDataRequest" + }, + "path": "v1/{+name}:import", + "id": "aiplatform.projects.locations.datasets.import", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:import", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "location": "path", + "description": "Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", + "type": "string", + "required": true + } + } + }, + "create": { + "parameterOrder": [ + "parent" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1Dataset" + }, + "description": "Creates a Dataset.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "path": "v1/{+parent}/datasets", + "parameters": { + "parent": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string", + "description": "Required. The resource name of the Location to create the Dataset in. Format: `projects/{project}/locations/{location}`", + "required": true + } + }, + "id": "aiplatform.projects.locations.datasets.create", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets" + }, + "searchDataItems": { + "id": "aiplatform.projects.locations.datasets.searchDataItems", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:searchDataItems", + "description": "Searches DataItems in a Dataset.", + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1SearchDataItemsResponse" + }, + "path": "v1/{+dataset}:searchDataItems", + "parameters": { + "dataLabelingJob": { + "description": "The resource name of a DataLabelingJob. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}` If this field is set, all of the search will be done in the context of this DataLabelingJob.", + "type": "string", + "location": "query" + }, + "orderByAnnotation.savedQuery": { + "type": "string", + "location": "query", + "description": "Required. Saved query of the Annotation. Only Annotations belong to this saved query will be considered for ordering." + }, + "orderBy": { + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending.", + "type": "string", + "location": "query", + "deprecated": true + }, + "pageToken": { + "description": "A token identifying a page of results for the server to return Typically obtained via SearchDataItemsResponse.next_page_token of the previous DatasetService.SearchDataItems call.", + "location": "query", + "type": "string" + }, + "orderByDataItem": { + "location": "query", + "description": "A comma-separated list of data item fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending.", + "type": "string" + }, + "annotationsLimit": { + "location": "query", + "format": "int32", + "type": "integer", + "description": "If set, only up to this many of Annotations will be returned per DataItemView. The maximum value is 1000. If not set, the maximum value will be used." + }, + "fieldMask": { + "location": "query", + "type": "string", + "description": "Mask specifying which fields of DataItemView to read.", + "format": "google-fieldmask" + }, + "annotationFilters": { + "description": "An expression that specifies what Annotations will be returned per DataItem. Annotations satisfied either of the conditions will be returned. * `annotation_spec_id` - for = or !=. Must specify `saved_query_id=` - saved query id that annotations should belong to.", + "location": "query", + "type": "string", + "repeated": true + }, + "annotationsFilter": { + "type": "string", + "location": "query", + "description": "An expression for filtering the Annotations that will be returned per DataItem. * `annotation_spec_id` - for = or !=.", + "deprecated": true + }, + "savedQuery": { + "location": "query", + "description": "The resource name of a SavedQuery(annotation set in UI). Format: `projects/{project}/locations/{location}/datasets/{dataset}/savedQueries/{saved_query}` All of the search will be done in the context of this SavedQuery.", + "deprecated": true, + "type": "string" + }, + "dataItemFilter": { + "location": "query", + "description": "An expression for filtering the DataItem that will be returned. * `data_item_id` - for = or !=. * `labeled` - for = or !=. * `has_annotation(ANNOTATION_SPEC_ID)` - true only for DataItem that have at least one annotation with annotation_spec_id = `ANNOTATION_SPEC_ID` in the context of SavedQuery or DataLabelingJob. For example: * `data_item=1` * `has_annotation(5)`", + "type": "string" + }, + "pageSize": { + "description": "Requested page size. Server may return fewer results than requested. Default and maximum page size is 100.", + "format": "int32", + "type": "integer", + "location": "query" + }, + "orderByAnnotation.orderBy": { + "description": "A comma-separated list of annotation fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Must also specify saved_query.", + "type": "string", + "location": "query" + }, + "dataset": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", + "description": "Required. The resource name of the Dataset from which to search DataItems. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", + "type": "string", + "location": "path", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "dataset" + ] + } + } + }, + "featurestores": { + "methods": { + "list": { + "id": "aiplatform.projects.locations.featurestores.list", + "parameterOrder": [ + "parent" + ], + "httpMethod": "GET", + "path": "v1/{+parent}/featurestores", + "description": "Lists Featurestores in a given project and location.", + "response": { + "$ref": "GoogleCloudAiplatformV1ListFeaturestoresResponse" + }, + "parameters": { + "readMask": { + "type": "string", + "description": "Mask specifying which fields to read.", + "location": "query", + "format": "google-fieldmask" + }, + "pageSize": { + "description": "The maximum number of Featurestores to return. The service may return fewer than this value. If unspecified, at most 100 Featurestores will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100.", + "location": "query", + "type": "integer", + "format": "int32" + }, + "filter": { + "description": "Lists the featurestores that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `online_serving_config.fixed_node_count`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. * `labels`: Supports key-value equality and key presence. Examples: * `create_time \u003e \"2020-01-01\" OR update_time \u003e \"2020-01-01\"` Featurestores created or updated after 2020-01-01. * `labels.env = \"prod\"` Featurestores with label \"env\" set to \"prod\".", + "location": "query", + "type": "string" + }, + "orderBy": { + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported Fields: * `create_time` * `update_time` * `online_serving_config.fixed_node_count`", + "type": "string", + "location": "query" + }, + "pageToken": { + "description": "A page token, received from a previous FeaturestoreService.ListFeaturestores call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.ListFeaturestores must match the call that provided the page token.", + "type": "string", + "location": "query" + }, + "parent": { + "required": true, + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location to list Featurestores. Format: `projects/{project}/locations/{location}`" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "patch": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "updateMask": { + "description": "Field mask is used to specify the fields to be overwritten in the Featurestore resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `online_serving_config.fixed_node_count` * `online_serving_config.scaling` * `online_storage_ttl_days`", + "format": "google-fieldmask", + "location": "query", + "type": "string" + }, + "name": { + "required": true, + "description": "Output only. Name of the Featurestore. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}", + "request": { + "$ref": "GoogleCloudAiplatformV1Featurestore" + }, + "httpMethod": "PATCH", + "description": "Updates the parameters of a single Featurestore.", + "path": "v1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.featurestores.patch" + }, + "getIamPolicy": { + "id": "aiplatform.projects.locations.featurestores.getIamPolicy", + "response": { + "$ref": "GoogleIamV1Policy" + }, + "parameterOrder": [ + "resource" + ], + "parameters": { + "resource": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", + "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "required": true, + "type": "string", + "location": "path" + }, + "options.requestedPolicyVersion": { + "format": "int32", + "type": "integer", + "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", + "location": "query" + } + }, + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+resource}:getIamPolicy", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}:getIamPolicy", + "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set." + }, + "create": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1Featurestore" + }, + "id": "aiplatform.projects.locations.featurestores.create", + "httpMethod": "POST", + "description": "Creates a new Featurestore in a given project and location.", + "parameterOrder": [ + "parent" + ], + "path": "v1/{+parent}/featurestores", + "parameters": { + "featurestoreId": { + "location": "query", + "type": "string", + "description": "Required. The ID to use for this Featurestore, which will become the final component of the Featurestore's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location." + }, + "parent": { + "type": "string", + "required": true, + "description": "Required. The resource name of the Location to create Featurestores. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "setIamPolicy": { + "path": "v1/{+resource}:setIamPolicy", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}:setIamPolicy", + "parameters": { + "resource": { + "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", + "type": "string", + "required": true, + "location": "path" + } + }, + "httpMethod": "POST", + "request": { + "$ref": "GoogleIamV1SetIamPolicyRequest" + }, + "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", + "parameterOrder": [ + "resource" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.featurestores.setIamPolicy", + "response": { + "$ref": "GoogleIamV1Policy" + } + }, + "testIamPermissions": { + "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", + "path": "v1/{+resource}:testIamPermissions", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}:testIamPermissions", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleIamV1TestIamPermissionsResponse" + }, + "parameterOrder": [ + "resource" + ], + "httpMethod": "POST", + "parameters": { + "resource": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", + "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "location": "path", + "type": "string", + "required": true + }, + "permissions": { + "repeated": true, + "location": "query", + "type": "string", + "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions)." + } + }, + "id": "aiplatform.projects.locations.featurestores.testIamPermissions" + }, + "delete": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}", + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.featurestores.delete", + "parameterOrder": [ + "name" + ], + "description": "Deletes a single Featurestore. The Featurestore must not contain any EntityTypes or `force` must be set to true for the request to succeed.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "force": { + "description": "If set to true, any EntityTypes and Features for this Featurestore will also be deleted. (Otherwise, the request will only work if the Featurestore has no EntityTypes.)", + "type": "boolean", + "location": "query" + }, + "name": { + "required": true, + "location": "path", + "description": "Required. The name of the Featurestore to be deleted. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", + "type": "string" + } + } + }, + "batchReadFeatureValues": { + "parameters": { + "featurestore": { + "description": "Required. The resource name of the Featurestore from which to query Feature values. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$" + } + }, + "id": "aiplatform.projects.locations.featurestores.batchReadFeatureValues", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}:batchReadFeatureValues", + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1BatchReadFeatureValuesRequest" + }, + "path": "v1/{+featurestore}:batchReadFeatureValues", + "description": "Batch reads Feature values from a Featurestore. This API enables batch reading Feature values, where each read instance in the batch may read Feature values of entities from one or more EntityTypes. Point-in-time correctness is guaranteed for Feature values of each read instance as of each instance's read timestamp.", + "parameterOrder": [ + "featurestore" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "searchFeatures": { + "description": "Searches Features matching a query in a given project.", + "path": "v1/{+location}/featurestores:searchFeatures", + "parameterOrder": [ + "location" + ], + "id": "aiplatform.projects.locations.featurestores.searchFeatures", + "response": { + "$ref": "GoogleCloudAiplatformV1SearchFeaturesResponse" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores:searchFeatures", + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "pageSize": { + "format": "int32", + "description": "The maximum number of Features to return. The service may return fewer than this value. If unspecified, at most 100 Features will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100.", + "type": "integer", + "location": "query" + }, + "location": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "description": "Required. The resource name of the Location to search Features. Format: `projects/{project}/locations/{location}`", + "type": "string", + "required": true + }, + "pageToken": { + "description": "A page token, received from a previous FeaturestoreService.SearchFeatures call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.SearchFeatures, except `page_size`, must match the call that provided the page token.", + "location": "query", + "type": "string" + }, + "query": { + "location": "query", + "description": "Query string that is a conjunction of field-restricted queries and/or field-restricted filters. Field-restricted queries and filters can be combined using `AND` to form a conjunction. A field query is in the form FIELD:QUERY. This implicitly checks if QUERY exists as a substring within Feature's FIELD. The QUERY and the FIELD are converted to a sequence of words (i.e. tokens) for comparison. This is done by: * Removing leading/trailing whitespace and tokenizing the search value. Characters that are not one of alphanumeric `[a-zA-Z0-9]`, underscore `_`, or asterisk `*` are treated as delimiters for tokens. `*` is treated as a wildcard that matches characters within a token. * Ignoring case. * Prepending an asterisk to the first and appending an asterisk to the last token in QUERY. A QUERY must be either a singular token or a phrase. A phrase is one or multiple words enclosed in double quotation marks (\"). With phrases, the order of the words is important. Words in the phrase must be matching in order and consecutively. Supported FIELDs for field-restricted queries: * `feature_id` * `description` * `entity_type_id` Examples: * `feature_id: foo` --\u003e Matches a Feature with ID containing the substring `foo` (eg. `foo`, `foofeature`, `barfoo`). * `feature_id: foo*feature` --\u003e Matches a Feature with ID containing the substring `foo*feature` (eg. `foobarfeature`). * `feature_id: foo AND description: bar` --\u003e Matches a Feature with ID containing the substring `foo` and description containing the substring `bar`. Besides field queries, the following exact-match filters are supported. The exact-match filters do not support wildcards. Unlike field-restricted queries, exact-match filters are case-sensitive. * `feature_id`: Supports = comparisons. * `description`: Supports = comparisons. Multi-token filters should be enclosed in quotes. * `entity_type_id`: Supports = comparisons. * `value_type`: Supports = and != comparisons. * `labels`: Supports key-value equality as well as key presence. * `featurestore_id`: Supports = comparisons. Examples: * `description = \"foo bar\"` --\u003e Any Feature with description exactly equal to `foo bar` * `value_type = DOUBLE` --\u003e Features whose type is DOUBLE. * `labels.active = yes AND labels.env = prod` --\u003e Features having both (active: yes) and (env: prod) labels. * `labels.env: *` --\u003e Any Feature which has a label with `env` as the key.", + "type": "string" + } + } + }, + "get": { + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.featurestores.get", + "description": "Gets details of a single Featurestore.", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", + "description": "Required. The name of the Featurestore resource.", + "required": true, + "type": "string" + } + }, + "httpMethod": "GET", + "path": "v1/{+name}", + "response": { + "$ref": "GoogleCloudAiplatformV1Featurestore" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}" + } + }, + "resources": { + "operations": { + "methods": { + "delete": { + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.featurestores.operations.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be deleted.", + "type": "string", + "required": true, + "location": "path" + } + }, + "httpMethod": "DELETE", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ] + }, + "wait": { + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations/{operationsId}:wait", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "id": "aiplatform.projects.locations.featurestores.operations.wait", + "parameters": { + "timeout": { + "format": "google-duration", + "type": "string", + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + }, + "name": { + "required": true, + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}:wait" + }, + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.featurestores.operations.list", + "httpMethod": "GET", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}/operations", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "name": { + "required": true, + "description": "The name of the operation's parent resource.", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$" + }, + "pageToken": { + "description": "The standard list page token.", + "location": "query", + "type": "string" + }, + "pageSize": { + "location": "query", + "type": "integer", + "format": "int32", + "description": "The standard list page size." + }, + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + } + } + }, + "cancel": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}:cancel", + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/operations/[^/]+$", + "location": "path", + "required": true + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations/{operationsId}:cancel", + "httpMethod": "POST", + "id": "aiplatform.projects.locations.featurestores.operations.cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "parameterOrder": [ + "name" + ] + }, + "get": { + "id": "aiplatform.projects.locations.featurestores.operations.get", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "required": true, + "description": "The name of the operation resource.", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/operations/[^/]+$" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." + } + } + }, + "entityTypes": { + "resources": { + "operations": { + "methods": { + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "httpMethod": "DELETE", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.delete", + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be deleted.", + "location": "path", + "required": true, + "type": "string" + } + } + }, + "get": { + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameters": { + "name": { + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource." + } + }, + "httpMethod": "GET", + "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "cancel": { + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.cancel", + "path": "v1/{+name}:cancel", + "parameters": { + "name": { + "location": "path", + "required": true, + "type": "string", + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$" + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "wait": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}:wait", + "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.wait", + "path": "v1/{+name}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "timeout": { + "location": "query", + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration" + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", + "type": "string", + "description": "The name of the operation resource to wait on.", + "location": "path", + "required": true + } + }, + "parameterOrder": [ + "name" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "httpMethod": "POST" + }, + "list": { + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.list", + "path": "v1/{+name}/operations", + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "description": "The name of the operation's parent resource.", + "location": "path", + "type": "string", + "required": true + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + }, + "filter": { + "description": "The standard list filter.", + "location": "query", + "type": "string" + }, + "pageSize": { + "location": "query", + "type": "integer", + "description": "The standard list page size.", + "format": "int32" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." + } + } + }, + "features": { + "resources": { + "operations": { + "methods": { + "get": { + "httpMethod": "GET", + "path": "v1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "required": true, + "description": "The name of the operation resource.", + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$" + } + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "path": "v1/{+name}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.list", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations", + "parameters": { + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "pageSize": { + "description": "The standard list page size.", + "format": "int32", + "location": "query", + "type": "integer" + }, + "name": { + "required": true, + "location": "path", + "type": "string", + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+$" + }, + "pageToken": { + "location": "query", + "description": "The standard list page token.", + "type": "string" + } + }, + "httpMethod": "GET" + }, + "wait": { + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "path": "v1/{+name}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.wait", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}:wait", + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "timeout": { + "format": "google-duration", + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query" + }, + "name": { + "type": "string", + "required": true, + "location": "path", + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$" + } + } + }, + "cancel": { + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}:cancel", + "httpMethod": "POST", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be cancelled.", + "location": "path", + "type": "string", + "required": true + } + }, + "path": "v1/{+name}:cancel" + }, + "delete": { + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.delete", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "parameters": { + "name": { + "type": "string", + "description": "The name of the operation resource to be deleted.", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$" + } + }, + "httpMethod": "DELETE" + } + } + } + }, + "methods": { + "delete": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}", + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.delete", + "parameters": { + "name": { + "type": "string", + "description": "Required. The name of the Features to be deleted. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}`", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+$", + "required": true, + "location": "path" + } + }, + "description": "Deletes a single Feature.", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "DELETE" + }, + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+parent}/features", + "description": "Lists Features in a given EntityType.", + "httpMethod": "GET", + "parameterOrder": [ + "parent" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features", + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.list", + "response": { + "$ref": "GoogleCloudAiplatformV1ListFeaturesResponse" + }, + "parameters": { + "pageToken": { + "location": "query", + "description": "A page token, received from a previous FeaturestoreService.ListFeatures call or FeatureRegistryService.ListFeatures call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.ListFeatures or FeatureRegistryService.ListFeatures must match the call that provided the page token.", + "type": "string" + }, + "pageSize": { + "location": "query", + "description": "The maximum number of Features to return. The service may return fewer than this value. If unspecified, at most 1000 Features will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000.", + "type": "integer", + "format": "int32" + }, + "filter": { + "type": "string", + "location": "query", + "description": "Lists the Features that match the filter expression. The following filters are supported: * `value_type`: Supports = and != comparisons. * `create_time`: Supports =, !=, \u003c, \u003e, \u003e=, and \u003c= comparisons. Values must be in RFC 3339 format. * `update_time`: Supports =, !=, \u003c, \u003e, \u003e=, and \u003c= comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality as well as key presence. Examples: * `value_type = DOUBLE` --\u003e Features whose type is DOUBLE. * `create_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\" OR update_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\"` --\u003e EntityTypes created or updated after 2020-01-31T15:30:00.000000Z. * `labels.active = yes AND labels.env = prod` --\u003e Features having both (active: yes) and (env: prod) labels. * `labels.env: *` --\u003e Any Feature which has a label with 'env' as the key." + }, + "latestStatsCount": { + "type": "integer", + "location": "query", + "format": "int32", + "description": "Only applicable for Vertex AI Feature Store (Legacy). If set, return the most recent ListFeaturesRequest.latest_stats_count of stats for each Feature in response. Valid value is [0, 10]. If number of stats exists \u003c ListFeaturesRequest.latest_stats_count, return all existing stats." + }, + "parent": { + "location": "path", + "description": "Required. The resource name of the Location to list Features. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$" + }, + "orderBy": { + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `feature_id` * `value_type` (Not supported for FeatureRegistry Feature) * `create_time` * `update_time`", + "type": "string", + "location": "query" + }, + "readMask": { + "format": "google-fieldmask", + "location": "query", + "description": "Mask specifying which fields to read.", + "type": "string" + } + } + }, + "create": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features", + "parameters": { + "parent": { + "type": "string", + "location": "path", + "description": "Required. The resource name of the EntityType or FeatureGroup to create a Feature. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$" + }, + "featureId": { + "type": "string", + "description": "Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.", + "location": "query" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Creates a new Feature in a given EntityType.", + "path": "v1/{+parent}/features", + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.create", + "request": { + "$ref": "GoogleCloudAiplatformV1Feature" + } + }, + "batchCreate": { + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.batchCreate", + "parameterOrder": [ + "parent" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features:batchCreate", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Creates a batch of Features in a given EntityType.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1BatchCreateFeaturesRequest" + }, + "parameters": { + "parent": { + "type": "string", + "description": "Required. The resource name of the EntityType to create the batch of Features under. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "required": true, + "location": "path" + } + }, + "path": "v1/{+parent}/features:batchCreate", + "httpMethod": "POST" + }, + "patch": { + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.patch", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "PATCH", + "description": "Updates the parameters of a single Feature.", + "response": { + "$ref": "GoogleCloudAiplatformV1Feature" + }, + "parameters": { + "name": { + "location": "path", + "type": "string", + "description": "Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+$", + "required": true + }, + "updateMask": { + "format": "google-fieldmask", + "description": "Field mask is used to specify the fields to be overwritten in the Features resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `description` * `labels` * `disable_monitoring` (Not supported for FeatureRegistryService Feature) * `point_of_contact` (Not supported for FeaturestoreService FeatureStore)", + "type": "string", + "location": "query" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1Feature" + } + }, + "get": { + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1Feature" + }, + "parameters": { + "name": { + "type": "string", + "description": "Required. The name of the Feature resource. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+$", + "location": "path" + } + }, + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.get", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}", + "parameterOrder": [ + "name" + ], + "description": "Gets details of a single Feature." + } + } + } + }, + "methods": { + "testIamPermissions": { + "response": { + "$ref": "GoogleIamV1TestIamPermissionsResponse" + }, + "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", + "path": "v1/{+resource}:testIamPermissions", + "parameters": { + "permissions": { + "type": "string", + "repeated": true, + "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", + "location": "query" + }, + "resource": { + "required": true, + "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "location": "path" + } + }, + "parameterOrder": [ + "resource" + ], + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.featurestores.entityTypes.testIamPermissions", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:testIamPermissions" + }, + "streamingReadFeatureValues": { + "parameters": { + "entityType": { + "description": "Required. The resource name of the entities' type. Value format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`. For example, for a machine learning model predicting user clicks on a website, an EntityType ID could be `user`.", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "entityType" + ], + "id": "aiplatform.projects.locations.featurestores.entityTypes.streamingReadFeatureValues", + "request": { + "$ref": "GoogleCloudAiplatformV1StreamingReadFeatureValuesRequest" + }, + "path": "v1/{+entityType}:streamingReadFeatureValues", + "response": { + "$ref": "GoogleCloudAiplatformV1ReadFeatureValuesResponse" + }, + "httpMethod": "POST", + "description": "Reads Feature values for multiple entities. Depending on their size, data for different entities may be broken up across multiple responses.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:streamingReadFeatureValues" + }, + "delete": { + "path": "v1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "DELETE", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "required": true, + "type": "string", + "description": "Required. The name of the EntityType to be deleted. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`", + "location": "path" + }, + "force": { + "type": "boolean", + "description": "If set to true, any Features for this EntityType will also be deleted. (Otherwise, the request will only work if the EntityType has no Features.)", + "location": "query" + } + }, + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.featurestores.entityTypes.delete", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}", + "description": "Deletes a single EntityType. The EntityType must not have any Features or `force` must be set to true for the request to succeed." + }, + "exportFeatureValues": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:exportFeatureValues", + "parameterOrder": [ + "entityType" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1ExportFeatureValuesRequest" + }, + "parameters": { + "entityType": { + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "required": true, + "description": "Required. The resource name of the EntityType from which to export Feature values. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`" + } + }, + "id": "aiplatform.projects.locations.featurestores.entityTypes.exportFeatureValues", + "description": "Exports Feature values from all the entities of a target EntityType.", + "path": "v1/{+entityType}:exportFeatureValues", + "httpMethod": "POST" + }, + "getIamPolicy": { + "parameters": { + "resource": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "type": "string" + }, + "options.requestedPolicyVersion": { + "location": "query", + "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", + "type": "integer", + "format": "int32" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.featurestores.entityTypes.getIamPolicy", + "response": { + "$ref": "GoogleIamV1Policy" + }, + "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:getIamPolicy", + "httpMethod": "POST", + "path": "v1/{+resource}:getIamPolicy", + "parameterOrder": [ + "resource" + ] + }, + "list": { + "path": "v1/{+parent}/entityTypes", + "parameters": { + "pageToken": { + "type": "string", + "description": "A page token, received from a previous FeaturestoreService.ListEntityTypes call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.ListEntityTypes must match the call that provided the page token.", + "location": "query" + }, + "readMask": { + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask", + "type": "string", + "location": "query" + }, + "pageSize": { + "type": "integer", + "description": "The maximum number of EntityTypes to return. The service may return fewer than this value. If unspecified, at most 1000 EntityTypes will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000.", + "location": "query", + "format": "int32" + }, + "parent": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", + "location": "path", + "description": "Required. The resource name of the Featurestore to list EntityTypes. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", + "type": "string" + }, + "filter": { + "description": "Lists the EntityTypes that match the filter expression. The following filters are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003e=`, and `\u003c=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003e=`, and `\u003c=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality as well as key presence. Examples: * `create_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\" OR update_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\"` --\u003e EntityTypes created or updated after 2020-01-31T15:30:00.000000Z. * `labels.active = yes AND labels.env = prod` --\u003e EntityTypes having both (active: yes) and (env: prod) labels. * `labels.env: *` --\u003e Any EntityType which has a label with 'env' as the key.", + "type": "string", + "location": "query" + }, + "orderBy": { + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `entity_type_id` * `create_time` * `update_time`", + "type": "string", + "location": "query" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1ListEntityTypesResponse" + }, + "description": "Lists EntityTypes in a given Featurestore.", + "httpMethod": "GET", + "parameterOrder": [ + "parent" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes", + "id": "aiplatform.projects.locations.featurestores.entityTypes.list" + }, + "readFeatureValues": { + "path": "v1/{+entityType}:readFeatureValues", + "response": { + "$ref": "GoogleCloudAiplatformV1ReadFeatureValuesResponse" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:readFeatureValues", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1ReadFeatureValuesRequest" + }, + "id": "aiplatform.projects.locations.featurestores.entityTypes.readFeatureValues", + "description": "Reads Feature values of a specific entity of an EntityType. For reading feature values of multiple entities of an EntityType, please use StreamingReadFeatureValues.", + "httpMethod": "POST", + "parameterOrder": [ + "entityType" + ], + "parameters": { + "entityType": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "required": true, + "description": "Required. The resource name of the EntityType for the entity being read. Value format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`. For example, for a machine learning model predicting user clicks on a website, an EntityType ID could be `user`.", + "type": "string", + "location": "path" + } + } + }, + "create": { + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", + "description": "Required. The resource name of the Featurestore to create EntityTypes. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", + "type": "string", + "location": "path", + "required": true + }, + "entityTypeId": { + "description": "Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within a featurestore.", + "location": "query", + "type": "string" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1EntityType" + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+parent}/entityTypes", + "parameterOrder": [ + "parent" + ], + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes", + "description": "Creates a new EntityType in a given Featurestore.", + "id": "aiplatform.projects.locations.featurestores.entityTypes.create", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "deleteFeatureValues": { + "description": "Delete Feature values from Featurestore. The progress of the deletion is tracked by the returned operation. The deleted feature values are guaranteed to be invisible to subsequent read operations after the operation is marked as successfully done. If a delete feature values operation fails, the feature values returned from reads and exports may be inconsistent. If consistency is required, the caller must retry the same delete request again and wait till the new operation returned is marked as successfully done.", + "id": "aiplatform.projects.locations.featurestores.entityTypes.deleteFeatureValues", + "parameters": { + "entityType": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "description": "Required. The resource name of the EntityType grouping the Features for which values are being deleted from. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`", + "type": "string", + "required": true + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:deleteFeatureValues", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1DeleteFeatureValuesRequest" + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "entityType" + ], + "httpMethod": "POST", + "path": "v1/{+entityType}:deleteFeatureValues" + }, + "writeFeatureValues": { + "parameters": { + "entityType": { + "description": "Required. The resource name of the EntityType for the entities being written. Value format: `projects/{project}/locations/{location}/featurestores/ {featurestore}/entityTypes/{entityType}`. For example, for a machine learning model predicting user clicks on a website, an EntityType ID could be `user`.", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "type": "string" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1WriteFeatureValuesRequest" + }, + "path": "v1/{+entityType}:writeFeatureValues", + "response": { + "$ref": "GoogleCloudAiplatformV1WriteFeatureValuesResponse" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:writeFeatureValues", + "description": "Writes Feature values of one or more entities of an EntityType. The Feature values are merged into existing entities if any. The Feature values to be written must have timestamp within the online storage retention.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "parameterOrder": [ + "entityType" + ], + "id": "aiplatform.projects.locations.featurestores.entityTypes.writeFeatureValues" + }, + "setIamPolicy": { + "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleIamV1SetIamPolicyRequest" + }, + "response": { + "$ref": "GoogleIamV1Policy" + }, + "parameters": { + "resource": { + "required": true, + "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:setIamPolicy", + "path": "v1/{+resource}:setIamPolicy", + "parameterOrder": [ + "resource" + ], + "id": "aiplatform.projects.locations.featurestores.entityTypes.setIamPolicy", + "httpMethod": "POST" + }, + "get": { + "httpMethod": "GET", + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "type": "string", + "required": true, + "location": "path", + "description": "Required. The name of the EntityType resource. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1EntityType" + }, + "description": "Gets details of a single EntityType.", + "id": "aiplatform.projects.locations.featurestores.entityTypes.get" + }, + "patch": { + "description": "Updates the parameters of a single EntityType.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}", + "id": "aiplatform.projects.locations.featurestores.entityTypes.patch", + "response": { + "$ref": "GoogleCloudAiplatformV1EntityType" + }, + "parameters": { + "name": { + "location": "path", + "description": "Immutable. Name of the EntityType. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "type": "string", + "required": true + }, + "updateMask": { + "format": "google-fieldmask", + "type": "string", + "description": "Field mask is used to specify the fields to be overwritten in the EntityType resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `description` * `labels` * `monitoring_config.snapshot_analysis.disabled` * `monitoring_config.snapshot_analysis.monitoring_interval_days` * `monitoring_config.snapshot_analysis.staleness_days` * `monitoring_config.import_features_analysis.state` * `monitoring_config.import_features_analysis.anomaly_detection_baseline` * `monitoring_config.numerical_threshold_config.value` * `monitoring_config.categorical_threshold_config.value` * `offline_storage_ttl_days`", + "location": "query" + } + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "PATCH", + "path": "v1/{+name}", + "request": { + "$ref": "GoogleCloudAiplatformV1EntityType" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "importFeatureValues": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:importFeatureValues", + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Imports Feature values into the Featurestore from a source storage. The progress of the import is tracked by the returned operation. The imported features are guaranteed to be visible to subsequent read operations after the operation is marked as successfully done. If an import operation fails, the Feature values returned from reads and exports may be inconsistent. If consistency is required, the caller must retry the same import request again and wait till the new operation returned is marked as successfully done. There are also scenarios where the caller can cause inconsistency. - Source data for import contains multiple distinct Feature values for the same entity ID and timestamp. - Source is modified during an import. This includes adding, updating, or removing source data and/or metadata. Examples of updating metadata include but are not limited to changing storage location, storage class, or retention policy. - Online serving cluster is under-provisioned.", + "parameters": { + "entityType": { + "location": "path", + "required": true, + "description": "Required. The resource name of the EntityType grouping the Features for which values are being imported. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$" + } + }, + "parameterOrder": [ + "entityType" + ], + "path": "v1/{+entityType}:importFeatureValues", + "request": { + "$ref": "GoogleCloudAiplatformV1ImportFeatureValuesRequest" + }, + "id": "aiplatform.projects.locations.featurestores.entityTypes.importFeatureValues" + } + } + } + } + }, + "notebookRuntimes": { + "resources": { + "operations": { + "methods": { + "wait": { + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}:wait", + "path": "v1/{+name}:wait", + "httpMethod": "POST", + "id": "aiplatform.projects.locations.notebookRuntimes.operations.wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "required": true, + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string" + }, + "timeout": { + "format": "google-duration", + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "get": { + "path": "v1/{+name}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "GET", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.notebookRuntimes.operations.get", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource.", + "required": true, + "type": "string", + "location": "path" + } + }, + "parameterOrder": [ + "name" + ] + }, + "list": { + "httpMethod": "GET", + "id": "aiplatform.projects.locations.notebookRuntimes.operations.list", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations", + "path": "v1/{+name}/operations", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", + "type": "string", + "required": true, + "location": "path", + "description": "The name of the operation's parent resource." + }, + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "pageSize": { + "type": "integer", + "format": "int32", + "description": "The standard list page size.", + "location": "query" + }, + "pageToken": { + "description": "The standard list page token.", + "location": "query", + "type": "string" + } + }, + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + } + }, + "delete": { + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+/operations/[^/]+$", + "required": true, + "type": "string", + "description": "The name of the operation resource to be deleted.", + "location": "path" + } + }, + "id": "aiplatform.projects.locations.notebookRuntimes.operations.delete", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}", + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ] + }, + "cancel": { + "id": "aiplatform.projects.locations.notebookRuntimes.operations.cancel", + "httpMethod": "POST", + "path": "v1/{+name}:cancel", + "parameters": { + "name": { + "type": "string", + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+/operations/[^/]+$", + "required": true + } + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}:cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ] + } + } + } + }, + "methods": { + "upgrade": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1UpgradeNotebookRuntimeRequest" + }, + "id": "aiplatform.projects.locations.notebookRuntimes.upgrade", + "path": "v1/{+name}:upgrade", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", + "required": true, + "type": "string", + "description": "Required. The name of the NotebookRuntime resource to be upgrade. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner." + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}:upgrade", + "httpMethod": "POST", + "description": "Upgrades a NotebookRuntime.", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "response": { + "$ref": "GoogleCloudAiplatformV1ListNotebookRuntimesResponse" + }, + "description": "Lists NotebookRuntimes in a Location.", + "parameterOrder": [ + "parent" + ], + "path": "v1/{+parent}/notebookRuntimes", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "readMask": { + "description": "Optional. Mask specifying which fields to read.", + "type": "string", + "format": "google-fieldmask", + "location": "query" + }, + "filter": { + "location": "query", + "type": "string", + "description": "Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `notebookRuntime` supports = and !=. `notebookRuntime` represents the NotebookRuntime ID, i.e. the last segment of the NotebookRuntime's resource name. * `displayName` supports = and != and regex. * `notebookRuntimeTemplate` supports = and !=. `notebookRuntimeTemplate` represents the NotebookRuntimeTemplate ID, i.e. the last segment of the NotebookRuntimeTemplate's resource name. * `healthState` supports = and !=. healthState enum: [HEALTHY, UNHEALTHY, HEALTH_STATE_UNSPECIFIED]. * `runtimeState` supports = and !=. runtimeState enum: [RUNTIME_STATE_UNSPECIFIED, RUNNING, BEING_STARTED, BEING_STOPPED, STOPPED, BEING_UPGRADED, ERROR, INVALID]. * `runtimeUser` supports = and !=. * API version is UI only: `uiState` supports = and !=. uiState enum: [UI_RESOURCE_STATE_UNSPECIFIED, UI_RESOURCE_STATE_BEING_CREATED, UI_RESOURCE_STATE_ACTIVE, UI_RESOURCE_STATE_BEING_DELETED, UI_RESOURCE_STATE_CREATION_FAILED]. * `notebookRuntimeType` supports = and !=. notebookRuntimeType enum: [USER_DEFINED, ONE_CLICK]. Some examples: * `notebookRuntime=\"notebookRuntime123\"` * `displayName=\"myDisplayName\"` and `displayName=~\"myDisplayNameRegex\"` * `notebookRuntimeTemplate=\"notebookRuntimeTemplate321\"` * `healthState=HEALTHY` * `runtimeState=RUNNING` * `runtimeUser=\"test@google.com\"` * `uiState=UI_RESOURCE_STATE_BEING_DELETED` * `notebookRuntimeType=USER_DEFINED`" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "Optional. The standard list page token. Typically obtained via ListNotebookRuntimesResponse.next_page_token of the previous NotebookService.ListNotebookRuntimes call." + }, + "pageSize": { + "description": "Optional. The standard list page size.", + "type": "integer", + "location": "query", + "format": "int32" + }, + "parent": { + "type": "string", + "location": "path", + "description": "Required. The resource name of the Location from which to list the NotebookRuntimes. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true + }, + "orderBy": { + "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`.", + "location": "query", + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes", + "httpMethod": "GET", + "id": "aiplatform.projects.locations.notebookRuntimes.list" + }, + "delete": { + "parameters": { + "name": { + "required": true, + "type": "string", + "description": "Required. The name of the NotebookRuntime resource to be deleted. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner.", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", + "location": "path" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "description": "Deletes a NotebookRuntime.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}", + "id": "aiplatform.projects.locations.notebookRuntimes.delete", + "httpMethod": "DELETE", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "start": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1StartNotebookRuntimeRequest" + }, + "httpMethod": "POST", + "parameters": { + "name": { + "required": true, + "description": "Required. The name of the NotebookRuntime resource to be started. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner.", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", + "type": "string", + "location": "path" + } + }, + "parameterOrder": [ + "name" + ], + "description": "Starts a NotebookRuntime.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}:start", + "path": "v1/{+name}:start", + "id": "aiplatform.projects.locations.notebookRuntimes.start" + }, + "get": { + "parameters": { + "name": { + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", + "description": "Required. The name of the NotebookRuntime resource. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner." + } + }, + "httpMethod": "GET", + "path": "v1/{+name}", + "description": "Gets a NotebookRuntime.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}", + "response": { + "$ref": "GoogleCloudAiplatformV1NotebookRuntime" + }, + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.notebookRuntimes.get" + }, + "assign": { + "parameterOrder": [ + "parent" + ], + "httpMethod": "POST", + "description": "Assigns a NotebookRuntime to a user for a particular Notebook file. This method will either returns an existing assignment or generates a new one.", + "request": { + "$ref": "GoogleCloudAiplatformV1AssignNotebookRuntimeRequest" + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+parent}/notebookRuntimes:assign", + "parameters": { + "parent": { + "type": "string", + "description": "Required. The resource name of the Location to get the NotebookRuntime assignment. Format: `projects/{project}/locations/{location}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true + } + }, + "id": "aiplatform.projects.locations.notebookRuntimes.assign", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes:assign" + } + } + }, + "publishers": { + "resources": { + "models": { + "methods": { + "computeTokens": { + "description": "Return a list of tokens based on the input text.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "parameters": { + "endpoint": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", + "location": "path", + "type": "string", + "description": "Required. The name of the Endpoint requested to get lists of tokens and token ids." + } + }, + "id": "aiplatform.projects.locations.publishers.models.computeTokens", + "parameterOrder": [ + "endpoint" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:computeTokens", + "response": { + "$ref": "GoogleCloudAiplatformV1ComputeTokensResponse" + }, + "path": "v1/{+endpoint}:computeTokens", + "request": { + "$ref": "GoogleCloudAiplatformV1ComputeTokensRequest" + } + }, + "generateContent": { + "id": "aiplatform.projects.locations.publishers.models.generateContent", + "httpMethod": "POST", + "path": "v1/{+model}:generateContent", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1GenerateContentResponse" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:generateContent", + "request": { + "$ref": "GoogleCloudAiplatformV1GenerateContentRequest" + }, + "description": "Generate content with multimodal inputs.", + "parameters": { + "model": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", + "description": "Required. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`", + "location": "path", + "type": "string" + } + }, + "parameterOrder": [ + "model" + ] + }, + "streamRawPredict": { + "id": "aiplatform.projects.locations.publishers.models.streamRawPredict", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:streamRawPredict", + "description": "Perform a streaming online prediction with an arbitrary HTTP payload.", + "httpMethod": "POST", + "parameterOrder": [ + "endpoint" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1StreamRawPredictRequest" + }, + "path": "v1/{+endpoint}:streamRawPredict", + "parameters": { + "endpoint": { + "type": "string", + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "response": { + "$ref": "GoogleApiHttpBody" + } + }, + "rawPredict": { + "response": { + "$ref": "GoogleApiHttpBody" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:rawPredict", + "path": "v1/{+endpoint}:rawPredict", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "description": "Perform an online prediction with an arbitrary HTTP payload. The response includes the following HTTP headers: * `X-Vertex-AI-Endpoint-Id`: ID of the Endpoint that served this prediction. * `X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's DeployedModel that served this prediction.", + "parameters": { + "endpoint": { + "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", + "required": true, + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "type": "string", + "location": "path" + } + }, + "parameterOrder": [ + "endpoint" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1RawPredictRequest" + }, + "id": "aiplatform.projects.locations.publishers.models.rawPredict" + }, + "serverStreamingPredict": { + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1StreamingPredictRequest" + }, + "id": "aiplatform.projects.locations.publishers.models.serverStreamingPredict", + "path": "v1/{+endpoint}:serverStreamingPredict", + "parameterOrder": [ + "endpoint" + ], + "parameters": { + "endpoint": { + "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", + "type": "string", + "required": true, + "location": "path", + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:serverStreamingPredict", + "description": "Perform a server-side streaming online prediction request for Vertex LLM streaming.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1StreamingPredictResponse" + } + }, + "countTokens": { + "id": "aiplatform.projects.locations.publishers.models.countTokens", + "httpMethod": "POST", + "path": "v1/{+endpoint}:countTokens", + "response": { + "$ref": "GoogleCloudAiplatformV1CountTokensResponse" + }, + "parameterOrder": [ + "endpoint" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1CountTokensRequest" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:countTokens", + "description": "Perform a token counting.", + "parameters": { + "endpoint": { + "description": "Required. The name of the Endpoint requested to perform token counting. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "type": "string", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "streamGenerateContent": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:streamGenerateContent", + "httpMethod": "POST", + "description": "Generate content with multimodal inputs with streaming support.", + "path": "v1/{+model}:streamGenerateContent", + "parameterOrder": [ + "model" + ], + "id": "aiplatform.projects.locations.publishers.models.streamGenerateContent", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1GenerateContentResponse" + }, + "parameters": { + "model": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", + "type": "string", + "description": "Required. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`", + "required": true + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1GenerateContentRequest" + } + }, + "predict": { + "parameters": { + "endpoint": { + "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", + "required": true, + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "type": "string", + "location": "path" + } + }, + "id": "aiplatform.projects.locations.publishers.models.predict", + "request": { + "$ref": "GoogleCloudAiplatformV1PredictRequest" + }, + "description": "Perform an online prediction.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:predict", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "parameterOrder": [ + "endpoint" + ], + "path": "v1/{+endpoint}:predict", + "response": { + "$ref": "GoogleCloudAiplatformV1PredictResponse" + } + } + } + } + } + }, + "metadataStores": { + "resources": { + "executions": { + "resources": { + "operations": { + "methods": { + "wait": { + "path": "v1/{+name}:wait", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}:wait", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.metadataStores.executions.operations.wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "parameters": { + "name": { + "description": "The name of the operation resource to wait on.", + "required": true, + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$" + }, + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "type": "string", + "location": "query" + } + } + }, + "get": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}", + "path": "v1/{+name}", + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource.", + "location": "path", + "required": true + } + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.metadataStores.executions.operations.get", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "filter": { + "description": "The standard list filter.", + "location": "query", + "type": "string" + }, + "name": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", + "required": true, + "description": "The name of the operation's parent resource." + }, + "pageToken": { + "description": "The standard list page token.", + "location": "query", + "type": "string" + }, + "pageSize": { + "location": "query", + "description": "The standard list page size.", + "format": "int32", + "type": "integer" + } + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "path": "v1/{+name}/operations", + "id": "aiplatform.projects.locations.metadataStores.executions.operations.list", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations", + "httpMethod": "GET" + }, + "delete": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}", + "httpMethod": "DELETE", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "description": "The name of the operation resource to be deleted." + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "id": "aiplatform.projects.locations.metadataStores.executions.operations.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "cancel": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "httpMethod": "POST", + "id": "aiplatform.projects.locations.metadataStores.executions.operations.cancel", + "parameterOrder": [ + "name" + ], + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", + "location": "path", + "required": true, + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}:cancel", + "path": "v1/{+name}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + } + } + } + }, + "methods": { + "patch": { + "parameters": { + "allowMissing": { + "type": "boolean", + "description": "If set to true, and the Execution is not found, a new Execution is created.", + "location": "query" + }, + "updateMask": { + "format": "google-fieldmask", + "description": "Optional. A FieldMask indicating which fields should be updated.", + "location": "query", + "type": "string" + }, + "name": { + "type": "string", + "location": "path", + "description": "Output only. The resource name of the Execution.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$" + } + }, + "path": "v1/{+name}", + "response": { + "$ref": "GoogleCloudAiplatformV1Execution" + }, + "id": "aiplatform.projects.locations.metadataStores.executions.patch", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1Execution" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}", + "description": "Updates a stored Execution.", + "httpMethod": "PATCH" + }, + "addExecutionEvents": { + "parameterOrder": [ + "execution" + ], + "parameters": { + "execution": { + "required": true, + "description": "Required. The resource name of the Execution that the Events connect Artifacts with. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$" + } + }, + "description": "Adds Events to the specified Execution. An Event indicates whether an Artifact was used as an input or output for an Execution. If an Event already exists between the Execution and the Artifact, the Event is skipped.", + "path": "v1/{+execution}:addExecutionEvents", + "response": { + "$ref": "GoogleCloudAiplatformV1AddExecutionEventsResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1AddExecutionEventsRequest" + }, + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}:addExecutionEvents", + "id": "aiplatform.projects.locations.metadataStores.executions.addExecutionEvents" + }, + "list": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions", + "response": { + "$ref": "GoogleCloudAiplatformV1ListExecutionsResponse" + }, + "id": "aiplatform.projects.locations.metadataStores.executions.list", + "description": "Lists Executions in the MetadataStore.", + "parameterOrder": [ + "parent" + ], + "parameters": { + "pageSize": { + "location": "query", + "description": "The maximum number of Executions to return. The service may return fewer. Must be in range 1-1000, inclusive. Defaults to 100.", + "format": "int32", + "type": "integer" + }, + "orderBy": { + "type": "string", + "location": "query", + "description": "How the list of messages is ordered. Specify the values to order by and an ordering operation. The default sorting order is ascending. To specify descending order for a field, users append a \" desc\" suffix; for example: \"foo desc, bar\". Subfields are specified with a `.` character, such as foo.bar. see https://google.aip.dev/132#ordering for more details." + }, + "filter": { + "description": "Filter specifying the boolean condition for the Executions to satisfy in order to be part of the result set. The syntax to define filter query is based on https://google.aip.dev/160. Following are the supported set of filters: * **Attribute filtering**: For example: `display_name = \"test\"`. Supported fields include: `name`, `display_name`, `state`, `schema_title`, `create_time`, and `update_time`. Time fields, such as `create_time` and `update_time`, require values specified in RFC-3339 format. For example: `create_time = \"2020-11-19T11:30:00-04:00\"`. * **Metadata field**: To filter on metadata fields use traversal operation as follows: `metadata..` For example: `metadata.field_1.number_value = 10.0` In case the field name contains special characters (such as colon), one can embed it inside double quote. For example: `metadata.\"field:1\".number_value = 10.0` * **Context based filtering**: To filter Executions based on the contexts to which they belong use the function operator with the full resource name: `in_context()`. For example: `in_context(\"projects//locations//metadataStores//contexts/\")` Each of the above supported filters can be combined together using logical operators (`AND` & `OR`). Maximum nested expression depth allowed is 5. For example: `display_name = \"test\" AND metadata.field1.bool_value = true`.", + "location": "query", + "type": "string" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "A page token, received from a previous MetadataService.ListExecutions call. Provide this to retrieve the subsequent page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with an INVALID_ARGUMENT error.)" + }, + "parent": { + "location": "path", + "description": "Required. The MetadataStore whose Executions should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "type": "string", + "required": true + } + }, + "httpMethod": "GET", + "path": "v1/{+parent}/executions", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "queryExecutionInputsAndOutputs": { + "path": "v1/{+execution}:queryExecutionInputsAndOutputs", + "parameterOrder": [ + "execution" + ], + "description": "Obtains the set of input and output Artifacts for this Execution, in the form of LineageSubgraph that also contains the Execution and connecting Events.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}:queryExecutionInputsAndOutputs", + "id": "aiplatform.projects.locations.metadataStores.executions.queryExecutionInputsAndOutputs", + "parameters": { + "execution": { + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", + "location": "path", + "description": "Required. The resource name of the Execution whose input and output Artifacts should be retrieved as a LineageSubgraph. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1LineageSubgraph" + } + }, + "purge": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "parent" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1PurgeExecutionsRequest" + }, + "description": "Purges Executions.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions:purge", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+parent}/executions:purge", + "id": "aiplatform.projects.locations.metadataStores.executions.purge", + "parameters": { + "parent": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "location": "path", + "required": true, + "description": "Required. The metadata store to purge Executions from. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`" + } + } + }, + "get": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "description": "Retrieves a specific Execution.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "description": "Required. The resource name of the Execution to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`", + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", + "required": true + } + }, + "id": "aiplatform.projects.locations.metadataStores.executions.get", + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1Execution" + } + }, + "delete": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "DELETE", + "description": "Deletes an Execution.", + "parameters": { + "etag": { + "description": "Optional. The etag of the Execution to delete. If this is provided, it must match the server's etag. Otherwise, the request will fail with a FAILED_PRECONDITION.", + "type": "string", + "location": "query" + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", + "description": "Required. The resource name of the Execution to delete. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`", + "required": true, + "location": "path", + "type": "string" + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.metadataStores.executions.delete", + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "create": { + "request": { + "$ref": "GoogleCloudAiplatformV1Execution" + }, + "httpMethod": "POST", + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1Execution" + }, + "id": "aiplatform.projects.locations.metadataStores.executions.create", + "parameters": { + "parent": { + "location": "path", + "description": "Required. The resource name of the MetadataStore where the Execution should be created. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "type": "string" + }, + "executionId": { + "type": "string", + "description": "The {execution} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}` If not provided, the Execution's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Executions in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Execution.)", + "location": "query" + } + }, + "description": "Creates an Execution associated with a MetadataStore.", + "path": "v1/{+parent}/executions", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions" + } + } + }, + "contexts": { + "resources": { + "operations": { + "methods": { + "delete": { + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "id": "aiplatform.projects.locations.metadataStores.contexts.operations.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be deleted.", + "required": true, + "location": "path" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}", + "httpMethod": "DELETE", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ] + }, + "get": { + "id": "aiplatform.projects.locations.metadataStores.contexts.operations.get", + "httpMethod": "GET", + "parameters": { + "name": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource.", + "required": true + } + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}" + }, + "list": { + "parameters": { + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter." + }, + "name": { + "required": true, + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", + "location": "path", + "type": "string" + }, + "pageToken": { + "description": "The standard list page token.", + "location": "query", + "type": "string" + }, + "pageSize": { + "type": "integer", + "format": "int32", + "location": "query", + "description": "The standard list page size." + } + }, + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}/operations", + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations", + "id": "aiplatform.projects.locations.metadataStores.contexts.operations.list", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + } + }, + "cancel": { + "httpMethod": "POST", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}:cancel", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}:cancel", + "parameters": { + "name": { + "required": true, + "description": "The name of the operation resource to be cancelled.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "id": "aiplatform.projects.locations.metadataStores.contexts.operations.cancel" + }, + "wait": { + "parameterOrder": [ + "name" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "timeout": { + "location": "query", + "type": "string", + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + }, + "name": { + "description": "The name of the operation resource to wait on.", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.metadataStores.contexts.operations.wait", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}:wait", + "path": "v1/{+name}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + } + } + } + } + }, + "methods": { + "get": { + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "description": "Retrieves a specific Context.", + "parameters": { + "name": { + "required": true, + "description": "Required. The resource name of the Context to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", + "type": "string" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1Context" + }, + "id": "aiplatform.projects.locations.metadataStores.contexts.get", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}", + "path": "v1/{+name}" + }, + "patch": { + "httpMethod": "PATCH", + "response": { + "$ref": "GoogleCloudAiplatformV1Context" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1Context" + }, + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "description": "Updates a stored Context.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.metadataStores.contexts.patch", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", + "location": "path", + "required": true, + "type": "string", + "description": "Immutable. The resource name of the Context." + }, + "updateMask": { + "format": "google-fieldmask", + "description": "Optional. A FieldMask indicating which fields should be updated.", + "type": "string", + "location": "query" + }, + "allowMissing": { + "type": "boolean", + "location": "query", + "description": "If set to true, and the Context is not found, a new Context is created." + } + } + }, + "delete": { + "httpMethod": "DELETE", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}", + "parameters": { + "force": { + "type": "boolean", + "description": "The force deletion semantics is still undefined. Users should not use this field.", + "location": "query" + }, + "etag": { + "location": "query", + "type": "string", + "description": "Optional. The etag of the Context to delete. If this is provided, it must match the server's etag. Otherwise, the request will fail with a FAILED_PRECONDITION." + }, + "name": { + "required": true, + "description": "Required. The resource name of the Context to delete. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", + "location": "path", + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}", + "id": "aiplatform.projects.locations.metadataStores.contexts.delete", + "description": "Deletes a stored Context.", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "addContextChildren": { + "request": { + "$ref": "GoogleCloudAiplatformV1AddContextChildrenRequest" + }, + "id": "aiplatform.projects.locations.metadataStores.contexts.addContextChildren", + "path": "v1/{+context}:addContextChildren", + "response": { + "$ref": "GoogleCloudAiplatformV1AddContextChildrenResponse" + }, + "parameters": { + "context": { + "type": "string", + "location": "path", + "description": "Required. The resource name of the parent Context. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$" + } + }, + "parameterOrder": [ + "context" + ], + "httpMethod": "POST", + "description": "Adds a set of Contexts as children to a parent Context. If any of the child Contexts have already been added to the parent Context, they are simply skipped. If this call would create a cycle or cause any Context to have more than 10 parents, the request will fail with an INVALID_ARGUMENT error.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}:addContextChildren" + }, + "addContextArtifactsAndExecutions": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}:addContextArtifactsAndExecutions", + "response": { + "$ref": "GoogleCloudAiplatformV1AddContextArtifactsAndExecutionsResponse" + }, + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "context": { + "type": "string", + "required": true, + "location": "path", + "description": "Required. The resource name of the Context that the Artifacts and Executions belong to. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$" + } + }, + "parameterOrder": [ + "context" + ], + "path": "v1/{+context}:addContextArtifactsAndExecutions", + "request": { + "$ref": "GoogleCloudAiplatformV1AddContextArtifactsAndExecutionsRequest" + }, + "id": "aiplatform.projects.locations.metadataStores.contexts.addContextArtifactsAndExecutions", + "description": "Adds a set of Artifacts and Executions to a Context. If any of the Artifacts or Executions have already been added to a Context, they are simply skipped." + }, + "removeContextChildren": { + "description": "Remove a set of children contexts from a parent Context. If any of the child Contexts were NOT added to the parent Context, they are simply skipped.", + "httpMethod": "POST", + "response": { + "$ref": "GoogleCloudAiplatformV1RemoveContextChildrenResponse" + }, + "path": "v1/{+context}:removeContextChildren", + "request": { + "$ref": "GoogleCloudAiplatformV1RemoveContextChildrenRequest" + }, + "id": "aiplatform.projects.locations.metadataStores.contexts.removeContextChildren", + "parameterOrder": [ + "context" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}:removeContextChildren", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "context": { + "location": "path", + "type": "string", + "required": true, + "description": "Required. The resource name of the parent Context. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$" + } + } + }, + "queryContextLineageSubgraph": { + "path": "v1/{+context}:queryContextLineageSubgraph", + "httpMethod": "GET", + "parameterOrder": [ + "context" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1LineageSubgraph" + }, + "id": "aiplatform.projects.locations.metadataStores.contexts.queryContextLineageSubgraph", + "parameters": { + "context": { + "location": "path", + "type": "string", + "description": "Required. The resource name of the Context whose Artifacts and Executions should be retrieved as a LineageSubgraph. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}` The request may error with FAILED_PRECONDITION if the number of Artifacts, the number of Executions, or the number of Events that would be returned for the Context exceeds 1000.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$" + } + }, + "description": "Retrieves Artifacts and Executions within the specified Context, connected by Event edges and returned as a LineageSubgraph.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}:queryContextLineageSubgraph", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "create": { + "request": { + "$ref": "GoogleCloudAiplatformV1Context" + }, + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts", + "parameterOrder": [ + "parent" + ], + "path": "v1/{+parent}/contexts", + "description": "Creates a Context associated with a MetadataStore.", + "id": "aiplatform.projects.locations.metadataStores.contexts.create", + "parameters": { + "parent": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "description": "Required. The resource name of the MetadataStore where the Context should be created. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", + "location": "path", + "required": true + }, + "contextId": { + "location": "query", + "description": "The {context} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`. If not provided, the Context's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Contexts in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Context.)", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1Context" + } + }, + "purge": { + "id": "aiplatform.projects.locations.metadataStores.contexts.purge", + "request": { + "$ref": "GoogleCloudAiplatformV1PurgeContextsRequest" + }, + "httpMethod": "POST", + "parameterOrder": [ + "parent" + ], + "description": "Purges Contexts.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts:purge", + "parameters": { + "parent": { + "description": "Required. The metadata store to purge Contexts from. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "location": "path", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+parent}/contexts:purge", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "list": { + "description": "Lists Contexts on the MetadataStore.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts", + "path": "v1/{+parent}/contexts", + "httpMethod": "GET", + "parameters": { + "filter": { + "location": "query", + "type": "string", + "description": "Filter specifying the boolean condition for the Contexts to satisfy in order to be part of the result set. The syntax to define filter query is based on https://google.aip.dev/160. Following are the supported set of filters: * **Attribute filtering**: For example: `display_name = \"test\"`. Supported fields include: `name`, `display_name`, `schema_title`, `create_time`, and `update_time`. Time fields, such as `create_time` and `update_time`, require values specified in RFC-3339 format. For example: `create_time = \"2020-11-19T11:30:00-04:00\"`. * **Metadata field**: To filter on metadata fields use traversal operation as follows: `metadata..`. For example: `metadata.field_1.number_value = 10.0`. In case the field name contains special characters (such as colon), one can embed it inside double quote. For example: `metadata.\"field:1\".number_value = 10.0` * **Parent Child filtering**: To filter Contexts based on parent-child relationship use the HAS operator as follows: ``` parent_contexts: \"projects//locations//metadataStores//contexts/\" child_contexts: \"projects//locations//metadataStores//contexts/\" ``` Each of the above supported filters can be combined together using logical operators (`AND` & `OR`). Maximum nested expression depth allowed is 5. For example: `display_name = \"test\" AND metadata.field1.bool_value = true`." + }, + "orderBy": { + "location": "query", + "description": "How the list of messages is ordered. Specify the values to order by and an ordering operation. The default sorting order is ascending. To specify descending order for a field, users append a \" desc\" suffix; for example: \"foo desc, bar\". Subfields are specified with a `.` character, such as foo.bar. see https://google.aip.dev/132#ordering for more details.", + "type": "string" + }, + "parent": { + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "description": "Required. The MetadataStore whose Contexts should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`" + }, + "pageToken": { + "type": "string", + "description": "A page token, received from a previous MetadataService.ListContexts call. Provide this to retrieve the subsequent page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with INVALID_ARGUMENT error.)", + "location": "query" + }, + "pageSize": { + "location": "query", + "format": "int32", + "description": "The maximum number of Contexts to return. The service may return fewer. Must be in range 1-1000, inclusive. Defaults to 100.", + "type": "integer" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1ListContextsResponse" + }, + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.metadataStores.contexts.list" + } + } + }, + "artifacts": { + "methods": { + "queryArtifactLineageSubgraph": { + "path": "v1/{+artifact}:queryArtifactLineageSubgraph", + "id": "aiplatform.projects.locations.metadataStores.artifacts.queryArtifactLineageSubgraph", + "parameterOrder": [ + "artifact" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1LineageSubgraph" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}:queryArtifactLineageSubgraph", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "filter": { + "description": "Filter specifying the boolean condition for the Artifacts to satisfy in order to be part of the Lineage Subgraph. The syntax to define filter query is based on https://google.aip.dev/160. The supported set of filters include the following: * **Attribute filtering**: For example: `display_name = \"test\"` Supported fields include: `name`, `display_name`, `uri`, `state`, `schema_title`, `create_time`, and `update_time`. Time fields, such as `create_time` and `update_time`, require values specified in RFC-3339 format. For example: `create_time = \"2020-11-19T11:30:00-04:00\"` * **Metadata field**: To filter on metadata fields use traversal operation as follows: `metadata..`. For example: `metadata.field_1.number_value = 10.0` In case the field name contains special characters (such as colon), one can embed it inside double quote. For example: `metadata.\"field:1\".number_value = 10.0` Each of the above supported filter types can be combined together using logical operators (`AND` & `OR`). Maximum nested expression depth allowed is 5. For example: `display_name = \"test\" AND metadata.field1.bool_value = true`.", + "type": "string", + "location": "query" + }, + "artifact": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$", + "required": true, + "description": "Required. The resource name of the Artifact whose Lineage needs to be retrieved as a LineageSubgraph. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}` The request may error with FAILED_PRECONDITION if the number of Artifacts, the number of Executions, or the number of Events that would be returned for the Context exceeds 1000." + }, + "maxHops": { + "type": "integer", + "description": "Specifies the size of the lineage graph in terms of number of hops from the specified artifact. Negative Value: INVALID_ARGUMENT error is returned 0: Only input artifact is returned. No value: Transitive closure is performed to return the complete graph.", + "format": "int32", + "location": "query" + } + }, + "httpMethod": "GET", + "description": "Retrieves lineage of an Artifact represented through Artifacts and Executions connected by Event edges and returned as a LineageSubgraph." + }, + "delete": { + "parameterOrder": [ + "name" + ], + "description": "Deletes an Artifact.", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$", + "required": true, + "type": "string", + "description": "Required. The resource name of the Artifact to delete. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`" + }, + "etag": { + "description": "Optional. The etag of the Artifact to delete. If this is provided, it must match the server's etag. Otherwise, the request will fail with a FAILED_PRECONDITION.", + "location": "query", + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}", + "id": "aiplatform.projects.locations.metadataStores.artifacts.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}", + "httpMethod": "DELETE" + }, + "get": { + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.metadataStores.artifacts.get", + "response": { + "$ref": "GoogleCloudAiplatformV1Artifact" + }, + "httpMethod": "GET", + "description": "Retrieves a specific Artifact.", + "parameters": { + "name": { + "type": "string", + "description": "Required. The resource name of the Artifact to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}" + }, + "list": { + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "parent": { + "location": "path", + "description": "Required. The MetadataStore whose Artifacts should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$" + }, + "orderBy": { + "location": "query", + "description": "How the list of messages is ordered. Specify the values to order by and an ordering operation. The default sorting order is ascending. To specify descending order for a field, users append a \" desc\" suffix; for example: \"foo desc, bar\". Subfields are specified with a `.` character, such as foo.bar. see https://google.aip.dev/132#ordering for more details.", + "type": "string" + }, + "pageSize": { + "type": "integer", + "location": "query", + "format": "int32", + "description": "The maximum number of Artifacts to return. The service may return fewer. Must be in range 1-1000, inclusive. Defaults to 100." + }, + "filter": { + "type": "string", + "location": "query", + "description": "Filter specifying the boolean condition for the Artifacts to satisfy in order to be part of the result set. The syntax to define filter query is based on https://google.aip.dev/160. The supported set of filters include the following: * **Attribute filtering**: For example: `display_name = \"test\"`. Supported fields include: `name`, `display_name`, `uri`, `state`, `schema_title`, `create_time`, and `update_time`. Time fields, such as `create_time` and `update_time`, require values specified in RFC-3339 format. For example: `create_time = \"2020-11-19T11:30:00-04:00\"` * **Metadata field**: To filter on metadata fields use traversal operation as follows: `metadata..`. For example: `metadata.field_1.number_value = 10.0` In case the field name contains special characters (such as colon), one can embed it inside double quote. For example: `metadata.\"field:1\".number_value = 10.0` * **Context based filtering**: To filter Artifacts based on the contexts to which they belong, use the function operator with the full resource name `in_context()`. For example: `in_context(\"projects//locations//metadataStores//contexts/\")` Each of the above supported filter types can be combined together using logical operators (`AND` & `OR`). Maximum nested expression depth allowed is 5. For example: `display_name = \"test\" AND metadata.field1.bool_value = true`." + }, + "pageToken": { + "description": "A page token, received from a previous MetadataService.ListArtifacts call. Provide this to retrieve the subsequent page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with INVALID_ARGUMENT error.)", + "location": "query", + "type": "string" + } + }, + "httpMethod": "GET", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts", + "response": { + "$ref": "GoogleCloudAiplatformV1ListArtifactsResponse" + }, + "description": "Lists Artifacts in the MetadataStore.", + "path": "v1/{+parent}/artifacts", + "id": "aiplatform.projects.locations.metadataStores.artifacts.list" + }, + "patch": { + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1Artifact" + }, + "path": "v1/{+name}", + "request": { + "$ref": "GoogleCloudAiplatformV1Artifact" + }, + "description": "Updates a stored Artifact.", + "httpMethod": "PATCH", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}", + "id": "aiplatform.projects.locations.metadataStores.artifacts.patch", + "parameters": { + "allowMissing": { + "location": "query", + "type": "boolean", + "description": "If set to true, and the Artifact is not found, a new Artifact is created." + }, + "updateMask": { + "location": "query", + "type": "string", + "description": "Optional. A FieldMask indicating which fields should be updated.", + "format": "google-fieldmask" + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$", + "description": "Output only. The resource name of the Artifact.", + "required": true, + "location": "path", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "create": { + "description": "Creates an Artifact associated with a MetadataStore.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1Artifact" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1Artifact" + }, + "path": "v1/{+parent}/artifacts", + "parameters": { + "artifactId": { + "location": "query", + "description": "The {artifact} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}` If not provided, the Artifact's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Artifacts in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Artifact.)", + "type": "string" + }, + "parent": { + "description": "Required. The resource name of the MetadataStore where the Artifact should be created. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "required": true, + "location": "path", + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts", + "id": "aiplatform.projects.locations.metadataStores.artifacts.create", + "parameterOrder": [ + "parent" + ], + "httpMethod": "POST" + }, + "purge": { + "request": { + "$ref": "GoogleCloudAiplatformV1PurgeArtifactsRequest" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "parent": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "required": true, + "description": "Required. The metadata store to purge Artifacts from. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`" + } + }, + "id": "aiplatform.projects.locations.metadataStores.artifacts.purge", + "path": "v1/{+parent}/artifacts:purge", + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Purges Artifacts.", + "parameterOrder": [ + "parent" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts:purge" + } + }, + "resources": { + "operations": { + "methods": { + "cancel": { + "path": "v1/{+name}:cancel", + "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.cancel", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}:cancel", + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "description": "The name of the operation resource to be cancelled." + } + }, + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + } + }, + "wait": { + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}:wait", + "httpMethod": "POST", + "parameters": { + "timeout": { + "type": "string", + "location": "query", + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + }, + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "location": "path", + "required": true + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations", + "parameters": { + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + }, + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "name": { + "required": true, + "location": "path", + "type": "string", + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$" + }, + "pageSize": { + "description": "The standard list page size.", + "format": "int32", + "location": "query", + "type": "integer" + } + }, + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}/operations", + "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.list", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." + }, + "delete": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.delete", + "httpMethod": "DELETE", + "parameters": { + "name": { + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be deleted." + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "get": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "httpMethod": "GET", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", + "type": "string", + "location": "path", + "required": true, + "description": "The name of the operation resource." + } + }, + "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.get" + } + } + } + } + }, + "metadataSchemas": { + "methods": { + "create": { + "parameters": { + "parent": { + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "location": "path", + "description": "Required. The resource name of the MetadataStore where the MetadataSchema should be created. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`" + }, + "metadataSchemaId": { + "type": "string", + "description": "The {metadata_schema} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/metadataSchemas/{metadataschema}` If not provided, the MetadataStore's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all MetadataSchemas in the parent Location. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting MetadataSchema.)", + "location": "query" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1MetadataSchema" + }, + "path": "v1/{+parent}/metadataSchemas", + "description": "Creates a MetadataSchema.", + "parameterOrder": [ + "parent" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1MetadataSchema" + }, + "id": "aiplatform.projects.locations.metadataStores.metadataSchemas.create", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/metadataSchemas", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST" + }, + "get": { + "parameters": { + "name": { + "type": "string", + "description": "Required. The resource name of the MetadataSchema to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/metadataSchemas/{metadataschema}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/metadataSchemas/[^/]+$", + "required": true + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/metadataSchemas/{metadataSchemasId}", + "response": { + "$ref": "GoogleCloudAiplatformV1MetadataSchema" + }, + "id": "aiplatform.projects.locations.metadataStores.metadataSchemas.get", + "description": "Retrieves a specific MetadataSchema.", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET" + }, + "list": { + "response": { + "$ref": "GoogleCloudAiplatformV1ListMetadataSchemasResponse" + }, + "parameters": { + "pageSize": { + "format": "int32", + "location": "query", + "description": "The maximum number of MetadataSchemas to return. The service may return fewer. Must be in range 1-1000, inclusive. Defaults to 100.", + "type": "integer" + }, + "parent": { + "description": "Required. The MetadataStore whose MetadataSchemas should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "required": true + }, + "filter": { + "type": "string", + "location": "query", + "description": "A query to filter available MetadataSchemas for matching results." + }, + "pageToken": { + "description": "A page token, received from a previous MetadataService.ListMetadataSchemas call. Provide this to retrieve the next page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with INVALID_ARGUMENT error.)", + "type": "string", + "location": "query" + } + }, + "parameterOrder": [ + "parent" + ], + "path": "v1/{+parent}/metadataSchemas", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/metadataSchemas", + "id": "aiplatform.projects.locations.metadataStores.metadataSchemas.list", + "description": "Lists MetadataSchemas.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET" + } + } + }, + "operations": { + "methods": { + "get": { + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/operations/[^/]+$", + "type": "string", + "description": "The name of the operation resource.", + "required": true, + "location": "path" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations/{operationsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "GET", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "id": "aiplatform.projects.locations.metadataStores.operations.get" + }, + "cancel": { + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations/{operationsId}:cancel", + "parameters": { + "name": { + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/operations/[^/]+$" + } + }, + "path": "v1/{+name}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "id": "aiplatform.projects.locations.metadataStores.operations.cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`." + }, + "wait": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.metadataStores.operations.wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "parameters": { + "timeout": { + "format": "google-duration", + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string" + }, + "name": { + "location": "path", + "required": true, + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations/{operationsId}:wait", + "httpMethod": "POST", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "path": "v1/{+name}:wait" + }, + "delete": { + "parameters": { + "name": { + "description": "The name of the operation resource to be deleted.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/operations/[^/]+$", + "type": "string", + "required": true + } + }, + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.metadataStores.operations.delete", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "DELETE" + }, + "list": { + "httpMethod": "GET", + "id": "aiplatform.projects.locations.metadataStores.operations.list", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter." + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "location": "path", + "required": true, + "type": "string", + "description": "The name of the operation's parent resource." + }, + "pageSize": { + "format": "int32", + "description": "The standard list page size.", + "location": "query", + "type": "integer" + }, + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "path": "v1/{+name}/operations", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations" + } + } + } + }, + "methods": { + "get": { + "id": "aiplatform.projects.locations.metadataStores.get", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "description": "Required. The resource name of the MetadataStore to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "description": "Retrieves a specific MetadataStore.", + "response": { + "$ref": "GoogleCloudAiplatformV1MetadataStore" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}", + "path": "v1/{+name}" + }, + "delete": { + "parameterOrder": [ + "name" + ], + "parameters": { + "force": { + "deprecated": true, + "description": "Deprecated: Field is no longer supported.", + "location": "query", + "type": "boolean" + }, + "name": { + "required": true, + "location": "path", + "description": "Required. The resource name of the MetadataStore to delete. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}", + "description": "Deletes a single MetadataStore and all its child resources (Artifacts, Executions, and Contexts).", + "id": "aiplatform.projects.locations.metadataStores.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}", + "httpMethod": "DELETE" + }, + "create": { + "parameterOrder": [ + "parent" + ], + "description": "Initializes a MetadataStore, including allocation of resources.", + "path": "v1/{+parent}/metadataStores", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1MetadataStore" + }, + "parameters": { + "parent": { + "description": "Required. The resource name of the Location where the MetadataStore should be created. Format: `projects/{project}/locations/{location}/`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true, + "location": "path" + }, + "metadataStoreId": { + "location": "query", + "description": "The {metadatastore} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` If not provided, the MetadataStore's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all MetadataStores in the parent Location. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting MetadataStore.)", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.metadataStores.create" + }, + "list": { + "id": "aiplatform.projects.locations.metadataStores.list", + "parameters": { + "pageSize": { + "location": "query", + "type": "integer", + "format": "int32", + "description": "The maximum number of Metadata Stores to return. The service may return fewer. Must be in range 1-1000, inclusive. Defaults to 100." + }, + "pageToken": { + "description": "A page token, received from a previous MetadataService.ListMetadataStores call. Provide this to retrieve the subsequent page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with INVALID_ARGUMENT error.)", + "location": "query", + "type": "string" + }, + "parent": { + "description": "Required. The Location whose MetadataStores should be listed. Format: `projects/{project}/locations/{location}`", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists MetadataStores for a Location.", + "parameterOrder": [ + "parent" + ], + "httpMethod": "GET", + "path": "v1/{+parent}/metadataStores", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores", + "response": { + "$ref": "GoogleCloudAiplatformV1ListMetadataStoresResponse" + } + } + } + }, + "operations": { + "methods": { + "wait": { + "httpMethod": "POST", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "type": "string", + "format": "google-duration" + }, + "name": { + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "location": "path" + } + }, + "path": "v1/{+name}:wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}:wait", + "id": "aiplatform.projects.locations.operations.wait" + }, + "cancel": { + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "required": true, + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}:cancel", + "id": "aiplatform.projects.locations.operations.cancel", + "path": "v1/{+name}:cancel", + "parameterOrder": [ + "name" + ] + }, + "list": { + "id": "aiplatform.projects.locations.operations.list", + "path": "v1/{+name}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/operations", + "parameters": { + "pageSize": { + "location": "query", + "description": "The standard list page size.", + "type": "integer", + "format": "int32" + }, + "filter": { + "location": "query", + "description": "The standard list filter.", + "type": "string" + }, + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string", + "description": "The name of the operation's parent resource." + }, + "pageToken": { + "description": "The standard list page token.", + "location": "query", + "type": "string" + } + }, + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + } + }, + "get": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "id": "aiplatform.projects.locations.operations.get", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "parameters": { + "name": { + "location": "path", + "description": "The name of the operation resource.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/operations/[^/]+$", + "type": "string" + } + } + }, + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/operations/[^/]+$", + "type": "string", + "location": "path", + "description": "The name of the operation resource to be deleted." + } + }, + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "httpMethod": "DELETE", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.operations.delete" + } + } + }, + "hyperparameterTuningJobs": { + "methods": { + "list": { + "parameterOrder": [ + "parent" + ], + "description": "Lists HyperparameterTuningJobs in a Location.", + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.list", + "path": "v1/{+parent}/hyperparameterTuningJobs", + "httpMethod": "GET", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs", + "parameters": { + "pageSize": { + "description": "The standard list page size.", + "location": "query", + "type": "integer", + "format": "int32" + }, + "parent": { + "required": true, + "description": "Required. The resource name of the Location to list the HyperparameterTuningJobs from. Format: `projects/{project}/locations/{location}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path" + }, + "pageToken": { + "description": "The standard list page token. Typically obtained via ListHyperparameterTuningJobsResponse.next_page_token of the previous JobService.ListHyperparameterTuningJobs call.", + "type": "string", + "location": "query" + }, + "readMask": { + "type": "string", + "location": "query", + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask" + }, + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1ListHyperparameterTuningJobsResponse" + } + }, + "create": { + "request": { + "$ref": "GoogleCloudAiplatformV1HyperparameterTuningJob" + }, + "httpMethod": "POST", + "response": { + "$ref": "GoogleCloudAiplatformV1HyperparameterTuningJob" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.create", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs", + "description": "Creates a HyperparameterTuningJob", + "parameters": { + "parent": { + "location": "path", + "required": true, + "type": "string", + "description": "Required. The resource name of the Location to create the HyperparameterTuningJob in. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "parameterOrder": [ + "parent" + ], + "path": "v1/{+parent}/hyperparameterTuningJobs" + }, + "cancel": { + "path": "v1/{+name}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.cancel", + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}:cancel", + "description": "Cancels a HyperparameterTuningJob. Starts asynchronous cancellation on the HyperparameterTuningJob. The server makes a best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetHyperparameterTuningJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On successful cancellation, the HyperparameterTuningJob is not deleted; instead it becomes a job with a HyperparameterTuningJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and HyperparameterTuningJob.state is set to `CANCELLED`.", + "parameterOrder": [ + "name" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1CancelHyperparameterTuningJobRequest" + }, + "parameters": { + "name": { + "location": "path", + "type": "string", + "required": true, + "description": "Required. The name of the HyperparameterTuningJob to cancel. Format: `projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyperparameter_tuning_job}`", + "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+$" + } + } + }, + "get": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}", + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.get", + "response": { + "$ref": "GoogleCloudAiplatformV1HyperparameterTuningJob" + }, + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "parameters": { + "name": { + "type": "string", + "location": "path", + "description": "Required. The name of the HyperparameterTuningJob resource. Format: `projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyperparameter_tuning_job}`", + "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+$", + "required": true + } + }, + "description": "Gets a HyperparameterTuningJob" + }, + "delete": { + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.delete", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+$", + "description": "Required. The name of the HyperparameterTuningJob resource to be deleted. Format: `projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyperparameter_tuning_job}`", + "type": "string", + "location": "path", + "required": true + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Deletes a HyperparameterTuningJob.", + "path": "v1/{+name}", + "httpMethod": "DELETE" + } + }, + "resources": { + "operations": { + "methods": { + "delete": { + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.delete", + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+/operations/[^/]+$", + "required": true, + "description": "The name of the operation resource to be deleted.", + "type": "string", + "location": "path" + } + }, + "httpMethod": "DELETE", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + } + }, + "get": { + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.get", + "httpMethod": "GET", + "parameters": { + "name": { + "required": true, + "location": "path", + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+/operations/[^/]+$", + "type": "string" + } + } + }, + "cancel": { + "parameters": { + "name": { + "required": true, + "type": "string", + "description": "The name of the operation resource to be cancelled.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+/operations/[^/]+$" + } + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.cancel", + "httpMethod": "POST", + "path": "v1/{+name}:cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}:cancel", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.list", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations", + "path": "v1/{+name}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "pageSize": { + "type": "integer", + "format": "int32", + "description": "The standard list page size.", + "location": "query" + }, + "filter": { + "type": "string", + "description": "The standard list filter.", + "location": "query" + }, + "name": { + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+$", + "description": "The name of the operation's parent resource.", + "location": "path" + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token." + } + } + }, + "wait": { + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}:wait", + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}:wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "type": "string", + "location": "path", + "required": true, + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+/operations/[^/]+$" + }, + "timeout": { + "type": "string", + "location": "query", + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + } + } + } + } + } + } + }, + "persistentResources": { + "methods": { + "patch": { + "parameters": { + "updateMask": { + "format": "google-fieldmask", + "type": "string", + "description": "Required. Specify the fields to be overwritten in the PersistentResource by the update method.", + "location": "query" + }, + "name": { + "location": "path", + "required": true, + "description": "Immutable. Resource name of a PersistentResource.", + "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}", + "request": { + "$ref": "GoogleCloudAiplatformV1PersistentResource" + }, + "description": "Updates a PersistentResource.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.persistentResources.patch", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "PATCH" + }, + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+parent}/persistentResources", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources", + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.persistentResources.list", + "httpMethod": "GET", + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "description": "Required. The resource name of the Location to list the PersistentResources from. Format: `projects/{project}/locations/{location}`", + "type": "string", + "required": true + }, + "pageToken": { + "description": "Optional. The standard list page token. Typically obtained via ListPersistentResourceResponse.next_page_token of the previous PersistentResourceService.ListPersistentResource call.", + "location": "query", + "type": "string" + }, + "pageSize": { + "format": "int32", + "description": "Optional. The standard list page size.", + "type": "integer", + "location": "query" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1ListPersistentResourcesResponse" + }, + "description": "Lists PersistentResources in a Location." + }, + "reboot": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "POST", + "description": "Reboots a PersistentResource.", + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", + "type": "string", + "description": "Required. The name of the PersistentResource resource. Format: `projects/{project_id_or_number}/locations/{location_id}/persistentResources/{persistent_resource_id}`", + "location": "path" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1RebootPersistentResourceRequest" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}:reboot", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}:reboot", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.persistentResources.reboot" + }, + "delete": { + "id": "aiplatform.projects.locations.persistentResources.delete", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a PersistentResource.", + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "required": true, + "location": "path", + "description": "Required. The name of the PersistentResource to be deleted. Format: `projects/{project}/locations/{location}/persistentResources/{persistent_resource}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$" + } + }, + "httpMethod": "DELETE" + }, + "create": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1PersistentResource" + }, + "parameters": { + "parent": { + "description": "Required. The resource name of the Location to create the PersistentResource in. Format: `projects/{project}/locations/{location}`", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path" + }, + "persistentResourceId": { + "location": "query", + "type": "string", + "description": "Required. The ID to use for the PersistentResource, which become the final component of the PersistentResource's resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`." + } + }, + "parameterOrder": [ + "parent" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Creates a PersistentResource.", + "path": "v1/{+parent}/persistentResources", + "id": "aiplatform.projects.locations.persistentResources.create", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources" + }, + "get": { + "description": "Gets a PersistentResource.", + "response": { + "$ref": "GoogleCloudAiplatformV1PersistentResource" + }, + "id": "aiplatform.projects.locations.persistentResources.get", + "parameters": { + "name": { + "description": "Required. The name of the PersistentResource resource. Format: `projects/{project_id_or_number}/locations/{location_id}/persistentResources/{persistent_resource_id}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", + "type": "string", + "required": true + } + }, + "httpMethod": "GET", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + } + }, + "resources": { + "operations": { + "methods": { + "cancel": { + "path": "v1/{+name}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "httpMethod": "POST", + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+/operations/[^/]+$", + "location": "path", + "required": true, + "description": "The name of the operation resource to be cancelled." + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations/{operationsId}:cancel", + "id": "aiplatform.projects.locations.persistentResources.operations.cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`." + }, + "delete": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "location": "path", + "required": true, + "type": "string", + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+/operations/[^/]+$" + } + }, + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations/{operationsId}", + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.persistentResources.operations.delete", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." + }, + "get": { + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "location": "path", + "required": true, + "type": "string", + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+/operations/[^/]+$" + } + }, + "httpMethod": "GET", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.persistentResources.operations.get" + }, + "list": { + "httpMethod": "GET", + "parameters": { + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + }, + "pageToken": { + "description": "The standard list page token.", + "location": "query", + "type": "string" + }, + "pageSize": { + "description": "The standard list page size.", + "format": "int32", + "location": "query", + "type": "integer" + }, + "name": { + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", + "location": "path", + "type": "string", + "required": true + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.persistentResources.operations.list", + "path": "v1/{+name}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." + }, + "wait": { + "path": "v1/{+name}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.persistentResources.operations.wait", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations/{operationsId}:wait", + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "parameters": { + "name": { + "required": true, + "description": "The name of the operation resource to wait on.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+/operations/[^/]+$", + "type": "string" + }, + "timeout": { + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "type": "string" + } + } + } + } + } + } + }, + "models": { + "resources": { + "evaluations": { + "resources": { + "slices": { + "methods": { + "batchImport": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/slices/{slicesId}:batchImport", + "parameters": { + "parent": { + "location": "path", + "description": "Required. The name of the parent ModelEvaluationSlice resource. Format: `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}/slices/{slice}`", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/slices/[^/]+$", + "type": "string", + "required": true + } + }, + "path": "v1/{+parent}:batchImport", + "response": { + "$ref": "GoogleCloudAiplatformV1BatchImportEvaluatedAnnotationsResponse" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1BatchImportEvaluatedAnnotationsRequest" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "description": "Imports a list of externally generated EvaluatedAnnotations.", + "id": "aiplatform.projects.locations.models.evaluations.slices.batchImport", + "httpMethod": "POST" + }, + "list": { + "parameters": { + "readMask": { + "location": "query", + "type": "string", + "format": "google-fieldmask", + "description": "Mask specifying which fields to read." + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token. Typically obtained via ListModelEvaluationSlicesResponse.next_page_token of the previous ModelService.ListModelEvaluationSlices call." + }, + "filter": { + "description": "The standard list filter. * `slice.dimension` - for =.", + "location": "query", + "type": "string" + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+$", + "required": true, + "type": "string", + "location": "path", + "description": "Required. The resource name of the ModelEvaluation to list the ModelEvaluationSlices from. Format: `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}`" + }, + "pageSize": { + "description": "The standard list page size.", + "location": "query", + "type": "integer", + "format": "int32" + } + }, + "description": "Lists ModelEvaluationSlices in a ModelEvaluation.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/slices", + "parameterOrder": [ + "parent" + ], + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+parent}/slices", + "id": "aiplatform.projects.locations.models.evaluations.slices.list", + "response": { + "$ref": "GoogleCloudAiplatformV1ListModelEvaluationSlicesResponse" + } + }, + "get": { + "description": "Gets a ModelEvaluationSlice.", + "response": { + "$ref": "GoogleCloudAiplatformV1ModelEvaluationSlice" + }, + "httpMethod": "GET", + "id": "aiplatform.projects.locations.models.evaluations.slices.get", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "type": "string", + "location": "path", + "required": true, + "description": "Required. The name of the ModelEvaluationSlice resource. Format: `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}/slices/{slice}`", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/slices/[^/]+$" + } + }, + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/slices/{slicesId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + } + } + }, + "operations": { + "methods": { + "wait": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "location": "path", + "type": "string", + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/operations/[^/]+$", + "required": true + }, + "timeout": { + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "type": "string" + } + }, + "path": "v1/{+name}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.models.evaluations.operations.wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}:wait", + "httpMethod": "POST", + "parameterOrder": [ + "name" + ] + }, + "delete": { + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.models.evaluations.operations.delete", + "parameters": { + "name": { + "type": "string", + "location": "path", + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/operations/[^/]+$", + "required": true + } + }, + "path": "v1/{+name}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "httpMethod": "DELETE" + }, + "list": { + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations", + "parameters": { + "pageSize": { + "format": "int32", + "description": "The standard list page size.", + "type": "integer", + "location": "query" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + }, + "filter": { + "location": "query", + "description": "The standard list filter.", + "type": "string" + }, + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+$", + "type": "string", + "description": "The name of the operation's parent resource.", + "required": true + } + }, + "path": "v1/{+name}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.models.evaluations.operations.list" + }, + "cancel": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "type": "string", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be cancelled." + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.models.evaluations.operations.cancel", + "path": "v1/{+name}:cancel", + "httpMethod": "POST", + "parameterOrder": [ + "name" + ] + }, + "get": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}", + "path": "v1/{+name}", + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource.", + "location": "path", + "required": true, + "type": "string" + } + }, + "id": "aiplatform.projects.locations.models.evaluations.operations.get", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + } + } + } + }, + "methods": { + "import": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations:import", + "httpMethod": "POST", + "parameterOrder": [ + "parent" + ], + "path": "v1/{+parent}/evaluations:import", + "parameters": { + "parent": { + "description": "Required. The name of the parent model resource. Format: `projects/{project}/locations/{location}/models/{model}`", + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$" + } + }, + "description": "Imports an externally generated ModelEvaluation.", + "id": "aiplatform.projects.locations.models.evaluations.import", + "request": { + "$ref": "GoogleCloudAiplatformV1ImportModelEvaluationRequest" + }, + "response": { + "$ref": "GoogleCloudAiplatformV1ModelEvaluation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "get": { + "id": "aiplatform.projects.locations.models.evaluations.get", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}", + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1ModelEvaluation" + }, + "parameters": { + "name": { + "description": "Required. The name of the ModelEvaluation resource. Format: `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}`", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+$", + "location": "path" + } + }, + "description": "Gets a ModelEvaluation." + }, + "list": { + "parameters": { + "pageToken": { + "description": "The standard list page token. Typically obtained via ListModelEvaluationsResponse.next_page_token of the previous ModelService.ListModelEvaluations call.", + "location": "query", + "type": "string" + }, + "pageSize": { + "format": "int32", + "description": "The standard list page size.", + "type": "integer", + "location": "query" + }, + "readMask": { + "format": "google-fieldmask", + "location": "query", + "description": "Mask specifying which fields to read.", + "type": "string" + }, + "filter": { + "description": "The standard list filter.", + "location": "query", + "type": "string" + }, + "parent": { + "description": "Required. The resource name of the Model to list the ModelEvaluations from. Format: `projects/{project}/locations/{location}/models/{model}`", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "type": "string" + } + }, + "path": "v1/{+parent}/evaluations", + "httpMethod": "GET", + "id": "aiplatform.projects.locations.models.evaluations.list", + "parameterOrder": [ + "parent" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1ListModelEvaluationsResponse" + }, + "description": "Lists ModelEvaluations in a Model.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations" + } + } + }, + "operations": { + "methods": { + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "id": "aiplatform.projects.locations.models.operations.list", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations", + "path": "v1/{+name}/operations", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "type": "string", + "description": "The name of the operation's parent resource.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "required": true + }, + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + }, + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + }, + "pageSize": { + "format": "int32", + "location": "query", + "description": "The standard list page size.", + "type": "integer" + } + } + }, + "delete": { + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource to be deleted.", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.models.operations.delete", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations/{operationsId}", + "httpMethod": "DELETE", + "path": "v1/{+name}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "wait": { + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "required": true + }, + "timeout": { + "format": "google-duration", + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations/{operationsId}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.models.operations.wait", + "path": "v1/{+name}:wait", + "parameterOrder": [ + "name" + ] + }, + "cancel": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}:cancel", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations/{operationsId}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "id": "aiplatform.projects.locations.models.operations.cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "description": "The name of the operation resource to be cancelled." + } + }, + "httpMethod": "POST", + "parameterOrder": [ + "name" + ] + }, + "get": { + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations/{operationsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource.", + "location": "path", + "required": true + } + }, + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.models.operations.get", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ] + } + } + } + }, + "methods": { + "delete": { + "description": "Deletes a Model. A model cannot be deleted if any Endpoint resource has a DeployedModel based on the model in its deployed_models field.", + "httpMethod": "DELETE", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "required": true, + "description": "Required. The name of the Model resource to be deleted. Format: `projects/{project}/locations/{location}/models/{model}`", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "type": "string", + "location": "path" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.models.delete", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ] + }, + "list": { + "path": "v1/{+parent}/models", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.models.list", + "description": "Lists Models in a Location.", + "response": { + "$ref": "GoogleCloudAiplatformV1ListModelsResponse" + }, + "parameters": { + "filter": { + "location": "query", + "type": "string", + "description": "An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `model` supports = and !=. `model` represents the Model ID, i.e. the last segment of the Model's resource name. * `display_name` supports = and != * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels.\"a key\"`. * `base_model_name` only supports = Some examples: * `model=1234` * `displayName=\"myDisplayName\"` * `labels.myKey=\"myValue\"` * `baseModelName=\"text-bison\"`" + }, + "pageSize": { + "location": "query", + "format": "int32", + "type": "integer", + "description": "The standard list page size." + }, + "orderBy": { + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`.", + "type": "string", + "location": "query" + }, + "readMask": { + "location": "query", + "type": "string", + "format": "google-fieldmask", + "description": "Mask specifying which fields to read." + }, + "parent": { + "description": "Required. The resource name of the Location to list the Models from. Format: `projects/{project}/locations/{location}`", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path" + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token. Typically obtained via ListModelsResponse.next_page_token of the previous ModelService.ListModels call." + } + }, + "httpMethod": "GET", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models" + }, + "listVersions": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:listVersions", + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1ListModelVersionsResponse" + }, + "parameterOrder": [ + "name" + ], + "description": "Lists versions of the specified model.", + "path": "v1/{+name}:listVersions", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.models.listVersions", + "parameters": { + "readMask": { + "format": "google-fieldmask", + "type": "string", + "description": "Mask specifying which fields to read.", + "location": "query" + }, + "filter": { + "description": "An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels.\"a key\"`. Some examples: * `labels.myKey=\"myValue\"`", + "type": "string", + "location": "query" + }, + "orderBy": { + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `create_time` * `update_time` Example: `update_time asc, create_time desc`.", + "location": "query", + "type": "string" + }, + "name": { + "type": "string", + "location": "path", + "description": "Required. The name of the model to list versions for.", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "required": true + }, + "pageSize": { + "type": "integer", + "location": "query", + "description": "The standard list page size.", + "format": "int32" + }, + "pageToken": { + "description": "The standard list page token. Typically obtained via next_page_token of the previous ListModelVersions call.", + "location": "query", + "type": "string" + } + } + }, + "testIamPermissions": { + "parameters": { + "permissions": { + "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", + "repeated": true, + "location": "query", + "type": "string" + }, + "resource": { + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "type": "string", + "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "location": "path", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.models.testIamPermissions", + "response": { + "$ref": "GoogleIamV1TestIamPermissionsResponse" + }, + "httpMethod": "POST", + "path": "v1/{+resource}:testIamPermissions", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:testIamPermissions", + "parameterOrder": [ + "resource" + ], + "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning." + }, + "get": { + "path": "v1/{+name}", + "parameters": { + "name": { + "description": "Required. The name of the Model resource. Format: `projects/{project}/locations/{location}/models/{model}` In order to retrieve a specific version of the model, also provide the version ID or version alias. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` If no version ID or alias is specified, the \"default\" version will be returned. The \"default\" version alias is created for the first version of the model, and can be moved to other versions later on. There will be exactly one default version.", + "type": "string", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}", + "response": { + "$ref": "GoogleCloudAiplatformV1Model" + }, + "httpMethod": "GET", + "id": "aiplatform.projects.locations.models.get", + "description": "Gets a Model.", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "updateExplanationDataset": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:updateExplanationDataset", + "description": "Incrementally update the dataset used for an examples model.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+model}:updateExplanationDataset", + "request": { + "$ref": "GoogleCloudAiplatformV1UpdateExplanationDatasetRequest" + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.models.updateExplanationDataset", + "httpMethod": "POST", + "parameterOrder": [ + "model" + ], + "parameters": { + "model": { + "location": "path", + "type": "string", + "required": true, + "description": "Required. The resource name of the Model to update. Format: `projects/{project}/locations/{location}/models/{model}`", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$" + } + } + }, + "getIamPolicy": { + "id": "aiplatform.projects.locations.models.getIamPolicy", + "httpMethod": "POST", + "path": "v1/{+resource}:getIamPolicy", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:getIamPolicy", + "parameterOrder": [ + "resource" + ], + "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", + "parameters": { + "options.requestedPolicyVersion": { + "location": "query", + "type": "integer", + "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", + "format": "int32" + }, + "resource": { + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "location": "path", + "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleIamV1Policy" + } + }, + "setIamPolicy": { + "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleIamV1SetIamPolicyRequest" + }, + "parameterOrder": [ + "resource" + ], + "path": "v1/{+resource}:setIamPolicy", + "parameters": { + "resource": { + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "required": true + } + }, + "id": "aiplatform.projects.locations.models.setIamPolicy", + "response": { + "$ref": "GoogleIamV1Policy" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:setIamPolicy" + }, + "copy": { + "parameters": { + "parent": { + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location into which to copy the Model. Format: `projects/{project}/locations/{location}`" + } + }, + "description": "Copies an already existing Vertex AI Model into the specified Location. The source Model must exist in the same Project. When copying custom Models, the users themselves are responsible for Model.metadata content to be region-agnostic, as well as making sure that any resources (e.g. files) it depends on remain accessible.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models:copy", + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1CopyModelRequest" + }, + "parameterOrder": [ + "parent" + ], + "path": "v1/{+parent}/models:copy", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.models.copy" + }, + "patch": { + "httpMethod": "PATCH", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}", + "parameterOrder": [ + "name" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1Model" + }, + "id": "aiplatform.projects.locations.models.patch", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1Model" + }, + "description": "Updates a Model.", + "parameters": { + "name": { + "location": "path", + "type": "string", + "description": "The resource name of the Model.", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "required": true + }, + "updateMask": { + "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask.", + "format": "google-fieldmask", + "type": "string", + "location": "query" + } + }, + "path": "v1/{+name}" + }, + "upload": { + "parameterOrder": [ + "parent" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models:upload", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "parent": { + "required": true, + "type": "string", + "description": "Required. The resource name of the Location into which to upload the Model. Format: `projects/{project}/locations/{location}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1UploadModelRequest" + }, + "description": "Uploads a Model artifact into Vertex AI.", + "id": "aiplatform.projects.locations.models.upload", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+parent}/models:upload" + }, + "mergeVersionAliases": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:mergeVersionAliases", + "request": { + "$ref": "GoogleCloudAiplatformV1MergeVersionAliasesRequest" + }, + "response": { + "$ref": "GoogleCloudAiplatformV1Model" + }, + "path": "v1/{+name}:mergeVersionAliases", + "description": "Merges a set of aliases for a Model version.", + "httpMethod": "POST", + "parameters": { + "name": { + "description": "Required. The name of the model version to merge aliases, with a version ID explicitly included. Example: `projects/{project}/locations/{location}/models/{model}@1234`", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "type": "string", + "location": "path", + "required": true + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.models.mergeVersionAliases" + }, + "export": { + "parameters": { + "name": { + "type": "string", + "description": "Required. The resource name of the Model to export. The resource name may contain version id or version alias to specify the version, if no version is specified, the default version will be exported.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "location": "path" + } + }, + "description": "Exports a trained, exportable Model to a location specified by the user. A Model is considered to be exportable if it has at least one supported export format.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.models.export", + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:export", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}:export", + "request": { + "$ref": "GoogleCloudAiplatformV1ExportModelRequest" + } + }, + "deleteVersion": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}:deleteVersion", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.models.deleteVersion", + "description": "Deletes a Model version. Model version can only be deleted if there are no DeployedModels created from it. Deleting the only version in the Model is not allowed. Use DeleteModel for deleting the Model instead.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "location": "path", + "type": "string", + "required": true, + "description": "Required. The name of the model version to be deleted, with a version ID explicitly included. Example: `projects/{project}/locations/{location}/models/{model}@1234`" + } + }, + "httpMethod": "DELETE", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:deleteVersion" + } + } + }, + "notebookRuntimeTemplates": { + "resources": { + "operations": { + "methods": { + "delete": { + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.delete", + "parameters": { + "name": { + "required": true, + "type": "string", + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+/operations/[^/]+$", + "location": "path" + } + } + }, + "list": { + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.list", + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}/operations", + "httpMethod": "GET", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "pageSize": { + "format": "int32", + "type": "integer", + "description": "The standard list page size.", + "location": "query" + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", + "location": "path", + "type": "string", + "required": true, + "description": "The name of the operation's parent resource." + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token." + }, + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." + }, + "get": { + "path": "v1/{+name}", + "parameters": { + "name": { + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource." + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.get", + "httpMethod": "GET" + }, + "cancel": { + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}:cancel", + "path": "v1/{+name}:cancel", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+/operations/[^/]+$", + "type": "string", + "required": true, + "description": "The name of the operation resource to be cancelled." + } + }, + "httpMethod": "POST" + }, + "wait": { + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+/operations/[^/]+$", + "required": true, + "description": "The name of the operation resource to wait on.", + "type": "string" + }, + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "type": "string", + "format": "google-duration" + } + }, + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "path": "v1/{+name}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.wait", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}:wait", + "httpMethod": "POST" + } + } + } + }, + "methods": { + "testIamPermissions": { + "response": { + "$ref": "GoogleIamV1TestIamPermissionsResponse" + }, + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.testIamPermissions", + "parameterOrder": [ + "resource" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}:testIamPermissions", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+resource}:testIamPermissions", + "parameters": { + "resource": { + "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "required": true, + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$" + }, + "permissions": { + "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", + "location": "query", + "type": "string", + "repeated": true + } + }, + "httpMethod": "POST", + "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning." + }, + "create": { + "description": "Creates a NotebookRuntimeTemplate.", + "parameters": { + "parent": { + "required": true, + "description": "Required. The resource name of the Location to create the NotebookRuntimeTemplate. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string", + "location": "path" + }, + "notebookRuntimeTemplateId": { + "location": "query", + "description": "Optional. User specified ID for the notebook runtime template.", + "type": "string" + } + }, + "path": "v1/{+parent}/notebookRuntimeTemplates", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates", + "request": { + "$ref": "GoogleCloudAiplatformV1NotebookRuntimeTemplate" + }, + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.create", + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "get": { + "response": { + "$ref": "GoogleCloudAiplatformV1NotebookRuntimeTemplate" + }, + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.get", + "parameters": { + "name": { + "location": "path", + "description": "Required. The name of the NotebookRuntimeTemplate resource. Format: `projects/{project}/locations/{location}/notebookRuntimeTemplates/{notebook_runtime_template}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", + "type": "string" + } + }, + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}", + "description": "Gets a NotebookRuntimeTemplate.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET" + }, + "patch": { + "response": { + "$ref": "GoogleCloudAiplatformV1NotebookRuntimeTemplate" + }, + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.patch", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}", + "parameters": { + "updateMask": { + "location": "query", + "format": "google-fieldmask", + "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Input format: `{paths: \"${updated_filed}\"}` Updatable fields: * `encryption_spec.kms_key_name`", + "type": "string" + }, + "name": { + "description": "The resource name of the NotebookRuntimeTemplate.", + "required": true, + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$" + } + }, + "httpMethod": "PATCH", + "description": "Updates a NotebookRuntimeTemplate.", + "request": { + "$ref": "GoogleCloudAiplatformV1NotebookRuntimeTemplate" + } + }, + "getIamPolicy": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}:getIamPolicy", + "httpMethod": "POST", + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.getIamPolicy", + "parameterOrder": [ + "resource" + ], + "path": "v1/{+resource}:getIamPolicy", + "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleIamV1Policy" + }, + "parameters": { + "options.requestedPolicyVersion": { + "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", + "type": "integer", + "format": "int32", + "location": "query" + }, + "resource": { + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", + "type": "string", + "location": "path", + "required": true, + "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field." + } + } + }, + "delete": { + "parameters": { + "name": { + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", + "description": "Required. The name of the NotebookRuntimeTemplate resource to be deleted. Format: `projects/{project}/locations/{location}/notebookRuntimeTemplates/{notebook_runtime_template}`", + "required": true + } + }, + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.delete", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a NotebookRuntimeTemplate." + }, + "setIamPolicy": { + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.setIamPolicy", + "parameters": { + "resource": { + "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", + "required": true, + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}:setIamPolicy", + "request": { + "$ref": "GoogleIamV1SetIamPolicyRequest" + }, + "response": { + "$ref": "GoogleIamV1Policy" + }, + "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", + "parameterOrder": [ + "resource" + ], + "httpMethod": "POST", + "path": "v1/{+resource}:setIamPolicy", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates", + "path": "v1/{+parent}/notebookRuntimeTemplates", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1ListNotebookRuntimeTemplatesResponse" + }, + "description": "Lists NotebookRuntimeTemplates in a Location.", + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.list", + "httpMethod": "GET", + "parameterOrder": [ + "parent" + ], + "parameters": { + "readMask": { + "format": "google-fieldmask", + "description": "Optional. Mask specifying which fields to read.", + "location": "query", + "type": "string" + }, + "parent": { + "description": "Required. The resource name of the Location from which to list the NotebookRuntimeTemplates. Format: `projects/{project}/locations/{location}`", + "type": "string", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$" + }, + "orderBy": { + "type": "string", + "location": "query", + "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`." + }, + "pageToken": { + "description": "Optional. The standard list page token. Typically obtained via ListNotebookRuntimeTemplatesResponse.next_page_token of the previous NotebookService.ListNotebookRuntimeTemplates call.", + "location": "query", + "type": "string" + }, + "filter": { + "type": "string", + "description": "Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `notebookRuntimeTemplate` supports = and !=. `notebookRuntimeTemplate` represents the NotebookRuntimeTemplate ID, i.e. the last segment of the NotebookRuntimeTemplate's resource name. * `display_name` supports = and != * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels.\"a key\"`. * `notebookRuntimeType` supports = and !=. notebookRuntimeType enum: [USER_DEFINED, ONE_CLICK]. Some examples: * `notebookRuntimeTemplate=notebookRuntimeTemplate123` * `displayName=\"myDisplayName\"` * `labels.myKey=\"myValue\"` * `notebookRuntimeType=USER_DEFINED`", + "location": "query" + }, + "pageSize": { + "location": "query", + "type": "integer", + "format": "int32", + "description": "Optional. The standard list page size." + } + } + } + } + }, + "batchPredictionJobs": { + "methods": { + "get": { + "path": "v1/{+name}", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs/{batchPredictionJobsId}", + "response": { + "$ref": "GoogleCloudAiplatformV1BatchPredictionJob" + }, + "id": "aiplatform.projects.locations.batchPredictionJobs.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/batchPredictionJobs/[^/]+$", + "type": "string", + "required": true, + "description": "Required. The name of the BatchPredictionJob resource. Format: `projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job}`", + "location": "path" + } + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "description": "Gets a BatchPredictionJob" + }, + "cancel": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "httpMethod": "POST", + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}:cancel", + "request": { + "$ref": "GoogleCloudAiplatformV1CancelBatchPredictionJobRequest" + }, + "parameters": { + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/batchPredictionJobs/[^/]+$", + "description": "Required. The name of the BatchPredictionJob to cancel. Format: `projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job}`", + "type": "string" + } + }, + "description": "Cancels a BatchPredictionJob. Starts asynchronous cancellation on the BatchPredictionJob. The server makes the best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetBatchPredictionJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On a successful cancellation, the BatchPredictionJob is not deleted;instead its BatchPredictionJob.state is set to `CANCELLED`. Any files already outputted by the job are not deleted.", + "id": "aiplatform.projects.locations.batchPredictionJobs.cancel", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs/{batchPredictionJobsId}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "delete": { + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ], + "description": "Deletes a BatchPredictionJob. Can only be called on jobs that already finished.", + "id": "aiplatform.projects.locations.batchPredictionJobs.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/batchPredictionJobs/[^/]+$", + "required": true, + "description": "Required. The name of the BatchPredictionJob resource to be deleted. Format: `projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job}`", + "location": "path", + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs/{batchPredictionJobsId}" + }, + "create": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1BatchPredictionJob" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1BatchPredictionJob" + }, + "path": "v1/{+parent}/batchPredictionJobs", + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true, + "description": "Required. The resource name of the Location to create the BatchPredictionJob in. Format: `projects/{project}/locations/{location}`", + "type": "string", + "location": "path" + } + }, + "parameterOrder": [ + "parent" + ], + "httpMethod": "POST", + "id": "aiplatform.projects.locations.batchPredictionJobs.create", + "description": "Creates a BatchPredictionJob. A BatchPredictionJob once created will right away be attempted to start." + }, + "list": { + "response": { + "$ref": "GoogleCloudAiplatformV1ListBatchPredictionJobsResponse" + }, + "path": "v1/{+parent}/batchPredictionJobs", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "parameters": { + "readMask": { + "type": "string", + "location": "query", + "format": "google-fieldmask", + "description": "Mask specifying which fields to read." + }, + "filter": { + "type": "string", + "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `model_display_name` supports `=`, `!=` comparisons. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`", + "location": "query" + }, + "pageSize": { + "location": "query", + "format": "int32", + "description": "The standard list page size.", + "type": "integer" + }, + "parent": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true, + "description": "Required. The resource name of the Location to list the BatchPredictionJobs from. Format: `projects/{project}/locations/{location}`", + "location": "path" + }, + "pageToken": { + "description": "The standard list page token. Typically obtained via ListBatchPredictionJobsResponse.next_page_token of the previous JobService.ListBatchPredictionJobs call.", + "type": "string", + "location": "query" + } + }, + "description": "Lists BatchPredictionJobs in a Location.", + "httpMethod": "GET", + "id": "aiplatform.projects.locations.batchPredictionJobs.list" + } + } + }, + "tuningJobs": { + "resources": { + "operations": { + "methods": { + "get": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "location": "path", + "required": true, + "type": "string", + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/tuningJobs/[^/]+/operations/[^/]+$" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tuningJobs/{tuningJobsId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.tuningJobs.operations.get", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET" + }, + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tuningJobs/[^/]+$", + "description": "The name of the operation's parent resource.", + "required": true, + "type": "string" + }, + "filter": { + "description": "The standard list filter.", + "location": "query", + "type": "string" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + }, + "pageSize": { + "location": "query", + "description": "The standard list page size.", + "type": "integer", + "format": "int32" + } + }, + "id": "aiplatform.projects.locations.tuningJobs.operations.list", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tuningJobs/{tuningJobsId}/operations", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "path": "v1/{+name}/operations" + }, + "cancel": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/tuningJobs/[^/]+/operations/[^/]+$", + "type": "string", + "required": true, + "location": "path", + "description": "The name of the operation resource to be cancelled." + } + }, + "httpMethod": "POST", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tuningJobs/{tuningJobsId}/operations/{operationsId}:cancel", + "path": "v1/{+name}:cancel", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.tuningJobs.operations.cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`." + } + } + } + }, + "methods": { + "list": { + "httpMethod": "GET", + "id": "aiplatform.projects.locations.tuningJobs.list", + "description": "Lists TuningJobs in a Location.", + "response": { + "$ref": "GoogleCloudAiplatformV1ListTuningJobsResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "pageSize": { + "format": "int32", + "location": "query", + "description": "Optional. The standard list page size.", + "type": "integer" + }, + "pageToken": { + "location": "query", + "description": "Optional. The standard list page token. Typically obtained via ListTuningJob.next_page_token of the previous GenAiTuningService.ListTuningJob][] call.", + "type": "string" + }, + "parent": { + "description": "Required. The resource name of the Location to list the TuningJobs from. Format: `projects/{project}/locations/{location}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string", + "required": true + }, + "filter": { + "type": "string", + "location": "query", + "description": "Optional. The standard list filter." + } + }, + "parameterOrder": [ + "parent" + ], + "path": "v1/{+parent}/tuningJobs", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tuningJobs" + }, + "get": { + "id": "aiplatform.projects.locations.tuningJobs.get", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1TuningJob" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tuningJobs/{tuningJobsId}", + "description": "Gets a TuningJob.", + "httpMethod": "GET", + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/tuningJobs/[^/]+$", + "type": "string", + "description": "Required. The name of the TuningJob resource. Format: `projects/{project}/locations/{location}/tuningJobs/{tuning_job}`", + "location": "path" + } + }, + "path": "v1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "cancel": { + "parameters": { + "name": { + "description": "Required. The name of the TuningJob to cancel. Format: `projects/{project}/locations/{location}/tuningJobs/{tuning_job}`", + "pattern": "^projects/[^/]+/locations/[^/]+/tuningJobs/[^/]+$", + "location": "path", + "type": "string", + "required": true + } + }, + "description": "Cancels a TuningJob. Starts asynchronous cancellation on the TuningJob. The server makes a best effort to cancel the job, but success is not guaranteed. Clients can use GenAiTuningService.GetTuningJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On successful cancellation, the TuningJob is not deleted; instead it becomes a job with a TuningJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and TuningJob.state is set to `CANCELLED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tuningJobs/{tuningJobsId}:cancel", + "id": "aiplatform.projects.locations.tuningJobs.cancel", + "httpMethod": "POST", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1CancelTuningJobRequest" + }, + "path": "v1/{+name}:cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + } + }, + "create": { + "path": "v1/{+parent}/tuningJobs", + "description": "Creates a TuningJob. A created TuningJob right away will be attempted to be run.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tuningJobs", + "response": { + "$ref": "GoogleCloudAiplatformV1TuningJob" + }, + "id": "aiplatform.projects.locations.tuningJobs.create", + "parameters": { + "parent": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location to create the TuningJob in. Format: `projects/{project}/locations/{location}`", + "required": true, + "location": "path" + } + }, + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1TuningJob" + }, + "parameterOrder": [ + "parent" + ] + } + } + }, + "deploymentResourcePools": { + "resources": { + "operations": { + "methods": { + "get": { + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "path": "v1/{+name}", + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "description": "The name of the operation resource." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.deploymentResourcePools.operations.get", + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "cancel": { + "httpMethod": "POST", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.deploymentResourcePools.operations.cancel", + "parameters": { + "name": { + "required": true, + "type": "string", + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+/operations/[^/]+$" + } + }, + "path": "v1/{+name}:cancel", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ] + }, + "wait": { + "id": "aiplatform.projects.locations.deploymentResourcePools.operations.wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+name}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "parameterOrder": [ + "name" + ], + "parameters": { + "timeout": { + "location": "query", + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string" + }, + "name": { + "required": true, + "location": "path", + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}:wait", + "httpMethod": "POST" + }, + "list": { + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "httpMethod": "GET", + "path": "v1/{+name}/operations", + "id": "aiplatform.projects.locations.deploymentResourcePools.operations.list", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "pageSize": { + "format": "int32", + "location": "query", + "description": "The standard list page size.", + "type": "integer" + }, + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + }, + "filter": { + "type": "string", + "description": "The standard list filter.", + "location": "query" + }, + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$", + "required": true, + "location": "path", + "description": "The name of the operation's parent resource." + } + } + }, + "delete": { + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}", + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.deploymentResourcePools.operations.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "description": "The name of the operation resource to be deleted.", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+/operations/[^/]+$", + "location": "path" + } + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE" + } + } + } + }, + "methods": { + "patch": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Update a DeploymentResourcePool.", + "httpMethod": "PATCH", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1DeploymentResourcePool" + }, + "id": "aiplatform.projects.locations.deploymentResourcePools.patch", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}", + "path": "v1/{+name}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$", + "description": "Immutable. The resource name of the DeploymentResourcePool. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", + "required": true, + "type": "string", + "location": "path" + }, + "updateMask": { + "format": "google-fieldmask", + "type": "string", + "description": "Required. The list of fields to update.", + "location": "query" + } + }, + "parameterOrder": [ + "name" + ] + }, + "queryDeployedModels": { + "httpMethod": "GET", + "description": "List DeployedModels that have been deployed on this DeploymentResourcePool.", + "response": { + "$ref": "GoogleCloudAiplatformV1QueryDeployedModelsResponse" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}:queryDeployedModels", + "path": "v1/{+deploymentResourcePool}:queryDeployedModels", + "id": "aiplatform.projects.locations.deploymentResourcePools.queryDeployedModels", + "parameters": { + "deploymentResourcePool": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$", + "location": "path", + "type": "string", + "description": "Required. The name of the target DeploymentResourcePool to query. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`" + }, + "pageToken": { + "location": "query", + "description": "A page token, received from a previous `QueryDeployedModels` call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to `QueryDeployedModels` must match the call that provided the page token.", + "type": "string" + }, + "pageSize": { + "format": "int32", + "location": "query", + "description": "The maximum number of DeployedModels to return. The service may return fewer than this value.", + "type": "integer" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "deploymentResourcePool" + ] + }, + "list": { + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools", + "id": "aiplatform.projects.locations.deploymentResourcePools.list", + "httpMethod": "GET", + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1ListDeploymentResourcePoolsResponse" + }, + "description": "List DeploymentResourcePools in a location.", + "parameters": { + "parent": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true, + "description": "Required. The parent Location which owns this collection of DeploymentResourcePools. Format: `projects/{project}/locations/{location}`", + "type": "string" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "A page token, received from a previous `ListDeploymentResourcePools` call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to `ListDeploymentResourcePools` must match the call that provided the page token." + }, + "pageSize": { + "description": "The maximum number of DeploymentResourcePools to return. The service may return fewer than this value.", + "format": "int32", + "type": "integer", + "location": "query" + } + }, + "path": "v1/{+parent}/deploymentResourcePools" + }, + "create": { + "description": "Create a DeploymentResourcePool.", + "parameters": { + "parent": { + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "description": "Required. The parent location resource where this DeploymentResourcePool will be created. Format: `projects/{project}/locations/{location}`" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools", + "request": { + "$ref": "GoogleCloudAiplatformV1CreateDeploymentResourcePoolRequest" + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "POST", + "parameterOrder": [ + "parent" + ], + "path": "v1/{+parent}/deploymentResourcePools", + "id": "aiplatform.projects.locations.deploymentResourcePools.create" + }, + "delete": { + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE", + "description": "Delete a DeploymentResourcePool.", + "id": "aiplatform.projects.locations.deploymentResourcePools.delete", + "parameters": { + "name": { + "location": "path", + "required": true, + "description": "Required. The name of the DeploymentResourcePool to delete. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}" + }, + "get": { + "description": "Get a DeploymentResourcePool.", + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "id": "aiplatform.projects.locations.deploymentResourcePools.get", + "parameters": { + "name": { + "type": "string", + "required": true, + "description": "Required. The name of the DeploymentResourcePool to retrieve. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", + "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$", + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1DeploymentResourcePool" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}" + } + } + }, + "pipelineJobs": { + "methods": { + "delete": { + "description": "Deletes a PipelineJob.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.pipelineJobs.delete", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}", + "path": "v1/{+name}", + "httpMethod": "DELETE", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "required": true, + "type": "string", + "description": "Required. The name of the PipelineJob resource to be deleted. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+$" + } + }, + "parameterOrder": [ + "name" + ] + }, + "batchDelete": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.pipelineJobs.batchDelete", + "path": "v1/{+parent}/pipelineJobs:batchDelete", + "parameters": { + "parent": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The name of the PipelineJobs' parent resource. Format: `projects/{project}/locations/{location}`", + "location": "path", + "type": "string" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1BatchDeletePipelineJobsRequest" + }, + "description": "Batch deletes PipelineJobs The Operation is atomic. If it fails, none of the PipelineJobs are deleted. If it succeeds, all of the PipelineJobs are deleted.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs:batchDelete", + "parameterOrder": [ + "parent" + ], + "httpMethod": "POST" + }, + "get": { + "id": "aiplatform.projects.locations.pipelineJobs.get", + "response": { + "$ref": "GoogleCloudAiplatformV1PipelineJob" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "description": "Required. The name of the PipelineJob resource. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+$", + "required": true, + "type": "string" + } + }, + "httpMethod": "GET", + "description": "Gets a PipelineJob.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}" + }, + "list": { + "path": "v1/{+parent}/pipelineJobs", + "description": "Lists PipelineJobs in a Location.", + "parameters": { + "pageToken": { + "description": "The standard list page token. Typically obtained via ListPipelineJobsResponse.next_page_token of the previous PipelineService.ListPipelineJobs call.", + "type": "string", + "location": "query" + }, + "parent": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "type": "string", + "description": "Required. The resource name of the Location to list the PipelineJobs from. Format: `projects/{project}/locations/{location}`" + }, + "filter": { + "location": "query", + "type": "string", + "description": "Lists the PipelineJobs that match the filter expression. The following fields are supported: * `pipeline_name`: Supports `=` and `!=` comparisons. * `display_name`: Supports `=`, `!=` comparisons, and `:` wildcard. * `pipeline_job_user_id`: Supports `=`, `!=` comparisons, and `:` wildcard. for example, can check if pipeline's display_name contains *step* by doing display_name:\\\"*step*\\\" * `state`: Supports `=` and `!=` comparisons. * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `end_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality and key presence. * `template_uri`: Supports `=`, `!=` comparisons, and `:` wildcard. * `template_metadata.version`: Supports `=`, `!=` comparisons, and `:` wildcard. Filter expressions can be combined together using logical operators (`AND` & `OR`). For example: `pipeline_name=\"test\" AND create_time\u003e\"2020-05-18T13:30:00Z\"`. The syntax to define filter expression is based on https://google.aip.dev/160. Examples: * `create_time\u003e\"2021-05-18T00:00:00Z\" OR update_time\u003e\"2020-05-18T00:00:00Z\"` PipelineJobs created or updated after 2020-05-18 00:00:00 UTC. * `labels.env = \"prod\"` PipelineJobs with label \"env\" set to \"prod\"." + }, + "pageSize": { + "location": "query", + "type": "integer", + "description": "The standard list page size.", + "format": "int32" + }, + "readMask": { + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask", + "location": "query", + "type": "string" + }, + "orderBy": { + "location": "query", + "type": "string", + "description": "A comma-separated list of fields to order by. The default sort order is in ascending order. Use \"desc\" after a field name for descending. You can have multiple order_by fields provided e.g. \"create_time desc, end_time\", \"end_time, start_time, update_time\" For example, using \"create_time desc, end_time\" will order results by create time in descending order, and if there are multiple jobs having the same create time, order them by the end time in ascending order. if order_by is not specified, it will order by default order is create time in descending order. Supported fields: * `create_time` * `update_time` * `end_time` * `start_time`" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs", + "response": { + "$ref": "GoogleCloudAiplatformV1ListPipelineJobsResponse" + }, + "id": "aiplatform.projects.locations.pipelineJobs.list", + "httpMethod": "GET" + }, + "cancel": { + "description": "Cancels a PipelineJob. Starts asynchronous cancellation on the PipelineJob. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use PipelineService.GetPipelineJob or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the PipelineJob is not deleted; instead it becomes a pipeline with a PipelineJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and PipelineJob.state is set to `CANCELLED`.", + "path": "v1/{+name}:cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1CancelPipelineJobRequest" + }, + "parameterOrder": [ + "name" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "parameters": { + "name": { + "type": "string", + "description": "Required. The name of the PipelineJob to cancel. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+$", + "required": true + } + }, + "id": "aiplatform.projects.locations.pipelineJobs.cancel" + }, + "batchCancel": { + "description": "Batch cancel PipelineJobs. Firstly the server will check if all the jobs are in non-terminal states, and skip the jobs that are already terminated. If the operation failed, none of the pipeline jobs are cancelled. The server will poll the states of all the pipeline jobs periodically to check the cancellation status. This operation will return an LRO.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1BatchCancelPipelineJobsRequest" + }, + "httpMethod": "POST", + "parameters": { + "parent": { + "location": "path", + "required": true, + "description": "Required. The name of the PipelineJobs' parent resource. Format: `projects/{project}/locations/{location}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "id": "aiplatform.projects.locations.pipelineJobs.batchCancel", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1/{+parent}/pipelineJobs:batchCancel", + "parameterOrder": [ + "parent" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs:batchCancel" + }, + "create": { + "parameterOrder": [ + "parent" + ], + "description": "Creates a PipelineJob. A PipelineJob will run immediately when created.", + "request": { + "$ref": "GoogleCloudAiplatformV1PipelineJob" + }, + "id": "aiplatform.projects.locations.pipelineJobs.create", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1PipelineJob" + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs", + "parameters": { + "pipelineJobId": { + "description": "The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.", + "type": "string", + "location": "query" + }, + "parent": { + "type": "string", + "description": "Required. The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "path": "v1/{+parent}/pipelineJobs", + "httpMethod": "POST" + } + }, + "resources": { + "operations": { + "methods": { + "get": { + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource.", + "required": true + } + }, + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations/{operationsId}", + "path": "v1/{+name}", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "id": "aiplatform.projects.locations.pipelineJobs.operations.get" + }, + "list": { + "parameterOrder": [ + "name" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "httpMethod": "GET", + "parameters": { + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token." + }, + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter." + }, + "pageSize": { + "format": "int32", + "description": "The standard list page size.", + "location": "query", + "type": "integer" + }, + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+$", + "description": "The name of the operation's parent resource.", + "type": "string", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1/{+name}/operations", + "id": "aiplatform.projects.locations.pipelineJobs.operations.list" + }, + "wait": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}:wait", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "type": "string", + "required": true + }, + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string", + "location": "query", + "format": "google-duration" + } + }, + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations/{operationsId}:wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "id": "aiplatform.projects.locations.pipelineJobs.operations.wait" + }, + "cancel": { + "path": "v1/{+name}:cancel", + "id": "aiplatform.projects.locations.pipelineJobs.operations.cancel", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "type": "string" + } + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations/{operationsId}:cancel" + }, + "delete": { + "id": "aiplatform.projects.locations.pipelineJobs.operations.delete", + "httpMethod": "DELETE", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations/{operationsId}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "path": "v1/{+name}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "parameters": { + "name": { + "location": "path", + "required": true, + "type": "string", + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+/operations/[^/]+$" + } + } + } + } + } + } + } + } + } + } + }, + "publishers": { + "resources": { + "models": { + "methods": { + "get": { + "path": "v1/{+name}", + "response": { + "$ref": "GoogleCloudAiplatformV1PublisherModel" + }, + "parameterOrder": [ + "name" + ], + "description": "Gets a Model Garden publisher model.", + "parameters": { + "name": { + "location": "path", + "type": "string", + "required": true, + "pattern": "^publishers/[^/]+/models/[^/]+$", + "description": "Required. The name of the PublisherModel resource. Format: `publishers/{publisher}/models/{publisher_model}`" + }, + "languageCode": { + "type": "string", + "location": "query", + "description": "Optional. The IETF BCP-47 language code representing the language in which the publisher model's text information should be written in." + }, + "view": { + "enumDescriptions": [ + "The default / unset value. The API will default to the BASIC view.", + "Include basic metadata about the publisher model, but not the full contents.", + "Include everything.", + "Include: VersionId, ModelVersionExternalName, and SupportedActions." + ], + "enum": [ + "PUBLISHER_MODEL_VIEW_UNSPECIFIED", + "PUBLISHER_MODEL_VIEW_BASIC", + "PUBLISHER_MODEL_VIEW_FULL", + "PUBLISHER_MODEL_VERSION_VIEW_BASIC" + ], + "location": "query", + "description": "Optional. PublisherModel view specifying which fields to read.", + "type": "string" + }, + "isHuggingFaceModel": { + "type": "boolean", + "location": "query", + "description": "Optional. Boolean indicates whether the requested model is a Hugging Face model." + } + }, + "httpMethod": "GET", + "flatPath": "v1/publishers/{publishersId}/models/{modelsId}", + "id": "aiplatform.publishers.models.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + } + } + } + } + } + }, + "auth": { + "oauth2": { + "scopes": { + "https://www.googleapis.com/auth/cloud-platform.read-only": { + "description": "View your data across Google Cloud services and see the email address of your Google Account" + }, + "https://www.googleapis.com/auth/cloud-platform": { + "description": "See, edit, configure, and delete your Google Cloud data and see the email address for your Google Account." + } + } + } + }, + "revision": "20240715", + "name": "aiplatform", + "version_module": true, + "title": "Vertex AI API", + "baseUrl": "https://aiplatform.googleapis.com/", + "documentationLink": "https://cloud.google.com/vertex-ai/", + "ownerDomain": "google.com", + "fullyEncodeReservedExpansion": true, + "icons": { + "x16": "http://www.google.com/images/icons/product/search-16.gif", + "x32": "http://www.google.com/images/icons/product/search-32.gif" + }, + "protocol": "rest", + "parameters": { + "$.xgafv": { + "type": "string", + "enumDescriptions": [ + "v1 error format", + "v2 error format" + ], + "description": "V1 error format.", + "location": "query", + "enum": [ + "1", + "2" + ] + }, + "prettyPrint": { + "description": "Returns response with indentations and line breaks.", + "default": "true", + "type": "boolean", + "location": "query" + }, + "quotaUser": { + "type": "string", + "description": "Available to use for quota purposes for server-side applications. Can be any arbitrary string assigned to a user, but should not exceed 40 characters.", + "location": "query" + }, + "upload_protocol": { + "description": "Upload protocol for media (e.g. \"raw\", \"multipart\").", + "location": "query", + "type": "string" + }, + "uploadType": { + "type": "string", + "description": "Legacy upload protocol for media (e.g. \"media\", \"multipart\").", + "location": "query" + }, + "key": { + "type": "string", + "description": "API key. Your API key identifies your project and provides you with API access, quota, and reports. Required unless you provide an OAuth 2.0 token.", + "location": "query" + }, + "fields": { + "type": "string", + "description": "Selector specifying which fields to include in a partial response.", + "location": "query" + }, + "oauth_token": { + "type": "string", + "description": "OAuth 2.0 token for the current user.", + "location": "query" + }, + "access_token": { + "type": "string", + "location": "query", + "description": "OAuth access token." + }, + "callback": { + "description": "JSONP", + "type": "string", + "location": "query" + }, + "alt": { + "default": "json", + "enumDescriptions": [ + "Responses with Content-Type of application/json", + "Media download with context-dependent Content-Type", + "Responses with Content-Type of application/x-protobuf" + ], + "type": "string", + "enum": [ + "json", + "media", + "proto" + ], + "location": "query", + "description": "Data format for response." + } + }, + "version": "v1", + "schemas": { + "GoogleCloudAiplatformV1WorkerPoolSpec": { + "id": "GoogleCloudAiplatformV1WorkerPoolSpec", + "properties": { + "replicaCount": { + "description": "Optional. The number of worker replicas to use for this worker pool.", + "format": "int64", + "type": "string" + }, + "machineSpec": { + "description": "Optional. Immutable. The specification of a single machine.", + "$ref": "GoogleCloudAiplatformV1MachineSpec" + }, + "diskSpec": { + "$ref": "GoogleCloudAiplatformV1DiskSpec", + "description": "Disk spec." + }, + "pythonPackageSpec": { + "description": "The Python packaged task.", + "$ref": "GoogleCloudAiplatformV1PythonPackageSpec" + }, + "nfsMounts": { + "type": "array", + "description": "Optional. List of NFS mount spec.", + "items": { + "$ref": "GoogleCloudAiplatformV1NfsMount" + } + }, + "containerSpec": { + "description": "The custom container task.", + "$ref": "GoogleCloudAiplatformV1ContainerSpec" + } + }, + "description": "Represents the spec of a worker pool in a job.", + "type": "object" + }, + "GoogleCloudAiplatformV1Scheduling": { + "properties": { + "restartJobOnWorkerRestart": { + "type": "boolean", + "description": "Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job." + }, + "disableRetries": { + "type": "boolean", + "description": "Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides `Scheduling.restart_job_on_worker_restart` to false." + }, + "strategy": { + "enumDescriptions": [ + "Strategy will default to ON_DEMAND.", + "Regular on-demand provisioning strategy.", + "Low cost by making potential use of spot resources." + ], + "type": "string", + "description": "Optional. This determines which type of scheduling strategy to use.", + "enum": [ + "STRATEGY_UNSPECIFIED", + "ON_DEMAND", + "LOW_COST" + ] + }, + "timeout": { + "type": "string", + "format": "google-duration", + "description": "The maximum job running time. The default is 7 days." + } + }, + "description": "All parameters related to queuing and scheduling of custom jobs.", + "id": "GoogleCloudAiplatformV1Scheduling", + "type": "object" + }, + "GoogleCloudAiplatformV1GenerateContentResponse": { + "type": "object", + "id": "GoogleCloudAiplatformV1GenerateContentResponse", + "properties": { + "candidates": { + "readOnly": true, + "type": "array", + "description": "Output only. Generated candidates.", + "items": { + "$ref": "GoogleCloudAiplatformV1Candidate" + } + }, + "usageMetadata": { + "description": "Usage metadata about the response(s).", + "$ref": "GoogleCloudAiplatformV1GenerateContentResponseUsageMetadata" + }, + "promptFeedback": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1GenerateContentResponsePromptFeedback", + "description": "Output only. Content filter results for a prompt sent in the request. Note: Sent only in the first stream chunk. Only happens when no candidates were generated due to content violations." + } + }, + "description": "Response message for [PredictionService.GenerateContent]." + }, + "GoogleCloudAiplatformV1ImportDataRequest": { + "description": "Request message for DatasetService.ImportData.", + "id": "GoogleCloudAiplatformV1ImportDataRequest", + "properties": { + "importConfigs": { + "type": "array", + "description": "Required. The desired input locations. The contents of all input locations will be imported in one batch.", + "items": { + "$ref": "GoogleCloudAiplatformV1ImportDataConfig" + } + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SearchDataItemsResponse": { + "properties": { + "dataItemViews": { + "description": "The DataItemViews read.", + "items": { + "$ref": "GoogleCloudAiplatformV1DataItemView" + }, + "type": "array" + }, + "nextPageToken": { + "type": "string", + "description": "A token to retrieve next page of results. Pass to SearchDataItemsRequest.page_token to obtain that page." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SearchDataItemsResponse", + "description": "Response message for DatasetService.SearchDataItems." + }, + "GoogleCloudAiplatformV1ImportDataConfig": { + "id": "GoogleCloudAiplatformV1ImportDataConfig", + "properties": { + "importSchemaUri": { + "type": "string", + "description": "Required. Points to a YAML file stored on Google Cloud Storage describing the import format. Validation will be done against the schema. The schema is defined as an [OpenAPI 3.0.2 Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject)." + }, + "gcsSource": { + "description": "The Google Cloud Storage location for the input content.", + "$ref": "GoogleCloudAiplatformV1GcsSource" + }, + "dataItemLabels": { + "description": "Labels that will be applied to newly imported DataItems. If an identical DataItem as one being imported already exists in the Dataset, then these labels will be appended to these of the already existing one, and if labels with identical key is imported before, the old label value will be overwritten. If two DataItems are identical in the same import data operation, the labels will be combined and if key collision happens in this case, one of the values will be picked randomly. Two DataItems are considered identical if their content bytes are identical (e.g. image bytes or pdf bytes). These labels will be overridden by Annotation labels specified inside index file referenced by import_schema_uri, e.g. jsonl file.", + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "annotationLabels": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "Labels that will be applied to newly imported Annotations. If two Annotations are identical, one of them will be deduped. Two Annotations are considered identical if their payload, payload_schema_uri and all of their labels are the same. These labels will be overridden by Annotation labels specified inside index file referenced by import_schema_uri, e.g. jsonl file." + } + }, + "description": "Describes the location from where we import data into a Dataset, together with the labels that will be applied to the DataItems and the Annotations.", + "type": "object" + }, + "GoogleCloudAiplatformV1PublisherModelCallToActionDeploy": { + "id": "GoogleCloudAiplatformV1PublisherModelCallToActionDeploy", + "description": "Model metadata that is needed for UploadModel or DeployModel/CreateEndpoint requests.", + "properties": { + "dedicatedResources": { + "description": "A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.", + "$ref": "GoogleCloudAiplatformV1DedicatedResources" + }, + "artifactUri": { + "description": "Optional. The path to the directory containing the Model artifact and any of its supporting files.", + "type": "string" + }, + "automaticResources": { + "description": "A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.", + "$ref": "GoogleCloudAiplatformV1AutomaticResources" + }, + "modelDisplayName": { + "description": "Optional. Default model display name.", + "type": "string" + }, + "sharedResources": { + "type": "string", + "description": "The resource name of the shared DeploymentResourcePool to deploy on. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`" + }, + "title": { + "type": "string", + "description": "Required. The title of the regional resource reference." + }, + "deployTaskName": { + "type": "string", + "description": "Optional. The name of the deploy task (e.g., \"text to image generation\")." + }, + "publicArtifactUri": { + "description": "Optional. The signed URI for ephemeral Cloud Storage access to model artifact.", + "type": "string" + }, + "largeModelReference": { + "$ref": "GoogleCloudAiplatformV1LargeModelReference", + "description": "Optional. Large model reference. When this is set, model_artifact_spec is not needed." + }, + "deployMetadata": { + "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionDeployDeployMetadata", + "description": "Optional. Metadata information about this deployment config." + }, + "containerSpec": { + "$ref": "GoogleCloudAiplatformV1ModelContainerSpec", + "description": "Optional. The specification of the container that is to be used when deploying this Model in Vertex AI. Not present for Large Models." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1PipelineTemplateMetadata": { + "properties": { + "version": { + "type": "string", + "description": "The version_name in artifact registry. Will always be presented in output if the PipelineJob.template_uri is from supported template registry. Format is \"sha256:abcdef123456...\"." + } + }, + "description": "Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry.", + "type": "object", + "id": "GoogleCloudAiplatformV1PipelineTemplateMetadata" + }, + "GoogleCloudAiplatformV1SchemaPredictParamsImageClassificationPredictionParams": { + "description": "Prediction model parameters for Image Classification.", + "properties": { + "confidenceThreshold": { + "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0", + "format": "float", + "type": "number" + }, + "maxPredictions": { + "type": "integer", + "format": "int32", + "description": "The Model only returns up to that many top, by confidence score, predictions per instance. If this number is very high, the Model may return fewer predictions. Default value is 10." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaPredictParamsImageClassificationPredictionParams" + }, + "GoogleCloudAiplatformV1PredictResponse": { + "description": "Response message for PredictionService.Predict.", + "type": "object", + "id": "GoogleCloudAiplatformV1PredictResponse", + "properties": { + "modelVersionId": { + "readOnly": true, + "description": "Output only. The version ID of the Model which is deployed as the DeployedModel that this prediction hits.", + "type": "string" + }, + "predictions": { + "description": "The predictions that are the output of the predictions call. The schema of any single prediction may be specified via Endpoint's DeployedModels' Model's PredictSchemata's prediction_schema_uri.", + "items": { + "type": "any" + }, + "type": "array" + }, + "modelDisplayName": { + "type": "string", + "readOnly": true, + "description": "Output only. The display name of the Model which is deployed as the DeployedModel that this prediction hits." + }, + "model": { + "readOnly": true, + "description": "Output only. The resource name of the Model which is deployed as the DeployedModel that this prediction hits.", + "type": "string" + }, + "deployedModelId": { + "type": "string", + "description": "ID of the Endpoint's DeployedModel that served this prediction." + }, + "metadata": { + "description": "Output only. Request-level metadata returned by the model. The metadata type will be dependent upon the model implementation.", + "readOnly": true, + "type": "any" + } + } + }, + "GoogleCloudAiplatformV1SchemaPredictInstanceImageObjectDetectionPredictionInstance": { + "id": "GoogleCloudAiplatformV1SchemaPredictInstanceImageObjectDetectionPredictionInstance", + "type": "object", + "description": "Prediction input format for Image Object Detection.", + "properties": { + "content": { + "type": "string", + "description": "The image bytes or Cloud Storage URI to make the prediction on." + }, + "mimeType": { + "description": "The MIME type of the content of the image. Only the images in below listed MIME types are supported. - image/jpeg - image/gif - image/png - image/webp - image/bmp - image/tiff - image/vnd.microsoft.icon", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadataInputConfig": { + "type": "object", + "description": "The time series Dataset's data source. The Dataset doesn't store the data directly, but only pointer(s) to its data.", + "id": "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadataInputConfig", + "properties": { + "gcsSource": { + "$ref": "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadataGcsSource" + }, + "bigquerySource": { + "$ref": "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadataBigQuerySource" + } + } + }, + "GoogleCloudAiplatformV1WriteFeatureValuesRequest": { + "id": "GoogleCloudAiplatformV1WriteFeatureValuesRequest", + "description": "Request message for FeaturestoreOnlineServingService.WriteFeatureValues.", + "properties": { + "payloads": { + "type": "array", + "description": "Required. The entities to be written. Up to 100,000 feature values can be written across all `payloads`.", + "items": { + "$ref": "GoogleCloudAiplatformV1WriteFeatureValuesPayload" + } + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1ExportModelOperationMetadata": { + "properties": { + "outputInfo": { + "readOnly": true, + "description": "Output only. Information further describing the output of this Model export.", + "$ref": "GoogleCloudAiplatformV1ExportModelOperationMetadataOutputInfo" + }, + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The common part of the operation metadata." + } + }, + "description": "Details of ModelService.ExportModel operation.", + "id": "GoogleCloudAiplatformV1ExportModelOperationMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1ListEntityTypesResponse": { + "properties": { + "entityTypes": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1EntityType" + }, + "description": "The EntityTypes matching the request." + }, + "nextPageToken": { + "description": "A token, which can be sent as ListEntityTypesRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + } + }, + "description": "Response message for FeaturestoreService.ListEntityTypes.", + "type": "object", + "id": "GoogleCloudAiplatformV1ListEntityTypesResponse" + }, + "GoogleCloudAiplatformV1PurgeArtifactsResponse": { + "id": "GoogleCloudAiplatformV1PurgeArtifactsResponse", + "properties": { + "purgeCount": { + "description": "The number of Artifacts that this request deleted (or, if `force` is false, the number of Artifacts that will be deleted). This can be an estimate.", + "type": "string", + "format": "int64" + }, + "purgeSample": { + "type": "array", + "items": { + "type": "string" + }, + "description": "A sample of the Artifact names that will be deleted. Only populated if `force` is set to false. The maximum number of samples is 100 (it is possible to return fewer)." + } + }, + "type": "object", + "description": "Response message for MetadataService.PurgeArtifacts." + }, + "GoogleCloudAiplatformV1SchemaTextPromptDatasetMetadata": { + "properties": { + "candidateCount": { + "description": "Number of candidates.", + "format": "int64", + "type": "string" + }, + "stopSequences": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Customized stop sequences." + }, + "maxOutputTokens": { + "description": "Value of the maximum number of tokens generated set when the dataset was saved.", + "format": "int64", + "type": "string" + }, + "gcsUri": { + "type": "string", + "description": "The Google Cloud Storage URI that stores the prompt data." + }, + "hasPromptVariable": { + "type": "boolean", + "description": "Whether the prompt dataset has prompt variable." + }, + "temperature": { + "description": "Temperature value used for sampling set when the dataset was saved. This value is used to tune the degree of randomness.", + "type": "number", + "format": "float" + }, + "groundingConfig": { + "$ref": "GoogleCloudAiplatformV1SchemaPredictParamsGroundingConfig", + "description": "Grounding checking configuration." + }, + "promptType": { + "description": "Type of the prompt dataset.", + "type": "string" + }, + "topP": { + "type": "number", + "format": "float", + "description": "Top P value set when the dataset was saved. Given topK tokens for decoding, top candidates will be selected until the sum of their probabilities is topP." + }, + "text": { + "type": "string", + "description": "The content of the prompt dataset." + }, + "note": { + "type": "string", + "description": "User-created prompt note. Note size limit is 2KB." + }, + "systemInstructionGcsUri": { + "type": "string", + "description": "The Google Cloud Storage URI that stores the system instruction, starting with gs://." + }, + "systemInstruction": { + "type": "string", + "description": "The content of the prompt dataset system instruction." + }, + "topK": { + "type": "string", + "format": "int64", + "description": "Top K value set when the dataset was saved. This value determines how many candidates with highest probability from the vocab would be selected for each decoding step." + } + }, + "description": "The metadata of Datasets that contain Text Prompt data.", + "id": "GoogleCloudAiplatformV1SchemaTextPromptDatasetMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1SafetyInstance": { + "description": "Spec for safety instance.", + "type": "object", + "id": "GoogleCloudAiplatformV1SafetyInstance", + "properties": { + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + } + } + }, + "GoogleCloudAiplatformV1VideoMetadata": { + "description": "Metadata describes the input video content.", + "properties": { + "startOffset": { + "format": "google-duration", + "type": "string", + "description": "Optional. The start offset of the video." + }, + "endOffset": { + "type": "string", + "format": "google-duration", + "description": "Optional. The end offset of the video." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1VideoMetadata" + }, + "GoogleCloudAiplatformV1BleuSpec": { + "description": "Spec for bleu score metric - calculates the precision of n-grams in the prediction as compared to reference - returns a score ranging between 0 to 1.", + "id": "GoogleCloudAiplatformV1BleuSpec", + "properties": { + "useEffectiveOrder": { + "description": "Optional. Whether to use_effective_order to compute bleu score.", + "type": "boolean" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1DataLabelingJob": { + "id": "GoogleCloudAiplatformV1DataLabelingJob", + "type": "object", + "properties": { + "state": { + "description": "Output only. The detailed state of the job.", + "enum": [ + "JOB_STATE_UNSPECIFIED", + "JOB_STATE_QUEUED", + "JOB_STATE_PENDING", + "JOB_STATE_RUNNING", + "JOB_STATE_SUCCEEDED", + "JOB_STATE_FAILED", + "JOB_STATE_CANCELLING", + "JOB_STATE_CANCELLED", + "JOB_STATE_PAUSED", + "JOB_STATE_EXPIRED", + "JOB_STATE_UPDATING", + "JOB_STATE_PARTIALLY_SUCCEEDED" + ], + "readOnly": true, + "enumDescriptions": [ + "The job state is unspecified.", + "The job has been just created or resumed and processing has not yet begun.", + "The service is preparing to run the job.", + "The job is in progress.", + "The job completed successfully.", + "The job failed.", + "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "The job has been cancelled.", + "The job has been stopped, and can be resumed.", + "The job has expired.", + "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", + "The job is partially succeeded, some results may be missing due to errors." + ], + "type": "string" + }, + "createTime": { + "description": "Output only. Timestamp when this DataLabelingJob was created.", + "readOnly": true, + "format": "google-datetime", + "type": "string" + }, + "activeLearningConfig": { + "$ref": "GoogleCloudAiplatformV1ActiveLearningConfig", + "description": "Parameters that configure the active learning pipeline. Active learning will label the data incrementally via several iterations. For every iteration, it will select a batch of data based on the sampling strategy." + }, + "labels": { + "description": "The labels with user-defined metadata to organize your DataLabelingJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable. Following system labels exist for each DataLabelingJob: * \"aiplatform.googleapis.com/schema\": output only, its value is the inputs_schema's title.", + "additionalProperties": { + "type": "string" + }, + "type": "object" + }, + "labelingProgress": { + "readOnly": true, + "type": "integer", + "format": "int32", + "description": "Output only. Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished." + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1EncryptionSpec", + "description": "Customer-managed encryption key spec for a DataLabelingJob. If set, this DataLabelingJob will be secured by this key. Note: Annotations created in the DataLabelingJob are associated with the EncryptionSpec of the Dataset they are exported to." + }, + "error": { + "readOnly": true, + "$ref": "GoogleRpcStatus", + "description": "Output only. DataLabelingJob errors. It is only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`." + }, + "name": { + "readOnly": true, + "type": "string", + "description": "Output only. Resource name of the DataLabelingJob." + }, + "inputs": { + "description": "Required. Input config parameters for the DataLabelingJob.", + "type": "any" + }, + "annotationLabels": { + "additionalProperties": { + "type": "string" + }, + "description": "Labels to assign to annotations generated by this DataLabelingJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", + "type": "object" + }, + "labelerCount": { + "format": "int32", + "type": "integer", + "description": "Required. Number of labelers to work on each DataItem." + }, + "datasets": { + "description": "Required. Dataset resource names. Right now we only support labeling from a single Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", + "type": "array", + "items": { + "type": "string" + } + }, + "displayName": { + "description": "Required. The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a DataLabelingJob.", + "type": "string" + }, + "instructionUri": { + "type": "string", + "description": "Required. The Google Cloud Storage location of the instruction pdf. This pdf is shared with labelers, and provides detailed description on how to label DataItems in Datasets." + }, + "currentSpend": { + "$ref": "GoogleTypeMoney", + "readOnly": true, + "description": "Output only. Estimated cost(in US dollars) that the DataLabelingJob has incurred to date." + }, + "inputsSchemaUri": { + "type": "string", + "description": "Required. Points to a YAML file stored on Google Cloud Storage describing the config for a specific type of DataLabelingJob. The schema files that can be used here are found in the https://storage.googleapis.com/google-cloud-aiplatform bucket in the /schema/datalabelingjob/inputs/ folder." + }, + "updateTime": { + "format": "google-datetime", + "readOnly": true, + "type": "string", + "description": "Output only. Timestamp when this DataLabelingJob was updated most recently." + }, + "specialistPools": { + "type": "array", + "description": "The SpecialistPools' resource names associated with this job.", + "items": { + "type": "string" + } + } + }, + "description": "DataLabelingJob is used to trigger a human labeling job on unlabeled data from the following Dataset:" + }, + "GoogleCloudAiplatformV1UndeployIndexOperationMetadata": { + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The operation generic information." + } + }, + "description": "Runtime operation information for IndexEndpointService.UndeployIndex.", + "id": "GoogleCloudAiplatformV1UndeployIndexOperationMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1MutateDeployedModelOperationMetadata": { + "id": "GoogleCloudAiplatformV1MutateDeployedModelOperationMetadata", + "type": "object", + "description": "Runtime operation information for EndpointService.MutateDeployedModel.", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The operation generic information." + } + } + }, + "GoogleCloudAiplatformV1ImportFeatureValuesOperationMetadata": { + "type": "object", + "properties": { + "importedFeatureValueCount": { + "type": "string", + "format": "int64", + "description": "Number of Feature values that have been imported by the operation." + }, + "sourceUris": { + "items": { + "type": "string" + }, + "description": "The source URI from where Feature values are imported.", + "type": "array" + }, + "blockingOperationIds": { + "items": { + "format": "int64", + "type": "string" + }, + "type": "array", + "description": "List of ImportFeatureValues operations running under a single EntityType that are blocking this operation." + }, + "importedEntityCount": { + "type": "string", + "format": "int64", + "description": "Number of entities that have been imported by the operation." + }, + "timestampOutsideRetentionRowsCount": { + "type": "string", + "description": "The number rows that weren't ingested due to having timestamps outside the retention boundary.", + "format": "int64" + }, + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "Operation metadata for Featurestore import Feature values." + }, + "invalidRowCount": { + "description": "The number of rows in input source that weren't imported due to either * Not having any featureValues. * Having a null entityId. * Having a null timestamp. * Not being parsable (applicable for CSV sources).", + "format": "int64", + "type": "string" + } + }, + "description": "Details of operations that perform import Feature values.", + "id": "GoogleCloudAiplatformV1ImportFeatureValuesOperationMetadata" + }, + "GoogleCloudAiplatformV1ResumeScheduleRequest": { + "id": "GoogleCloudAiplatformV1ResumeScheduleRequest", + "properties": { + "catchUp": { + "description": "Optional. Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. This will also update Schedule.catch_up field. Default to false.", + "type": "boolean" + } + }, + "description": "Request message for ScheduleService.ResumeSchedule.", + "type": "object" + }, + "GoogleCloudAiplatformV1Annotation": { + "type": "object", + "id": "GoogleCloudAiplatformV1Annotation", + "properties": { + "createTime": { + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Timestamp when this Annotation was created.", + "type": "string" + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "description": "Optional. The labels with user-defined metadata to organize your Annotations. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Annotation(System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable. Following system labels exist for each Annotation: * \"aiplatform.googleapis.com/annotation_set_name\": optional, name of the UI's annotation set this Annotation belongs to. If not set, the Annotation is not visible in the UI. * \"aiplatform.googleapis.com/payload_schema\": output only, its value is the payload_schema's title.", + "type": "object" + }, + "annotationSource": { + "readOnly": true, + "description": "Output only. The source of the Annotation.", + "$ref": "GoogleCloudAiplatformV1UserActionReference" + }, + "updateTime": { + "format": "google-datetime", + "readOnly": true, + "type": "string", + "description": "Output only. Timestamp when this Annotation was last updated." + }, + "payload": { + "description": "Required. The schema of the payload can be found in payload_schema.", + "type": "any" + }, + "payloadSchemaUri": { + "description": "Required. Google Cloud Storage URI points to a YAML file describing payload. The schema is defined as an [OpenAPI 3.0.2 Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/annotation/, note that the chosen schema must be consistent with the parent Dataset's metadata.", + "type": "string" + }, + "etag": { + "type": "string", + "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + }, + "name": { + "readOnly": true, + "description": "Output only. Resource name of the Annotation.", + "type": "string" + } + }, + "description": "Used to assign specific AnnotationSpec to a particular area of a DataItem or the whole part of the DataItem." + }, + "GoogleCloudAiplatformV1ListNasTrialDetailsResponse": { + "description": "Response message for JobService.ListNasTrialDetails", + "id": "GoogleCloudAiplatformV1ListNasTrialDetailsResponse", + "properties": { + "nextPageToken": { + "description": "A token to retrieve the next page of results. Pass to ListNasTrialDetailsRequest.page_token to obtain that page.", + "type": "string" + }, + "nasTrialDetails": { + "items": { + "$ref": "GoogleCloudAiplatformV1NasTrialDetail" + }, + "type": "array", + "description": "List of top NasTrials in the requested page." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1ExactMatchMetricValue": { + "description": "Exact match metric value for an instance.", + "id": "GoogleCloudAiplatformV1ExactMatchMetricValue", + "properties": { + "score": { + "type": "number", + "description": "Output only. Exact match score.", + "readOnly": true, + "format": "float" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1ExportModelRequest": { + "type": "object", + "id": "GoogleCloudAiplatformV1ExportModelRequest", + "properties": { + "outputConfig": { + "$ref": "GoogleCloudAiplatformV1ExportModelRequestOutputConfig", + "description": "Required. The desired output location and configuration." + } + }, + "description": "Request message for ModelService.ExportModel." + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageSegmentationMetadata": { + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageSegmentationMetadata", + "type": "object", + "properties": { + "successfulStopReason": { + "type": "string", + "enumDescriptions": [ + "Should not be set.", + "The inputs.budgetMilliNodeHours had been reached.", + "Further training of the Model ceased to increase its quality, since it already has converged." + ], + "description": "For successful job completions, this is the reason why the job has finished.", + "enum": [ + "SUCCESSFUL_STOP_REASON_UNSPECIFIED", + "BUDGET_REACHED", + "MODEL_CONVERGED" + ] + }, + "costMilliNodeHours": { + "type": "string", + "format": "int64", + "description": "The actual training cost of creating this model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed inputs.budgetMilliNodeHours." + } + } + }, + "GoogleCloudAiplatformV1TFRecordDestination": { + "type": "object", + "id": "GoogleCloudAiplatformV1TFRecordDestination", + "properties": { + "gcsDestination": { + "$ref": "GoogleCloudAiplatformV1GcsDestination", + "description": "Required. Google Cloud Storage location." + } + }, + "description": "The storage details for TFRecord output content." + }, + "GoogleCloudAiplatformV1SchemaTextSentimentAnnotation": { + "properties": { + "sentimentMax": { + "type": "integer", + "description": "The sentiment max score for text.", + "format": "int32" + }, + "displayName": { + "description": "The display name of the AnnotationSpec that this Annotation pertains to.", + "type": "string" + }, + "annotationSpecId": { + "type": "string", + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." + }, + "sentiment": { + "type": "integer", + "description": "The sentiment score for text.", + "format": "int32" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTextSentimentAnnotation", + "description": "Annotation details specific to text sentiment." + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageClassificationMetadata": { + "properties": { + "costMilliNodeHours": { + "description": "The actual training cost of creating this model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed inputs.budgetMilliNodeHours.", + "format": "int64", + "type": "string" + }, + "successfulStopReason": { + "enumDescriptions": [ + "Should not be set.", + "The inputs.budgetMilliNodeHours had been reached.", + "Further training of the Model ceased to increase its quality, since it already has converged." + ], + "description": "For successful job completions, this is the reason why the job has finished.", + "enum": [ + "SUCCESSFUL_STOP_REASON_UNSPECIFIED", + "BUDGET_REACHED", + "MODEL_CONVERGED" + ], + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageClassificationMetadata" + }, + "GoogleCloudAiplatformV1CreatePipelineJobRequest": { + "properties": { + "pipelineJob": { + "description": "Required. The PipelineJob to create.", + "$ref": "GoogleCloudAiplatformV1PipelineJob" + }, + "pipelineJobId": { + "description": "The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.", + "type": "string" + }, + "parent": { + "type": "string", + "description": "Required. The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`" + } + }, + "id": "GoogleCloudAiplatformV1CreatePipelineJobRequest", + "type": "object", + "description": "Request message for PipelineService.CreatePipelineJob." + }, + "GoogleCloudAiplatformV1DeploymentResourcePool": { + "id": "GoogleCloudAiplatformV1DeploymentResourcePool", + "properties": { + "dedicatedResources": { + "$ref": "GoogleCloudAiplatformV1DedicatedResources", + "description": "Required. The underlying DedicatedResources that the DeploymentResourcePool uses." + }, + "disableContainerLogging": { + "type": "boolean", + "description": "If the DeploymentResourcePool is deployed with custom-trained Models or AutoML Tabular Models, the container(s) of the DeploymentResourcePool will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true." + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1EncryptionSpec", + "description": "Customer-managed encryption key spec for a DeploymentResourcePool. If set, this DeploymentResourcePool will be secured by this key. Endpoints and the DeploymentResourcePool they deploy in need to have the same EncryptionSpec." + }, + "serviceAccount": { + "description": "The service account that the DeploymentResourcePool's container(s) run as. Specify the email address of the service account. If this service account is not specified, the container(s) run as a service account that doesn't have access to the resource project. Users deploying the Models to this DeploymentResourcePool must have the `iam.serviceAccounts.actAs` permission on this service account.", + "type": "string" + }, + "name": { + "type": "string", + "description": "Immutable. The resource name of the DeploymentResourcePool. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`" + }, + "createTime": { + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Timestamp when this DeploymentResourcePool was created.", + "type": "string" + } + }, + "description": "A description of resources that can be shared by multiple DeployedModels, whose underlying specification consists of a DedicatedResources.", + "type": "object" + }, + "GoogleCloudAiplatformV1ModelBaseModelSource": { + "type": "object", + "properties": { + "modelGardenSource": { + "$ref": "GoogleCloudAiplatformV1ModelGardenSource", + "description": "Source information of Model Garden models." + }, + "genieSource": { + "description": "Information about the base model of Genie models.", + "$ref": "GoogleCloudAiplatformV1GenieSource" + } + }, + "id": "GoogleCloudAiplatformV1ModelBaseModelSource", + "description": "User input field to specify the base model source. Currently it only supports specifing the Model Garden models and Genie models." + }, + "GoogleCloudAiplatformV1SampleConfig": { + "type": "object", + "description": "Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.", + "id": "GoogleCloudAiplatformV1SampleConfig", + "properties": { + "sampleStrategy": { + "enum": [ + "SAMPLE_STRATEGY_UNSPECIFIED", + "UNCERTAINTY" + ], + "description": "Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.", + "enumDescriptions": [ + "Default will be treated as UNCERTAINTY.", + "Sample the most uncertain data to label." + ], + "type": "string" + }, + "followingBatchSamplePercentage": { + "description": "The percentage of data needed to be labeled in each following batch (except the first batch).", + "format": "int32", + "type": "integer" + }, + "initialBatchSamplePercentage": { + "format": "int32", + "type": "integer", + "description": "The percentage of data needed to be labeled in the first batch." + } + } + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsBoundingBoxMetricsConfidenceMetrics": { + "properties": { + "recall": { + "description": "Recall under the given confidence threshold.", + "type": "number", + "format": "float" + }, + "precision": { + "description": "Precision under the given confidence threshold.", + "type": "number", + "format": "float" + }, + "confidenceThreshold": { + "format": "float", + "type": "number", + "description": "The confidence threshold value used to compute the metrics." + }, + "f1Score": { + "format": "float", + "type": "number", + "description": "The harmonic mean of recall and precision." + } + }, + "type": "object", + "description": "Metrics for a single confidence threshold.", + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsBoundingBoxMetricsConfidenceMetrics" + }, + "GoogleCloudAiplatformV1ModelExplanation": { + "type": "object", + "description": "Aggregated explanation metrics for a Model over a set of instances.", + "properties": { + "meanAttributions": { + "readOnly": true, + "description": "Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. Attribution.output_index can be used to identify which output this attribution is explaining. The baselineOutputValue, instanceOutputValue and featureAttributions fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. Attribution.approximation_error is not populated.", + "items": { + "$ref": "GoogleCloudAiplatformV1Attribution" + }, + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1ModelExplanation" + }, + "GoogleCloudAiplatformV1RestoreDatasetVersionOperationMetadata": { + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The common part of the operation metadata." + } + }, + "type": "object", + "description": "Runtime operation information for DatasetService.RestoreDatasetVersion.", + "id": "GoogleCloudAiplatformV1RestoreDatasetVersionOperationMetadata" + }, + "GoogleCloudAiplatformV1CancelBatchPredictionJobRequest": { + "description": "Request message for JobService.CancelBatchPredictionJob.", + "type": "object", + "id": "GoogleCloudAiplatformV1CancelBatchPredictionJobRequest", + "properties": {} + }, + "GoogleCloudAiplatformV1SchemaPredictionResultError": { + "id": "GoogleCloudAiplatformV1SchemaPredictionResultError", + "type": "object", + "properties": { + "message": { + "description": "Error message with additional details.", + "type": "string" + }, + "status": { + "description": "Error status. This will be serialized into the enum name e.g. \"NOT_FOUND\".", + "enumDescriptions": [ + "Not an error; returned on success. HTTP Mapping: 200 OK", + "The operation was cancelled, typically by the caller. HTTP Mapping: 499 Client Closed Request", + "Unknown error. For example, this error may be returned when a `Status` value received from another address space belongs to an error space that is not known in this address space. Also errors raised by APIs that do not return enough error information may be converted to this error. HTTP Mapping: 500 Internal Server Error", + "The client specified an invalid argument. Note that this differs from `FAILED_PRECONDITION`. `INVALID_ARGUMENT` indicates arguments that are problematic regardless of the state of the system (e.g., a malformed file name). HTTP Mapping: 400 Bad Request", + "The deadline expired before the operation could complete. For operations that change the state of the system, this error may be returned even if the operation has completed successfully. For example, a successful response from a server could have been delayed long enough for the deadline to expire. HTTP Mapping: 504 Gateway Timeout", + "Some requested entity (e.g., file or directory) was not found. Note to server developers: if a request is denied for an entire class of users, such as gradual feature rollout or undocumented allowlist, `NOT_FOUND` may be used. If a request is denied for some users within a class of users, such as user-based access control, `PERMISSION_DENIED` must be used. HTTP Mapping: 404 Not Found", + "The entity that a client attempted to create (e.g., file or directory) already exists. HTTP Mapping: 409 Conflict", + "The caller does not have permission to execute the specified operation. `PERMISSION_DENIED` must not be used for rejections caused by exhausting some resource (use `RESOURCE_EXHAUSTED` instead for those errors). `PERMISSION_DENIED` must not be used if the caller can not be identified (use `UNAUTHENTICATED` instead for those errors). This error code does not imply the request is valid or the requested entity exists or satisfies other pre-conditions. HTTP Mapping: 403 Forbidden", + "The request does not have valid authentication credentials for the operation. HTTP Mapping: 401 Unauthorized", + "Some resource has been exhausted, perhaps a per-user quota, or perhaps the entire file system is out of space. HTTP Mapping: 429 Too Many Requests", + "The operation was rejected because the system is not in a state required for the operation's execution. For example, the directory to be deleted is non-empty, an rmdir operation is applied to a non-directory, etc. Service implementors can use the following guidelines to decide between `FAILED_PRECONDITION`, `ABORTED`, and `UNAVAILABLE`: (a) Use `UNAVAILABLE` if the client can retry just the failing call. (b) Use `ABORTED` if the client should retry at a higher level. For example, when a client-specified test-and-set fails, indicating the client should restart a read-modify-write sequence. (c) Use `FAILED_PRECONDITION` if the client should not retry until the system state has been explicitly fixed. For example, if an \"rmdir\" fails because the directory is non-empty, `FAILED_PRECONDITION` should be returned since the client should not retry unless the files are deleted from the directory. HTTP Mapping: 400 Bad Request", + "The operation was aborted, typically due to a concurrency issue such as a sequencer check failure or transaction abort. See the guidelines above for deciding between `FAILED_PRECONDITION`, `ABORTED`, and `UNAVAILABLE`. HTTP Mapping: 409 Conflict", + "The operation was attempted past the valid range. E.g., seeking or reading past end-of-file. Unlike `INVALID_ARGUMENT`, this error indicates a problem that may be fixed if the system state changes. For example, a 32-bit file system will generate `INVALID_ARGUMENT` if asked to read at an offset that is not in the range [0,2^32-1], but it will generate `OUT_OF_RANGE` if asked to read from an offset past the current file size. There is a fair bit of overlap between `FAILED_PRECONDITION` and `OUT_OF_RANGE`. We recommend using `OUT_OF_RANGE` (the more specific error) when it applies so that callers who are iterating through a space can easily look for an `OUT_OF_RANGE` error to detect when they are done. HTTP Mapping: 400 Bad Request", + "The operation is not implemented or is not supported/enabled in this service. HTTP Mapping: 501 Not Implemented", + "Internal errors. This means that some invariants expected by the underlying system have been broken. This error code is reserved for serious errors. HTTP Mapping: 500 Internal Server Error", + "The service is currently unavailable. This is most likely a transient condition, which can be corrected by retrying with a backoff. Note that it is not always safe to retry non-idempotent operations. See the guidelines above for deciding between `FAILED_PRECONDITION`, `ABORTED`, and `UNAVAILABLE`. HTTP Mapping: 503 Service Unavailable", + "Unrecoverable data loss or corruption. HTTP Mapping: 500 Internal Server Error" + ], + "enum": [ + "OK", + "CANCELLED", + "UNKNOWN", + "INVALID_ARGUMENT", + "DEADLINE_EXCEEDED", + "NOT_FOUND", + "ALREADY_EXISTS", + "PERMISSION_DENIED", + "UNAUTHENTICATED", + "RESOURCE_EXHAUSTED", + "FAILED_PRECONDITION", + "ABORTED", + "OUT_OF_RANGE", + "UNIMPLEMENTED", + "INTERNAL", + "UNAVAILABLE", + "DATA_LOSS" + ], + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpecRange": { + "type": "object", + "properties": { + "high": { + "type": "number", + "description": "Exclusive high value for the range.", + "format": "float" + }, + "low": { + "type": "number", + "description": "Inclusive low value for the range.", + "format": "float" + } + }, + "description": "A range of values for slice(s). `low` is inclusive, `high` is exclusive.", + "id": "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpecRange" + }, + "GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfig": { + "type": "object", + "id": "GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfig", + "properties": { + "objectiveConfig": { + "description": "The objective config of for the modelmonitoring job of this deployed model.", + "$ref": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfig" + }, + "deployedModelId": { + "type": "string", + "description": "The DeployedModel ID of the objective config." + } + }, + "description": "ModelDeploymentMonitoringObjectiveConfig contains the pair of deployed_model_id to ModelMonitoringObjectiveConfig." + }, + "GoogleCloudAiplatformV1RayLogsSpec": { + "type": "object", + "id": "GoogleCloudAiplatformV1RayLogsSpec", + "description": "Configuration for the Ray OSS Logs.", + "properties": { + "disabled": { + "description": "Optional. Flag to disable the export of Ray OSS logs to Cloud Logging.", + "type": "boolean" + } + } + }, + "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadataContentValidationStats": { + "properties": { + "invalidSparseRecordCount": { + "description": "Number of sparse records in this file we skipped due to validate errors.", + "format": "int64", + "type": "string" + }, + "validSparseRecordCount": { + "type": "string", + "description": "Number of sparse records in this file that were successfully processed.", + "format": "int64" + }, + "invalidRecordCount": { + "description": "Number of records in this file we skipped due to validate errors.", + "type": "string", + "format": "int64" + }, + "validRecordCount": { + "type": "string", + "format": "int64", + "description": "Number of records in this file that were successfully processed." + }, + "sourceGcsUri": { + "type": "string", + "description": "Cloud Storage URI pointing to the original file in user's bucket." + }, + "partialErrors": { + "description": "The detail information of the partial failures encountered for those invalid records that couldn't be parsed. Up to 50 partial errors will be reported.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadataRecordError" + } + } + }, + "id": "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadataContentValidationStats", + "type": "object" + }, + "GoogleCloudAiplatformV1ExportFeatureValuesRequestSnapshotExport": { + "type": "object", + "id": "GoogleCloudAiplatformV1ExportFeatureValuesRequestSnapshotExport", + "description": "Describes exporting the latest Feature values of all entities of the EntityType between [start_time, snapshot_time].", + "properties": { + "startTime": { + "type": "string", + "format": "google-datetime", + "description": "Excludes Feature values with feature generation timestamp before this timestamp. If not set, retrieve oldest values kept in Feature Store. Timestamp, if present, must not have higher than millisecond precision." + }, + "snapshotTime": { + "description": "Exports Feature values as of this timestamp. If not set, retrieve values as of now. Timestamp, if present, must not have higher than millisecond precision.", + "format": "google-datetime", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1SchemaPredictPredictionVideoObjectTrackingPredictionResult": { + "description": "Prediction output format for Video Object Tracking.", + "id": "GoogleCloudAiplatformV1SchemaPredictPredictionVideoObjectTrackingPredictionResult", + "properties": { + "frames": { + "type": "array", + "description": "All of the frames of the video in which a single object instance has been detected. The bounding boxes in the frames identify the same object.", + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaPredictPredictionVideoObjectTrackingPredictionResultFrame" + } + }, + "timeSegmentStart": { + "type": "string", + "description": "The beginning, inclusive, of the video's time segment in which the object instance has been detected. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end.", + "format": "google-duration" + }, + "timeSegmentEnd": { + "format": "google-duration", + "type": "string", + "description": "The end, inclusive, of the video's time segment in which the object instance has been detected. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end." + }, + "confidence": { + "description": "The Model's confidence in correction of this prediction, higher value means higher confidence.", + "type": "number", + "format": "float" + }, + "displayName": { + "description": "The display name of the AnnotationSpec that had been identified.", + "type": "string" + }, + "id": { + "description": "The resource ID of the AnnotationSpec that had been identified.", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextExtractionInputs": { + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextExtractionInputs", + "properties": {} + }, + "GoogleCloudAiplatformV1FeatureNoiseSigma": { + "id": "GoogleCloudAiplatformV1FeatureNoiseSigma", + "description": "Noise sigma by features. Noise sigma represents the standard deviation of the gaussian kernel that will be used to add noise to interpolated inputs prior to computing gradients.", + "type": "object", + "properties": { + "noiseSigma": { + "description": "Noise sigma per feature. No noise is added to features that are not set.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeature" + } + } + } + }, + "GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfig": { + "properties": { + "userEmails": { + "items": { + "type": "string" + }, + "type": "array", + "description": "The email addresses to send the alert." + } + }, + "description": "The config for email alert.", + "type": "object", + "id": "GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfig" + }, + "GoogleCloudAiplatformV1Value": { + "properties": { + "intValue": { + "format": "int64", + "type": "string", + "description": "An integer value." + }, + "doubleValue": { + "format": "double", + "type": "number", + "description": "A double value." + }, + "stringValue": { + "type": "string", + "description": "A string value." + } + }, + "type": "object", + "description": "Value is the value of the field.", + "id": "GoogleCloudAiplatformV1Value" + }, + "GoogleCloudAiplatformV1SchemaPredictParamsImageSegmentationPredictionParams": { + "id": "GoogleCloudAiplatformV1SchemaPredictParamsImageSegmentationPredictionParams", + "description": "Prediction model parameters for Image Segmentation.", + "properties": { + "confidenceThreshold": { + "format": "float", + "type": "number", + "description": "When the model predicts category of pixels of the image, it will only provide predictions for pixels that it is at least this much confident about. All other pixels will be classified as background. Default value is 0.5." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformation": { + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformation", + "properties": { + "text": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTextTransformation" + }, + "timestamp": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTimestampTransformation" + }, + "numeric": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationNumericTransformation" + }, + "auto": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationAutoTransformation" + }, + "categorical": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationCategoricalTransformation" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1RougeInput": { + "description": "Input for rouge metric.", + "id": "GoogleCloudAiplatformV1RougeInput", + "properties": { + "metricSpec": { + "description": "Required. Spec for rouge score metric.", + "$ref": "GoogleCloudAiplatformV1RougeSpec" + }, + "instances": { + "items": { + "$ref": "GoogleCloudAiplatformV1RougeInstance" + }, + "description": "Required. Repeated rouge instances.", + "type": "array" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1ShieldedVmConfig": { + "type": "object", + "description": "A set of Shielded Instance options. See [Images using supported Shielded VM features](https://cloud.google.com/compute/docs/instances/modifying-shielded-vm).", + "properties": { + "enableSecureBoot": { + "type": "boolean", + "description": "Defines whether the instance has [Secure Boot](https://cloud.google.com/compute/shielded-vm/docs/shielded-vm#secure-boot) enabled. Secure Boot helps ensure that the system only runs authentic software by verifying the digital signature of all boot components, and halting the boot process if signature verification fails." + } + }, + "id": "GoogleCloudAiplatformV1ShieldedVmConfig" + }, + "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueCondition": { + "type": "object", + "id": "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueCondition", + "properties": { + "values": { + "type": "array", + "description": "Required. Matches values of the parent parameter of 'CATEGORICAL' type. All values must exist in `categorical_value_spec` of parent parameter.", + "items": { + "type": "string" + } + } + }, + "description": "Represents the spec to match categorical values from parent parameter." + }, + "GoogleCloudAiplatformV1PipelineJobDetail": { + "properties": { + "taskDetails": { + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1PipelineTaskDetail" + }, + "description": "Output only. The runtime details of the tasks under the pipeline.", + "type": "array" + }, + "pipelineRunContext": { + "description": "Output only. The context of the current pipeline run.", + "$ref": "GoogleCloudAiplatformV1Context", + "readOnly": true + }, + "pipelineContext": { + "description": "Output only. The context of the pipeline.", + "$ref": "GoogleCloudAiplatformV1Context", + "readOnly": true + } + }, + "description": "The runtime detail of PipelineJob.", + "type": "object", + "id": "GoogleCloudAiplatformV1PipelineJobDetail" + }, + "GoogleCloudAiplatformV1DeleteFeatureValuesRequestSelectEntity": { + "type": "object", + "properties": { + "entityIdSelector": { + "$ref": "GoogleCloudAiplatformV1EntityIdSelector", + "description": "Required. Selectors choosing feature values of which entity id to be deleted from the EntityType." + } + }, + "description": "Message to select entity. If an entity id is selected, all the feature values corresponding to the entity id will be deleted, including the entityId.", + "id": "GoogleCloudAiplatformV1DeleteFeatureValuesRequestSelectEntity" + }, + "GoogleCloudAiplatformV1RougeResults": { + "id": "GoogleCloudAiplatformV1RougeResults", + "description": "Results for rouge metric.", + "properties": { + "rougeMetricValues": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1RougeMetricValue" + }, + "readOnly": true, + "description": "Output only. Rouge metric values." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1FetchFeatureValuesRequest": { + "description": "Request message for FeatureOnlineStoreService.FetchFeatureValues. All the features under the requested feature view will be returned.", + "id": "GoogleCloudAiplatformV1FetchFeatureValuesRequest", + "type": "object", + "properties": { + "dataKey": { + "$ref": "GoogleCloudAiplatformV1FeatureViewDataKey", + "description": "Optional. The request key to fetch feature values for." + }, + "dataFormat": { + "type": "string", + "description": "Optional. Response data format. If not set, FeatureViewDataFormat.KEY_VALUE will be used.", + "enumDescriptions": [ + "Not set. Will be treated as the KeyValue format.", + "Return response data in key-value format.", + "Return response data in proto Struct format." + ], + "enum": [ + "FEATURE_VIEW_DATA_FORMAT_UNSPECIFIED", + "KEY_VALUE", + "PROTO_STRUCT" + ] + } + } + }, + "CloudAiLargeModelsVisionVideo": { + "properties": { + "video": { + "format": "byte", + "type": "string", + "description": "Raw bytes." + }, + "uri": { + "type": "string", + "description": "Path to another storage (typically Google Cloud Storage)." + } + }, + "description": "Video", + "type": "object", + "id": "CloudAiLargeModelsVisionVideo" + }, + "GoogleCloudAiplatformV1BatchCreateFeaturesResponse": { + "properties": { + "features": { + "items": { + "$ref": "GoogleCloudAiplatformV1Feature" + }, + "description": "The Features created.", + "type": "array" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1BatchCreateFeaturesResponse", + "description": "Response message for FeaturestoreService.BatchCreateFeatures." + }, + "GoogleCloudAiplatformV1CitationMetadata": { + "id": "GoogleCloudAiplatformV1CitationMetadata", + "properties": { + "citations": { + "type": "array", + "description": "Output only. List of citations.", + "items": { + "$ref": "GoogleCloudAiplatformV1Citation" + }, + "readOnly": true + } + }, + "description": "A collection of source attributions for a piece of content.", + "type": "object" + }, + "GoogleCloudAiplatformV1ToolParameterKeyMatchInstance": { + "type": "object", + "properties": { + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + }, + "reference": { + "type": "string", + "description": "Required. Ground truth used to compare against the prediction." + } + }, + "id": "GoogleCloudAiplatformV1ToolParameterKeyMatchInstance", + "description": "Spec for tool parameter key match instance." + }, + "GoogleCloudAiplatformV1SchemaPredictPredictionTabularClassificationPredictionResult": { + "id": "GoogleCloudAiplatformV1SchemaPredictPredictionTabularClassificationPredictionResult", + "type": "object", + "properties": { + "classes": { + "items": { + "type": "string" + }, + "type": "array", + "description": "The name of the classes being classified, contains all possible values of the target column." + }, + "scores": { + "items": { + "type": "number", + "format": "float" + }, + "type": "array", + "description": "The model's confidence in each class being correct, higher value means higher confidence. The N-th score corresponds to the N-th class in classes." + } + }, + "description": "Prediction output format for Tabular Classification." + }, + "GoogleCloudAiplatformV1SchemaPredictPredictionClassificationPredictionResult": { + "properties": { + "ids": { + "description": "The resource IDs of the AnnotationSpecs that had been identified.", + "type": "array", + "items": { + "type": "string", + "format": "int64" + } + }, + "displayNames": { + "description": "The display names of the AnnotationSpecs that had been identified, order matches the IDs.", + "type": "array", + "items": { + "type": "string" + } + }, + "confidences": { + "type": "array", + "items": { + "type": "number", + "format": "float" + }, + "description": "The Model's confidences in correctness of the predicted IDs, higher value means higher confidence. Order matches the Ids." + } + }, + "description": "Prediction output format for Image and Text Classification.", + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaPredictPredictionClassificationPredictionResult" + }, + "GoogleCloudAiplatformV1Retrieval": { + "description": "Defines a retrieval tool that model can call to access external knowledge.", + "properties": { + "disableAttribution": { + "description": "Optional. Deprecated. This option is no longer supported.", + "deprecated": true, + "type": "boolean" + }, + "vertexAiSearch": { + "$ref": "GoogleCloudAiplatformV1VertexAISearch", + "description": "Set to use data source powered by Vertex AI Search." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1Retrieval" + }, + "GoogleCloudAiplatformV1DeployedModel": { + "id": "GoogleCloudAiplatformV1DeployedModel", + "type": "object", + "properties": { + "sharedResources": { + "type": "string", + "description": "The resource name of the shared DeploymentResourcePool to deploy on. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`" + }, + "createTime": { + "format": "google-datetime", + "description": "Output only. Timestamp when the DeployedModel was created.", + "readOnly": true, + "type": "string" + }, + "explanationSpec": { + "description": "Explanation configuration for this DeployedModel. When deploying a Model using EndpointService.DeployModel, this value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of explanation_spec is not populated, the value of the same field of Model.explanation_spec is inherited. If the corresponding Model.explanation_spec is not populated, all fields of the explanation_spec will be used for the explanation configuration.", + "$ref": "GoogleCloudAiplatformV1ExplanationSpec" + }, + "disableExplanations": { + "type": "boolean", + "description": "If true, deploy the model without explainable feature, regardless the existence of Model.explanation_spec or explanation_spec." + }, + "enableAccessLogging": { + "type": "boolean", + "description": "If true, online prediction access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each prediction request. Note that logs may incur a cost, especially if your project receives prediction requests at a high queries per second rate (QPS). Estimate your costs before enabling this option." + }, + "modelVersionId": { + "description": "Output only. The version ID of the model that is deployed.", + "type": "string", + "readOnly": true + }, + "disableContainerLogging": { + "description": "For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.", + "type": "boolean" + }, + "model": { + "description": "Required. The resource name of the Model that this is the deployment of. Note that the Model may be in a different location than the DeployedModel's Endpoint. The resource name may contain version id or version alias to specify the version. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` if no version is specified, the default version will be deployed.", + "type": "string" + }, + "id": { + "type": "string", + "description": "Immutable. The ID of the DeployedModel. If not provided upon deployment, Vertex AI will generate a value for this ID. This value should be 1-10 characters, and valid characters are `/[0-9]/`." + }, + "displayName": { + "type": "string", + "description": "The display name of the DeployedModel. If not provided upon creation, the Model's display_name is used." + }, + "automaticResources": { + "description": "A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.", + "$ref": "GoogleCloudAiplatformV1AutomaticResources" + }, + "serviceAccount": { + "description": "The service account that the DeployedModel's container runs as. Specify the email address of the service account. If this service account is not specified, the container runs as a service account that doesn't have access to the resource project. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account.", + "type": "string" + }, + "dedicatedResources": { + "description": "A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.", + "$ref": "GoogleCloudAiplatformV1DedicatedResources" + }, + "privateEndpoints": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1PrivateEndpoints", + "description": "Output only. Provide paths for users to send predict/explain/health requests directly to the deployed model services running on Cloud via private services access. This field is populated if network is configured." + } + }, + "description": "A deployment of a Model. Endpoints contain one or more DeployedModels." + }, + "GoogleCloudAiplatformV1SchemaImageDatasetMetadata": { + "description": "The metadata of Datasets that contain Image DataItems.", + "properties": { + "dataItemSchemaUri": { + "type": "string", + "description": "Points to a YAML file stored on Google Cloud Storage describing payload of the Image DataItems that belong to this Dataset." + }, + "gcsBucket": { + "type": "string", + "description": "Google Cloud Storage Bucket name that contains the blob data of this Dataset." + } + }, + "id": "GoogleCloudAiplatformV1SchemaImageDatasetMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1ListFeatureOnlineStoresResponse": { + "description": "Response message for FeatureOnlineStoreAdminService.ListFeatureOnlineStores.", + "type": "object", + "properties": { + "nextPageToken": { + "description": "A token, which can be sent as ListFeatureOnlineStoresRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + }, + "featureOnlineStores": { + "description": "The FeatureOnlineStores matching the request.", + "items": { + "$ref": "GoogleCloudAiplatformV1FeatureOnlineStore" + }, + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1ListFeatureOnlineStoresResponse" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageSegmentationInputs": { + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageSegmentationInputs", + "properties": { + "baseModelId": { + "type": "string", + "description": "The ID of the `base` model. If it is specified, the new model will be trained based on the `base` model. Otherwise, the new model will be trained from scratch. The `base` model must be in the same Project and Location as the new Model to train, and have the same modelType." + }, + "modelType": { + "enum": [ + "MODEL_TYPE_UNSPECIFIED", + "CLOUD_HIGH_ACCURACY_1", + "CLOUD_LOW_ACCURACY_1", + "MOBILE_TF_LOW_LATENCY_1" + ], + "type": "string", + "enumDescriptions": [ + "Should not be set.", + "A model to be used via prediction calls to uCAIP API. Expected to have a higher latency, but should also have a higher prediction quality than other models.", + "A model to be used via prediction calls to uCAIP API. Expected to have a lower latency but relatively lower prediction quality.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow model and used on a mobile or edge device afterwards. Expected to have low latency, but may have lower prediction quality than other mobile models." + ] + }, + "budgetMilliNodeHours": { + "description": "The training budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The actual metadata.costMilliNodeHours will be equal or less than this value. If further model training ceases to provide any improvements, it will stop without using the full budget and the metadata.successfulStopReason will be `model-converged`. Note, node_hour = actual_hour * number_of_nodes_involved. Or actual_wall_clock_hours = train_budget_milli_node_hours / (number_of_nodes_involved * 1000) For modelType `cloud-high-accuracy-1`(default), the budget must be between 20,000 and 2,000,000 milli node hours, inclusive. The default value is 192,000 which represents one day in wall time (1000 milli * 24 hours * 8 nodes).", + "type": "string", + "format": "int64" + } + } + }, + "GoogleCloudAiplatformV1CheckTrialEarlyStoppingStateMetatdata": { + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "Operation metadata for suggesting Trials." + }, + "trial": { + "description": "The Trial name.", + "type": "string" + }, + "study": { + "type": "string", + "description": "The name of the Study that the Trial belongs to." + } + }, + "type": "object", + "description": "This message will be placed in the metadata field of a google.longrunning.Operation associated with a CheckTrialEarlyStoppingState request.", + "id": "GoogleCloudAiplatformV1CheckTrialEarlyStoppingStateMetatdata" + }, + "GoogleCloudAiplatformV1NasTrial": { + "type": "object", + "description": "Represents a uCAIP NasJob trial.", + "properties": { + "finalMeasurement": { + "$ref": "GoogleCloudAiplatformV1Measurement", + "description": "Output only. The final measurement containing the objective value.", + "readOnly": true + }, + "startTime": { + "format": "google-datetime", + "type": "string", + "readOnly": true, + "description": "Output only. Time when the NasTrial was started." + }, + "id": { + "description": "Output only. The identifier of the NasTrial assigned by the service.", + "type": "string", + "readOnly": true + }, + "endTime": { + "type": "string", + "description": "Output only. Time when the NasTrial's status changed to `SUCCEEDED` or `INFEASIBLE`.", + "format": "google-datetime", + "readOnly": true + }, + "state": { + "enum": [ + "STATE_UNSPECIFIED", + "REQUESTED", + "ACTIVE", + "STOPPING", + "SUCCEEDED", + "INFEASIBLE" + ], + "readOnly": true, + "type": "string", + "description": "Output only. The detailed state of the NasTrial.", + "enumDescriptions": [ + "The NasTrial state is unspecified.", + "Indicates that a specific NasTrial has been requested, but it has not yet been suggested by the service.", + "Indicates that the NasTrial has been suggested.", + "Indicates that the NasTrial should stop according to the service.", + "Indicates that the NasTrial is completed successfully.", + "Indicates that the NasTrial should not be attempted again. The service will set a NasTrial to INFEASIBLE when it's done but missing the final_measurement." + ] + } + }, + "id": "GoogleCloudAiplatformV1NasTrial" + }, + "GoogleCloudAiplatformV1IndexEndpoint": { + "properties": { + "network": { + "description": "Optional. The full name of the Google Compute Engine [network](https://cloud.google.com/compute/docs/networks-and-firewalls#networks) to which the IndexEndpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. network and private_service_connect_config are mutually exclusive. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert): `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in '12345', and {network} is network name.", + "type": "string" + }, + "name": { + "type": "string", + "description": "Output only. The resource name of the IndexEndpoint.", + "readOnly": true + }, + "enablePrivateServiceConnect": { + "type": "boolean", + "deprecated": true, + "description": "Optional. Deprecated: If true, expose the IndexEndpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set." + }, + "labels": { + "description": "The labels with user-defined metadata to organize your IndexEndpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "createTime": { + "description": "Output only. Timestamp when this IndexEndpoint was created.", + "format": "google-datetime", + "type": "string", + "readOnly": true + }, + "displayName": { + "description": "Required. The display name of the IndexEndpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1EncryptionSpec", + "description": "Immutable. Customer-managed encryption key spec for an IndexEndpoint. If set, this IndexEndpoint and all sub-resources of this IndexEndpoint will be secured by this key." + }, + "publicEndpointDomainName": { + "readOnly": true, + "type": "string", + "description": "Output only. If public_endpoint_enabled is true, this field will be populated with the domain name to use for this index endpoint." + }, + "updateTime": { + "type": "string", + "readOnly": true, + "description": "Output only. Timestamp when this IndexEndpoint was last updated. This timestamp is not updated when the endpoint's DeployedIndexes are updated, e.g. due to updates of the original Indexes they are the deployments of.", + "format": "google-datetime" + }, + "privateServiceConnectConfig": { + "description": "Optional. Configuration for private service connect. network and private_service_connect_config are mutually exclusive.", + "$ref": "GoogleCloudAiplatformV1PrivateServiceConnectConfig" + }, + "deployedIndexes": { + "items": { + "$ref": "GoogleCloudAiplatformV1DeployedIndex" + }, + "description": "Output only. The indexes deployed in this endpoint.", + "type": "array", + "readOnly": true + }, + "publicEndpointEnabled": { + "description": "Optional. If true, the deployed index will be accessible through public endpoint.", + "type": "boolean" + }, + "description": { + "type": "string", + "description": "The description of the IndexEndpoint." + }, + "etag": { + "type": "string", + "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + } + }, + "description": "Indexes are deployed into it. An IndexEndpoint can have multiple DeployedIndexes.", + "id": "GoogleCloudAiplatformV1IndexEndpoint", + "type": "object" + }, + "GoogleCloudAiplatformV1PredictRequest": { + "type": "object", + "properties": { + "instances": { + "items": { + "type": "any" + }, + "description": "Required. The instances that are the input to the prediction call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the prediction call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.", + "type": "array" + }, + "parameters": { + "description": "The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri.", + "type": "any" + } + }, + "description": "Request message for PredictionService.Predict.", + "id": "GoogleCloudAiplatformV1PredictRequest" + }, + "GoogleCloudAiplatformV1ListDataItemsResponse": { + "properties": { + "nextPageToken": { + "type": "string", + "description": "The standard List next-page token." + }, + "dataItems": { + "description": "A list of DataItems that matches the specified filter in the request.", + "items": { + "$ref": "GoogleCloudAiplatformV1DataItem" + }, + "type": "array" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1ListDataItemsResponse", + "description": "Response message for DatasetService.ListDataItems." + }, + "GoogleCloudAiplatformV1Featurestore": { + "properties": { + "createTime": { + "readOnly": true, + "type": "string", + "format": "google-datetime", + "description": "Output only. Timestamp when this Featurestore was created." + }, + "name": { + "readOnly": true, + "description": "Output only. Name of the Featurestore. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", + "type": "string" + }, + "updateTime": { + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Timestamp when this Featurestore was last updated.", + "type": "string" + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "Optional. The labels with user-defined metadata to organize your Featurestore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Featurestore(System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." + }, + "onlineServingConfig": { + "description": "Optional. Config for online storage resources. The field should not co-exist with the field of `OnlineStoreReplicationConfig`. If both of it and OnlineStoreReplicationConfig are unset, the feature store will not have an online store and cannot be used for online serving.", + "$ref": "GoogleCloudAiplatformV1FeaturestoreOnlineServingConfig" + }, + "etag": { + "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "state": { + "description": "Output only. State of the featurestore.", + "readOnly": true, + "enumDescriptions": [ + "Default value. This value is unused.", + "State when the featurestore configuration is not being updated and the fields reflect the current configuration of the featurestore. The featurestore is usable in this state.", + "The state of the featurestore configuration when it is being updated. During an update, the fields reflect either the original configuration or the updated configuration of the featurestore. For example, `online_serving_config.fixed_node_count` can take minutes to update. While the update is in progress, the featurestore is in the UPDATING state, and the value of `fixed_node_count` can be the original value or the updated value, depending on the progress of the operation. Until the update completes, the actual number of nodes can still be the original value of `fixed_node_count`. The featurestore is still usable in this state." + ], + "type": "string", + "enum": [ + "STATE_UNSPECIFIED", + "STABLE", + "UPDATING" + ] + }, + "onlineStorageTtlDays": { + "type": "integer", + "description": "Optional. TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than `online_storage_ttl_days` since the feature generation time. Note that `online_storage_ttl_days` should be less than or equal to `offline_storage_ttl_days` for each EntityType under a featurestore. If not set, default to 4000 days", + "format": "int32" + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1EncryptionSpec", + "description": "Optional. Customer-managed encryption key spec for data storage. If set, both of the online and offline data storage will be secured by this key." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1Featurestore", + "description": "Vertex AI Feature Store provides a centralized repository for organizing, storing, and serving ML features. The Featurestore is a top-level container for your features and their values." + }, + "GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpec": { + "properties": { + "values": { + "type": "array", + "items": { + "type": "number", + "format": "double" + }, + "description": "Required. A list of possible values. The list should be in increasing order and at least 1e-10 apart. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values." + }, + "defaultValue": { + "description": "A default value for a `DISCRETE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. It automatically rounds to the nearest feasible discrete point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.", + "type": "number", + "format": "double" + } + }, + "description": "Value specification for a parameter in `DISCRETE` type.", + "type": "object", + "id": "GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpec" + }, + "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessResult": { + "type": "object", + "description": "Spec for question answering helpfulness result.", + "id": "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessResult", + "properties": { + "confidence": { + "description": "Output only. Confidence for question answering helpfulness score.", + "type": "number", + "format": "float", + "readOnly": true + }, + "explanation": { + "type": "string", + "readOnly": true, + "description": "Output only. Explanation for question answering helpfulness score." + }, + "score": { + "description": "Output only. Question Answering Helpfulness score.", + "readOnly": true, + "format": "float", + "type": "number" + } + } + }, + "GoogleCloudAiplatformV1RougeMetricValue": { + "type": "object", + "id": "GoogleCloudAiplatformV1RougeMetricValue", + "description": "Rouge metric value for an instance.", + "properties": { + "score": { + "description": "Output only. Rouge score.", + "readOnly": true, + "format": "float", + "type": "number" + } + } + }, + "GoogleCloudAiplatformV1QuestionAnsweringRelevanceSpec": { + "id": "GoogleCloudAiplatformV1QuestionAnsweringRelevanceSpec", + "properties": { + "version": { + "type": "integer", + "description": "Optional. Which version to use for evaluation.", + "format": "int32" + }, + "useReference": { + "type": "boolean", + "description": "Optional. Whether to use instance.reference to compute question answering relevance." + } + }, + "description": "Spec for question answering relevance metric.", + "type": "object" + }, + "GoogleCloudAiplatformV1DeployIndexResponse": { + "properties": { + "deployedIndex": { + "$ref": "GoogleCloudAiplatformV1DeployedIndex", + "description": "The DeployedIndex that had been deployed in the IndexEndpoint." + } + }, + "type": "object", + "description": "Response message for IndexEndpointService.DeployIndex.", + "id": "GoogleCloudAiplatformV1DeployIndexResponse" + }, + "GoogleCloudAiplatformV1ProbeExecAction": { + "properties": { + "command": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Command is the command line to execute inside the container, the working directory for the command is root ('/') in the container's filesystem. The command is simply exec'd, it is not run inside a shell, so traditional shell instructions ('|', etc) won't work. To use a shell, you need to explicitly call out to that shell. Exit status of 0 is treated as live/healthy and non-zero is unhealthy." + } + }, + "type": "object", + "description": "ExecAction specifies a command to execute.", + "id": "GoogleCloudAiplatformV1ProbeExecAction" + }, + "GoogleCloudAiplatformV1AssignNotebookRuntimeOperationMetadata": { + "type": "object", + "description": "Metadata information for NotebookService.AssignNotebookRuntime.", + "id": "GoogleCloudAiplatformV1AssignNotebookRuntimeOperationMetadata", + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + }, + "progressMessage": { + "type": "string", + "description": "A human-readable message that shows the intermediate progress details of NotebookRuntime." + } + } + }, + "GoogleCloudAiplatformV1ReadFeatureValuesRequest": { + "type": "object", + "properties": { + "entityId": { + "type": "string", + "description": "Required. ID for a specific entity. For example, for a machine learning model predicting user clicks on a website, an entity ID could be `user_123`." + }, + "featureSelector": { + "$ref": "GoogleCloudAiplatformV1FeatureSelector", + "description": "Required. Selector choosing Features of the target EntityType." + } + }, + "description": "Request message for FeaturestoreOnlineServingService.ReadFeatureValues.", + "id": "GoogleCloudAiplatformV1ReadFeatureValuesRequest" + }, + "GoogleCloudAiplatformV1StructFieldValue": { + "properties": { + "value": { + "$ref": "GoogleCloudAiplatformV1FeatureValue", + "description": "The value for this field." + }, + "name": { + "description": "Name of the field in the struct feature.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1StructFieldValue", + "description": "One field of a Struct (or object) type feature value.", + "type": "object" + }, + "GoogleCloudAiplatformV1QuestionAnsweringQualityResult": { + "description": "Spec for question answering quality result.", + "properties": { + "explanation": { + "type": "string", + "readOnly": true, + "description": "Output only. Explanation for question answering quality score." + }, + "score": { + "type": "number", + "description": "Output only. Question Answering Quality score.", + "readOnly": true, + "format": "float" + }, + "confidence": { + "format": "float", + "type": "number", + "readOnly": true, + "description": "Output only. Confidence for question answering quality score." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1QuestionAnsweringQualityResult" + }, + "GoogleCloudAiplatformV1RebootPersistentResourceOperationMetadata": { + "id": "GoogleCloudAiplatformV1RebootPersistentResourceOperationMetadata", + "type": "object", + "properties": { + "genericMetadata": { + "description": "Operation metadata for PersistentResource.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + }, + "progressMessage": { + "description": "Progress Message for Reboot LRO", + "type": "string" + } + }, + "description": "Details of operations that perform reboot PersistentResource." + }, + "GoogleCloudAiplatformV1Int64Array": { + "type": "object", + "properties": { + "values": { + "description": "A list of int64 values.", + "items": { + "type": "string", + "format": "int64" + }, + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1Int64Array", + "description": "A list of int64 values." + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextSentimentInputs": { + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextSentimentInputs", + "properties": { + "sentimentMax": { + "type": "integer", + "description": "A sentiment is expressed as an integer ordinal, where higher value means a more positive sentiment. The range of sentiments that will be used is between 0 and sentimentMax (inclusive on both ends), and all the values in the range must be represented in the dataset before a model can be created. Only the Annotations with this sentimentMax will be used for training. sentimentMax value must be between 1 and 10 (inclusive).", + "format": "int32" + } + } + }, + "GoogleCloudAiplatformV1SmoothGradConfig": { + "type": "object", + "description": "Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf", + "id": "GoogleCloudAiplatformV1SmoothGradConfig", + "properties": { + "noiseSigma": { + "format": "float", + "description": "This is a single float value and will be used to add noise to all the features. Use this field when all features are normalized to have the same distribution: scale to range [0, 1], [-1, 1] or z-scoring, where features are normalized to have 0-mean and 1-variance. Learn more about [normalization](https://developers.google.com/machine-learning/data-prep/transform/normalization). For best results the recommended value is about 10% - 20% of the standard deviation of the input feature. Refer to section 3.2 of the SmoothGrad paper: https://arxiv.org/pdf/1706.03825.pdf. Defaults to 0.1. If the distribution is different per feature, set feature_noise_sigma instead for each feature.", + "type": "number" + }, + "noisySampleCount": { + "type": "integer", + "description": "The number of gradient samples to use for approximation. The higher this number, the more accurate the gradient is, but the runtime complexity increases by this factor as well. Valid range of its value is [1, 50]. Defaults to 3.", + "format": "int32" + }, + "featureNoiseSigma": { + "$ref": "GoogleCloudAiplatformV1FeatureNoiseSigma", + "description": "This is similar to noise_sigma, but provides additional flexibility. A separate noise sigma can be provided for each feature, which is useful if their distributions are different. No noise is added to features that are not set. If this field is unset, noise_sigma will be used for all features." + } + } + }, + "GoogleCloudAiplatformV1CancelTrainingPipelineRequest": { + "type": "object", + "id": "GoogleCloudAiplatformV1CancelTrainingPipelineRequest", + "properties": {}, + "description": "Request message for PipelineService.CancelTrainingPipeline." + }, + "GoogleCloudAiplatformV1UndeployIndexRequest": { + "id": "GoogleCloudAiplatformV1UndeployIndexRequest", + "type": "object", + "description": "Request message for IndexEndpointService.UndeployIndex.", + "properties": { + "deployedIndexId": { + "type": "string", + "description": "Required. The ID of the DeployedIndex to be undeployed from the IndexEndpoint." + } + } + }, + "GoogleCloudAiplatformV1DeleteOperationMetadata": { + "type": "object", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The common part of the operation metadata." + } + }, + "id": "GoogleCloudAiplatformV1DeleteOperationMetadata", + "description": "Details of operations that perform deletes of any entities." + }, + "GoogleCloudAiplatformV1ListModelVersionsResponse": { + "id": "GoogleCloudAiplatformV1ListModelVersionsResponse", + "properties": { + "models": { + "description": "List of Model versions in the requested page. In the returned Model name field, version ID instead of regvision tag will be included.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1Model" + } + }, + "nextPageToken": { + "description": "A token to retrieve the next page of results. Pass to ListModelVersionsRequest.page_token to obtain that page.", + "type": "string" + } + }, + "description": "Response message for ModelService.ListModelVersions", + "type": "object" + }, + "GoogleCloudAiplatformV1ExplanationSpecOverride": { + "type": "object", + "id": "GoogleCloudAiplatformV1ExplanationSpecOverride", + "description": "The ExplanationSpec entries that can be overridden at online explanation time.", + "properties": { + "metadata": { + "$ref": "GoogleCloudAiplatformV1ExplanationMetadataOverride", + "description": "The metadata to be overridden. If not specified, no metadata is overridden." + }, + "examplesOverride": { + "description": "The example-based explanations parameter overrides.", + "$ref": "GoogleCloudAiplatformV1ExamplesOverride" + }, + "parameters": { + "$ref": "GoogleCloudAiplatformV1ExplanationParameters", + "description": "The parameters to be overridden. Note that the attribution method cannot be changed. If not specified, no parameter is overridden." + } + } + }, + "GoogleCloudAiplatformV1ListModelDeploymentMonitoringJobsResponse": { + "type": "object", + "id": "GoogleCloudAiplatformV1ListModelDeploymentMonitoringJobsResponse", + "description": "Response message for JobService.ListModelDeploymentMonitoringJobs.", + "properties": { + "nextPageToken": { + "type": "string", + "description": "The standard List next-page token." + }, + "modelDeploymentMonitoringJobs": { + "description": "A list of ModelDeploymentMonitoringJobs that matches the specified filter in the request.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1ModelDeploymentMonitoringJob" + } + } + } + }, + "GoogleCloudAiplatformV1QuestionAnsweringRelevanceInstance": { + "type": "object", + "properties": { + "reference": { + "description": "Optional. Ground truth used to compare against the prediction.", + "type": "string" + }, + "instruction": { + "type": "string", + "description": "Required. The question asked and other instruction in the inference prompt." + }, + "context": { + "description": "Optional. Text provided as context to answer the question.", + "type": "string" + }, + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + } + }, + "id": "GoogleCloudAiplatformV1QuestionAnsweringRelevanceInstance", + "description": "Spec for question answering relevance instance." + }, + "GoogleCloudAiplatformV1FluencyInput": { + "id": "GoogleCloudAiplatformV1FluencyInput", + "properties": { + "instance": { + "description": "Required. Fluency instance.", + "$ref": "GoogleCloudAiplatformV1FluencyInstance" + }, + "metricSpec": { + "description": "Required. Spec for fluency score metric.", + "$ref": "GoogleCloudAiplatformV1FluencySpec" + } + }, + "type": "object", + "description": "Input for fluency metric." + }, + "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpec": { + "description": "Specification for how the data should be sliced.", + "properties": { + "configs": { + "description": "Mapping configuration for this SliceSpec. The key is the name of the feature. By default, the key will be prefixed by \"instance\" as a dictionary prefix for Vertex Batch Predictions output format.", + "type": "object", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpecSliceConfig" + } + } + }, + "id": "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpec", + "type": "object" + }, + "GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetail": { + "description": "The detailed info for a custom job executor.", + "properties": { + "job": { + "description": "Output only. The name of the CustomJob.", + "type": "string", + "readOnly": true + }, + "failedJobs": { + "type": "array", + "description": "Output only. The names of the previously failed CustomJob. The list includes the all attempts in chronological order.", + "readOnly": true, + "items": { + "type": "string" + } + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetail" + }, + "GoogleCloudAiplatformV1BatchReadFeatureValuesOperationMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1BatchReadFeatureValuesOperationMetadata", + "description": "Details of operations that batch reads Feature values.", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "Operation metadata for Featurestore batch read Features values." + } + } + }, + "GoogleCloudAiplatformV1ModelSourceInfo": { + "type": "object", + "id": "GoogleCloudAiplatformV1ModelSourceInfo", + "properties": { + "copy": { + "type": "boolean", + "description": "If this Model is copy of another Model. If true then source_type pertains to the original." + }, + "sourceType": { + "description": "Type of the model source.", + "type": "string", + "enum": [ + "MODEL_SOURCE_TYPE_UNSPECIFIED", + "AUTOML", + "CUSTOM", + "BQML", + "MODEL_GARDEN", + "GENIE", + "CUSTOM_TEXT_EMBEDDING", + "MARKETPLACE" + ], + "enumDescriptions": [ + "Should not be used.", + "The Model is uploaded by automl training pipeline.", + "The Model is uploaded by user or custom training pipeline.", + "The Model is registered and sync'ed from BigQuery ML.", + "The Model is saved or tuned from Model Garden.", + "The Model is saved or tuned from Genie.", + "The Model is uploaded by text embedding finetuning pipeline.", + "The Model is saved or tuned from Marketplace." + ] + } + }, + "description": "Detail description of the source information of the model." + }, + "GoogleTypeMoney": { + "properties": { + "nanos": { + "description": "Number of nano (10^-9) units of the amount. The value must be between -999,999,999 and +999,999,999 inclusive. If `units` is positive, `nanos` must be positive or zero. If `units` is zero, `nanos` can be positive, zero, or negative. If `units` is negative, `nanos` must be negative or zero. For example $-1.75 is represented as `units`=-1 and `nanos`=-750,000,000.", + "type": "integer", + "format": "int32" + }, + "currencyCode": { + "description": "The three-letter currency code defined in ISO 4217.", + "type": "string" + }, + "units": { + "type": "string", + "description": "The whole units of the amount. For example if `currencyCode` is `\"USD\"`, then 1 unit is one US dollar.", + "format": "int64" + } + }, + "type": "object", + "id": "GoogleTypeMoney", + "description": "Represents an amount of money with its currency type." + }, + "GoogleCloudAiplatformV1ActiveLearningConfig": { + "type": "object", + "properties": { + "trainingConfig": { + "$ref": "GoogleCloudAiplatformV1TrainingConfig", + "description": "CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems." + }, + "sampleConfig": { + "description": "Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.", + "$ref": "GoogleCloudAiplatformV1SampleConfig" + }, + "maxDataItemCount": { + "description": "Max number of human labeled DataItems.", + "format": "int64", + "type": "string" + }, + "maxDataItemPercentage": { + "description": "Max percent of total DataItems for human labeling.", + "format": "int32", + "type": "integer" + } + }, + "id": "GoogleCloudAiplatformV1ActiveLearningConfig", + "description": "Parameters that configure the active learning pipeline. Active learning will label the data incrementally by several iterations. For every iteration, it will select a batch of data based on the sampling strategy." + }, + "GoogleCloudAiplatformV1LineageSubgraph": { + "id": "GoogleCloudAiplatformV1LineageSubgraph", + "description": "A subgraph of the overall lineage graph. Event edges connect Artifact and Execution nodes.", + "type": "object", + "properties": { + "executions": { + "items": { + "$ref": "GoogleCloudAiplatformV1Execution" + }, + "type": "array", + "description": "The Execution nodes in the subgraph." + }, + "artifacts": { + "items": { + "$ref": "GoogleCloudAiplatformV1Artifact" + }, + "description": "The Artifact nodes in the subgraph.", + "type": "array" + }, + "events": { + "items": { + "$ref": "GoogleCloudAiplatformV1Event" + }, + "type": "array", + "description": "The Event edges between Artifacts and Executions in the subgraph." + } + } + }, + "GoogleCloudAiplatformV1ListFeaturestoresResponse": { + "id": "GoogleCloudAiplatformV1ListFeaturestoresResponse", + "description": "Response message for FeaturestoreService.ListFeaturestores.", + "properties": { + "featurestores": { + "type": "array", + "description": "The Featurestores matching the request.", + "items": { + "$ref": "GoogleCloudAiplatformV1Featurestore" + } + }, + "nextPageToken": { + "description": "A token, which can be sent as ListFeaturestoresRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1ReadTensorboardUsageResponsePerUserUsageData": { + "id": "GoogleCloudAiplatformV1ReadTensorboardUsageResponsePerUserUsageData", + "properties": { + "username": { + "description": "User's username", + "type": "string" + }, + "viewCount": { + "description": "Number of times the user has read data within the Tensorboard.", + "format": "int64", + "type": "string" + } + }, + "type": "object", + "description": "Per user usage data." + }, + "GoogleCloudAiplatformV1UndeployModelResponse": { + "description": "Response message for EndpointService.UndeployModel.", + "id": "GoogleCloudAiplatformV1UndeployModelResponse", + "properties": {}, + "type": "object" + }, + "GoogleCloudAiplatformV1Feature": { + "id": "GoogleCloudAiplatformV1Feature", + "type": "object", + "description": "Feature Metadata information. For example, color is a feature that describes an apple.", + "properties": { + "name": { + "description": "Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.", + "type": "string" + }, + "etag": { + "description": "Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "createTime": { + "description": "Output only. Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.", + "readOnly": true, + "format": "google-datetime", + "type": "string" + }, + "updateTime": { + "type": "string", + "description": "Output only. Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.", + "readOnly": true, + "format": "google-datetime" + }, + "pointOfContact": { + "type": "string", + "description": "Entity responsible for maintaining this feature. Can be comma separated list of email addresses or URIs." + }, + "valueType": { + "type": "string", + "description": "Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.", + "enum": [ + "VALUE_TYPE_UNSPECIFIED", + "BOOL", + "BOOL_ARRAY", + "DOUBLE", + "DOUBLE_ARRAY", + "INT64", + "INT64_ARRAY", + "STRING", + "STRING_ARRAY", + "BYTES", + "STRUCT" + ], + "enumDescriptions": [ + "The value type is unspecified.", + "Used for Feature that is a boolean.", + "Used for Feature that is a list of boolean.", + "Used for Feature that is double.", + "Used for Feature that is a list of double.", + "Used for Feature that is INT64.", + "Used for Feature that is a list of INT64.", + "Used for Feature that is string.", + "Used for Feature that is a list of String.", + "Used for Feature that is bytes.", + "Used for Feature that is struct." + ] + }, + "labels": { + "description": "Optional. The labels with user-defined metadata to organize your Features. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", + "additionalProperties": { + "type": "string" + }, + "type": "object" + }, + "monitoringStatsAnomalies": { + "items": { + "$ref": "GoogleCloudAiplatformV1FeatureMonitoringStatsAnomaly" + }, + "readOnly": true, + "description": "Output only. Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.", + "type": "array" + }, + "versionColumnName": { + "description": "Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View column hosting data for this version. If no value is provided, will use feature_id.", + "type": "string" + }, + "disableMonitoring": { + "type": "boolean", + "description": "Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType." + }, + "description": { + "type": "string", + "description": "Description of the Feature." + } + } + }, + "GoogleCloudAiplatformV1PipelineJobRuntimeConfig": { + "properties": { + "inputArtifacts": { + "type": "object", + "description": "The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1PipelineJobRuntimeConfigInputArtifact" + } + }, + "gcsOutputDirectory": { + "description": "Required. A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.", + "type": "string" + }, + "parameterValues": { + "type": "object", + "description": "The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.", + "additionalProperties": { + "type": "any" + } + }, + "parameters": { + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1Value" + }, + "deprecated": true, + "description": "Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.", + "type": "object" + }, + "failurePolicy": { + "enum": [ + "PIPELINE_FAILURE_POLICY_UNSPECIFIED", + "PIPELINE_FAILURE_POLICY_FAIL_SLOW", + "PIPELINE_FAILURE_POLICY_FAIL_FAST" + ], + "type": "string", + "description": "Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.", + "enumDescriptions": [ + "Default value, and follows fail slow behavior.", + "Indicates that the pipeline should continue to run until all possible tasks have been scheduled and completed.", + "Indicates that the pipeline should stop scheduling new tasks after a task has failed." + ] + } + }, + "id": "GoogleCloudAiplatformV1PipelineJobRuntimeConfig", + "description": "The runtime config of a PipelineJob.", + "type": "object" + }, + "GoogleCloudAiplatformV1ModelExportFormat": { + "properties": { + "exportableContents": { + "type": "array", + "readOnly": true, + "description": "Output only. The content of this Model that may be exported.", + "items": { + "enum": [ + "EXPORTABLE_CONTENT_UNSPECIFIED", + "ARTIFACT", + "IMAGE" + ], + "type": "string", + "enumDescriptions": [ + "Should not be used.", + "Model artifact and any of its supported files. Will be exported to the location specified by the `artifactDestination` field of the ExportModelRequest.output_config object.", + "The container image that is to be used when deploying this Model. Will be exported to the location specified by the `imageDestination` field of the ExportModelRequest.output_config object." + ] + } + }, + "id": { + "readOnly": true, + "description": "Output only. The ID of the export format. The possible format IDs are: * `tflite` Used for Android mobile devices. * `edgetpu-tflite` Used for [Edge TPU](https://cloud.google.com/edge-tpu/) devices. * `tf-saved-model` A tensorflow model in SavedModel format. * `tf-js` A [TensorFlow.js](https://www.tensorflow.org/js) model that can be used in the browser and in Node.js using JavaScript. * `core-ml` Used for iOS mobile devices. * `custom-trained` A Model that was uploaded or trained by custom code.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1ModelExportFormat", + "type": "object", + "description": "Represents export format supported by the Model. All formats export to Google Cloud Storage." + }, + "GoogleCloudAiplatformV1StudySpec": { + "type": "object", + "properties": { + "convexAutomatedStoppingSpec": { + "$ref": "GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpec", + "description": "The automated early stopping spec using convex stopping rule." + }, + "measurementSelectionType": { + "enumDescriptions": [ + "Will be treated as LAST_MEASUREMENT.", + "Use the last measurement reported.", + "Use the best measurement reported." + ], + "enum": [ + "MEASUREMENT_SELECTION_TYPE_UNSPECIFIED", + "LAST_MEASUREMENT", + "BEST_MEASUREMENT" + ], + "description": "Describe which measurement selection type will be used", + "type": "string" + }, + "metrics": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1StudySpecMetricSpec" + }, + "description": "Required. Metric specs for the Study." + }, + "parameters": { + "description": "Required. The set of parameters to tune.", + "items": { + "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpec" + }, + "type": "array" + }, + "decayCurveStoppingSpec": { + "description": "The automated early stopping spec using decay curve rule.", + "$ref": "GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpec" + }, + "medianAutomatedStoppingSpec": { + "$ref": "GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpec", + "description": "The automated early stopping spec using median rule." + }, + "studyStoppingConfig": { + "$ref": "GoogleCloudAiplatformV1StudySpecStudyStoppingConfig", + "description": "Conditions for automated stopping of a Study. Enable automated stopping by configuring at least one condition." + }, + "algorithm": { + "enum": [ + "ALGORITHM_UNSPECIFIED", + "GRID_SEARCH", + "RANDOM_SEARCH" + ], + "description": "The search algorithm specified for the Study.", + "enumDescriptions": [ + "The default algorithm used by Vertex AI for [hyperparameter tuning](https://cloud.google.com/vertex-ai/docs/training/hyperparameter-tuning-overview) and [Vertex AI Vizier](https://cloud.google.com/vertex-ai/docs/vizier).", + "Simple grid search within the feasible space. To use grid search, all parameters must be `INTEGER`, `CATEGORICAL`, or `DISCRETE`.", + "Simple random search within the feasible space." + ], + "type": "string" + }, + "observationNoise": { + "description": "The observation noise level of the study. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.", + "enumDescriptions": [ + "The default noise level chosen by Vertex AI.", + "Vertex AI assumes that the objective function is (nearly) perfectly reproducible, and will never repeat the same Trial parameters.", + "Vertex AI will estimate the amount of noise in metric evaluations, it may repeat the same Trial parameters more than once." + ], + "type": "string", + "enum": [ + "OBSERVATION_NOISE_UNSPECIFIED", + "LOW", + "HIGH" + ] + } + }, + "description": "Represents specification of a Study.", + "id": "GoogleCloudAiplatformV1StudySpec" + }, + "GoogleCloudAiplatformV1UpdateSpecialistPoolOperationMetadata": { + "type": "object", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The operation generic information." + }, + "specialistPool": { + "type": "string", + "description": "Output only. The name of the SpecialistPool to which the specialists are being added. Format: `projects/{project_id}/locations/{location_id}/specialistPools/{specialist_pool}`", + "readOnly": true + } + }, + "description": "Runtime operation metadata for SpecialistPoolService.UpdateSpecialistPool.", + "id": "GoogleCloudAiplatformV1UpdateSpecialistPoolOperationMetadata" + }, + "GoogleCloudAiplatformV1PairwiseSummarizationQualityInstance": { + "description": "Spec for pairwise summarization quality instance.", + "id": "GoogleCloudAiplatformV1PairwiseSummarizationQualityInstance", + "properties": { + "reference": { + "type": "string", + "description": "Optional. Ground truth used to compare against the prediction." + }, + "context": { + "description": "Required. Text to be summarized.", + "type": "string" + }, + "instruction": { + "type": "string", + "description": "Required. Summarization prompt for LLM." + }, + "prediction": { + "type": "string", + "description": "Required. Output of the candidate model." + }, + "baselinePrediction": { + "description": "Required. Output of the baseline model.", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaPredictParamsGroundingConfigSourceEntry": { + "description": "Single source entry for the grounding checking.", + "type": "object", + "properties": { + "type": { + "type": "string", + "enumDeprecated": [ + false, + false, + true, + false, + false + ], + "enum": [ + "UNSPECIFIED", + "WEB", + "ENTERPRISE", + "VERTEX_AI_SEARCH", + "INLINE" + ], + "enumDescriptions": [ + "", + "Uses Web Search to check the grounding.", + "Uses Vertex AI Search to check the grounding. Deprecated. Use VERTEX_AI_SEARCH instead.", + "Uses Vertex AI Search to check the grounding", + "Uses inline context to check the grounding." + ], + "description": "The type of the grounding checking source." + }, + "inlineContext": { + "type": "string", + "description": "The grounding text passed inline with the Predict API. It can support up to 1 million bytes." + }, + "vertexAiSearchDatastore": { + "description": "The uri of the Vertex AI Search data source.", + "type": "string" + }, + "enterpriseDatastore": { + "description": "The uri of the Vertex AI Search data source. Deprecated. Use vertex_ai_search_datastore instead.", + "deprecated": true, + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SchemaPredictParamsGroundingConfigSourceEntry" + }, + "GoogleCloudAiplatformV1EncryptionSpec": { + "properties": { + "kmsKeyName": { + "description": "Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.", + "type": "string" + } + }, + "description": "Represents a customer-managed encryption key spec that can be applied to a top-level resource.", + "id": "GoogleCloudAiplatformV1EncryptionSpec", + "type": "object" + }, + "GoogleCloudAiplatformV1ModelEvaluationSliceSlice": { + "id": "GoogleCloudAiplatformV1ModelEvaluationSliceSlice", + "properties": { + "dimension": { + "description": "Output only. The dimension of the slice. Well-known dimensions are: * `annotationSpec`: This slice is on the test data that has either ground truth or prediction with AnnotationSpec.display_name equals to value. * `slice`: This slice is a user customized slice defined by its SliceSpec.", + "readOnly": true, + "type": "string" + }, + "sliceSpec": { + "description": "Output only. Specification for how the data was sliced.", + "$ref": "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpec", + "readOnly": true + }, + "value": { + "readOnly": true, + "type": "string", + "description": "Output only. The value of the dimension in this slice." + } + }, + "type": "object", + "description": "Definition of a slice." + }, + "GoogleCloudAiplatformV1SchemaPredictInstanceTextClassificationPredictionInstance": { + "id": "GoogleCloudAiplatformV1SchemaPredictInstanceTextClassificationPredictionInstance", + "type": "object", + "description": "Prediction input format for Text Classification.", + "properties": { + "content": { + "type": "string", + "description": "The text snippet to make the predictions on." + }, + "mimeType": { + "description": "The MIME type of the text snippet. The supported MIME types are listed below. - text/plain", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1SchemaVertex": { + "id": "GoogleCloudAiplatformV1SchemaVertex", + "description": "A vertex represents a 2D point in the image. NOTE: the normalized vertex coordinates are relative to the original image and range from 0 to 1.", + "type": "object", + "properties": { + "x": { + "type": "number", + "description": "X coordinate.", + "format": "double" + }, + "y": { + "description": "Y coordinate.", + "type": "number", + "format": "double" + } + } + }, + "GoogleCloudAiplatformV1SuggestTrialsRequest": { + "description": "Request message for VizierService.SuggestTrials.", + "id": "GoogleCloudAiplatformV1SuggestTrialsRequest", + "type": "object", + "properties": { + "suggestionCount": { + "description": "Required. The number of suggestions requested. It must be positive.", + "format": "int32", + "type": "integer" + }, + "contexts": { + "description": "Optional. This allows you to specify the \"context\" for a Trial; a context is a slice (a subspace) of the search space. Typical uses for contexts: 1) You are using Vizier to tune a server for best performance, but there's a strong weekly cycle. The context specifies the day-of-week. This allows Tuesday to generalize from Wednesday without assuming that everything is identical. 2) Imagine you're optimizing some medical treatment for people. As they walk in the door, you know certain facts about them (e.g. sex, weight, height, blood-pressure). Put that information in the context, and Vizier will adapt its suggestions to the patient. 3) You want to do a fair A/B test efficiently. Specify the \"A\" and \"B\" conditions as contexts, and Vizier will generalize between \"A\" and \"B\" conditions. If they are similar, this will allow Vizier to converge to the optimum faster than if \"A\" and \"B\" were separate Studies. NOTE: You can also enter contexts as REQUESTED Trials, e.g. via the CreateTrial() RPC; that's the asynchronous option where you don't need a close association between contexts and suggestions. NOTE: All the Parameters you set in a context MUST be defined in the Study. NOTE: You must supply 0 or $suggestion_count contexts. If you don't supply any contexts, Vizier will make suggestions from the full search space specified in the StudySpec; if you supply a full set of context, each suggestion will match the corresponding context. NOTE: A Context with no features set matches anything, and allows suggestions from the full search space. NOTE: Contexts MUST lie within the search space specified in the StudySpec. It's an error if they don't. NOTE: Contexts preferentially match ACTIVE then REQUESTED trials before new suggestions are generated. NOTE: Generation of suggestions involves a match between a Context and (optionally) a REQUESTED trial; if that match is not fully specified, a suggestion will be geneated in the merged subspace.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1TrialContext" + } + }, + "clientId": { + "type": "string", + "description": "Required. The identifier of the client that is requesting the suggestion. If multiple SuggestTrialsRequests have the same `client_id`, the service will return the identical suggested Trial if the Trial is pending, and provide a new Trial if the last suggested Trial was completed." + } + } + }, + "GoogleCloudAiplatformV1FeatureMonitoringStatsAnomaly": { + "type": "object", + "id": "GoogleCloudAiplatformV1FeatureMonitoringStatsAnomaly", + "description": "A list of historical SnapshotAnalysis or ImportFeaturesAnalysis stats requested by user, sorted by FeatureStatsAnomaly.start_time descending.", + "properties": { + "featureStatsAnomaly": { + "$ref": "GoogleCloudAiplatformV1FeatureStatsAnomaly", + "readOnly": true, + "description": "Output only. The stats and anomalies generated at specific timestamp." + }, + "objective": { + "type": "string", + "readOnly": true, + "enum": [ + "OBJECTIVE_UNSPECIFIED", + "IMPORT_FEATURE_ANALYSIS", + "SNAPSHOT_ANALYSIS" + ], + "enumDescriptions": [ + "If it's OBJECTIVE_UNSPECIFIED, monitoring_stats will be empty.", + "Stats are generated by Import Feature Analysis.", + "Stats are generated by Snapshot Analysis." + ], + "description": "Output only. The objective for each stats." + } + } + }, + "GoogleCloudAiplatformV1BatchPredictionJob": { + "description": "A job that uses a Model to produce predictions on multiple input instances. If predictions for significant portion of the instances fail, the job may finish without attempting predictions for all remaining instances.", + "properties": { + "updateTime": { + "readOnly": true, + "type": "string", + "format": "google-datetime", + "description": "Output only. Time when the BatchPredictionJob was most recently updated." + }, + "displayName": { + "type": "string", + "description": "Required. The user-defined name of this BatchPredictionJob." + }, + "modelParameters": { + "description": "The parameters that govern the predictions. The schema of the parameters may be specified via the Model's PredictSchemata's parameters_schema_uri.", + "type": "any" + }, + "inputConfig": { + "$ref": "GoogleCloudAiplatformV1BatchPredictionJobInputConfig", + "description": "Required. Input configuration of the instances on which predictions are performed. The schema of any single instance may be specified via the Model's PredictSchemata's instance_schema_uri." + }, + "createTime": { + "description": "Output only. Time when the BatchPredictionJob was created.", + "format": "google-datetime", + "type": "string", + "readOnly": true + }, + "instanceConfig": { + "$ref": "GoogleCloudAiplatformV1BatchPredictionJobInstanceConfig", + "description": "Configuration for how to convert batch prediction input instances to the prediction instances that are sent to the Model." + }, + "dedicatedResources": { + "$ref": "GoogleCloudAiplatformV1BatchDedicatedResources", + "description": "The config of resources used by the Model during the batch prediction. If the Model supports DEDICATED_RESOURCES this config may be provided (and the job will use these resources), if the Model doesn't support AUTOMATIC_RESOURCES, this config must be provided." + }, + "modelVersionId": { + "readOnly": true, + "description": "Output only. The version ID of the Model that produces the predictions via this job.", + "type": "string" + }, + "unmanagedContainerModel": { + "description": "Contains model information necessary to perform batch prediction without requiring uploading to model registry. Exactly one of model and unmanaged_container_model must be set.", + "$ref": "GoogleCloudAiplatformV1UnmanagedContainerModel" + }, + "resourcesConsumed": { + "description": "Output only. Information about resources that had been consumed by this job. Provided in real time at best effort basis, as well as a final value once the job completes. Note: This field currently may be not populated for batch predictions that use AutoML Models.", + "$ref": "GoogleCloudAiplatformV1ResourcesConsumed", + "readOnly": true + }, + "labels": { + "type": "object", + "additionalProperties": { + "type": "string" + }, + "description": "The labels with user-defined metadata to organize BatchPredictionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels." + }, + "manualBatchTuningParameters": { + "$ref": "GoogleCloudAiplatformV1ManualBatchTuningParameters", + "description": "Immutable. Parameters configuring the batch behavior. Currently only applicable when dedicated_resources are used (in other cases Vertex AI does the tuning itself)." + }, + "explanationSpec": { + "description": "Explanation configuration for this BatchPredictionJob. Can be specified only if generate_explanation is set to `true`. This value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of the explanation_spec object is not populated, the corresponding field of the Model.explanation_spec object is inherited.", + "$ref": "GoogleCloudAiplatformV1ExplanationSpec" + }, + "error": { + "readOnly": true, + "$ref": "GoogleRpcStatus", + "description": "Output only. Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED." + }, + "disableContainerLogging": { + "description": "For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.", + "type": "boolean" + }, + "state": { + "enum": [ + "JOB_STATE_UNSPECIFIED", + "JOB_STATE_QUEUED", + "JOB_STATE_PENDING", + "JOB_STATE_RUNNING", + "JOB_STATE_SUCCEEDED", + "JOB_STATE_FAILED", + "JOB_STATE_CANCELLING", + "JOB_STATE_CANCELLED", + "JOB_STATE_PAUSED", + "JOB_STATE_EXPIRED", + "JOB_STATE_UPDATING", + "JOB_STATE_PARTIALLY_SUCCEEDED" + ], + "description": "Output only. The detailed state of the job.", + "enumDescriptions": [ + "The job state is unspecified.", + "The job has been just created or resumed and processing has not yet begun.", + "The service is preparing to run the job.", + "The job is in progress.", + "The job completed successfully.", + "The job failed.", + "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "The job has been cancelled.", + "The job has been stopped, and can be resumed.", + "The job has expired.", + "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", + "The job is partially succeeded, some results may be missing due to errors." + ], + "readOnly": true, + "type": "string" + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1EncryptionSpec", + "description": "Customer-managed encryption key options for a BatchPredictionJob. If this is set, then all resources created by the BatchPredictionJob will be encrypted with the provided encryption key." + }, + "serviceAccount": { + "description": "The service account that the DeployedModel's container runs as. If not specified, a system generated one will be used, which has minimal permissions and the custom container, if used, may not have enough permission to access other Google Cloud resources. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account.", + "type": "string" + }, + "generateExplanation": { + "description": "Generate explanation with the batch prediction results. When set to `true`, the batch prediction output changes based on the `predictions_format` field of the BatchPredictionJob.output_config object: * `bigquery`: output includes a column named `explanation`. The value is a struct that conforms to the Explanation object. * `jsonl`: The JSON objects on each line include an additional entry keyed `explanation`. The value of the entry is a JSON object that conforms to the Explanation object. * `csv`: Generating explanations for CSV format is not supported. If this field is set to true, either the Model.explanation_spec or explanation_spec must be populated.", + "type": "boolean" + }, + "outputConfig": { + "description": "Required. The Configuration specifying where output predictions should be written. The schema of any single prediction may be specified as a concatenation of Model's PredictSchemata's instance_schema_uri and prediction_schema_uri.", + "$ref": "GoogleCloudAiplatformV1BatchPredictionJobOutputConfig" + }, + "name": { + "type": "string", + "readOnly": true, + "description": "Output only. Resource name of the BatchPredictionJob." + }, + "partialFailures": { + "items": { + "$ref": "GoogleRpcStatus" + }, + "description": "Output only. Partial failures encountered. For example, single files that can't be read. This field never exceeds 20 entries. Status details fields contain standard Google Cloud error details.", + "readOnly": true, + "type": "array" + }, + "endTime": { + "description": "Output only. Time when the BatchPredictionJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.", + "readOnly": true, + "format": "google-datetime", + "type": "string" + }, + "completionStats": { + "description": "Output only. Statistics on completed and failed prediction instances.", + "$ref": "GoogleCloudAiplatformV1CompletionStats", + "readOnly": true + }, + "outputInfo": { + "$ref": "GoogleCloudAiplatformV1BatchPredictionJobOutputInfo", + "description": "Output only. Information further describing the output of this job.", + "readOnly": true + }, + "model": { + "type": "string", + "description": "The name of the Model resource that produces the predictions via this job, must share the same ancestor Location. Starting this job has no impact on any existing deployments of the Model and their resources. Exactly one of model and unmanaged_container_model must be set. The model resource name may contain version id or version alias to specify the version. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` if no version is specified, the default version will be deployed. The model resource could also be a publisher model. Example: `publishers/{publisher}/models/{model}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`" + }, + "startTime": { + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Time when the BatchPredictionJob for the first time entered the `JOB_STATE_RUNNING` state.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1BatchPredictionJob" + }, + "GoogleCloudAiplatformV1HyperparameterTuningJob": { + "properties": { + "createTime": { + "description": "Output only. Time when the HyperparameterTuningJob was created.", + "readOnly": true, + "format": "google-datetime", + "type": "string" + }, + "maxTrialCount": { + "description": "Required. The desired total number of Trials.", + "type": "integer", + "format": "int32" + }, + "endTime": { + "description": "Output only. Time when the HyperparameterTuningJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.", + "format": "google-datetime", + "readOnly": true, + "type": "string" + }, + "trialJobSpec": { + "$ref": "GoogleCloudAiplatformV1CustomJobSpec", + "description": "Required. The spec of a trial job. The same spec applies to the CustomJobs created in all the trials." + }, + "studySpec": { + "description": "Required. Study configuration of the HyperparameterTuningJob.", + "$ref": "GoogleCloudAiplatformV1StudySpec" + }, + "error": { + "readOnly": true, + "description": "Output only. Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.", + "$ref": "GoogleRpcStatus" + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1EncryptionSpec", + "description": "Customer-managed encryption key options for a HyperparameterTuningJob. If this is set, then all resources created by the HyperparameterTuningJob will be encrypted with the provided encryption key." + }, + "maxFailedTrialCount": { + "type": "integer", + "format": "int32", + "description": "The number of failed Trials that need to be seen before failing the HyperparameterTuningJob. If set to 0, Vertex AI decides how many Trials must fail before the whole job fails." + }, + "updateTime": { + "format": "google-datetime", + "type": "string", + "description": "Output only. Time when the HyperparameterTuningJob was most recently updated.", + "readOnly": true + }, + "trials": { + "readOnly": true, + "description": "Output only. Trials of the HyperparameterTuningJob.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1Trial" + } + }, + "state": { + "enumDescriptions": [ + "The job state is unspecified.", + "The job has been just created or resumed and processing has not yet begun.", + "The service is preparing to run the job.", + "The job is in progress.", + "The job completed successfully.", + "The job failed.", + "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "The job has been cancelled.", + "The job has been stopped, and can be resumed.", + "The job has expired.", + "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", + "The job is partially succeeded, some results may be missing due to errors." + ], + "enum": [ + "JOB_STATE_UNSPECIFIED", + "JOB_STATE_QUEUED", + "JOB_STATE_PENDING", + "JOB_STATE_RUNNING", + "JOB_STATE_SUCCEEDED", + "JOB_STATE_FAILED", + "JOB_STATE_CANCELLING", + "JOB_STATE_CANCELLED", + "JOB_STATE_PAUSED", + "JOB_STATE_EXPIRED", + "JOB_STATE_UPDATING", + "JOB_STATE_PARTIALLY_SUCCEEDED" + ], + "description": "Output only. The detailed state of the job.", + "type": "string", + "readOnly": true + }, + "labels": { + "type": "object", + "description": "The labels with user-defined metadata to organize HyperparameterTuningJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", + "additionalProperties": { + "type": "string" + } + }, + "parallelTrialCount": { + "type": "integer", + "format": "int32", + "description": "Required. The desired number of Trials to run in parallel." + }, + "name": { + "description": "Output only. Resource name of the HyperparameterTuningJob.", + "type": "string", + "readOnly": true + }, + "startTime": { + "type": "string", + "description": "Output only. Time when the HyperparameterTuningJob for the first time entered the `JOB_STATE_RUNNING` state.", + "readOnly": true, + "format": "google-datetime" + }, + "displayName": { + "type": "string", + "description": "Required. The display name of the HyperparameterTuningJob. The name can be up to 128 characters long and can consist of any UTF-8 characters." + } + }, + "description": "Represents a HyperparameterTuningJob. A HyperparameterTuningJob has a Study specification and multiple CustomJobs with identical CustomJob specification.", + "type": "object", + "id": "GoogleCloudAiplatformV1HyperparameterTuningJob" + }, + "GoogleCloudAiplatformV1BatchCreateTensorboardTimeSeriesRequest": { + "properties": { + "requests": { + "items": { + "$ref": "GoogleCloudAiplatformV1CreateTensorboardTimeSeriesRequest" + }, + "type": "array", + "description": "Required. The request message specifying the TensorboardTimeSeries to create. A maximum of 1000 TensorboardTimeSeries can be created in a batch." + } + }, + "id": "GoogleCloudAiplatformV1BatchCreateTensorboardTimeSeriesRequest", + "description": "Request message for TensorboardService.BatchCreateTensorboardTimeSeries.", + "type": "object" + }, + "GoogleCloudAiplatformV1ExactMatchInput": { + "properties": { + "instances": { + "items": { + "$ref": "GoogleCloudAiplatformV1ExactMatchInstance" + }, + "description": "Required. Repeated exact match instances.", + "type": "array" + }, + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1ExactMatchSpec", + "description": "Required. Spec for exact match metric." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1ExactMatchInput", + "description": "Input for exact match metric." + }, + "GoogleCloudAiplatformV1ResourcesConsumed": { + "description": "Statistics information about resource consumption.", + "type": "object", + "id": "GoogleCloudAiplatformV1ResourcesConsumed", + "properties": { + "replicaHours": { + "readOnly": true, + "description": "Output only. The number of replica hours used. Note that many replicas may run in parallel, and additionally any given work may be queued for some time. Therefore this value is not strictly related to wall time.", + "format": "double", + "type": "number" + } + } + }, + "GoogleCloudAiplatformV1SearchEntryPoint": { + "properties": { + "renderedContent": { + "description": "Optional. Web content snippet that can be embedded in a web page or an app webview.", + "type": "string" + }, + "sdkBlob": { + "type": "string", + "format": "byte", + "description": "Optional. Base64 encoded JSON representing array of tuple." + } + }, + "type": "object", + "description": "Google search entry point.", + "id": "GoogleCloudAiplatformV1SearchEntryPoint" + }, + "GoogleCloudAiplatformV1Segment": { + "type": "object", + "description": "Segment of the content.", + "id": "GoogleCloudAiplatformV1Segment", + "properties": { + "text": { + "type": "string", + "description": "Output only. The text corresponding to the segment from the response.", + "readOnly": true + }, + "endIndex": { + "format": "int32", + "type": "integer", + "readOnly": true, + "description": "Output only. End index in the given Part, measured in bytes. Offset from the start of the Part, exclusive, starting at zero." + }, + "partIndex": { + "type": "integer", + "description": "Output only. The index of a Part object within its parent Content object.", + "format": "int32", + "readOnly": true + }, + "startIndex": { + "readOnly": true, + "description": "Output only. Start index in the given Part, measured in bytes. Offset from the start of the Part, inclusive, starting at zero.", + "format": "int32", + "type": "integer" + } + } + }, + "GoogleCloudAiplatformV1StartNotebookRuntimeRequest": { + "description": "Request message for NotebookService.StartNotebookRuntime.", + "id": "GoogleCloudAiplatformV1StartNotebookRuntimeRequest", + "type": "object", + "properties": {} + }, + "GoogleCloudAiplatformV1CancelCustomJobRequest": { + "type": "object", + "description": "Request message for JobService.CancelCustomJob.", + "properties": {}, + "id": "GoogleCloudAiplatformV1CancelCustomJobRequest" + }, + "GoogleCloudAiplatformV1RebootPersistentResourceRequest": { + "properties": {}, + "description": "Request message for PersistentResourceService.RebootPersistentResource.", + "id": "GoogleCloudAiplatformV1RebootPersistentResourceRequest", + "type": "object" + }, + "GoogleCloudAiplatformV1PublisherModelCallToActionViewRestApi": { + "properties": { + "documentations": { + "description": "Required.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1PublisherModelDocumentation" + } + }, + "title": { + "type": "string", + "description": "Required. The title of the view rest API." + } + }, + "description": "Rest API docs.", + "id": "GoogleCloudAiplatformV1PublisherModelCallToActionViewRestApi", + "type": "object" + }, + "GoogleLongrunningOperation": { + "type": "object", + "properties": { + "done": { + "type": "boolean", + "description": "If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available." + }, + "response": { + "additionalProperties": { + "description": "Properties of the object. Contains field @type with type URL.", + "type": "any" + }, + "description": "The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.", + "type": "object" + }, + "name": { + "description": "The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.", + "type": "string" + }, + "error": { + "description": "The error result of the operation in case of failure or cancellation.", + "$ref": "GoogleRpcStatus" + }, + "metadata": { + "type": "object", + "additionalProperties": { + "description": "Properties of the object. Contains field @type with type URL.", + "type": "any" + }, + "description": "Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any." + } + }, + "id": "GoogleLongrunningOperation", + "description": "This resource represents a long-running operation that is the result of a network API call." + }, + "GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpec": { + "type": "object", + "properties": { + "useElapsedDuration": { + "description": "True if Measurement.elapsed_duration is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.step_count will be used as the x-axis.", + "type": "boolean" + } + }, + "description": "The decay curve automated stopping rule builds a Gaussian Process Regressor to predict the final objective value of a Trial based on the already completed Trials and the intermediate measurements of the current Trial. Early stopping is requested for the current Trial if there is very low probability to exceed the optimal value found so far.", + "id": "GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpec" + }, + "CloudAiLargeModelsVisionGenerateVideoResponse": { + "type": "object", + "description": "Generate video response.", + "properties": { + "raiMediaFilteredReasons": { + "type": "array", + "description": "Returns rai failure reasons if any.", + "items": { + "type": "string" + } + }, + "raiMediaFilteredCount": { + "type": "integer", + "format": "int32", + "description": "Returns if any videos were filtered due to RAI policies." + }, + "generatedSamples": { + "description": "The generates samples.", + "type": "array", + "items": { + "$ref": "CloudAiLargeModelsVisionMedia" + } + } + }, + "id": "CloudAiLargeModelsVisionGenerateVideoResponse" + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsImageSegmentationEvaluationMetrics": { + "type": "object", + "properties": { + "confidenceMetricsEntries": { + "description": "Metrics for each confidenceThreshold in 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 Precision-recall curve can be derived from it.", + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsImageSegmentationEvaluationMetricsConfidenceMetricsEntry" + }, + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsImageSegmentationEvaluationMetrics", + "description": "Metrics for image segmentation evaluation results." + }, + "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualityResult": { + "properties": { + "pairwiseChoice": { + "enumDescriptions": [ + "Unspecified prediction choice.", + "Baseline prediction wins", + "Candidate prediction wins", + "Winner cannot be determined" + ], + "type": "string", + "readOnly": true, + "enum": [ + "PAIRWISE_CHOICE_UNSPECIFIED", + "BASELINE", + "CANDIDATE", + "TIE" + ], + "description": "Output only. Pairwise question answering prediction choice." + }, + "explanation": { + "description": "Output only. Explanation for question answering quality score.", + "readOnly": true, + "type": "string" + }, + "confidence": { + "type": "number", + "format": "float", + "readOnly": true, + "description": "Output only. Confidence for question answering quality score." + } + }, + "description": "Spec for pairwise question answering quality result.", + "id": "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualityResult", + "type": "object" + }, + "GoogleCloudAiplatformV1DeployModelRequest": { + "type": "object", + "id": "GoogleCloudAiplatformV1DeployModelRequest", + "description": "Request message for EndpointService.DeployModel.", + "properties": { + "trafficSplit": { + "description": "A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If this field is non-empty, then the Endpoint's traffic_split will be overwritten with it. To refer to the ID of the just being deployed Model, a \"0\" should be used, and the actual ID of the new DeployedModel will be filled in its place by this method. The traffic percentage values must add up to 100. If this field is empty, then the Endpoint's traffic_split is not updated.", + "type": "object", + "additionalProperties": { + "type": "integer", + "format": "int32" + } + }, + "deployedModel": { + "description": "Required. The DeployedModel to be created within the Endpoint. Note that Endpoint.traffic_split must be updated for the DeployedModel to start receiving traffic, either as part of this call, or via EndpointService.UpdateEndpoint.", + "$ref": "GoogleCloudAiplatformV1DeployedModel" + } + } + }, + "GoogleCloudAiplatformV1MutateDeployedIndexResponse": { + "type": "object", + "id": "GoogleCloudAiplatformV1MutateDeployedIndexResponse", + "properties": { + "deployedIndex": { + "description": "The DeployedIndex that had been updated in the IndexEndpoint.", + "$ref": "GoogleCloudAiplatformV1DeployedIndex" + } + }, + "description": "Response message for IndexEndpointService.MutateDeployedIndex." + }, + "GoogleCloudAiplatformV1DeployModelResponse": { + "description": "Response message for EndpointService.DeployModel.", + "type": "object", + "properties": { + "deployedModel": { + "description": "The DeployedModel that had been deployed in the Endpoint.", + "$ref": "GoogleCloudAiplatformV1DeployedModel" + } + }, + "id": "GoogleCloudAiplatformV1DeployModelResponse" + }, + "GoogleCloudAiplatformV1ModelDeploymentMonitoringJob": { + "type": "object", + "properties": { + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1EncryptionSpec", + "description": "Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key." + }, + "createTime": { + "description": "Output only. Timestamp when this ModelDeploymentMonitoringJob was created.", + "type": "string", + "readOnly": true, + "format": "google-datetime" + }, + "latestMonitoringPipelineMetadata": { + "description": "Output only. Latest triggered monitoring pipeline metadata.", + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata" + }, + "modelDeploymentMonitoringScheduleConfig": { + "description": "Required. Schedule config for running the monitoring job.", + "$ref": "GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfig" + }, + "displayName": { + "type": "string", + "description": "Required. The user-defined name of the ModelDeploymentMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob." + }, + "samplePredictInstance": { + "type": "any", + "description": "Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests." + }, + "modelMonitoringAlertConfig": { + "description": "Alert config for model monitoring.", + "$ref": "GoogleCloudAiplatformV1ModelMonitoringAlertConfig" + }, + "logTtl": { + "description": "The TTL of BigQuery tables in user projects which stores logs. A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day.", + "format": "google-duration", + "type": "string" + }, + "nextScheduleTime": { + "type": "string", + "description": "Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.", + "format": "google-datetime", + "readOnly": true + }, + "error": { + "$ref": "GoogleRpcStatus", + "description": "Output only. Only populated when the job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "readOnly": true + }, + "analysisInstanceSchemaUri": { + "type": "string", + "description": "YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze. If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string." + }, + "labels": { + "type": "object", + "additionalProperties": { + "type": "string" + }, + "description": "The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels." + }, + "enableMonitoringPipelineLogs": { + "description": "If true, the scheduled monitoring pipeline logs are sent to Google Cloud Logging, including pipeline status and anomalies detected. Please note the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging#pricing).", + "type": "boolean" + }, + "statsAnomaliesBaseDirectory": { + "$ref": "GoogleCloudAiplatformV1GcsDestination", + "description": "Stats anomalies base folder path." + }, + "scheduleState": { + "description": "Output only. Schedule state when the monitoring job is in Running state.", + "enumDescriptions": [ + "Unspecified state.", + "The pipeline is picked up and wait to run.", + "The pipeline is offline and will be scheduled for next run.", + "The pipeline is running." + ], + "readOnly": true, + "type": "string", + "enum": [ + "MONITORING_SCHEDULE_STATE_UNSPECIFIED", + "PENDING", + "OFFLINE", + "RUNNING" + ] + }, + "updateTime": { + "readOnly": true, + "format": "google-datetime", + "type": "string", + "description": "Output only. Timestamp when this ModelDeploymentMonitoringJob was updated most recently." + }, + "bigqueryTables": { + "items": { + "$ref": "GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTable" + }, + "type": "array", + "readOnly": true, + "description": "Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum: 1. Training data logging predict request/response 2. Serving data logging predict request/response" + }, + "predictInstanceSchemaUri": { + "description": "YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation). If not set, we will generate predict schema from collected predict requests.", + "type": "string" + }, + "loggingSamplingStrategy": { + "$ref": "GoogleCloudAiplatformV1SamplingStrategy", + "description": "Required. Sample Strategy for logging." + }, + "modelDeploymentMonitoringObjectiveConfigs": { + "items": { + "$ref": "GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfig" + }, + "type": "array", + "description": "Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately." + }, + "endpoint": { + "type": "string", + "description": "Required. Endpoint resource name. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" + }, + "name": { + "readOnly": true, + "description": "Output only. Resource name of a ModelDeploymentMonitoringJob.", + "type": "string" + }, + "state": { + "enum": [ + "JOB_STATE_UNSPECIFIED", + "JOB_STATE_QUEUED", + "JOB_STATE_PENDING", + "JOB_STATE_RUNNING", + "JOB_STATE_SUCCEEDED", + "JOB_STATE_FAILED", + "JOB_STATE_CANCELLING", + "JOB_STATE_CANCELLED", + "JOB_STATE_PAUSED", + "JOB_STATE_EXPIRED", + "JOB_STATE_UPDATING", + "JOB_STATE_PARTIALLY_SUCCEEDED" + ], + "description": "Output only. The detailed state of the monitoring job. When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'.", + "readOnly": true, + "type": "string", + "enumDescriptions": [ + "The job state is unspecified.", + "The job has been just created or resumed and processing has not yet begun.", + "The service is preparing to run the job.", + "The job is in progress.", + "The job completed successfully.", + "The job failed.", + "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "The job has been cancelled.", + "The job has been stopped, and can be resumed.", + "The job has expired.", + "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", + "The job is partially succeeded, some results may be missing due to errors." + ] + } + }, + "id": "GoogleCloudAiplatformV1ModelDeploymentMonitoringJob", + "description": "Represents a job that runs periodically to monitor the deployed models in an endpoint. It will analyze the logged training & prediction data to detect any abnormal behaviors." + }, + "GoogleCloudAiplatformV1GroundednessSpec": { + "properties": { + "version": { + "type": "integer", + "description": "Optional. Which version to use for evaluation.", + "format": "int32" + } + }, + "id": "GoogleCloudAiplatformV1GroundednessSpec", + "type": "object", + "description": "Spec for groundedness metric." + }, + "GoogleCloudAiplatformV1CreateFeaturestoreOperationMetadata": { + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "Operation metadata for Featurestore." + } + }, + "description": "Details of operations that perform create Featurestore.", + "id": "GoogleCloudAiplatformV1CreateFeaturestoreOperationMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1GroundingSupport": { + "type": "object", + "description": "Grounding support.", + "id": "GoogleCloudAiplatformV1GroundingSupport", + "properties": { + "segment": { + "description": "Segment of the content this support belongs to.", + "$ref": "GoogleCloudAiplatformV1Segment" + }, + "groundingChunkIndices": { + "items": { + "format": "int32", + "type": "integer" + }, + "type": "array", + "description": "A list of indices (into 'grounding_chunk') specifying the citations associated with the claim. For instance [1,3,4] means that grounding_chunk[1], grounding_chunk[3], grounding_chunk[4] are the retrieved content attributed to the claim." + }, + "confidenceScores": { + "description": "Confidence score of the support references. Ranges from 0 to 1. 1 is the most confident. This list must have the same size as the grounding_chunk_indices.", + "items": { + "type": "number", + "format": "float" + }, + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsGranularity": { + "type": "object", + "properties": { + "unit": { + "description": "The time granularity unit of this time period. The supported units are: * \"minute\" * \"hour\" * \"day\" * \"week\" * \"month\" * \"year\"", + "type": "string" + }, + "quantity": { + "type": "string", + "format": "int64", + "description": "The number of granularity_units between data points in the training data. If `granularity_unit` is `minute`, can be 1, 5, 10, 15, or 30. For all other values of `granularity_unit`, must be 1." + } + }, + "description": "A duration of time expressed in time granularity units.", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsGranularity" + }, + "GoogleCloudAiplatformV1Probe": { + "id": "GoogleCloudAiplatformV1Probe", + "type": "object", + "description": "Probe describes a health check to be performed against a container to determine whether it is alive or ready to receive traffic.", + "properties": { + "periodSeconds": { + "description": "How often (in seconds) to perform the probe. Default to 10 seconds. Minimum value is 1. Must be less than timeout_seconds. Maps to Kubernetes probe argument 'periodSeconds'.", + "format": "int32", + "type": "integer" + }, + "exec": { + "description": "ExecAction probes the health of a container by executing a command.", + "$ref": "GoogleCloudAiplatformV1ProbeExecAction" + }, + "timeoutSeconds": { + "description": "Number of seconds after which the probe times out. Defaults to 1 second. Minimum value is 1. Must be greater or equal to period_seconds. Maps to Kubernetes probe argument 'timeoutSeconds'.", + "format": "int32", + "type": "integer" + } + } + }, + "GoogleCloudAiplatformV1CopyModelResponse": { + "description": "Response message of ModelService.CopyModel operation.", + "type": "object", + "id": "GoogleCloudAiplatformV1CopyModelResponse", + "properties": { + "model": { + "description": "The name of the copied Model resource. Format: `projects/{project}/locations/{location}/models/{model}`", + "type": "string" + }, + "modelVersionId": { + "readOnly": true, + "description": "Output only. The version ID of the model that is copied.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1ToolParameterKVMatchInput": { + "id": "GoogleCloudAiplatformV1ToolParameterKVMatchInput", + "properties": { + "instances": { + "type": "array", + "description": "Required. Repeated tool parameter key value match instances.", + "items": { + "$ref": "GoogleCloudAiplatformV1ToolParameterKVMatchInstance" + } + }, + "metricSpec": { + "description": "Required. Spec for tool parameter key value match metric.", + "$ref": "GoogleCloudAiplatformV1ToolParameterKVMatchSpec" + } + }, + "description": "Input for tool parameter key value match metric.", + "type": "object" + }, + "GoogleCloudAiplatformV1FeatureStatsAnomaly": { + "id": "GoogleCloudAiplatformV1FeatureStatsAnomaly", + "description": "Stats and Anomaly generated at specific timestamp for specific Feature. The start_time and end_time are used to define the time range of the dataset that current stats belongs to, e.g. prediction traffic is bucketed into prediction datasets by time window. If the Dataset is not defined by time window, start_time = end_time. Timestamp of the stats and anomalies always refers to end_time. Raw stats and anomalies are stored in stats_uri or anomaly_uri in the tensorflow defined protos. Field data_stats contains almost identical information with the raw stats in Vertex AI defined proto, for UI to display.", + "type": "object", + "properties": { + "score": { + "format": "double", + "description": "Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT.", + "type": "number" + }, + "statsUri": { + "description": "Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:////stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message [tensorflow.metadata.v0.FeatureNameStatistics](https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/statistics.proto).", + "type": "string" + }, + "endTime": { + "type": "string", + "description": "The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).", + "format": "google-datetime" + }, + "anomalyDetectionThreshold": { + "format": "double", + "description": "This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.", + "type": "number" + }, + "distributionDeviation": { + "description": "Deviation from the current stats to baseline stats. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.", + "format": "double", + "type": "number" + }, + "anomalyUri": { + "type": "string", + "description": "Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message [tensorflow.metadata.v0.AnomalyInfo] (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto)." + }, + "startTime": { + "description": "The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).", + "type": "string", + "format": "google-datetime" + } + } + }, + "GoogleCloudAiplatformV1ModelEvaluationSlice": { + "type": "object", + "properties": { + "metricsSchemaUri": { + "type": "string", + "readOnly": true, + "description": "Output only. Points to a YAML file stored on Google Cloud Storage describing the metrics of this ModelEvaluationSlice. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject)." + }, + "slice": { + "readOnly": true, + "description": "Output only. The slice of the test data that is used to evaluate the Model.", + "$ref": "GoogleCloudAiplatformV1ModelEvaluationSliceSlice" + }, + "modelExplanation": { + "description": "Output only. Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for tabular Models.", + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1ModelExplanation" + }, + "metrics": { + "type": "any", + "readOnly": true, + "description": "Output only. Sliced evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri" + }, + "name": { + "description": "Output only. The resource name of the ModelEvaluationSlice.", + "type": "string", + "readOnly": true + }, + "createTime": { + "type": "string", + "format": "google-datetime", + "description": "Output only. Timestamp when this ModelEvaluationSlice was created.", + "readOnly": true + } + }, + "id": "GoogleCloudAiplatformV1ModelEvaluationSlice", + "description": "A collection of metrics calculated by comparing Model's predictions on a slice of the test data against ground truth annotations." + }, + "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadata", + "properties": { + "contentValidationStats": { + "items": { + "$ref": "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadataContentValidationStats" + }, + "description": "The validation stats of the content (per file) to be inserted or updated on the Matching Engine Index resource. Populated if contentsDeltaUri is provided as part of Index.metadata. Please note that, currently for those files that are broken or has unsupported file format, we will not have the stats for those files.", + "type": "array" + }, + "dataBytesCount": { + "format": "int64", + "description": "The ingested data size in bytes.", + "type": "string" + } + }, + "description": "Runtime operation metadata with regard to Matching Engine Index." + }, + "GoogleCloudAiplatformV1TensorboardBlob": { + "id": "GoogleCloudAiplatformV1TensorboardBlob", + "description": "One blob (e.g, image, graph) viewable on a blob metric plot.", + "properties": { + "data": { + "format": "byte", + "type": "string", + "description": "Optional. The bytes of the blob is not present unless it's returned by the ReadTensorboardBlobData endpoint." + }, + "id": { + "type": "string", + "description": "Output only. A URI safe key uniquely identifying a blob. Can be used to locate the blob stored in the Cloud Storage bucket of the consumer project.", + "readOnly": true + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1XraiAttribution": { + "description": "An explanation method that redistributes Integrated Gradients attributions to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Supported only by image Models.", + "type": "object", + "properties": { + "stepCount": { + "format": "int32", + "type": "integer", + "description": "Required. The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range. Valid range of its value is [1, 100], inclusively." + }, + "smoothGradConfig": { + "description": "Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf", + "$ref": "GoogleCloudAiplatformV1SmoothGradConfig" + }, + "blurBaselineConfig": { + "$ref": "GoogleCloudAiplatformV1BlurBaselineConfig", + "description": "Config for XRAI with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383" + } + }, + "id": "GoogleCloudAiplatformV1XraiAttribution" + }, + "GoogleCloudAiplatformV1SafetySpec": { + "properties": { + "version": { + "format": "int32", + "type": "integer", + "description": "Optional. Which version to use for evaluation." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SafetySpec", + "description": "Spec for safety metric." + }, + "GoogleCloudAiplatformV1FulfillmentInstance": { + "type": "object", + "id": "GoogleCloudAiplatformV1FulfillmentInstance", + "description": "Spec for fulfillment instance.", + "properties": { + "instruction": { + "type": "string", + "description": "Required. Inference instruction prompt to compare prediction with." + }, + "prediction": { + "description": "Required. Output of the evaluated model.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1ListModelsResponse": { + "description": "Response message for ModelService.ListModels", + "id": "GoogleCloudAiplatformV1ListModelsResponse", + "type": "object", + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token to retrieve next page of results. Pass to ListModelsRequest.page_token to obtain that page." + }, + "models": { + "items": { + "$ref": "GoogleCloudAiplatformV1Model" + }, + "description": "List of Models in the requested page.", + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1FeatureViewDataKey": { + "id": "GoogleCloudAiplatformV1FeatureViewDataKey", + "type": "object", + "properties": { + "compositeKey": { + "$ref": "GoogleCloudAiplatformV1FeatureViewDataKeyCompositeKey", + "description": "The actual Entity ID will be composed from this struct. This should match with the way ID is defined in the FeatureView spec." + }, + "key": { + "type": "string", + "description": "String key to use for lookup." + } + }, + "description": "Lookup key for a feature view." + }, + "GoogleCloudAiplatformV1RaySpec": { + "description": "Configuration information for the Ray cluster. For experimental launch, Ray cluster creation and Persistent cluster creation are 1:1 mapping: We will provision all the nodes within the Persistent cluster as Ray nodes.", + "id": "GoogleCloudAiplatformV1RaySpec", + "properties": { + "resourcePoolImages": { + "description": "Optional. Required if image_uri isn't set. A map of resource_pool_id to prebuild Ray image if user need to use different images for different head/worker pools. This map needs to cover all the resource pool ids. Example: { \"ray_head_node_pool\": \"head image\" \"ray_worker_node_pool1\": \"worker image\" \"ray_worker_node_pool2\": \"another worker image\" }", + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "rayLogsSpec": { + "description": "Optional. OSS Ray logging configurations.", + "$ref": "GoogleCloudAiplatformV1RayLogsSpec" + }, + "imageUri": { + "description": "Optional. Default image for user to choose a preferred ML framework (for example, TensorFlow or Pytorch) by choosing from [Vertex prebuilt images](https://cloud.google.com/vertex-ai/docs/training/pre-built-containers). Either this or the resource_pool_images is required. Use this field if you need all the resource pools to have the same Ray image. Otherwise, use the {@code resource_pool_images} field.", + "type": "string" + }, + "rayMetricSpec": { + "description": "Optional. Ray metrics configurations.", + "$ref": "GoogleCloudAiplatformV1RayMetricSpec" + }, + "headNodeResourcePoolId": { + "type": "string", + "description": "Optional. This will be used to indicate which resource pool will serve as the Ray head node(the first node within that pool). Will use the machine from the first workerpool as the head node by default if this field isn't set." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoObjectTrackingMetrics": { + "description": "Model evaluation metrics for video object tracking problems. Evaluates prediction quality of both labeled bounding boxes and labeled tracks (i.e. series of bounding boxes sharing same label and instance ID).", + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoObjectTrackingMetrics", + "type": "object", + "properties": { + "evaluatedTrackCount": { + "type": "integer", + "description": "UNIMPLEMENTED. The total number of tracks (i.e. as seen across all frames) the ground truth used to create this evaluation had.", + "format": "int32" + }, + "boundingBoxMeanAveragePrecision": { + "type": "number", + "description": "The single metric for bounding boxes evaluation: the `meanAveragePrecision` averaged over all `boundingBoxMetrics`.", + "format": "float" + }, + "trackMeanBoundingBoxIou": { + "description": "UNIMPLEMENTED. The single metric for tracks bounding box iou evaluation: the `meanBoundingBoxIou` averaged over all `trackMetrics`.", + "format": "float", + "type": "number" + }, + "evaluatedBoundingBoxCount": { + "format": "int32", + "description": "UNIMPLEMENTED. The total number of bounding boxes (i.e. summed over all frames) the ground truth used to create this evaluation had.", + "type": "integer" + }, + "boundingBoxMetrics": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsBoundingBoxMetrics" + }, + "description": "The bounding boxes match metrics for each intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair." + }, + "trackMeanAveragePrecision": { + "description": "UNIMPLEMENTED. The single metric for tracks accuracy evaluation: the `meanAveragePrecision` averaged over all `trackMetrics`.", + "format": "float", + "type": "number" + }, + "evaluatedFrameCount": { + "format": "int32", + "type": "integer", + "description": "UNIMPLEMENTED. The number of video frames used to create this evaluation." + }, + "trackMetrics": { + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTrackMetrics" + }, + "description": "UNIMPLEMENTED. The tracks match metrics for each intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.", + "type": "array" + }, + "trackMeanMismatchRate": { + "type": "number", + "format": "float", + "description": "UNIMPLEMENTED. The single metric for tracking consistency evaluation: the `meanMismatchRate` averaged over all `trackMetrics`." + } + } + }, + "GoogleCloudAiplatformV1SummarizationVerbosityInput": { + "description": "Input for summarization verbosity metric.", + "properties": { + "metricSpec": { + "description": "Required. Spec for summarization verbosity score metric.", + "$ref": "GoogleCloudAiplatformV1SummarizationVerbositySpec" + }, + "instance": { + "description": "Required. Summarization verbosity instance.", + "$ref": "GoogleCloudAiplatformV1SummarizationVerbosityInstance" + } + }, + "id": "GoogleCloudAiplatformV1SummarizationVerbosityInput", + "type": "object" + }, + "GoogleCloudAiplatformV1MachineSpec": { + "properties": { + "acceleratorCount": { + "type": "integer", + "format": "int32", + "description": "The number of accelerators to attach to the machine." + }, + "acceleratorType": { + "enum": [ + "ACCELERATOR_TYPE_UNSPECIFIED", + "NVIDIA_TESLA_K80", + "NVIDIA_TESLA_P100", + "NVIDIA_TESLA_V100", + "NVIDIA_TESLA_P4", + "NVIDIA_TESLA_T4", + "NVIDIA_TESLA_A100", + "NVIDIA_A100_80GB", + "NVIDIA_L4", + "NVIDIA_H100_80GB", + "TPU_V2", + "TPU_V3", + "TPU_V4_POD", + "TPU_V5_LITEPOD" + ], + "description": "Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.", + "enumDeprecated": [ + false, + true, + false, + false, + false, + false, + false, + false, + false, + false, + false, + false, + false, + false + ], + "enumDescriptions": [ + "Unspecified accelerator type, which means no accelerator.", + "Nvidia Tesla K80 GPU.", + "Nvidia Tesla P100 GPU.", + "Nvidia Tesla V100 GPU.", + "Nvidia Tesla P4 GPU.", + "Nvidia Tesla T4 GPU.", + "Nvidia Tesla A100 GPU.", + "Nvidia A100 80GB GPU.", + "Nvidia L4 GPU.", + "Nvidia H100 80Gb GPU.", + "TPU v2.", + "TPU v3.", + "TPU v4.", + "TPU v5." + ], + "type": "string" + }, + "tpuTopology": { + "description": "Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: \"2x2x1\").", + "type": "string" + }, + "machineType": { + "type": "string", + "description": "Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required." + } + }, + "id": "GoogleCloudAiplatformV1MachineSpec", + "type": "object", + "description": "Specification of a single machine." + }, + "GoogleCloudAiplatformV1GenerateContentResponsePromptFeedback": { + "description": "Content filter results for a prompt sent in the request.", + "properties": { + "safetyRatings": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1SafetyRating" + }, + "readOnly": true, + "description": "Output only. Safety ratings." + }, + "blockReason": { + "enumDescriptions": [ + "Unspecified blocked reason.", + "Candidates blocked due to safety.", + "Candidates blocked due to other reason.", + "Candidates blocked due to the terms which are included from the terminology blocklist.", + "Candidates blocked due to prohibited content." + ], + "enum": [ + "BLOCKED_REASON_UNSPECIFIED", + "SAFETY", + "OTHER", + "BLOCKLIST", + "PROHIBITED_CONTENT" + ], + "readOnly": true, + "description": "Output only. Blocked reason.", + "type": "string" + }, + "blockReasonMessage": { + "description": "Output only. A readable block reason message.", + "readOnly": true, + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1GenerateContentResponsePromptFeedback" + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetricsQuantileMetricsEntry": { + "description": "Entry for the Quantiles loss type optimization objective.", + "properties": { + "scaledPinballLoss": { + "format": "float", + "type": "number", + "description": "The scaled pinball loss of this quantile." + }, + "quantile": { + "type": "number", + "description": "The quantile for this entry.", + "format": "double" + }, + "observedQuantile": { + "format": "double", + "description": "This is a custom metric that calculates the percentage of true values that were less than the predicted value for that quantile. Only populated when optimization_objective is minimize-quantile-loss and each entry corresponds to an entry in quantiles The percent value can be used to compare with the quantile value, which is the target value.", + "type": "number" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetricsQuantileMetricsEntry" + }, + "GoogleCloudAiplatformV1PipelineTaskDetailArtifactList": { + "id": "GoogleCloudAiplatformV1PipelineTaskDetailArtifactList", + "description": "A list of artifact metadata.", + "properties": { + "artifacts": { + "description": "Output only. A list of artifact metadata.", + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1Artifact" + }, + "type": "array" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1UpdateFeaturestoreOperationMetadata": { + "type": "object", + "description": "Details of operations that perform update Featurestore.", + "id": "GoogleCloudAiplatformV1UpdateFeaturestoreOperationMetadata", + "properties": { + "genericMetadata": { + "description": "Operation metadata for Featurestore.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + } + }, + "GoogleCloudAiplatformV1BatchDeletePipelineJobsRequest": { + "type": "object", + "properties": { + "names": { + "description": "Required. The names of the PipelineJobs to delete. A maximum of 32 PipelineJobs can be deleted in a batch. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipelineJob}`", + "type": "array", + "items": { + "type": "string" + } + } + }, + "id": "GoogleCloudAiplatformV1BatchDeletePipelineJobsRequest", + "description": "Request message for PipelineService.BatchDeletePipelineJobs." + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionCustomTask": { + "description": "A TrainingJob that trains a custom code Model.", + "properties": { + "inputs": { + "$ref": "GoogleCloudAiplatformV1CustomJobSpec", + "description": "The input parameters of this CustomTask." + }, + "metadata": { + "description": "The metadata information.", + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionCustomJobMetadata" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionCustomTask", + "type": "object" + }, + "GoogleCloudLocationListLocationsResponse": { + "description": "The response message for Locations.ListLocations.", + "properties": { + "nextPageToken": { + "type": "string", + "description": "The standard List next-page token." + }, + "locations": { + "items": { + "$ref": "GoogleCloudLocationLocation" + }, + "description": "A list of locations that matches the specified filter in the request.", + "type": "array" + } + }, + "id": "GoogleCloudLocationListLocationsResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTable": { + "properties": { + "logType": { + "type": "string", + "enum": [ + "LOG_TYPE_UNSPECIFIED", + "PREDICT", + "EXPLAIN" + ], + "enumDescriptions": [ + "Unspecified type.", + "Predict logs.", + "Explain logs." + ], + "description": "The type of log." + }, + "bigqueryTablePath": { + "description": "The created BigQuery table to store logs. Customer could do their own query & analysis. Format: `bq://.model_deployment_monitoring_._`", + "type": "string" + }, + "requestResponseLoggingSchemaVersion": { + "description": "Output only. The schema version of the request/response logging BigQuery table. Default to v1 if unset.", + "type": "string", + "readOnly": true + }, + "logSource": { + "enumDescriptions": [ + "Unspecified source.", + "Logs coming from Training dataset.", + "Logs coming from Serving traffic." + ], + "type": "string", + "description": "The source of log.", + "enum": [ + "LOG_SOURCE_UNSPECIFIED", + "TRAINING", + "SERVING" + ] + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTable", + "description": "ModelDeploymentMonitoringBigQueryTable specifies the BigQuery table name as well as some information of the logs stored in this table." + }, + "GoogleCloudAiplatformV1BlurBaselineConfig": { + "description": "Config for blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383", + "id": "GoogleCloudAiplatformV1BlurBaselineConfig", + "type": "object", + "properties": { + "maxBlurSigma": { + "format": "float", + "type": "number", + "description": "The standard deviation of the blur kernel for the blurred baseline. The same blurring parameter is used for both the height and the width dimension. If not set, the method defaults to the zero (i.e. black for images) baseline." + } + } + }, + "GoogleCloudAiplatformV1BatchCreateFeaturesOperationMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1BatchCreateFeaturesOperationMetadata", + "description": "Details of operations that perform batch create Features.", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "Operation metadata for Feature." + } + } + }, + "GoogleCloudAiplatformV1ExplainResponse": { + "properties": { + "predictions": { + "type": "array", + "items": { + "type": "any" + }, + "description": "The predictions that are the output of the predictions call. Same as PredictResponse.predictions." + }, + "explanations": { + "description": "The explanations of the Model's PredictResponse.predictions. It has the same number of elements as instances to be explained.", + "items": { + "$ref": "GoogleCloudAiplatformV1Explanation" + }, + "type": "array" + }, + "deployedModelId": { + "description": "ID of the Endpoint's DeployedModel that served this explanation.", + "type": "string" + } + }, + "description": "Response message for PredictionService.Explain.", + "type": "object", + "id": "GoogleCloudAiplatformV1ExplainResponse" + }, + "GoogleCloudAiplatformV1InputDataConfig": { + "description": "Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model.", + "id": "GoogleCloudAiplatformV1InputDataConfig", + "properties": { + "timestampSplit": { + "description": "Supported only for tabular Datasets. Split based on the timestamp of the input data pieces.", + "$ref": "GoogleCloudAiplatformV1TimestampSplit" + }, + "annotationSchemaUri": { + "type": "string", + "description": "Applicable only to custom training with Datasets that have DataItems and Annotations. Cloud Storage URI that points to a YAML file describing the annotation schema. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/annotation/ , note that the chosen schema must be consistent with metadata of the Dataset specified by dataset_id. Only Annotations that both match this schema and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both annotations_filter and annotation_schema_uri." + }, + "bigqueryDestination": { + "description": "Only applicable to custom training with tabular Dataset with BigQuery source. The BigQuery project location where the training data is to be written to. In the given project a new dataset is created with name `dataset___` where timestamp is in YYYY_MM_DDThh_mm_ss_sssZ format. All training input data is written into that dataset. In the dataset three tables are created, `training`, `validation` and `test`. * AIP_DATA_FORMAT = \"bigquery\". * AIP_TRAINING_DATA_URI = \"bigquery_destination.dataset___.training\" * AIP_VALIDATION_DATA_URI = \"bigquery_destination.dataset___.validation\" * AIP_TEST_DATA_URI = \"bigquery_destination.dataset___.test\"", + "$ref": "GoogleCloudAiplatformV1BigQueryDestination" + }, + "fractionSplit": { + "description": "Split based on fractions defining the size of each set.", + "$ref": "GoogleCloudAiplatformV1FractionSplit" + }, + "gcsDestination": { + "description": "The Cloud Storage location where the training data is to be written to. In the given directory a new directory is created with name: `dataset---` where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All training input data is written into that directory. The Vertex AI environment variables representing Cloud Storage data URIs are represented in the Cloud Storage wildcard format to support sharded data. e.g.: \"gs://.../training-*.jsonl\" * AIP_DATA_FORMAT = \"jsonl\" for non-tabular data, \"csv\" for tabular data * AIP_TRAINING_DATA_URI = \"gcs_destination/dataset---/training-*.${AIP_DATA_FORMAT}\" * AIP_VALIDATION_DATA_URI = \"gcs_destination/dataset---/validation-*.${AIP_DATA_FORMAT}\" * AIP_TEST_DATA_URI = \"gcs_destination/dataset---/test-*.${AIP_DATA_FORMAT}\"", + "$ref": "GoogleCloudAiplatformV1GcsDestination" + }, + "predefinedSplit": { + "$ref": "GoogleCloudAiplatformV1PredefinedSplit", + "description": "Supported only for tabular Datasets. Split based on a predefined key." + }, + "savedQueryId": { + "description": "Only applicable to Datasets that have SavedQueries. The ID of a SavedQuery (annotation set) under the Dataset specified by dataset_id used for filtering Annotations for training. Only Annotations that are associated with this SavedQuery are used in respectively training. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both saved_query_id and annotations_filter. Only one of saved_query_id and annotation_schema_uri should be specified as both of them represent the same thing: problem type.", + "type": "string" + }, + "persistMlUseAssignment": { + "type": "boolean", + "description": "Whether to persist the ML use assignment to data item system labels." + }, + "stratifiedSplit": { + "description": "Supported only for tabular Datasets. Split based on the distribution of the specified column.", + "$ref": "GoogleCloudAiplatformV1StratifiedSplit" + }, + "annotationsFilter": { + "type": "string", + "description": "Applicable only to Datasets that have DataItems and Annotations. A filter on Annotations of the Dataset. Only Annotations that both match this filter and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on (for the auto-assigned that role is decided by Vertex AI). A filter with same syntax as the one used in ListAnnotations may be used, but note here it filters across all Annotations of the Dataset, and not just within a single DataItem." + }, + "filterSplit": { + "$ref": "GoogleCloudAiplatformV1FilterSplit", + "description": "Split based on the provided filters for each set." + }, + "datasetId": { + "type": "string", + "description": "Required. The ID of the Dataset in the same Project and Location which data will be used to train the Model. The Dataset must use schema compatible with Model being trained, and what is compatible should be described in the used TrainingPipeline's training_task_definition. For tabular Datasets, all their data is exported to training, to pick and choose from." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SearchMigratableResourcesRequest": { + "properties": { + "pageToken": { + "description": "The standard page token.", + "type": "string" + }, + "pageSize": { + "type": "integer", + "format": "int32", + "description": "The standard page size. The default and maximum value is 100." + }, + "filter": { + "type": "string", + "description": "A filter for your search. You can use the following types of filters: * Resource type filters. The following strings filter for a specific type of MigratableResource: * `ml_engine_model_version:*` * `automl_model:*` * `automl_dataset:*` * `data_labeling_dataset:*` * \"Migrated or not\" filters. The following strings filter for resources that either have or have not already been migrated: * `last_migrate_time:*` filters for migrated resources. * `NOT last_migrate_time:*` filters for not yet migrated resources." + } + }, + "description": "Request message for MigrationService.SearchMigratableResources.", + "type": "object", + "id": "GoogleCloudAiplatformV1SearchMigratableResourcesRequest" + }, + "GoogleCloudAiplatformV1SummarizationQualityInput": { + "type": "object", + "id": "GoogleCloudAiplatformV1SummarizationQualityInput", + "description": "Input for summarization quality metric.", + "properties": { + "instance": { + "description": "Required. Summarization quality instance.", + "$ref": "GoogleCloudAiplatformV1SummarizationQualityInstance" + }, + "metricSpec": { + "description": "Required. Spec for summarization quality score metric.", + "$ref": "GoogleCloudAiplatformV1SummarizationQualitySpec" + } + } + }, + "GoogleCloudAiplatformV1EntityIdSelector": { + "properties": { + "entityIdField": { + "description": "Source column that holds entity IDs. If not provided, entity IDs are extracted from the column named entity_id.", + "type": "string" + }, + "csvSource": { + "$ref": "GoogleCloudAiplatformV1CsvSource", + "description": "Source of Csv" + } + }, + "description": "Selector for entityId. Getting ids from the given source.", + "id": "GoogleCloudAiplatformV1EntityIdSelector", + "type": "object" + }, + "GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutput": { + "id": "GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutput", + "properties": { + "trainTrials": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1NasTrial" + }, + "readOnly": true, + "description": "Output only. List of NasTrials that were started as part of train stage." + }, + "searchTrials": { + "description": "Output only. List of NasTrials that were started as part of search stage.", + "type": "array", + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1NasTrial" + } + } + }, + "description": "The output of a multi-trial Neural Architecture Search (NAS) jobs.", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotation": { + "description": "Annotation details specific to image segmentation.", + "id": "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotation", + "type": "object", + "properties": { + "polygonAnnotation": { + "description": "Polygon annotation.", + "$ref": "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotationPolygonAnnotation" + }, + "maskAnnotation": { + "description": "Mask based segmentation annotation. Only one mask annotation can exist for one image.", + "$ref": "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotationMaskAnnotation" + }, + "polylineAnnotation": { + "$ref": "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotationPolylineAnnotation", + "description": "Polyline annotation." + } + } + }, + "GoogleCloudAiplatformV1PurgeArtifactsRequest": { + "properties": { + "force": { + "description": "Optional. Flag to indicate to actually perform the purge. If `force` is set to false, the method will return a sample of Artifact names that would be deleted.", + "type": "boolean" + }, + "filter": { + "type": "string", + "description": "Required. A required filter matching the Artifacts to be purged. E.g., `update_time \u003c= 2020-11-19T11:30:00-04:00`." + } + }, + "id": "GoogleCloudAiplatformV1PurgeArtifactsRequest", + "type": "object", + "description": "Request message for MetadataService.PurgeArtifacts." + }, + "GoogleCloudAiplatformV1TensorboardBlobSequence": { + "description": "One point viewable on a blob metric plot, but mostly just a wrapper message to work around repeated fields can't be used directly within `oneof` fields.", + "type": "object", + "id": "GoogleCloudAiplatformV1TensorboardBlobSequence", + "properties": { + "values": { + "description": "List of blobs contained within the sequence.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1TensorboardBlob" + } + } + } + }, + "GoogleCloudAiplatformV1ToolCallValidSpec": { + "type": "object", + "id": "GoogleCloudAiplatformV1ToolCallValidSpec", + "properties": {}, + "description": "Spec for tool call valid metric." + }, + "GoogleCloudAiplatformV1NotebookEucConfig": { + "id": "GoogleCloudAiplatformV1NotebookEucConfig", + "type": "object", + "description": "The euc configuration of NotebookRuntimeTemplate.", + "properties": { + "bypassActasCheck": { + "description": "Output only. Whether ActAs check is bypassed for service account attached to the VM. If false, we need ActAs check for the default Compute Engine Service account. When a Runtime is created, a VM is allocated using Default Compute Engine Service Account. Any user requesting to use this Runtime requires Service Account User (ActAs) permission over this SA. If true, Runtime owner is using EUC and does not require the above permission as VM no longer use default Compute Engine SA, but a P4SA.", + "type": "boolean", + "readOnly": true + }, + "eucDisabled": { + "type": "boolean", + "description": "Input only. Whether EUC is disabled in this NotebookRuntimeTemplate. In proto3, the default value of a boolean is false. In this way, by default EUC will be enabled for NotebookRuntimeTemplate." + } + } + }, + "CloudAiLargeModelsVisionImage": { + "type": "object", + "properties": { + "text": { + "type": "string", + "description": "Text/Expanded text input for imagen." + }, + "raiInfo": { + "$ref": "CloudAiLargeModelsVisionRaiInfo", + "description": "RAI info for image." + }, + "uri": { + "description": "Path to another storage (typically Google Cloud Storage).", + "type": "string" + }, + "imageRaiScores": { + "description": "RAI scores for generated image.", + "$ref": "CloudAiLargeModelsVisionImageRAIScores" + }, + "semanticFilterResponse": { + "description": "Semantic filter info for image.", + "$ref": "CloudAiLargeModelsVisionSemanticFilterResponse" + }, + "image": { + "format": "byte", + "type": "string", + "description": "Raw bytes." + }, + "encoding": { + "type": "string", + "description": "Image encoding, encoded as \"image/png\" or \"image/jpg\"." + } + }, + "description": "Image.", + "id": "CloudAiLargeModelsVisionImage" + }, + "GoogleCloudAiplatformV1ReadFeatureValuesResponse": { + "id": "GoogleCloudAiplatformV1ReadFeatureValuesResponse", + "description": "Response message for FeaturestoreOnlineServingService.ReadFeatureValues.", + "properties": { + "entityView": { + "$ref": "GoogleCloudAiplatformV1ReadFeatureValuesResponseEntityView", + "description": "Entity view with Feature values. This may be the entity in the Featurestore if values for all Features were requested, or a projection of the entity in the Featurestore if values for only some Features were requested." + }, + "header": { + "$ref": "GoogleCloudAiplatformV1ReadFeatureValuesResponseHeader", + "description": "Response header." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1BatchMigrateResourcesResponse": { + "type": "object", + "properties": { + "migrateResourceResponses": { + "description": "Successfully migrated resources.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1MigrateResourceResponse" + } + } + }, + "description": "Response message for MigrationService.BatchMigrateResources.", + "id": "GoogleCloudAiplatformV1BatchMigrateResourcesResponse" + }, + "GoogleCloudAiplatformV1ListTrialsResponse": { + "properties": { + "trials": { + "type": "array", + "description": "The Trials associated with the Study.", + "items": { + "$ref": "GoogleCloudAiplatformV1Trial" + } + }, + "nextPageToken": { + "type": "string", + "description": "Pass this token as the `page_token` field of the request for a subsequent call. If this field is omitted, there are no subsequent pages." + } + }, + "type": "object", + "description": "Response message for VizierService.ListTrials.", + "id": "GoogleCloudAiplatformV1ListTrialsResponse" + }, + "GoogleCloudAiplatformV1RemoveDatapointsRequest": { + "id": "GoogleCloudAiplatformV1RemoveDatapointsRequest", + "properties": { + "datapointIds": { + "type": "array", + "items": { + "type": "string" + }, + "description": "A list of datapoint ids to be deleted." + } + }, + "description": "Request message for IndexService.RemoveDatapoints", + "type": "object" + }, + "GoogleCloudAiplatformV1SummarizationVerbosityResult": { + "properties": { + "explanation": { + "type": "string", + "description": "Output only. Explanation for summarization verbosity score.", + "readOnly": true + }, + "score": { + "type": "number", + "description": "Output only. Summarization Verbosity score.", + "readOnly": true, + "format": "float" + }, + "confidence": { + "readOnly": true, + "format": "float", + "description": "Output only. Confidence for summarization verbosity score.", + "type": "number" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SummarizationVerbosityResult", + "description": "Spec for summarization verbosity result." + }, + "GoogleCloudAiplatformV1ReadFeatureValuesResponseHeader": { + "description": "Response header with metadata for the requested ReadFeatureValuesRequest.entity_type and Features.", + "type": "object", + "properties": { + "entityType": { + "type": "string", + "description": "The resource name of the EntityType from the ReadFeatureValuesRequest. Value format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`." + }, + "featureDescriptors": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1ReadFeatureValuesResponseFeatureDescriptor" + }, + "description": "List of Feature metadata corresponding to each piece of ReadFeatureValuesResponse.EntityView.data." + } + }, + "id": "GoogleCloudAiplatformV1ReadFeatureValuesResponseHeader" + }, + "GoogleCloudAiplatformV1StreamingReadFeatureValuesRequest": { + "id": "GoogleCloudAiplatformV1StreamingReadFeatureValuesRequest", + "properties": { + "featureSelector": { + "description": "Required. Selector choosing Features of the target EntityType. Feature IDs will be deduplicated.", + "$ref": "GoogleCloudAiplatformV1FeatureSelector" + }, + "entityIds": { + "description": "Required. IDs of entities to read Feature values of. The maximum number of IDs is 100. For example, for a machine learning model predicting user clicks on a website, an entity ID could be `user_123`.", + "type": "array", + "items": { + "type": "string" + } + } + }, + "description": "Request message for FeaturestoreOnlineServingService.StreamingFeatureValuesRead.", + "type": "object" + }, + "GoogleCloudAiplatformV1SupervisedHyperParameters": { + "id": "GoogleCloudAiplatformV1SupervisedHyperParameters", + "description": "Hyperparameters for SFT.", + "type": "object", + "properties": { + "adapterSize": { + "enumDescriptions": [ + "Adapter size is unspecified.", + "Adapter size 1.", + "Adapter size 4.", + "Adapter size 8.", + "Adapter size 16.", + "Adapter size 32." + ], + "type": "string", + "description": "Optional. Adapter size for tuning.", + "enum": [ + "ADAPTER_SIZE_UNSPECIFIED", + "ADAPTER_SIZE_ONE", + "ADAPTER_SIZE_FOUR", + "ADAPTER_SIZE_EIGHT", + "ADAPTER_SIZE_SIXTEEN", + "ADAPTER_SIZE_THIRTY_TWO" + ] + }, + "epochCount": { + "description": "Optional. Number of complete passes the model makes over the entire training dataset during training.", + "format": "int64", + "type": "string" + }, + "learningRateMultiplier": { + "description": "Optional. Multiplier for adjusting the default learning rate.", + "type": "number", + "format": "double" + } + } + }, + "GoogleCloudAiplatformV1ModelOriginalModelInfo": { + "id": "GoogleCloudAiplatformV1ModelOriginalModelInfo", + "type": "object", + "properties": { + "model": { + "description": "Output only. The resource name of the Model this Model is a copy of, including the revision. Format: `projects/{project}/locations/{location}/models/{model_id}@{version_id}`", + "readOnly": true, + "type": "string" + } + }, + "description": "Contains information about the original Model if this Model is a copy." + }, + "GoogleCloudAiplatformV1SuggestTrialsResponse": { + "type": "object", + "id": "GoogleCloudAiplatformV1SuggestTrialsResponse", + "properties": { + "endTime": { + "description": "The time at which operation processing completed.", + "type": "string", + "format": "google-datetime" + }, + "studyState": { + "enum": [ + "STATE_UNSPECIFIED", + "ACTIVE", + "INACTIVE", + "COMPLETED" + ], + "type": "string", + "enumDescriptions": [ + "The study state is unspecified.", + "The study is active.", + "The study is stopped due to an internal error.", + "The study is done when the service exhausts the parameter search space or max_trial_count is reached." + ], + "description": "The state of the Study." + }, + "trials": { + "items": { + "$ref": "GoogleCloudAiplatformV1Trial" + }, + "type": "array", + "description": "A list of Trials." + }, + "startTime": { + "description": "The time at which the operation was started.", + "type": "string", + "format": "google-datetime" + } + }, + "description": "Response message for VizierService.SuggestTrials." + }, + "GoogleCloudAiplatformV1FeatureViewIndexConfigTreeAHConfig": { + "type": "object", + "id": "GoogleCloudAiplatformV1FeatureViewIndexConfigTreeAHConfig", + "properties": { + "leafNodeEmbeddingCount": { + "description": "Optional. Number of embeddings on each leaf node. The default value is 1000 if not set.", + "type": "string", + "format": "int64" + } + }, + "description": "Configuration options for the tree-AH algorithm." + }, + "GoogleCloudAiplatformV1ListNotebookRuntimeTemplatesResponse": { + "properties": { + "notebookRuntimeTemplates": { + "items": { + "$ref": "GoogleCloudAiplatformV1NotebookRuntimeTemplate" + }, + "type": "array", + "description": "List of NotebookRuntimeTemplates in the requested page." + }, + "nextPageToken": { + "description": "A token to retrieve next page of results. Pass to ListNotebookRuntimeTemplatesRequest.page_token to obtain that page.", + "type": "string" + } + }, + "description": "Response message for NotebookService.ListNotebookRuntimeTemplates.", + "id": "GoogleCloudAiplatformV1ListNotebookRuntimeTemplatesResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaPredictParamsVideoClassificationPredictionParams": { + "description": "Prediction model parameters for Video Classification.", + "properties": { + "shotClassification": { + "type": "boolean", + "description": "Set to true to request shot-level classification. Vertex AI determines the boundaries for each camera shot in the entire time segment of the video that user specified in the input instance. Vertex AI then returns labels and their confidence scores for each detected shot, along with the start and end time of the shot. WARNING: Model evaluation is not done for this classification type, the quality of it depends on the training data, but there are no metrics provided to describe that quality. Default value is false" + }, + "maxPredictions": { + "type": "integer", + "format": "int32", + "description": "The Model only returns up to that many top, by confidence score, predictions per instance. If this number is very high, the Model may return fewer predictions. Default value is 10,000." + }, + "segmentClassification": { + "description": "Set to true to request segment-level classification. Vertex AI returns labels and their confidence scores for the entire time segment of the video that user specified in the input instance. Default value is true", + "type": "boolean" + }, + "oneSecIntervalClassification": { + "type": "boolean", + "description": "Set to true to request classification for a video at one-second intervals. Vertex AI returns labels and their confidence scores for each second of the entire time segment of the video that user specified in the input WARNING: Model evaluation is not done for this classification type, the quality of it depends on the training data, but there are no metrics provided to describe that quality. Default value is false" + }, + "confidenceThreshold": { + "format": "float", + "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0", + "type": "number" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaPredictParamsVideoClassificationPredictionParams" + }, + "GoogleCloudAiplatformV1SyncFeatureViewResponse": { + "properties": { + "featureViewSync": { + "description": "Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}/featureViewSyncs/{feature_view_sync}`", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SyncFeatureViewResponse", + "type": "object", + "description": "Respose message for FeatureOnlineStoreAdminService.SyncFeatureView." + }, + "GoogleCloudAiplatformV1ToolParameterKeyMatchInput": { + "type": "object", + "id": "GoogleCloudAiplatformV1ToolParameterKeyMatchInput", + "description": "Input for tool parameter key match metric.", + "properties": { + "instances": { + "type": "array", + "description": "Required. Repeated tool parameter key match instances.", + "items": { + "$ref": "GoogleCloudAiplatformV1ToolParameterKeyMatchInstance" + } + }, + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1ToolParameterKeyMatchSpec", + "description": "Required. Spec for tool parameter key match metric." + } + } + }, + "GoogleCloudAiplatformV1ContainerSpec": { + "type": "object", + "id": "GoogleCloudAiplatformV1ContainerSpec", + "description": "The spec of a Container.", + "properties": { + "args": { + "items": { + "type": "string" + }, + "type": "array", + "description": "The arguments to be passed when starting the container." + }, + "env": { + "items": { + "$ref": "GoogleCloudAiplatformV1EnvVar" + }, + "description": "Environment variables to be passed to the container. Maximum limit is 100.", + "type": "array" + }, + "imageUri": { + "type": "string", + "description": "Required. The URI of a container image in the Container Registry that is to be run on each worker replica." + }, + "command": { + "type": "array", + "description": "The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.", + "items": { + "type": "string" + } + } + } + }, + "GoogleCloudAiplatformV1PurgeArtifactsMetadata": { + "id": "GoogleCloudAiplatformV1PurgeArtifactsMetadata", + "type": "object", + "properties": { + "genericMetadata": { + "description": "Operation metadata for purging Artifacts.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + }, + "description": "Details of operations that perform MetadataService.PurgeArtifacts." + }, + "GoogleCloudAiplatformV1CancelTuningJobRequest": { + "description": "Request message for GenAiTuningService.CancelTuningJob.", + "type": "object", + "id": "GoogleCloudAiplatformV1CancelTuningJobRequest", + "properties": {} + }, + "GoogleCloudAiplatformV1ReadTensorboardUsageResponse": { + "properties": { + "monthlyUsageData": { + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1ReadTensorboardUsageResponsePerMonthUsageData" + }, + "type": "object", + "description": "Maps year-month (YYYYMM) string to per month usage data." + } + }, + "description": "Response message for TensorboardService.ReadTensorboardUsage.", + "type": "object", + "id": "GoogleCloudAiplatformV1ReadTensorboardUsageResponse" + }, + "GoogleCloudAiplatformV1Measurement": { + "description": "A message representing a Measurement of a Trial. A Measurement contains the Metrics got by executing a Trial using suggested hyperparameter values.", + "id": "GoogleCloudAiplatformV1Measurement", + "type": "object", + "properties": { + "stepCount": { + "type": "string", + "format": "int64", + "description": "Output only. The number of steps the machine learning model has been trained for. Must be non-negative.", + "readOnly": true + }, + "elapsedDuration": { + "format": "google-duration", + "type": "string", + "readOnly": true, + "description": "Output only. Time that the Trial has been running at the point of this Measurement." + }, + "metrics": { + "type": "array", + "description": "Output only. A list of metrics got by evaluating the objective functions using suggested Parameter values.", + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1MeasurementMetric" + } + } + } + }, + "GoogleCloudAiplatformV1PythonPackageSpec": { + "id": "GoogleCloudAiplatformV1PythonPackageSpec", + "description": "The spec of a Python packaged code.", + "properties": { + "executorImageUri": { + "description": "Required. The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of [pre-built containers for training](https://cloud.google.com/vertex-ai/docs/training/pre-built-containers). You must use an image from this list.", + "type": "string" + }, + "env": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1EnvVar" + }, + "description": "Environment variables to be passed to the python module. Maximum limit is 100." + }, + "packageUris": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Required. The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100." + }, + "pythonModule": { + "type": "string", + "description": "Required. The Python module name to run after installing the packages." + }, + "args": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Command line arguments to be passed to the Python task." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHyperparameterTuningJobSpec": { + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHyperparameterTuningJobSpec", + "properties": { + "maxTrialCount": { + "type": "integer", + "format": "int32", + "description": "The desired total number of Trials." + }, + "studySpec": { + "description": "Study configuration of the HyperparameterTuningJob.", + "$ref": "GoogleCloudAiplatformV1StudySpec" + }, + "parallelTrialCount": { + "description": "The desired number of Trials to run in parallel.", + "format": "int32", + "type": "integer" + }, + "maxFailedTrialCount": { + "description": "The number of failed Trials that need to be seen before failing the HyperparameterTuningJob. If set to 0, Vertex AI decides how many Trials must fail before the whole job fails.", + "type": "integer", + "format": "int32" + }, + "trialJobSpec": { + "$ref": "GoogleCloudAiplatformV1CustomJobSpec", + "description": "The spec of a trial job. The same spec applies to the CustomJobs created in all the trials." + } + } + }, + "CloudAiLargeModelsVisionRaiInfoDetectedLabelsEntity": { + "id": "CloudAiLargeModelsVisionRaiInfoDetectedLabelsEntity", + "properties": { + "description": { + "description": "Description of the label", + "type": "string" + }, + "mid": { + "type": "string", + "description": "MID of the label" + }, + "score": { + "description": "Confidence score of the label", + "type": "number", + "format": "float" + }, + "boundingBox": { + "description": "Bounding box of the label", + "$ref": "CloudAiLargeModelsVisionRaiInfoDetectedLabelsBoundingBox" + }, + "iouScore": { + "description": "The intersection ratio between the detection bounding box and the mask.", + "type": "number", + "format": "float" + } + }, + "type": "object", + "description": "The properties for a detected entity from the rai signal." + }, + "GoogleCloudAiplatformV1SchemaPredictPredictionVideoObjectTrackingPredictionResultFrame": { + "type": "object", + "description": "The fields `xMin`, `xMax`, `yMin`, and `yMax` refer to a bounding box, i.e. the rectangle over the video frame pinpointing the found AnnotationSpec. The coordinates are relative to the frame size, and the point 0,0 is in the top left of the frame.", + "id": "GoogleCloudAiplatformV1SchemaPredictPredictionVideoObjectTrackingPredictionResultFrame", + "properties": { + "timeOffset": { + "format": "google-duration", + "description": "A time (frame) of a video in which the object has been detected. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end.", + "type": "string" + }, + "xMin": { + "type": "number", + "description": "The leftmost coordinate of the bounding box.", + "format": "float" + }, + "yMin": { + "type": "number", + "format": "float", + "description": "The topmost coordinate of the bounding box." + }, + "xMax": { + "format": "float", + "description": "The rightmost coordinate of the bounding box.", + "type": "number" + }, + "yMax": { + "description": "The bottommost coordinate of the bounding box.", + "type": "number", + "format": "float" + } + } + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextExtraction": { + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextExtraction", + "type": "object", + "properties": { + "inputs": { + "description": "The input parameters of this TrainingJob.", + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextExtractionInputs" + } + }, + "description": "A TrainingJob that trains and uploads an AutoML Text Extraction Model." + }, + "GoogleCloudAiplatformV1TrainingPipeline": { + "id": "GoogleCloudAiplatformV1TrainingPipeline", + "properties": { + "startTime": { + "description": "Output only. Time when the TrainingPipeline for the first time entered the `PIPELINE_STATE_RUNNING` state.", + "type": "string", + "format": "google-datetime", + "readOnly": true + }, + "endTime": { + "readOnly": true, + "format": "google-datetime", + "type": "string", + "description": "Output only. Time when the TrainingPipeline entered any of the following states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`, `PIPELINE_STATE_CANCELLED`." + }, + "trainingTaskMetadata": { + "type": "any", + "description": "Output only. The metadata information as specified in the training_task_definition's `metadata`. This metadata is an auxiliary runtime and final information about the training task. While the pipeline is running this information is populated only at a best effort basis. Only present if the pipeline's training_task_definition contains `metadata` object.", + "readOnly": true + }, + "trainingTaskDefinition": { + "type": "string", + "description": "Required. A Google Cloud Storage path to the YAML file that defines the training task which is responsible for producing the model artifact, and may also include additional auxiliary work. The definition files that can be used here are found in gs://google-cloud-aiplatform/schema/trainingjob/definition/. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access." + }, + "displayName": { + "type": "string", + "description": "Required. The user-defined name of this TrainingPipeline." + }, + "name": { + "description": "Output only. Resource name of the TrainingPipeline.", + "readOnly": true, + "type": "string" + }, + "inputDataConfig": { + "description": "Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's training_task_definition should make clear whether this config is used and if there are any special requirements on how it should be filled. If nothing about this config is mentioned in the training_task_definition, then it should be assumed that the TrainingPipeline does not depend on this configuration.", + "$ref": "GoogleCloudAiplatformV1InputDataConfig" + }, + "createTime": { + "description": "Output only. Time when the TrainingPipeline was created.", + "format": "google-datetime", + "type": "string", + "readOnly": true + }, + "error": { + "description": "Output only. Only populated when the pipeline's state is `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`.", + "$ref": "GoogleRpcStatus", + "readOnly": true + }, + "state": { + "enum": [ + "PIPELINE_STATE_UNSPECIFIED", + "PIPELINE_STATE_QUEUED", + "PIPELINE_STATE_PENDING", + "PIPELINE_STATE_RUNNING", + "PIPELINE_STATE_SUCCEEDED", + "PIPELINE_STATE_FAILED", + "PIPELINE_STATE_CANCELLING", + "PIPELINE_STATE_CANCELLED", + "PIPELINE_STATE_PAUSED" + ], + "type": "string", + "description": "Output only. The detailed state of the pipeline.", + "enumDescriptions": [ + "The pipeline state is unspecified.", + "The pipeline has been created or resumed, and processing has not yet begun.", + "The service is preparing to run the pipeline.", + "The pipeline is in progress.", + "The pipeline completed successfully.", + "The pipeline failed.", + "The pipeline is being cancelled. From this state, the pipeline may only go to either PIPELINE_STATE_SUCCEEDED, PIPELINE_STATE_FAILED or PIPELINE_STATE_CANCELLED.", + "The pipeline has been cancelled.", + "The pipeline has been stopped, and can be resumed." + ], + "readOnly": true + }, + "modelToUpload": { + "$ref": "GoogleCloudAiplatformV1Model", + "description": "Describes the Model that may be uploaded (via ModelService.UploadModel) by this TrainingPipeline. The TrainingPipeline's training_task_definition should make clear whether this Model description should be populated, and if there are any special requirements regarding how it should be filled. If nothing is mentioned in the training_task_definition, then it should be assumed that this field should not be filled and the training task either uploads the Model without a need of this information, or that training task does not support uploading a Model as part of the pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and the trained Model had been uploaded into Vertex AI, then the model_to_upload's resource name is populated. The Model is always uploaded into the Project and Location in which this pipeline is." + }, + "labels": { + "type": "object", + "description": "The labels with user-defined metadata to organize TrainingPipelines. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", + "additionalProperties": { + "type": "string" + } + }, + "modelId": { + "type": "string", + "description": "Optional. The ID to use for the uploaded Model, which will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen." + }, + "parentModel": { + "type": "string", + "description": "Optional. When specify this field, the `model_to_upload` will not be uploaded as a new model, instead, it will become a new version of this `parent_model`." + }, + "updateTime": { + "description": "Output only. Time when the TrainingPipeline was most recently updated.", + "format": "google-datetime", + "readOnly": true, + "type": "string" + }, + "trainingTaskInputs": { + "description": "Required. The training task's parameter(s), as specified in the training_task_definition's `inputs`.", + "type": "any" + }, + "encryptionSpec": { + "description": "Customer-managed encryption key spec for a TrainingPipeline. If set, this TrainingPipeline will be secured by this key. Note: Model trained by this TrainingPipeline is also secured by this key if model_to_upload is not set separately.", + "$ref": "GoogleCloudAiplatformV1EncryptionSpec" + } + }, + "description": "The TrainingPipeline orchestrates tasks associated with training a Model. It always executes the training task, and optionally may also export data from Vertex AI's Dataset which becomes the training input, upload the Model to Vertex AI, and evaluate the Model.", + "type": "object" + }, + "GoogleCloudAiplatformV1PredictRequestResponseLoggingConfig": { + "properties": { + "bigqueryDestination": { + "$ref": "GoogleCloudAiplatformV1BigQueryDestination", + "description": "BigQuery table for logging. If only given a project, a new dataset will be created with name `logging__` where will be made BigQuery-dataset-name compatible (e.g. most special characters will become underscores). If no table name is given, a new table will be created with name `request_response_logging`" + }, + "enabled": { + "description": "If logging is enabled or not.", + "type": "boolean" + }, + "samplingRate": { + "format": "double", + "description": "Percentage of requests to be logged, expressed as a fraction in range(0,1].", + "type": "number" + } + }, + "description": "Configuration for logging request-response to a BigQuery table.", + "type": "object", + "id": "GoogleCloudAiplatformV1PredictRequestResponseLoggingConfig" + }, + "GoogleCloudAiplatformV1PublisherModelDocumentation": { + "description": "A named piece of documentation.", + "properties": { + "title": { + "type": "string", + "description": "Required. E.g., OVERVIEW, USE CASES, DOCUMENTATION, SDK & SAMPLES, JAVA, NODE.JS, etc.." + }, + "content": { + "description": "Required. Content of this piece of document (in Markdown format).", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1PublisherModelDocumentation", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsGranularity": { + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsGranularity", + "description": "A duration of time expressed in time granularity units.", + "properties": { + "unit": { + "description": "The time granularity unit of this time period. The supported units are: * \"minute\" * \"hour\" * \"day\" * \"week\" * \"month\" * \"year\"", + "type": "string" + }, + "quantity": { + "description": "The number of granularity_units between data points in the training data. If `granularity_unit` is `minute`, can be 1, 5, 10, 15, or 30. For all other values of `granularity_unit`, must be 1.", + "type": "string", + "format": "int64" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1NotebookExecutionJobDirectNotebookSource": { + "id": "GoogleCloudAiplatformV1NotebookExecutionJobDirectNotebookSource", + "properties": { + "content": { + "type": "string", + "description": "The base64-encoded contents of the input notebook file.", + "format": "byte" + } + }, + "description": "The content of the input notebook in ipynb format.", + "type": "object" + }, + "GoogleCloudAiplatformV1ListTrainingPipelinesResponse": { + "description": "Response message for PipelineService.ListTrainingPipelines", + "type": "object", + "properties": { + "nextPageToken": { + "description": "A token to retrieve the next page of results. Pass to ListTrainingPipelinesRequest.page_token to obtain that page.", + "type": "string" + }, + "trainingPipelines": { + "items": { + "$ref": "GoogleCloudAiplatformV1TrainingPipeline" + }, + "type": "array", + "description": "List of TrainingPipelines in the requested page." + } + }, + "id": "GoogleCloudAiplatformV1ListTrainingPipelinesResponse" + }, + "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessInstance": { + "properties": { + "instruction": { + "type": "string", + "description": "Required. The question asked and other instruction in the inference prompt." + }, + "reference": { + "type": "string", + "description": "Optional. Ground truth used to compare against the prediction." + }, + "prediction": { + "description": "Required. Output of the evaluated model.", + "type": "string" + }, + "context": { + "type": "string", + "description": "Optional. Text provided as context to answer the question." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessInstance", + "description": "Spec for question answering helpfulness instance." + }, + "GoogleCloudAiplatformV1DeployedIndexRef": { + "description": "Points to a DeployedIndex.", + "id": "GoogleCloudAiplatformV1DeployedIndexRef", + "type": "object", + "properties": { + "displayName": { + "type": "string", + "description": "Output only. The display name of the DeployedIndex.", + "readOnly": true + }, + "deployedIndexId": { + "type": "string", + "description": "Immutable. The ID of the DeployedIndex in the above IndexEndpoint." + }, + "indexEndpoint": { + "description": "Immutable. A resource name of the IndexEndpoint.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1ExamplesExampleGcsSource": { + "description": "The Cloud Storage input instances.", + "type": "object", + "properties": { + "gcsSource": { + "description": "The Cloud Storage location for the input instances.", + "$ref": "GoogleCloudAiplatformV1GcsSource" + }, + "dataFormat": { + "enum": [ + "DATA_FORMAT_UNSPECIFIED", + "JSONL" + ], + "enumDescriptions": [ + "Format unspecified, used when unset.", + "Examples are stored in JSONL files." + ], + "type": "string", + "description": "The format in which instances are given, if not specified, assume it's JSONL format. Currently only JSONL format is supported." + } + }, + "id": "GoogleCloudAiplatformV1ExamplesExampleGcsSource" + }, + "GoogleCloudAiplatformV1MutateDeployedIndexOperationMetadata": { + "id": "GoogleCloudAiplatformV1MutateDeployedIndexOperationMetadata", + "description": "Runtime operation information for IndexEndpointService.MutateDeployedIndex.", + "type": "object", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The operation generic information." + }, + "deployedIndexId": { + "description": "The unique index id specified by user", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1SchemaPredictParamsImageObjectDetectionPredictionParams": { + "type": "object", + "description": "Prediction model parameters for Image Object Detection.", + "properties": { + "maxPredictions": { + "description": "The Model only returns up to that many top, by confidence score, predictions per instance. Note that number of returned predictions is also limited by metadata's predictionsLimit. Default value is 10.", + "format": "int32", + "type": "integer" + }, + "confidenceThreshold": { + "type": "number", + "format": "float", + "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0" + } + }, + "id": "GoogleCloudAiplatformV1SchemaPredictParamsImageObjectDetectionPredictionParams" + }, + "GoogleCloudAiplatformV1ExportTensorboardTimeSeriesDataRequest": { + "description": "Request message for TensorboardService.ExportTensorboardTimeSeriesData.", + "id": "GoogleCloudAiplatformV1ExportTensorboardTimeSeriesDataRequest", + "type": "object", + "properties": { + "filter": { + "description": "Exports the TensorboardTimeSeries' data that match the filter expression.", + "type": "string" + }, + "pageSize": { + "description": "The maximum number of data points to return per page. The default page_size is 1000. Values must be between 1 and 10000. Values above 10000 are coerced to 10000.", + "format": "int32", + "type": "integer" + }, + "orderBy": { + "description": "Field to use to sort the TensorboardTimeSeries' data. By default, TensorboardTimeSeries' data is returned in a pseudo random order.", + "type": "string" + }, + "pageToken": { + "description": "A page token, received from a previous ExportTensorboardTimeSeriesData call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to ExportTensorboardTimeSeriesData must match the call that provided the page token.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1StopTrialRequest": { + "type": "object", + "properties": {}, + "id": "GoogleCloudAiplatformV1StopTrialRequest", + "description": "Request message for VizierService.StopTrial." + }, + "GoogleCloudAiplatformV1AutoscalingMetricSpec": { + "id": "GoogleCloudAiplatformV1AutoscalingMetricSpec", + "type": "object", + "description": "The metric specification that defines the target resource utilization (CPU utilization, accelerator's duty cycle, and so on) for calculating the desired replica count.", + "properties": { + "target": { + "format": "int32", + "description": "The target resource utilization in percentage (1% - 100%) for the given metric; once the real usage deviates from the target by a certain percentage, the machine replicas change. The default value is 60 (representing 60%) if not provided.", + "type": "integer" + }, + "metricName": { + "description": "Required. The resource metric name. Supported metrics: * For Online Prediction: * `aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle` * `aiplatform.googleapis.com/prediction/online/cpu/utilization`", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1NasJob": { + "description": "Represents a Neural Architecture Search (NAS) job.", + "properties": { + "createTime": { + "type": "string", + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Time when the NasJob was created." + }, + "nasJobOutput": { + "readOnly": true, + "description": "Output only. Output of the NasJob.", + "$ref": "GoogleCloudAiplatformV1NasJobOutput" + }, + "encryptionSpec": { + "description": "Customer-managed encryption key options for a NasJob. If this is set, then all resources created by the NasJob will be encrypted with the provided encryption key.", + "$ref": "GoogleCloudAiplatformV1EncryptionSpec" + }, + "updateTime": { + "description": "Output only. Time when the NasJob was most recently updated.", + "type": "string", + "readOnly": true, + "format": "google-datetime" + }, + "endTime": { + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Time when the NasJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.", + "type": "string" + }, + "enableRestrictedImageTraining": { + "type": "boolean", + "description": "Optional. Enable a separation of Custom model training and restricted image training for tenant project.", + "deprecated": true + }, + "error": { + "description": "Output only. Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.", + "readOnly": true, + "$ref": "GoogleRpcStatus" + }, + "name": { + "description": "Output only. Resource name of the NasJob.", + "type": "string", + "readOnly": true + }, + "displayName": { + "type": "string", + "description": "Required. The display name of the NasJob. The name can be up to 128 characters long and can consist of any UTF-8 characters." + }, + "labels": { + "type": "object", + "additionalProperties": { + "type": "string" + }, + "description": "The labels with user-defined metadata to organize NasJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels." + }, + "startTime": { + "format": "google-datetime", + "type": "string", + "description": "Output only. Time when the NasJob for the first time entered the `JOB_STATE_RUNNING` state.", + "readOnly": true + }, + "state": { + "readOnly": true, + "type": "string", + "enumDescriptions": [ + "The job state is unspecified.", + "The job has been just created or resumed and processing has not yet begun.", + "The service is preparing to run the job.", + "The job is in progress.", + "The job completed successfully.", + "The job failed.", + "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "The job has been cancelled.", + "The job has been stopped, and can be resumed.", + "The job has expired.", + "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", + "The job is partially succeeded, some results may be missing due to errors." + ], + "enum": [ + "JOB_STATE_UNSPECIFIED", + "JOB_STATE_QUEUED", + "JOB_STATE_PENDING", + "JOB_STATE_RUNNING", + "JOB_STATE_SUCCEEDED", + "JOB_STATE_FAILED", + "JOB_STATE_CANCELLING", + "JOB_STATE_CANCELLED", + "JOB_STATE_PAUSED", + "JOB_STATE_EXPIRED", + "JOB_STATE_UPDATING", + "JOB_STATE_PARTIALLY_SUCCEEDED" + ], + "description": "Output only. The detailed state of the job." + }, + "nasJobSpec": { + "$ref": "GoogleCloudAiplatformV1NasJobSpec", + "description": "Required. The specification of a NasJob." + } + }, + "id": "GoogleCloudAiplatformV1NasJob", + "type": "object" + }, + "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualityInstance": { + "description": "Spec for pairwise question answering quality instance.", + "type": "object", + "properties": { + "instruction": { + "description": "Required. Question Answering prompt for LLM.", + "type": "string" + }, + "reference": { + "description": "Optional. Ground truth used to compare against the prediction.", + "type": "string" + }, + "context": { + "type": "string", + "description": "Required. Text to answer the question." + }, + "prediction": { + "description": "Required. Output of the candidate model.", + "type": "string" + }, + "baselinePrediction": { + "type": "string", + "description": "Required. Output of the baseline model." + } + }, + "id": "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualityInstance" + }, + "GoogleCloudAiplatformV1EvaluateInstancesResponse": { + "properties": { + "toolParameterKeyMatchResults": { + "$ref": "GoogleCloudAiplatformV1ToolParameterKeyMatchResults", + "description": "Results for tool parameter key match metric." + }, + "bleuResults": { + "$ref": "GoogleCloudAiplatformV1BleuResults", + "description": "Results for bleu metric." + }, + "pairwiseSummarizationQualityResult": { + "$ref": "GoogleCloudAiplatformV1PairwiseSummarizationQualityResult", + "description": "Result for pairwise summarization quality metric." + }, + "questionAnsweringRelevanceResult": { + "description": "Result for question answering relevance metric.", + "$ref": "GoogleCloudAiplatformV1QuestionAnsweringRelevanceResult" + }, + "summarizationHelpfulnessResult": { + "description": "Result for summarization helpfulness metric.", + "$ref": "GoogleCloudAiplatformV1SummarizationHelpfulnessResult" + }, + "fulfillmentResult": { + "$ref": "GoogleCloudAiplatformV1FulfillmentResult", + "description": "Result for fulfillment metric." + }, + "rougeResults": { + "$ref": "GoogleCloudAiplatformV1RougeResults", + "description": "Results for rouge metric." + }, + "exactMatchResults": { + "$ref": "GoogleCloudAiplatformV1ExactMatchResults", + "description": "Auto metric evaluation results. Results for exact match metric." + }, + "summarizationQualityResult": { + "description": "Summarization only metrics. Result for summarization quality metric.", + "$ref": "GoogleCloudAiplatformV1SummarizationQualityResult" + }, + "summarizationVerbosityResult": { + "description": "Result for summarization verbosity metric.", + "$ref": "GoogleCloudAiplatformV1SummarizationVerbosityResult" + }, + "coherenceResult": { + "$ref": "GoogleCloudAiplatformV1CoherenceResult", + "description": "Result for coherence metric." + }, + "fluencyResult": { + "description": "LLM-based metric evaluation result. General text generation metrics, applicable to other categories. Result for fluency metric.", + "$ref": "GoogleCloudAiplatformV1FluencyResult" + }, + "questionAnsweringCorrectnessResult": { + "description": "Result for question answering correctness metric.", + "$ref": "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessResult" + }, + "toolNameMatchResults": { + "$ref": "GoogleCloudAiplatformV1ToolNameMatchResults", + "description": "Results for tool name match metric." + }, + "questionAnsweringHelpfulnessResult": { + "$ref": "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessResult", + "description": "Result for question answering helpfulness metric." + }, + "questionAnsweringQualityResult": { + "$ref": "GoogleCloudAiplatformV1QuestionAnsweringQualityResult", + "description": "Question answering only metrics. Result for question answering quality metric." + }, + "pairwiseQuestionAnsweringQualityResult": { + "$ref": "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualityResult", + "description": "Result for pairwise question answering quality metric." + }, + "groundednessResult": { + "$ref": "GoogleCloudAiplatformV1GroundednessResult", + "description": "Result for groundedness metric." + }, + "toolParameterKvMatchResults": { + "$ref": "GoogleCloudAiplatformV1ToolParameterKVMatchResults", + "description": "Results for tool parameter key value match metric." + }, + "toolCallValidResults": { + "$ref": "GoogleCloudAiplatformV1ToolCallValidResults", + "description": "Tool call metrics. Results for tool call valid metric." + }, + "safetyResult": { + "description": "Result for safety metric.", + "$ref": "GoogleCloudAiplatformV1SafetyResult" + } + }, + "description": "Response message for EvaluationService.EvaluateInstances.", + "id": "GoogleCloudAiplatformV1EvaluateInstancesResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1UploadModelRequest": { + "properties": { + "parentModel": { + "type": "string", + "description": "Optional. The resource name of the model into which to upload the version. Only specify this field when uploading a new version." + }, + "serviceAccount": { + "description": "Optional. The user-provided custom service account to use to do the model upload. If empty, [Vertex AI Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) will be used to access resources needed to upload the model. This account must belong to the target project where the model is uploaded to, i.e., the project specified in the `parent` field of this request and have necessary read permissions (to Google Cloud Storage, Artifact Registry, etc.).", + "type": "string" + }, + "model": { + "$ref": "GoogleCloudAiplatformV1Model", + "description": "Required. The Model to create." + }, + "modelId": { + "type": "string", + "description": "Optional. The ID to use for the uploaded Model, which will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen." + } + }, + "description": "Request message for ModelService.UploadModel.", + "type": "object", + "id": "GoogleCloudAiplatformV1UploadModelRequest" + }, + "GoogleCloudAiplatformV1CsvDestination": { + "description": "The storage details for CSV output content.", + "properties": { + "gcsDestination": { + "$ref": "GoogleCloudAiplatformV1GcsDestination", + "description": "Required. Google Cloud Storage location." + } + }, + "id": "GoogleCloudAiplatformV1CsvDestination", + "type": "object" + }, + "GoogleCloudAiplatformV1ImportFeatureValuesResponse": { + "description": "Response message for FeaturestoreService.ImportFeatureValues.", + "properties": { + "invalidRowCount": { + "type": "string", + "description": "The number of rows in input source that weren't imported due to either * Not having any featureValues. * Having a null entityId. * Having a null timestamp. * Not being parsable (applicable for CSV sources).", + "format": "int64" + }, + "importedEntityCount": { + "format": "int64", + "type": "string", + "description": "Number of entities that have been imported by the operation." + }, + "timestampOutsideRetentionRowsCount": { + "format": "int64", + "description": "The number rows that weren't ingested due to having feature timestamps outside the retention boundary.", + "type": "string" + }, + "importedFeatureValueCount": { + "type": "string", + "format": "int64", + "description": "Number of Feature values that have been imported by the operation." + } + }, + "id": "GoogleCloudAiplatformV1ImportFeatureValuesResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputs": { + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputs", + "properties": { + "optimizationObjective": { + "type": "string", + "description": "Objective function the model is optimizing towards. The training process creates a model that optimizes the value of the objective function over the validation set. The supported optimization objectives: * \"minimize-rmse\" (default) - Minimize root-mean-squared error (RMSE). * \"minimize-mae\" - Minimize mean-absolute error (MAE). * \"minimize-rmsle\" - Minimize root-mean-squared log error (RMSLE). * \"minimize-rmspe\" - Minimize root-mean-squared percentage error (RMSPE). * \"minimize-wape-mae\" - Minimize the combination of weighted absolute percentage error (WAPE) and mean-absolute-error (MAE). * \"minimize-quantile-loss\" - Minimize the quantile loss at the quantiles defined in `quantiles`. * \"minimize-mape\" - Minimize the mean absolute percentage error." + }, + "unavailableAtForecastColumns": { + "description": "Names of columns that are unavailable when a forecast is requested. This column contains information for the given entity (identified by the time_series_identifier_column) that is unknown before the forecast For example, actual weather on a given day.", + "items": { + "type": "string" + }, + "type": "array" + }, + "validationOptions": { + "type": "string", + "description": "Validation options for the data validation component. The available options are: * \"fail-pipeline\" - default, will validate against the validation and fail the pipeline if it fails. * \"ignore-validation\" - ignore the results of the validation and continue" + }, + "additionalExperiments": { + "type": "array", + "description": "Additional experiment flags for the time series forcasting training.", + "items": { + "type": "string" + } + }, + "hierarchyConfig": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHierarchyConfig", + "description": "Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies." + }, + "availableAtForecastColumns": { + "description": "Names of columns that are available and provided when a forecast is requested. These columns contain information for the given entity (identified by the time_series_identifier_column column) that is known at forecast. For example, predicted weather for a specific day.", + "type": "array", + "items": { + "type": "string" + } + }, + "timeColumn": { + "type": "string", + "description": "The name of the column that identifies time order in the time series. This column must be available at forecast." + }, + "quantiles": { + "items": { + "type": "number", + "format": "double" + }, + "type": "array", + "description": "Quantiles to use for minimize-quantile-loss `optimization_objective`. Up to 5 quantiles are allowed of values between 0 and 1, exclusive. Required if the value of optimization_objective is minimize-quantile-loss. Represents the percent quantiles to use for that objective. Quantiles must be unique." + }, + "dataGranularity": { + "description": "Expected difference in time granularity between rows in the data.", + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsGranularity" + }, + "timeSeriesAttributeColumns": { + "description": "Column names that should be used as attribute columns. The value of these columns does not vary as a function of time. For example, store ID or item color.", + "items": { + "type": "string" + }, + "type": "array" + }, + "transformations": { + "type": "array", + "description": "Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using \".\" as the delimiter.", + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformation" + } + }, + "contextWindow": { + "type": "string", + "format": "int64", + "description": "The amount of time into the past training and prediction data is used for model training and prediction respectively. Expressed in number of units defined by the `data_granularity` field." + }, + "holidayRegions": { + "description": "The geographical region based on which the holiday effect is applied in modeling by adding holiday categorical array feature that include all holidays matching the date. This option only allowed when data_granularity is day. By default, holiday effect modeling is disabled. To turn it on, specify the holiday region using this option.", + "type": "array", + "items": { + "type": "string" + } + }, + "exportEvaluatedDataItemsConfig": { + "description": "Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed.", + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig" + }, + "windowConfig": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionWindowConfig", + "description": "Config containing strategy for generating sliding windows." + }, + "timeSeriesIdentifierColumn": { + "type": "string", + "description": "The name of the column that identifies the time series." + }, + "targetColumn": { + "description": "The name of the column that the Model is to predict values for. This column must be unavailable at forecast.", + "type": "string" + }, + "forecastHorizon": { + "format": "int64", + "description": "The amount of time into the future for which forecasted values for the target are returned. Expressed in number of units defined by the `data_granularity` field.", + "type": "string" + }, + "trainBudgetMilliNodeHours": { + "type": "string", + "format": "int64", + "description": "Required. The train budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The training cost of the model will not exceed this budget. The final cost will be attempted to be close to the budget, though may end up being (even) noticeably smaller - at the backend's discretion. This especially may happen when further model training ceases to provide any improvements. If the budget is set to a value known to be insufficient to train a model for the given dataset, the training won't be attempted and will error. The train budget must be between 1,000 and 72,000 milli node hours, inclusive." + }, + "weightColumn": { + "description": "Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1. This column must be available at forecast.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1SummarizationVerbosityInstance": { + "properties": { + "prediction": { + "description": "Required. Output of the evaluated model.", + "type": "string" + }, + "context": { + "type": "string", + "description": "Required. Text to be summarized." + }, + "instruction": { + "type": "string", + "description": "Optional. Summarization prompt for LLM." + }, + "reference": { + "type": "string", + "description": "Optional. Ground truth used to compare against the prediction." + } + }, + "description": "Spec for summarization verbosity instance.", + "id": "GoogleCloudAiplatformV1SummarizationVerbosityInstance", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaPredictParamsGroundingConfig": { + "properties": { + "disableAttribution": { + "deprecated": true, + "type": "boolean", + "description": "If set, skip finding claim attributions (i.e not generate grounding citation)." + }, + "sources": { + "description": "The sources for the grounding checking.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaPredictParamsGroundingConfigSourceEntry" + } + } + }, + "id": "GoogleCloudAiplatformV1SchemaPredictParamsGroundingConfig", + "type": "object", + "description": "The configuration for grounding checking." + }, + "GoogleCloudAiplatformV1ListDatasetVersionsResponse": { + "id": "GoogleCloudAiplatformV1ListDatasetVersionsResponse", + "type": "object", + "description": "Response message for DatasetService.ListDatasetVersions.", + "properties": { + "nextPageToken": { + "description": "The standard List next-page token.", + "type": "string" + }, + "datasetVersions": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1DatasetVersion" + }, + "description": "A list of DatasetVersions that matches the specified filter in the request." + } + } + }, + "GoogleCloudAiplatformV1FunctionResponse": { + "properties": { + "response": { + "additionalProperties": { + "description": "Properties of the object.", + "type": "any" + }, + "type": "object", + "description": "Required. The function response in JSON object format." + }, + "name": { + "type": "string", + "description": "Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name]." + } + }, + "id": "GoogleCloudAiplatformV1FunctionResponse", + "description": "The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction.", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextArrayTransformation": { + "properties": { + "columnName": { + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextArrayTransformation", + "description": "Treats the column as text array and performs following transformation functions. * Concatenate all text values in the array into a single text value using a space (\" \") as a delimiter, and then treat the result as a single text value. Apply the transformations for Text columns. * Empty arrays treated as an empty text.", + "type": "object" + }, + "GoogleCloudAiplatformV1StratifiedSplit": { + "id": "GoogleCloudAiplatformV1StratifiedSplit", + "description": "Assigns input data to the training, validation, and test sets so that the distribution of values found in the categorical column (as specified by the `key` field) is mirrored within each split. The fraction values determine the relative sizes of the splits. For example, if the specified column has three values, with 50% of the rows having value \"A\", 25% value \"B\", and 25% value \"C\", and the split fractions are specified as 80/10/10, then the training set will constitute 80% of the training data, with about 50% of the training set rows having the value \"A\" for the specified column, about 25% having the value \"B\", and about 25% having the value \"C\". Only the top 500 occurring values are used; any values not in the top 500 values are randomly assigned to a split. If less than three rows contain a specific value, those rows are randomly assigned. Supported only for tabular Datasets.", + "type": "object", + "properties": { + "validationFraction": { + "format": "double", + "description": "The fraction of the input data that is to be used to validate the Model.", + "type": "number" + }, + "testFraction": { + "type": "number", + "format": "double", + "description": "The fraction of the input data that is to be used to evaluate the Model." + }, + "trainingFraction": { + "format": "double", + "description": "The fraction of the input data that is to be used to train the Model.", + "type": "number" + }, + "key": { + "description": "Required. The key is a name of one of the Dataset's data columns. The key provided must be for a categorical column.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1ToolParameterKVMatchInstance": { + "description": "Spec for tool parameter key value match instance.", + "properties": { + "prediction": { + "description": "Required. Output of the evaluated model.", + "type": "string" + }, + "reference": { + "description": "Required. Ground truth used to compare against the prediction.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1ToolParameterKVMatchInstance", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHyperparameterTuningJobMetadata": { + "properties": { + "bestTrialBackingCustomJob": { + "description": "The resource name of the CustomJob that has been created to run the best Trial of this HyperparameterTuning task.", + "type": "string" + }, + "backingHyperparameterTuningJob": { + "type": "string", + "description": "The resource name of the HyperparameterTuningJob that has been created to carry out this HyperparameterTuning task." + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHyperparameterTuningJobMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1ToolParameterKeyMatchSpec": { + "type": "object", + "description": "Spec for tool parameter key match metric.", + "properties": {}, + "id": "GoogleCloudAiplatformV1ToolParameterKeyMatchSpec" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionInputs": { + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionInputs", + "properties": { + "uptrainBaseModelId": { + "type": "string", + "description": "The ID of `base` model for upTraining. If it is specified, the new model will be upTrained based on the `base` model for upTraining. Otherwise, the new model will be trained from scratch. The `base` model for upTraining must be in the same Project and Location as the new Model to train, and have the same modelType." + }, + "tunableParameter": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter", + "description": "Trainer type for Vision TrainRequest." + }, + "disableEarlyStopping": { + "description": "Use the entire training budget. This disables the early stopping feature. When false the early stopping feature is enabled, which means that AutoML Image Object Detection might stop training before the entire training budget has been used.", + "type": "boolean" + }, + "budgetMilliNodeHours": { + "description": "The training budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The actual metadata.costMilliNodeHours will be equal or less than this value. If further model training ceases to provide any improvements, it will stop without using the full budget and the metadata.successfulStopReason will be `model-converged`. Note, node_hour = actual_hour * number_of_nodes_involved. For modelType `cloud`(default), the budget must be between 20,000 and 900,000 milli node hours, inclusive. The default value is 216,000 which represents one day in wall time, considering 9 nodes are used. For model types `mobile-tf-low-latency-1`, `mobile-tf-versatile-1`, `mobile-tf-high-accuracy-1` the training budget must be between 1,000 and 100,000 milli node hours, inclusive. The default value is 24,000 which represents one day in wall time on a single node that is used.", + "format": "int64", + "type": "string" + }, + "modelType": { + "enum": [ + "MODEL_TYPE_UNSPECIFIED", + "CLOUD_HIGH_ACCURACY_1", + "CLOUD_LOW_LATENCY_1", + "CLOUD_1", + "MOBILE_TF_LOW_LATENCY_1", + "MOBILE_TF_VERSATILE_1", + "MOBILE_TF_HIGH_ACCURACY_1", + "CLOUD_STREAMING_1", + "SPINENET", + "YOLO" + ], + "enumDescriptions": [ + "Should not be set.", + "A model best tailored to be used within Google Cloud, and which cannot be exported. Expected to have a higher latency, but should also have a higher prediction quality than other cloud models.", + "A model best tailored to be used within Google Cloud, and which cannot be exported. Expected to have a low latency, but may have lower prediction quality than other cloud models.", + "A model best tailored to be used within Google Cloud, and which cannot be exported. Compared to the CLOUD_HIGH_ACCURACY_1 and CLOUD_LOW_LATENCY_1 models above, it is expected to have higher prediction quality and lower latency.", + "A model that, in addition to being available within Google Cloud can also be exported (see ModelService.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have low latency, but may have lower prediction quality than other mobile models.", + "A model that, in addition to being available within Google Cloud can also be exported (see ModelService.ExportModel) and used on a mobile or edge device with TensorFlow afterwards.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other mobile models.", + "A model best tailored to be used within Google Cloud, and which cannot be exported. Expected to best support predictions in streaming with lower latency and lower prediction quality than other cloud models.", + "SpineNet for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally.", + "YOLO for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally." + ], + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1MeasurementMetric": { + "description": "A message representing a metric in the measurement.", + "properties": { + "value": { + "readOnly": true, + "description": "Output only. The value for this metric.", + "format": "double", + "type": "number" + }, + "metricId": { + "type": "string", + "description": "Output only. The ID of the Metric. The Metric should be defined in StudySpec's Metrics.", + "readOnly": true + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1MeasurementMetric" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHierarchyConfig": { + "description": "Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies.", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHierarchyConfig", + "type": "object", + "properties": { + "groupColumns": { + "description": "A list of time series attribute column names that define the time series hierarchy. Only one level of hierarchy is supported, ex. 'region' for a hierarchy of stores or 'department' for a hierarchy of products. If multiple columns are specified, time series will be grouped by their combined values, ex. ('blue', 'large') for 'color' and 'size', up to 5 columns are accepted. If no group columns are specified, all time series are considered to be part of the same group.", + "type": "array", + "items": { + "type": "string" + } + }, + "groupTotalWeight": { + "description": "The weight of the loss for predictions aggregated over time series in the same group.", + "format": "double", + "type": "number" + }, + "groupTemporalTotalWeight": { + "type": "number", + "description": "The weight of the loss for predictions aggregated over both the horizon and time series in the same hierarchy group.", + "format": "double" + }, + "temporalTotalWeight": { + "type": "number", + "description": "The weight of the loss for predictions aggregated over the horizon for a single time series.", + "format": "double" + } + } + }, + "GoogleCloudAiplatformV1Tensorboard": { + "id": "GoogleCloudAiplatformV1Tensorboard", + "description": "Tensorboard is a physical database that stores users' training metrics. A default Tensorboard is provided in each region of a Google Cloud project. If needed users can also create extra Tensorboards in their projects.", + "type": "object", + "properties": { + "isDefault": { + "type": "boolean", + "description": "Used to indicate if the TensorBoard instance is the default one. Each project & region can have at most one default TensorBoard instance. Creation of a default TensorBoard instance and updating an existing TensorBoard instance to be default will mark all other TensorBoard instances (if any) as non default." + }, + "labels": { + "type": "object", + "additionalProperties": { + "type": "string" + }, + "description": "The labels with user-defined metadata to organize your Tensorboards. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Tensorboard (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1EncryptionSpec", + "description": "Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key." + }, + "satisfiesPzs": { + "readOnly": true, + "description": "Output only. Reserved for future use.", + "type": "boolean" + }, + "etag": { + "description": "Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "name": { + "description": "Output only. Name of the Tensorboard. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", + "readOnly": true, + "type": "string" + }, + "updateTime": { + "description": "Output only. Timestamp when this Tensorboard was last updated.", + "readOnly": true, + "type": "string", + "format": "google-datetime" + }, + "blobStoragePathPrefix": { + "description": "Output only. Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.", + "readOnly": true, + "type": "string" + }, + "displayName": { + "type": "string", + "description": "Required. User provided name of this Tensorboard." + }, + "createTime": { + "readOnly": true, + "description": "Output only. Timestamp when this Tensorboard was created.", + "type": "string", + "format": "google-datetime" + }, + "runCount": { + "format": "int32", + "readOnly": true, + "description": "Output only. The number of Runs stored in this Tensorboard.", + "type": "integer" + }, + "description": { + "description": "Description of this Tensorboard.", + "type": "string" + }, + "satisfiesPzi": { + "type": "boolean", + "description": "Output only. Reserved for future use.", + "readOnly": true + } + } + }, + "GoogleCloudAiplatformV1ScheduleRunResponse": { + "type": "object", + "properties": { + "runResponse": { + "description": "The response of the scheduled run.", + "type": "string" + }, + "scheduledRunTime": { + "type": "string", + "format": "google-datetime", + "description": "The scheduled run time based on the user-specified schedule." + } + }, + "description": "Status of a scheduled run.", + "id": "GoogleCloudAiplatformV1ScheduleRunResponse" + }, + "GoogleCloudAiplatformV1BatchPredictionJobInputConfig": { + "properties": { + "bigquerySource": { + "description": "The BigQuery location of the input table. The schema of the table should be in the format described by the given context OpenAPI Schema, if one is provided. The table may contain additional columns that are not described by the schema, and they will be ignored.", + "$ref": "GoogleCloudAiplatformV1BigQuerySource" + }, + "gcsSource": { + "description": "The Cloud Storage location for the input instances.", + "$ref": "GoogleCloudAiplatformV1GcsSource" + }, + "instancesFormat": { + "type": "string", + "description": "Required. The format in which instances are given, must be one of the Model's supported_input_storage_formats." + } + }, + "type": "object", + "description": "Configures the input to BatchPredictionJob. See Model.supported_input_storage_formats for Model's supported input formats, and how instances should be expressed via any of them.", + "id": "GoogleCloudAiplatformV1BatchPredictionJobInputConfig" + }, + "GoogleCloudAiplatformV1SchemaVideoDatasetMetadata": { + "properties": { + "dataItemSchemaUri": { + "description": "Points to a YAML file stored on Google Cloud Storage describing payload of the Video DataItems that belong to this Dataset.", + "type": "string" + }, + "gcsBucket": { + "type": "string", + "description": "Google Cloud Storage Bucket name that contains the blob data of this Dataset." + } + }, + "type": "object", + "description": "The metadata of Datasets that contain Video DataItems.", + "id": "GoogleCloudAiplatformV1SchemaVideoDatasetMetadata" + }, + "GoogleCloudAiplatformV1PurgeContextsRequest": { + "properties": { + "force": { + "type": "boolean", + "description": "Optional. Flag to indicate to actually perform the purge. If `force` is set to false, the method will return a sample of Context names that would be deleted." + }, + "filter": { + "type": "string", + "description": "Required. A required filter matching the Contexts to be purged. E.g., `update_time \u003c= 2020-11-19T11:30:00-04:00`." + } + }, + "description": "Request message for MetadataService.PurgeContexts.", + "type": "object", + "id": "GoogleCloudAiplatformV1PurgeContextsRequest" + }, + "GoogleCloudAiplatformV1FluencyResult": { + "properties": { + "score": { + "readOnly": true, + "type": "number", + "format": "float", + "description": "Output only. Fluency score." + }, + "confidence": { + "type": "number", + "format": "float", + "readOnly": true, + "description": "Output only. Confidence for fluency score." + }, + "explanation": { + "type": "string", + "readOnly": true, + "description": "Output only. Explanation for fluency score." + } + }, + "id": "GoogleCloudAiplatformV1FluencyResult", + "type": "object", + "description": "Spec for fluency result." + }, + "GoogleCloudAiplatformV1NearestNeighborQueryParameters": { + "id": "GoogleCloudAiplatformV1NearestNeighborQueryParameters", + "properties": { + "approximateNeighborCandidates": { + "format": "int32", + "description": "Optional. The number of neighbors to find via approximate search before exact reordering is performed; if set, this value must be \u003e neighbor_count.", + "type": "integer" + }, + "leafNodesSearchFraction": { + "type": "number", + "format": "double", + "description": "Optional. The fraction of the number of leaves to search, set at query time allows user to tune search performance. This value increase result in both search accuracy and latency increase. The value should be between 0.0 and 1.0." + } + }, + "type": "object", + "description": "Parameters that can be overrided in each query to tune query latency and recall." + }, + "GoogleCloudAiplatformV1FeatureViewSyncConfig": { + "description": "Configuration for Sync. Only one option is set.", + "type": "object", + "id": "GoogleCloudAiplatformV1FeatureViewSyncConfig", + "properties": { + "cron": { + "description": "Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: \"CRON_TZ=${IANA_TIME_ZONE}\" or \"TZ=${IANA_TIME_ZONE}\". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, \"CRON_TZ=America/New_York 1 * * * *\", or \"TZ=America/New_York 1 * * * *\".", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1SupervisedTuningDataStats": { + "description": "Tuning data statistics for Supervised Tuning.", + "id": "GoogleCloudAiplatformV1SupervisedTuningDataStats", + "properties": { + "userInputTokenDistribution": { + "description": "Output only. Dataset distributions for the user input tokens.", + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1SupervisedTuningDatasetDistribution" + }, + "userMessagePerExampleDistribution": { + "description": "Output only. Dataset distributions for the messages per example.", + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1SupervisedTuningDatasetDistribution" + }, + "userOutputTokenDistribution": { + "description": "Output only. Dataset distributions for the user output tokens.", + "$ref": "GoogleCloudAiplatformV1SupervisedTuningDatasetDistribution", + "readOnly": true + }, + "totalBillableTokenCount": { + "format": "int64", + "description": "Output only. Number of billable tokens in the tuning dataset.", + "readOnly": true, + "type": "string" + }, + "totalBillableCharacterCount": { + "format": "int64", + "description": "Output only. Number of billable characters in the tuning dataset.", + "deprecated": true, + "readOnly": true, + "type": "string" + }, + "tuningDatasetExampleCount": { + "type": "string", + "readOnly": true, + "format": "int64", + "description": "Output only. Number of examples in the tuning dataset." + }, + "totalTuningCharacterCount": { + "description": "Output only. Number of tuning characters in the tuning dataset.", + "readOnly": true, + "type": "string", + "format": "int64" + }, + "tuningStepCount": { + "type": "string", + "readOnly": true, + "format": "int64", + "description": "Output only. Number of tuning steps for this Tuning Job." + }, + "userDatasetExamples": { + "readOnly": true, + "description": "Output only. Sample user messages in the training dataset uri.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1Content" + } + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotationMaskAnnotation": { + "description": "The mask based segmentation annotation.", + "id": "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotationMaskAnnotation", + "properties": { + "annotationSpecColors": { + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaAnnotationSpecColor" + }, + "type": "array", + "description": "The mapping between color and AnnotationSpec for this Annotation." + }, + "maskGcsUri": { + "type": "string", + "description": "Google Cloud Storage URI that points to the mask image. The image must be in PNG format. It must have the same size as the DataItem's image. Each pixel in the image mask represents the AnnotationSpec which the pixel in the image DataItem belong to. Each color is mapped to one AnnotationSpec based on annotation_spec_colors." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1PredefinedSplit": { + "description": "Assigns input data to training, validation, and test sets based on the value of a provided key. Supported only for tabular Datasets.", + "id": "GoogleCloudAiplatformV1PredefinedSplit", + "type": "object", + "properties": { + "key": { + "type": "string", + "description": "Required. The key is a name of one of the Dataset's data columns. The value of the key (either the label's value or value in the column) must be one of {`training`, `validation`, `test`}, and it defines to which set the given piece of data is assigned. If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline." + } + } + }, + "GoogleCloudAiplatformV1ModelMonitoringStatsAnomaliesFeatureHistoricStatsAnomalies": { + "description": "Historical Stats (and Anomalies) for a specific Feature.", + "properties": { + "threshold": { + "$ref": "GoogleCloudAiplatformV1ThresholdConfig", + "description": "Threshold for anomaly detection." + }, + "trainingStats": { + "description": "Stats calculated for the Training Dataset.", + "$ref": "GoogleCloudAiplatformV1FeatureStatsAnomaly" + }, + "predictionStats": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1FeatureStatsAnomaly" + }, + "description": "A list of historical stats generated by different time window's Prediction Dataset." + }, + "featureDisplayName": { + "type": "string", + "description": "Display Name of the Feature." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1ModelMonitoringStatsAnomaliesFeatureHistoricStatsAnomalies" + }, + "GoogleCloudAiplatformV1ListNotebookRuntimesResponse": { + "type": "object", + "description": "Response message for NotebookService.ListNotebookRuntimes.", + "id": "GoogleCloudAiplatformV1ListNotebookRuntimesResponse", + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token to retrieve next page of results. Pass to ListNotebookRuntimesRequest.page_token to obtain that page." + }, + "notebookRuntimes": { + "items": { + "$ref": "GoogleCloudAiplatformV1NotebookRuntime" + }, + "type": "array", + "description": "List of NotebookRuntimes in the requested page." + } + } + }, + "GoogleCloudAiplatformV1DirectRawPredictResponse": { + "description": "Response message for PredictionService.DirectRawPredict.", + "id": "GoogleCloudAiplatformV1DirectRawPredictResponse", + "properties": { + "output": { + "description": "The prediction output.", + "type": "string", + "format": "byte" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SearchFeaturesResponse": { + "description": "Response message for FeaturestoreService.SearchFeatures.", + "properties": { + "features": { + "description": "The Features matching the request. Fields returned: * `name` * `description` * `labels` * `create_time` * `update_time`", + "items": { + "$ref": "GoogleCloudAiplatformV1Feature" + }, + "type": "array" + }, + "nextPageToken": { + "description": "A token, which can be sent as SearchFeaturesRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SearchFeaturesResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1QuestionAnsweringRelevanceResult": { + "description": "Spec for question answering relevance result.", + "type": "object", + "properties": { + "confidence": { + "readOnly": true, + "type": "number", + "format": "float", + "description": "Output only. Confidence for question answering relevance score." + }, + "score": { + "readOnly": true, + "type": "number", + "description": "Output only. Question Answering Relevance score.", + "format": "float" + }, + "explanation": { + "description": "Output only. Explanation for question answering relevance score.", + "readOnly": true, + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1QuestionAnsweringRelevanceResult" + }, + "GoogleCloudAiplatformV1DestinationFeatureSetting": { + "type": "object", + "id": "GoogleCloudAiplatformV1DestinationFeatureSetting", + "properties": { + "destinationField": { + "description": "Specify the field name in the export destination. If not specified, Feature ID is used.", + "type": "string" + }, + "featureId": { + "type": "string", + "description": "Required. The ID of the Feature to apply the setting to." + } + } + }, + "GoogleCloudAiplatformV1NasJobSpec": { + "description": "Represents the spec of a NasJob.", + "id": "GoogleCloudAiplatformV1NasJobSpec", + "properties": { + "searchSpaceSpec": { + "description": "It defines the search space for Neural Architecture Search (NAS).", + "type": "string" + }, + "multiTrialAlgorithmSpec": { + "description": "The spec of multi-trial algorithms.", + "$ref": "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpec" + }, + "resumeNasJobId": { + "description": "The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1CustomJobSpec": { + "type": "object", + "id": "GoogleCloudAiplatformV1CustomJobSpec", + "description": "Represents the spec of a CustomJob.", + "properties": { + "workerPoolSpecs": { + "description": "Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1WorkerPoolSpec" + } + }, + "scheduling": { + "$ref": "GoogleCloudAiplatformV1Scheduling", + "description": "Scheduling options for a CustomJob." + }, + "tensorboard": { + "description": "Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", + "type": "string" + }, + "experiment": { + "type": "string", + "description": "Optional. The Experiment associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}`" + }, + "experimentRun": { + "type": "string", + "description": "Optional. The Experiment Run associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}`" + }, + "protectedArtifactLocationId": { + "description": "The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations", + "type": "string" + }, + "reservedIpRanges": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range']." + }, + "serviceAccount": { + "type": "string", + "description": "Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the [Vertex AI Custom Code Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) for the CustomJob's project is used." + }, + "persistentResourceId": { + "type": "string", + "description": "Optional. The ID of the PersistentResource in the same Project and Location which to run If this is specified, the job will be run on existing machines held by the PersistentResource instead of on-demand short-live machines. The network and CMEK configs on the job should be consistent with those on the PersistentResource, otherwise, the job will be rejected." + }, + "network": { + "description": "Optional. The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Job should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. To specify this field, you must have already [configured VPC Network Peering for Vertex AI](https://cloud.google.com/vertex-ai/docs/general/vpc-peering). If this field is left unspecified, the job is not peered with any network.", + "type": "string" + }, + "enableDashboardAccess": { + "type": "boolean", + "description": "Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to `true`, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials)." + }, + "baseOutputDirectory": { + "$ref": "GoogleCloudAiplatformV1GcsDestination", + "description": "The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = `/model/` * AIP_CHECKPOINT_DIR = `/checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `/logs/` For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = `//model/` * AIP_CHECKPOINT_DIR = `//checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `//logs/`" + }, + "models": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Optional. The name of the Model resources for which to generate a mapping to artifact URIs. Applicable only to some of the Google-provided custom jobs. Format: `projects/{project}/locations/{location}/models/{model}` In order to retrieve a specific version of the model, also provide the version ID or version alias. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` If no version ID or alias is specified, the \"default\" version will be returned. The \"default\" version alias is created for the first version of the model, and can be moved to other versions later on. There will be exactly one default version." + }, + "enableWebAccess": { + "type": "boolean", + "description": "Optional. Whether you want Vertex AI to enable [interactive shell access](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) to training containers. If set to `true`, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials)." + } + } + }, + "GoogleCloudAiplatformV1ListFeatureGroupsResponse": { + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token, which can be sent as ListFeatureGroupsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages." + }, + "featureGroups": { + "description": "The FeatureGroups matching the request.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1FeatureGroup" + } + } + }, + "id": "GoogleCloudAiplatformV1ListFeatureGroupsResponse", + "description": "Response message for FeatureRegistryService.ListFeatureGroups.", + "type": "object" + }, + "GoogleCloudAiplatformV1UpdateFeatureOnlineStoreOperationMetadata": { + "id": "GoogleCloudAiplatformV1UpdateFeatureOnlineStoreOperationMetadata", + "description": "Details of operations that perform update FeatureOnlineStore.", + "type": "object", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "Operation metadata for FeatureOnlineStore." + } + } + }, + "GoogleCloudAiplatformV1SchemaPredictPredictionTimeSeriesForecastingPredictionResult": { + "description": "Prediction output format for Time Series Forecasting.", + "properties": { + "value": { + "description": "The regression value.", + "type": "number", + "format": "float" + }, + "quantilePredictions": { + "description": "Quantile predictions, in 1-1 correspondence with quantile_values.", + "type": "array", + "items": { + "type": "number", + "format": "float" + } + }, + "tftFeatureImportance": { + "$ref": "GoogleCloudAiplatformV1SchemaPredictPredictionTftFeatureImportance", + "description": "Only use these if TFt is enabled." + }, + "quantileValues": { + "type": "array", + "items": { + "type": "number", + "format": "float" + }, + "description": "Quantile values." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaPredictPredictionTimeSeriesForecastingPredictionResult" + }, + "GoogleCloudAiplatformV1BigQueryDestination": { + "type": "object", + "description": "The BigQuery location for the output content.", + "properties": { + "outputUri": { + "type": "string", + "description": "Required. BigQuery URI to a project or table, up to 2000 characters long. When only the project is specified, the Dataset and Table is created. When the full table reference is specified, the Dataset must exist and table must not exist. Accepted forms: * BigQuery path. For example: `bq://projectId` or `bq://projectId.bqDatasetId` or `bq://projectId.bqDatasetId.bqTableId`." + } + }, + "id": "GoogleCloudAiplatformV1BigQueryDestination" + }, + "GoogleCloudAiplatformV1BigQuerySource": { + "type": "object", + "description": "The BigQuery location for the input content.", + "properties": { + "inputUri": { + "description": "Required. BigQuery URI to a table, up to 2000 characters long. Accepted forms: * BigQuery path. For example: `bq://projectId.bqDatasetId.bqTableId`.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1BigQuerySource" + }, + "GoogleCloudAiplatformV1CancelNasJobRequest": { + "properties": {}, + "type": "object", + "description": "Request message for JobService.CancelNasJob.", + "id": "GoogleCloudAiplatformV1CancelNasJobRequest" + }, + "GoogleCloudAiplatformV1FeatureValueMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1FeatureValueMetadata", + "description": "Metadata of feature value.", + "properties": { + "generateTime": { + "description": "Feature generation timestamp. Typically, it is provided by user at feature ingestion time. If not, feature store will use the system timestamp when the data is ingested into feature store. For streaming ingestion, the time, aligned by days, must be no older than five years (1825 days) and no later than one year (366 days) in the future.", + "format": "google-datetime", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationNumericTransformation": { + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationNumericTransformation", + "type": "object", + "properties": { + "columnName": { + "type": "string" + } + }, + "description": "Training pipeline will perform following transformation functions. * The value converted to float32. * The z_score of the value. * log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * A boolean value that indicates whether the value is valid." + }, + "GoogleCloudAiplatformV1Index": { + "description": "A representation of a collection of database items organized in a way that allows for approximate nearest neighbor (a.k.a ANN) algorithms search.", + "type": "object", + "id": "GoogleCloudAiplatformV1Index", + "properties": { + "labels": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "The labels with user-defined metadata to organize your Indexes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels." + }, + "updateTime": { + "format": "google-datetime", + "readOnly": true, + "type": "string", + "description": "Output only. Timestamp when this Index was most recently updated. This also includes any update to the contents of the Index. Note that Operations working on this Index may have their Operations.metadata.generic_metadata.update_time a little after the value of this timestamp, yet that does not mean their results are not already reflected in the Index. Result of any successfully completed Operation on the Index is reflected in it." + }, + "indexStats": { + "readOnly": true, + "description": "Output only. Stats of the index resource.", + "$ref": "GoogleCloudAiplatformV1IndexStats" + }, + "etag": { + "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "encryptionSpec": { + "description": "Immutable. Customer-managed encryption key spec for an Index. If set, this Index and all sub-resources of this Index will be secured by this key.", + "$ref": "GoogleCloudAiplatformV1EncryptionSpec" + }, + "createTime": { + "description": "Output only. Timestamp when this Index was created.", + "type": "string", + "format": "google-datetime", + "readOnly": true + }, + "description": { + "type": "string", + "description": "The description of the Index." + }, + "name": { + "readOnly": true, + "type": "string", + "description": "Output only. The resource name of the Index." + }, + "deployedIndexes": { + "type": "array", + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1DeployedIndexRef" + }, + "description": "Output only. The pointers to DeployedIndexes created from this Index. An Index can be only deleted if all its DeployedIndexes had been undeployed first." + }, + "indexUpdateMethod": { + "description": "Immutable. The update method to use with this Index. If not set, BATCH_UPDATE will be used by default.", + "enumDescriptions": [ + "Should not be used.", + "BatchUpdate: user can call UpdateIndex with files on Cloud Storage of Datapoints to update.", + "StreamUpdate: user can call UpsertDatapoints/DeleteDatapoints to update the Index and the updates will be applied in corresponding DeployedIndexes in nearly real-time." + ], + "type": "string", + "enum": [ + "INDEX_UPDATE_METHOD_UNSPECIFIED", + "BATCH_UPDATE", + "STREAM_UPDATE" + ] + }, + "metadata": { + "description": "An additional information about the Index; the schema of the metadata can be found in metadata_schema.", + "type": "any" + }, + "metadataSchemaUri": { + "type": "string", + "description": "Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Index, that is specific to it. Unset if the Index does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access." + }, + "displayName": { + "type": "string", + "description": "Required. The display name of the Index. The name can be up to 128 characters long and can consist of any UTF-8 characters." + } + } + }, + "GoogleCloudAiplatformV1ExportDataOperationMetadata": { + "type": "object", + "description": "Runtime operation information for DatasetService.ExportData.", + "properties": { + "gcsOutputDirectory": { + "description": "A Google Cloud Storage directory which path ends with '/'. The exported data is stored in the directory.", + "type": "string" + }, + "genericMetadata": { + "description": "The common part of the operation metadata.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + }, + "id": "GoogleCloudAiplatformV1ExportDataOperationMetadata" + }, + "GoogleCloudAiplatformV1ToolCallValidInput": { + "description": "Input for tool call valid metric.", + "properties": { + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1ToolCallValidSpec", + "description": "Required. Spec for tool call valid metric." + }, + "instances": { + "description": "Required. Repeated tool call valid instances.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1ToolCallValidInstance" + } + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1ToolCallValidInput" + }, + "GoogleCloudAiplatformV1ErrorAnalysisAnnotationAttributedItem": { + "id": "GoogleCloudAiplatformV1ErrorAnalysisAnnotationAttributedItem", + "properties": { + "distance": { + "format": "double", + "description": "The distance of this item to the annotation.", + "type": "number" + }, + "annotationResourceName": { + "description": "The unique ID for each annotation. Used by FE to allocate the annotation in DB.", + "type": "string" + } + }, + "description": "Attributed items for a given annotation, typically representing neighbors from the training sets constrained by the query type.", + "type": "object" + }, + "GoogleCloudAiplatformV1BatchDedicatedResources": { + "id": "GoogleCloudAiplatformV1BatchDedicatedResources", + "type": "object", + "description": "A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration.", + "properties": { + "maxReplicaCount": { + "type": "integer", + "format": "int32", + "description": "Immutable. The maximum number of machine replicas the batch operation may be scaled to. The default value is 10." + }, + "startingReplicaCount": { + "description": "Immutable. The number of machine replicas used at the start of the batch operation. If not set, Vertex AI decides starting number, not greater than max_replica_count", + "format": "int32", + "type": "integer" + }, + "machineSpec": { + "description": "Required. Immutable. The specification of a single machine.", + "$ref": "GoogleCloudAiplatformV1MachineSpec" + } + } + }, + "GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatus": { + "id": "GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatus", + "properties": { + "updateTime": { + "description": "Output only. Update time of this status.", + "readOnly": true, + "format": "google-datetime", + "type": "string" + }, + "error": { + "$ref": "GoogleRpcStatus", + "description": "Output only. The error that occurred during the state. May be set when the state is any of the non-final state (PENDING/RUNNING/CANCELLING) or FAILED state. If the state is FAILED, the error here is final and not going to be retried. If the state is a non-final state, the error indicates a system-error being retried.", + "readOnly": true + }, + "state": { + "type": "string", + "enum": [ + "STATE_UNSPECIFIED", + "PENDING", + "RUNNING", + "SUCCEEDED", + "CANCEL_PENDING", + "CANCELLING", + "CANCELLED", + "FAILED", + "SKIPPED", + "NOT_TRIGGERED" + ], + "description": "Output only. The state of the task.", + "enumDescriptions": [ + "Unspecified.", + "Specifies pending state for the task.", + "Specifies task is being executed.", + "Specifies task completed successfully.", + "Specifies Task cancel is in pending state.", + "Specifies task is being cancelled.", + "Specifies task was cancelled.", + "Specifies task failed.", + "Specifies task was skipped due to cache hit.", + "Specifies that the task was not triggered because the task's trigger policy is not satisfied. The trigger policy is specified in the `condition` field of PipelineJob.pipeline_spec." + ], + "readOnly": true + } + }, + "description": "A single record of the task status.", + "type": "object" + }, + "GoogleCloudAiplatformV1QuestionAnsweringRelevanceInput": { + "id": "GoogleCloudAiplatformV1QuestionAnsweringRelevanceInput", + "type": "object", + "properties": { + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1QuestionAnsweringRelevanceSpec", + "description": "Required. Spec for question answering relevance score metric." + }, + "instance": { + "$ref": "GoogleCloudAiplatformV1QuestionAnsweringRelevanceInstance", + "description": "Required. Question answering relevance instance." + } + }, + "description": "Input for question answering relevance metric." + }, + "GoogleCloudAiplatformV1CreateNotebookExecutionJobOperationMetadata": { + "properties": { + "progressMessage": { + "description": "A human-readable message that shows the intermediate progress details of NotebookRuntime.", + "type": "string" + }, + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The operation generic information." + } + }, + "description": "Metadata information for NotebookService.CreateNotebookExecutionJob.", + "id": "GoogleCloudAiplatformV1CreateNotebookExecutionJobOperationMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1ExamplesOverride": { + "description": "Overrides for example-based explanations.", + "type": "object", + "properties": { + "restrictions": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1ExamplesRestrictionsNamespace" + }, + "description": "Restrict the resulting nearest neighbors to respect these constraints." + }, + "dataFormat": { + "description": "The format of the data being provided with each call.", + "type": "string", + "enum": [ + "DATA_FORMAT_UNSPECIFIED", + "INSTANCES", + "EMBEDDINGS" + ], + "enumDescriptions": [ + "Unspecified format. Must not be used.", + "Provided data is a set of model inputs.", + "Provided data is a set of embeddings." + ] + }, + "returnEmbeddings": { + "description": "If true, return the embeddings instead of neighbors.", + "type": "boolean" + }, + "crowdingCount": { + "type": "integer", + "description": "The number of neighbors to return that have the same crowding tag.", + "format": "int32" + }, + "neighborCount": { + "format": "int32", + "type": "integer", + "description": "The number of neighbors to return." + } + }, + "id": "GoogleCloudAiplatformV1ExamplesOverride" + }, + "GoogleCloudAiplatformV1ContainerRegistryDestination": { + "type": "object", + "description": "The Container Registry location for the container image.", + "properties": { + "outputUri": { + "type": "string", + "description": "Required. Container Registry URI of a container image. Only Google Container Registry and Artifact Registry are supported now. Accepted forms: * Google Container Registry path. For example: `gcr.io/projectId/imageName:tag`. * Artifact Registry path. For example: `us-central1-docker.pkg.dev/projectId/repoName/imageName:tag`. If a tag is not specified, \"latest\" will be used as the default tag." + } + }, + "id": "GoogleCloudAiplatformV1ContainerRegistryDestination" + }, + "GoogleCloudAiplatformV1CreatePersistentResourceOperationMetadata": { + "properties": { + "genericMetadata": { + "description": "Operation metadata for PersistentResource.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + }, + "progressMessage": { + "type": "string", + "description": "Progress Message for Create LRO" + } + }, + "type": "object", + "description": "Details of operations that perform create PersistentResource.", + "id": "GoogleCloudAiplatformV1CreatePersistentResourceOperationMetadata" + }, + "GoogleCloudAiplatformV1DeleteFeatureValuesRequest": { + "properties": { + "selectEntity": { + "$ref": "GoogleCloudAiplatformV1DeleteFeatureValuesRequestSelectEntity", + "description": "Select feature values to be deleted by specifying entities." + }, + "selectTimeRangeAndFeature": { + "$ref": "GoogleCloudAiplatformV1DeleteFeatureValuesRequestSelectTimeRangeAndFeature", + "description": "Select feature values to be deleted by specifying time range and features." + } + }, + "description": "Request message for FeaturestoreService.DeleteFeatureValues.", + "id": "GoogleCloudAiplatformV1DeleteFeatureValuesRequest", + "type": "object" + }, + "GoogleCloudAiplatformV1FetchFeatureValuesResponseFeatureNameValuePairListFeatureNameValuePair": { + "id": "GoogleCloudAiplatformV1FetchFeatureValuesResponseFeatureNameValuePairListFeatureNameValuePair", + "description": "Feature name & value pair.", + "properties": { + "name": { + "type": "string", + "description": "Feature short name." + }, + "value": { + "description": "Feature value.", + "$ref": "GoogleCloudAiplatformV1FeatureValue" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1FunctionDeclaration": { + "id": "GoogleCloudAiplatformV1FunctionDeclaration", + "type": "object", + "description": "Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name and parameters. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.", + "properties": { + "description": { + "type": "string", + "description": "Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function." + }, + "parameters": { + "$ref": "GoogleCloudAiplatformV1Schema", + "description": "Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1" + }, + "name": { + "type": "string", + "description": "Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots and dashes, with a maximum length of 64." + } + } + }, + "GoogleCloudAiplatformV1ModelContainerSpec": { + "properties": { + "healthRoute": { + "type": "string", + "description": "Immutable. HTTP path on the container to send health checks to. Vertex AI intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#health). For example, if you set this field to `/bar`, then Vertex AI intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/ DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)" + }, + "sharedMemorySizeMb": { + "format": "int64", + "description": "Immutable. The amount of the VM memory to reserve as the shared memory for the model in megabytes.", + "type": "string" + }, + "env": { + "items": { + "$ref": "GoogleCloudAiplatformV1EnvVar" + }, + "type": "array", + "description": "Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: ```json [ { \"name\": \"VAR_1\", \"value\": \"foo\" }, { \"name\": \"VAR_2\", \"value\": \"$(VAR_1) bar\" } ] ``` If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the `env` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core)." + }, + "imageUri": { + "type": "string", + "description": "Required. Immutable. URI of the Docker image to be used as the custom container for serving predictions. This URI must identify an image in Artifact Registry or Container Registry. Learn more about the [container publishing requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#publishing), including permissions requirements for the Vertex AI Service Agent. The container image is ingested upon ModelService.UploadModel, stored internally, and this original path is afterwards not used. To learn about the requirements for the Docker image itself, see [Custom container requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#). You can use the URI to one of Vertex AI's [pre-built container images for prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre-built-containers) in this field." + }, + "deploymentTimeout": { + "description": "Immutable. Deployment timeout. Limit for deployment timeout is 2 hours.", + "format": "google-duration", + "type": "string" + }, + "startupProbe": { + "$ref": "GoogleCloudAiplatformV1Probe", + "description": "Immutable. Specification for Kubernetes startup probe." + }, + "predictRoute": { + "description": "Immutable. HTTP path on the container to send prediction requests to. Vertex AI forwards requests sent using projects.locations.endpoints.predict to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response. For example, if you set this field to `/foo`, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)", + "type": "string" + }, + "command": { + "description": "Immutable. Specifies the command that runs when the container starts. This overrides the container's [ENTRYPOINT](https://docs.docker.com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s \"exec\" form, not its \"shell\" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the args field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).", + "type": "array", + "items": { + "type": "string" + } + }, + "grpcPorts": { + "items": { + "$ref": "GoogleCloudAiplatformV1Port" + }, + "description": "Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.", + "type": "array" + }, + "ports": { + "items": { + "$ref": "GoogleCloudAiplatformV1Port" + }, + "description": "Immutable. List of ports to expose from the container. Vertex AI sends any prediction requests that it receives to the first port on this list. Vertex AI also sends [liveness and health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#liveness) to this port. If you do not specify this field, it defaults to following value: ```json [ { \"containerPort\": 8080 } ] ``` Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).", + "type": "array" + }, + "healthProbe": { + "description": "Immutable. Specification for Kubernetes readiness probe.", + "$ref": "GoogleCloudAiplatformV1Probe" + }, + "args": { + "description": "Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s \"default parameters\" form. If you don't specify this field but do specify the command field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).", + "type": "array", + "items": { + "type": "string" + } + } + }, + "id": "GoogleCloudAiplatformV1ModelContainerSpec", + "type": "object", + "description": "Specification of a container for serving predictions. Some fields in this message correspond to fields in the [Kubernetes Container v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core)." + }, + "GoogleCloudAiplatformV1StructValue": { + "properties": { + "values": { + "items": { + "$ref": "GoogleCloudAiplatformV1StructFieldValue" + }, + "description": "A list of field values.", + "type": "array" + } + }, + "type": "object", + "description": "Struct (or object) type feature value.", + "id": "GoogleCloudAiplatformV1StructValue" + }, + "GoogleCloudAiplatformV1ExportFilterSplit": { + "properties": { + "validationFilter": { + "type": "string", + "description": "Required. A filter on DataItems of the Dataset. DataItems that match this filter are used to validate the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order." + }, + "testFilter": { + "description": "Required. A filter on DataItems of the Dataset. DataItems that match this filter are used to test the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.", + "type": "string" + }, + "trainingFilter": { + "type": "string", + "description": "Required. A filter on DataItems of the Dataset. DataItems that match this filter are used to train the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order." + } + }, + "id": "GoogleCloudAiplatformV1ExportFilterSplit", + "description": "Assigns input data to training, validation, and test sets based on the given filters, data pieces not matched by any filter are ignored. Currently only supported for Datasets containing DataItems. If any of the filters in this message are to match nothing, then they can be set as '-' (the minus sign). Supported only for unstructured Datasets.", + "type": "object" + }, + "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig": { + "properties": { + "driftThresholds": { + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1ThresholdConfig" + }, + "type": "object", + "description": "Key is the feature name and value is the threshold. If a feature needs to be monitored for drift, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between different time windws." + }, + "defaultDriftThreshold": { + "$ref": "GoogleCloudAiplatformV1ThresholdConfig", + "description": "Drift anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features." + }, + "attributionScoreDriftThresholds": { + "description": "Key is the feature name and value is the threshold. The threshold here is against attribution score distance between different time windows.", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1ThresholdConfig" + }, + "type": "object" + } + }, + "description": "The config for Prediction data drift detection.", + "type": "object", + "id": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig" + }, + "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessInput": { + "id": "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessInput", + "type": "object", + "properties": { + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessSpec", + "description": "Required. Spec for question answering helpfulness score metric." + }, + "instance": { + "description": "Required. Question answering helpfulness instance.", + "$ref": "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessInstance" + } + }, + "description": "Input for question answering helpfulness metric." + }, + "GoogleCloudAiplatformV1CreateIndexOperationMetadata": { + "type": "object", + "description": "Runtime operation information for IndexService.CreateIndex.", + "id": "GoogleCloudAiplatformV1CreateIndexOperationMetadata", + "properties": { + "nearestNeighborSearchOperationMetadata": { + "$ref": "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadata", + "description": "The operation metadata with regard to Matching Engine Index operation." + }, + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The operation generic information." + } + } + }, + "GoogleCloudAiplatformV1SchemaAnnotationSpecColor": { + "properties": { + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec represented by the color in the segmentation mask." + }, + "color": { + "description": "The color of the AnnotationSpec in a segmentation mask.", + "$ref": "GoogleTypeColor" + }, + "id": { + "type": "string", + "description": "The ID of the AnnotationSpec represented by the color in the segmentation mask." + } + }, + "type": "object", + "description": "An entry of mapping between color and AnnotationSpec. The mapping is used in segmentation mask.", + "id": "GoogleCloudAiplatformV1SchemaAnnotationSpecColor" + }, + "GoogleCloudAiplatformV1ReadFeatureValuesResponseFeatureDescriptor": { + "description": "Metadata for requested Features.", + "type": "object", + "properties": { + "id": { + "type": "string", + "description": "Feature ID." + } + }, + "id": "GoogleCloudAiplatformV1ReadFeatureValuesResponseFeatureDescriptor" + }, + "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDataset": { + "properties": { + "dataFormat": { + "description": "Data format of the dataset, only applicable if the input is from Google Cloud Storage. The possible formats are: \"tf-record\" The source file is a TFRecord file. \"csv\" The source file is a CSV file. \"jsonl\" The source file is a JSONL file.", + "type": "string" + }, + "gcsSource": { + "description": "The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.", + "$ref": "GoogleCloudAiplatformV1GcsSource" + }, + "loggingSamplingStrategy": { + "description": "Strategy to sample data from Training Dataset. If not set, we process the whole dataset.", + "$ref": "GoogleCloudAiplatformV1SamplingStrategy" + }, + "bigquerySource": { + "$ref": "GoogleCloudAiplatformV1BigQuerySource", + "description": "The BigQuery table of the unmanaged Dataset used to train this Model." + }, + "dataset": { + "description": "The resource name of the Dataset used to train this Model.", + "type": "string" + }, + "targetField": { + "description": "The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDataset", + "description": "Training Dataset information." + }, + "GoogleCloudAiplatformV1SchemaPredictInstanceVideoActionRecognitionPredictionInstance": { + "description": "Prediction input format for Video Action Recognition.", + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaPredictInstanceVideoActionRecognitionPredictionInstance", + "properties": { + "mimeType": { + "type": "string", + "description": "The MIME type of the content of the video. Only the following are supported: video/mp4 video/avi video/quicktime" + }, + "content": { + "description": "The Google Cloud Storage location of the video on which to perform the prediction.", + "type": "string" + }, + "timeSegmentEnd": { + "type": "string", + "description": "The end, exclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with \"s\" appended at the end. Fractions are allowed, up to a microsecond precision, and \"inf\" or \"Infinity\" is allowed, which means the end of the video." + }, + "timeSegmentStart": { + "description": "The beginning, inclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with \"s\" appended at the end. Fractions are allowed, up to a microsecond precision.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1BatchMigrateResourcesRequest": { + "id": "GoogleCloudAiplatformV1BatchMigrateResourcesRequest", + "type": "object", + "description": "Request message for MigrationService.BatchMigrateResources.", + "properties": { + "migrateResourceRequests": { + "items": { + "$ref": "GoogleCloudAiplatformV1MigrateResourceRequest" + }, + "type": "array", + "description": "Required. The request messages specifying the resources to migrate. They must be in the same location as the destination. Up to 50 resources can be migrated in one batch." + } + } + }, + "GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetail": { + "description": "The detail of a container execution. It contains the job names of the lifecycle of a container execution.", + "id": "GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetail", + "type": "object", + "properties": { + "failedPreCachingCheckJobs": { + "description": "Output only. The names of the previously failed CustomJob for the pre-caching-check container executions. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events. The list includes the all attempts in chronological order.", + "items": { + "type": "string" + }, + "readOnly": true, + "type": "array" + }, + "preCachingCheckJob": { + "readOnly": true, + "type": "string", + "description": "Output only. The name of the CustomJob for the pre-caching-check container execution. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events." + }, + "failedMainJobs": { + "description": "Output only. The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.", + "items": { + "type": "string" + }, + "type": "array", + "readOnly": true + }, + "mainJob": { + "type": "string", + "description": "Output only. The name of the CustomJob for the main container execution.", + "readOnly": true + } + } + }, + "CloudAiLargeModelsVisionMedia": { + "properties": { + "video": { + "description": "Video", + "$ref": "CloudAiLargeModelsVisionVideo" + }, + "image": { + "$ref": "CloudAiLargeModelsVisionImage", + "description": "Image." + } + }, + "description": "Media.", + "type": "object", + "id": "CloudAiLargeModelsVisionMedia" + }, + "GoogleCloudAiplatformV1Artifact": { + "id": "GoogleCloudAiplatformV1Artifact", + "description": "Instance of a general artifact.", + "properties": { + "schemaTitle": { + "type": "string", + "description": "The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store." + }, + "updateTime": { + "readOnly": true, + "description": "Output only. Timestamp when this Artifact was last updated.", + "type": "string", + "format": "google-datetime" + }, + "uri": { + "description": "The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.", + "type": "string" + }, + "metadata": { + "type": "object", + "additionalProperties": { + "description": "Properties of the object.", + "type": "any" + }, + "description": "Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB." + }, + "labels": { + "type": "object", + "additionalProperties": { + "type": "string" + }, + "description": "The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded)." + }, + "displayName": { + "type": "string", + "description": "User provided display name of the Artifact. May be up to 128 Unicode characters." + }, + "state": { + "description": "The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.", + "enumDescriptions": [ + "Unspecified state for the Artifact.", + "A state used by systems like Vertex AI Pipelines to indicate that the underlying data item represented by this Artifact is being created.", + "A state indicating that the Artifact should exist, unless something external to the system deletes it." + ], + "enum": [ + "STATE_UNSPECIFIED", + "PENDING", + "LIVE" + ], + "type": "string" + }, + "etag": { + "description": "An eTag used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "name": { + "readOnly": true, + "type": "string", + "description": "Output only. The resource name of the Artifact." + }, + "createTime": { + "description": "Output only. Timestamp when this Artifact was created.", + "readOnly": true, + "format": "google-datetime", + "type": "string" + }, + "schemaVersion": { + "description": "The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.", + "type": "string" + }, + "description": { + "description": "Description of the Artifact", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SafetyRating": { + "id": "GoogleCloudAiplatformV1SafetyRating", + "type": "object", + "description": "Safety rating corresponding to the generated content.", + "properties": { + "category": { + "enum": [ + "HARM_CATEGORY_UNSPECIFIED", + "HARM_CATEGORY_HATE_SPEECH", + "HARM_CATEGORY_DANGEROUS_CONTENT", + "HARM_CATEGORY_HARASSMENT", + "HARM_CATEGORY_SEXUALLY_EXPLICIT" + ], + "description": "Output only. Harm category.", + "type": "string", + "enumDescriptions": [ + "The harm category is unspecified.", + "The harm category is hate speech.", + "The harm category is dangerous content.", + "The harm category is harassment.", + "The harm category is sexually explicit content." + ], + "readOnly": true + }, + "probability": { + "readOnly": true, + "type": "string", + "enum": [ + "HARM_PROBABILITY_UNSPECIFIED", + "NEGLIGIBLE", + "LOW", + "MEDIUM", + "HIGH" + ], + "description": "Output only. Harm probability levels in the content.", + "enumDescriptions": [ + "Harm probability unspecified.", + "Negligible level of harm.", + "Low level of harm.", + "Medium level of harm.", + "High level of harm." + ] + }, + "blocked": { + "type": "boolean", + "description": "Output only. Indicates whether the content was filtered out because of this rating.", + "readOnly": true + }, + "severity": { + "enum": [ + "HARM_SEVERITY_UNSPECIFIED", + "HARM_SEVERITY_NEGLIGIBLE", + "HARM_SEVERITY_LOW", + "HARM_SEVERITY_MEDIUM", + "HARM_SEVERITY_HIGH" + ], + "type": "string", + "description": "Output only. Harm severity levels in the content.", + "enumDescriptions": [ + "Harm severity unspecified.", + "Negligible level of harm severity.", + "Low level of harm severity.", + "Medium level of harm severity.", + "High level of harm severity." + ], + "readOnly": true + }, + "probabilityScore": { + "format": "float", + "description": "Output only. Harm probability score.", + "readOnly": true, + "type": "number" + }, + "severityScore": { + "format": "float", + "description": "Output only. Harm severity score.", + "readOnly": true, + "type": "number" + } + } + }, + "GoogleCloudAiplatformV1CreateFeatureGroupOperationMetadata": { + "properties": { + "genericMetadata": { + "description": "Operation metadata for FeatureGroup.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + }, + "type": "object", + "description": "Details of operations that perform create FeatureGroup.", + "id": "GoogleCloudAiplatformV1CreateFeatureGroupOperationMetadata" + }, + "GoogleCloudAiplatformV1BatchCreateFeaturesRequest": { + "description": "Request message for FeaturestoreService.BatchCreateFeatures.", + "id": "GoogleCloudAiplatformV1BatchCreateFeaturesRequest", + "properties": { + "requests": { + "items": { + "$ref": "GoogleCloudAiplatformV1CreateFeatureRequest" + }, + "description": "Required. The request message specifying the Features to create. All Features must be created under the same parent EntityType. The `parent` field in each child request message can be omitted. If `parent` is set in a child request, then the value must match the `parent` value in this request message.", + "type": "array" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1ListNasJobsResponse": { + "properties": { + "nasJobs": { + "description": "List of NasJobs in the requested page. NasJob.nas_job_output of the jobs will not be returned.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1NasJob" + } + }, + "nextPageToken": { + "type": "string", + "description": "A token to retrieve the next page of results. Pass to ListNasJobsRequest.page_token to obtain that page." + } + }, + "description": "Response message for JobService.ListNasJobs", + "id": "GoogleCloudAiplatformV1ListNasJobsResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaPredictInstanceImageClassificationPredictionInstance": { + "type": "object", + "description": "Prediction input format for Image Classification.", + "properties": { + "mimeType": { + "description": "The MIME type of the content of the image. Only the images in below listed MIME types are supported. - image/jpeg - image/gif - image/png - image/webp - image/bmp - image/tiff - image/vnd.microsoft.icon", + "type": "string" + }, + "content": { + "type": "string", + "description": "The image bytes or Cloud Storage URI to make the prediction on." + } + }, + "id": "GoogleCloudAiplatformV1SchemaPredictInstanceImageClassificationPredictionInstance" + }, + "GoogleCloudAiplatformV1PurgeExecutionsRequest": { + "properties": { + "force": { + "description": "Optional. Flag to indicate to actually perform the purge. If `force` is set to false, the method will return a sample of Execution names that would be deleted.", + "type": "boolean" + }, + "filter": { + "type": "string", + "description": "Required. A required filter matching the Executions to be purged. E.g., `update_time \u003c= 2020-11-19T11:30:00-04:00`." + } + }, + "id": "GoogleCloudAiplatformV1PurgeExecutionsRequest", + "description": "Request message for MetadataService.PurgeExecutions.", + "type": "object" + }, + "GoogleCloudAiplatformV1SummarizationQualitySpec": { + "id": "GoogleCloudAiplatformV1SummarizationQualitySpec", + "properties": { + "useReference": { + "type": "boolean", + "description": "Optional. Whether to use instance.reference to compute summarization quality." + }, + "version": { + "format": "int32", + "description": "Optional. Which version to use for evaluation.", + "type": "integer" + } + }, + "description": "Spec for summarization quality score metric.", + "type": "object" + }, + "GoogleCloudAiplatformV1CancelPipelineJobRequest": { + "id": "GoogleCloudAiplatformV1CancelPipelineJobRequest", + "type": "object", + "properties": {}, + "description": "Request message for PipelineService.CancelPipelineJob." + }, + "GoogleCloudAiplatformV1ToolCallValidResults": { + "description": "Results for tool call valid metric.", + "id": "GoogleCloudAiplatformV1ToolCallValidResults", + "type": "object", + "properties": { + "toolCallValidMetricValues": { + "description": "Output only. Tool call valid metric values.", + "items": { + "$ref": "GoogleCloudAiplatformV1ToolCallValidMetricValue" + }, + "readOnly": true, + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1ResourcePool": { + "type": "object", + "properties": { + "replicaCount": { + "format": "int64", + "description": "Optional. The total number of machines to use for this resource pool.", + "type": "string" + }, + "machineSpec": { + "$ref": "GoogleCloudAiplatformV1MachineSpec", + "description": "Required. Immutable. The specification of a single machine." + }, + "usedReplicaCount": { + "type": "string", + "readOnly": true, + "description": "Output only. The number of machines currently in use by training jobs for this resource pool. Will replace idle_replica_count.", + "format": "int64" + }, + "id": { + "description": "Immutable. The unique ID in a PersistentResource for referring to this resource pool. User can specify it if necessary. Otherwise, it's generated automatically.", + "type": "string" + }, + "autoscalingSpec": { + "description": "Optional. Optional spec to configure GKE or Ray-on-Vertex autoscaling", + "$ref": "GoogleCloudAiplatformV1ResourcePoolAutoscalingSpec" + }, + "diskSpec": { + "description": "Optional. Disk spec for the machine in this node pool.", + "$ref": "GoogleCloudAiplatformV1DiskSpec" + } + }, + "description": "Represents the spec of a group of resources of the same type, for example machine type, disk, and accelerators, in a PersistentResource.", + "id": "GoogleCloudAiplatformV1ResourcePool" + }, + "GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpec": { + "type": "object", + "id": "GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpec", + "properties": { + "defaultValue": { + "type": "string", + "description": "A default value for a `CATEGORICAL` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline." + }, + "values": { + "items": { + "type": "string" + }, + "description": "Required. The list of possible categories.", + "type": "array" + } + }, + "description": "Value specification for a parameter in `CATEGORICAL` type." + }, + "GoogleCloudAiplatformV1Tool": { + "id": "GoogleCloudAiplatformV1Tool", + "properties": { + "googleSearchRetrieval": { + "$ref": "GoogleCloudAiplatformV1GoogleSearchRetrieval", + "description": "Optional. GoogleSearchRetrieval tool type. Specialized retrieval tool that is powered by Google search." + }, + "retrieval": { + "$ref": "GoogleCloudAiplatformV1Retrieval", + "description": "Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation." + }, + "functionDeclarations": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1FunctionDeclaration" + }, + "description": "Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 64 function declarations can be provided." + } + }, + "description": "Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).", + "type": "object" + }, + "GoogleCloudAiplatformV1SummarizationHelpfulnessSpec": { + "id": "GoogleCloudAiplatformV1SummarizationHelpfulnessSpec", + "description": "Spec for summarization helpfulness score metric.", + "type": "object", + "properties": { + "useReference": { + "type": "boolean", + "description": "Optional. Whether to use instance.reference to compute summarization helpfulness." + }, + "version": { + "type": "integer", + "format": "int32", + "description": "Optional. Which version to use for evaluation." + } + } + }, + "GoogleCloudAiplatformV1WriteTensorboardExperimentDataRequest": { + "id": "GoogleCloudAiplatformV1WriteTensorboardExperimentDataRequest", + "description": "Request message for TensorboardService.WriteTensorboardExperimentData.", + "type": "object", + "properties": { + "writeRunDataRequests": { + "description": "Required. Requests containing per-run TensorboardTimeSeries data to write.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1WriteTensorboardRunDataRequest" + } + } + } + }, + "GoogleCloudAiplatformV1NotebookIdleShutdownConfig": { + "description": "The idle shutdown configuration of NotebookRuntimeTemplate, which contains the idle_timeout as required field.", + "properties": { + "idleShutdownDisabled": { + "description": "Whether Idle Shutdown is disabled in this NotebookRuntimeTemplate.", + "type": "boolean" + }, + "idleTimeout": { + "type": "string", + "format": "google-duration", + "description": "Required. Duration is accurate to the second. In Notebook, Idle Timeout is accurate to minute so the range of idle_timeout (second) is: 10 * 60 ~ 1440 * 60." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1NotebookIdleShutdownConfig" + }, + "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessInstance": { + "type": "object", + "id": "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessInstance", + "properties": { + "reference": { + "type": "string", + "description": "Optional. Ground truth used to compare against the prediction." + }, + "instruction": { + "type": "string", + "description": "Required. The question asked and other instruction in the inference prompt." + }, + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + }, + "context": { + "type": "string", + "description": "Optional. Text provided as context to answer the question." + } + }, + "description": "Spec for question answering correctness instance." + }, + "GoogleCloudAiplatformV1CreateFeatureOperationMetadata": { + "type": "object", + "description": "Details of operations that perform create Feature.", + "id": "GoogleCloudAiplatformV1CreateFeatureOperationMetadata", + "properties": { + "genericMetadata": { + "description": "Operation metadata for Feature.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + } + }, + "GoogleCloudAiplatformV1SchemaPredictPredictionTftFeatureImportance": { + "id": "GoogleCloudAiplatformV1SchemaPredictPredictionTftFeatureImportance", + "type": "object", + "properties": { + "contextWeights": { + "type": "array", + "items": { + "type": "number", + "format": "float" + }, + "description": "TFT feature importance values. Each pair for {context/horizon/attribute} should have the same shape since the weight corresponds to the column names." + }, + "contextColumns": { + "items": { + "type": "string" + }, + "type": "array" + }, + "horizonColumns": { + "items": { + "type": "string" + }, + "type": "array" + }, + "attributeColumns": { + "type": "array", + "items": { + "type": "string" + } + }, + "attributeWeights": { + "items": { + "format": "float", + "type": "number" + }, + "type": "array" + }, + "horizonWeights": { + "type": "array", + "items": { + "format": "float", + "type": "number" + } + } + } + }, + "GoogleCloudAiplatformV1UnmanagedContainerModel": { + "type": "object", + "properties": { + "containerSpec": { + "$ref": "GoogleCloudAiplatformV1ModelContainerSpec", + "description": "Input only. The specification of the container that is to be used when deploying this Model." + }, + "predictSchemata": { + "$ref": "GoogleCloudAiplatformV1PredictSchemata", + "description": "Contains the schemata used in Model's predictions and explanations" + }, + "artifactUri": { + "type": "string", + "description": "The path to the directory containing the Model artifact and any of its supporting files." + } + }, + "description": "Contains model information necessary to perform batch prediction without requiring a full model import.", + "id": "GoogleCloudAiplatformV1UnmanagedContainerModel" + }, + "GoogleCloudAiplatformV1CopyModelOperationMetadata": { + "description": "Details of ModelService.CopyModel operation.", + "type": "object", + "id": "GoogleCloudAiplatformV1CopyModelOperationMetadata", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The common part of the operation metadata." + } + } + }, + "GoogleCloudAiplatformV1SchemaVideoObjectTrackingAnnotation": { + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaVideoObjectTrackingAnnotation", + "properties": { + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that this Annotation pertains to." + }, + "yMax": { + "format": "double", + "type": "number", + "description": "The bottommost coordinate of the bounding box." + }, + "xMin": { + "type": "number", + "format": "double", + "description": "The leftmost coordinate of the bounding box." + }, + "xMax": { + "format": "double", + "type": "number", + "description": "The rightmost coordinate of the bounding box." + }, + "instanceId": { + "type": "string", + "description": "The instance of the object, expressed as a positive integer. Used to track the same object across different frames.", + "format": "int64" + }, + "timeOffset": { + "description": "A time (frame) of a video to which this annotation pertains. Represented as the duration since the video's start.", + "type": "string", + "format": "google-duration" + }, + "annotationSpecId": { + "type": "string", + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." + }, + "yMin": { + "format": "double", + "type": "number", + "description": "The topmost coordinate of the bounding box." + } + }, + "description": "Annotation details specific to video object tracking." + }, + "GoogleCloudAiplatformV1ToolNameMatchResults": { + "type": "object", + "description": "Results for tool name match metric.", + "id": "GoogleCloudAiplatformV1ToolNameMatchResults", + "properties": { + "toolNameMatchMetricValues": { + "readOnly": true, + "type": "array", + "description": "Output only. Tool name match metric values.", + "items": { + "$ref": "GoogleCloudAiplatformV1ToolNameMatchMetricValue" + } + } + } + }, + "GoogleCloudAiplatformV1ListOptimalTrialsRequest": { + "type": "object", + "description": "Request message for VizierService.ListOptimalTrials.", + "id": "GoogleCloudAiplatformV1ListOptimalTrialsRequest", + "properties": {} + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsRegressionEvaluationMetrics": { + "type": "object", + "properties": { + "rootMeanSquaredLogError": { + "description": "Root mean squared log error. Undefined when there are negative ground truth values or predictions.", + "type": "number", + "format": "float" + }, + "rSquared": { + "format": "float", + "type": "number", + "description": "Coefficient of determination as Pearson correlation coefficient. Undefined when ground truth or predictions are constant or near constant." + }, + "meanAbsoluteError": { + "format": "float", + "type": "number", + "description": "Mean Absolute Error (MAE)." + }, + "rootMeanSquaredError": { + "format": "float", + "type": "number", + "description": "Root Mean Squared Error (RMSE)." + }, + "meanAbsolutePercentageError": { + "format": "float", + "description": "Mean absolute percentage error. Infinity when there are zeros in the ground truth.", + "type": "number" + } + }, + "description": "Metrics for regression evaluation results.", + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsRegressionEvaluationMetrics" + }, + "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualityInput": { + "properties": { + "instance": { + "description": "Required. Pairwise question answering quality instance.", + "$ref": "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualityInstance" + }, + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualitySpec", + "description": "Required. Spec for pairwise question answering quality score metric." + } + }, + "description": "Input for pairwise question answering quality metric.", + "id": "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualityInput", + "type": "object" + }, + "GoogleCloudAiplatformV1MigrateResourceRequestMigrateAutomlModelConfig": { + "description": "Config for migrating Model in automl.googleapis.com to Vertex AI's Model.", + "type": "object", + "id": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateAutomlModelConfig", + "properties": { + "modelDisplayName": { + "type": "string", + "description": "Optional. Display name of the model in Vertex AI. System will pick a display name if unspecified." + }, + "model": { + "description": "Required. Full resource name of automl Model. Format: `projects/{project}/locations/{location}/models/{model}`.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1ThresholdConfig": { + "type": "object", + "description": "The config for feature monitoring threshold.", + "properties": { + "value": { + "type": "number", + "description": "Specify a threshold value that can trigger the alert. If this threshold config is for feature distribution distance: 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.", + "format": "double" + } + }, + "id": "GoogleCloudAiplatformV1ThresholdConfig" + }, + "GoogleCloudAiplatformV1SchemaPredictPredictionImageSegmentationPredictionResult": { + "type": "object", + "properties": { + "confidenceMask": { + "type": "string", + "description": "A one channel image which is encoded as an 8bit lossless PNG. The size of the image will be the same as the original image. For a specific pixel, darker color means less confidence in correctness of the cateogry in the categoryMask for the corresponding pixel. Black means no confidence and white means complete confidence." + }, + "categoryMask": { + "description": "A PNG image where each pixel in the mask represents the category in which the pixel in the original image was predicted to belong to. The size of this image will be the same as the original image. The mapping between the AnntoationSpec and the color can be found in model's metadata. The model will choose the most likely category and if none of the categories reach the confidence threshold, the pixel will be marked as background.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SchemaPredictPredictionImageSegmentationPredictionResult", + "description": "Prediction output format for Image Segmentation." + }, + "GoogleCloudAiplatformV1FeatureOnlineStoreDedicatedServingEndpoint": { + "type": "object", + "id": "GoogleCloudAiplatformV1FeatureOnlineStoreDedicatedServingEndpoint", + "properties": { + "publicEndpointDomainName": { + "type": "string", + "readOnly": true, + "description": "Output only. This field will be populated with the domain name to use for this FeatureOnlineStore" + }, + "privateServiceConnectConfig": { + "description": "Optional. Private service connect config. The private service connection is available only for Optimized storage type, not for embedding management now. If PrivateServiceConnectConfig.enable_private_service_connect set to true, customers will use private service connection to send request. Otherwise, the connection will set to public endpoint.", + "$ref": "GoogleCloudAiplatformV1PrivateServiceConnectConfig" + }, + "serviceAttachment": { + "readOnly": true, + "type": "string", + "description": "Output only. The name of the service attachment resource. Populated if private service connect is enabled and after FeatureViewSync is created." + } + }, + "description": "The dedicated serving endpoint for this FeatureOnlineStore. Only need to set when you choose Optimized storage type. Public endpoint is provisioned by default." + }, + "GoogleCloudAiplatformV1ToolParameterKeyMatchResults": { + "description": "Results for tool parameter key match metric.", + "type": "object", + "id": "GoogleCloudAiplatformV1ToolParameterKeyMatchResults", + "properties": { + "toolParameterKeyMatchMetricValues": { + "type": "array", + "description": "Output only. Tool parameter key match metric values.", + "items": { + "$ref": "GoogleCloudAiplatformV1ToolParameterKeyMatchMetricValue" + }, + "readOnly": true + } + } + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingMetadata": { + "properties": { + "trainCostMilliNodeHours": { + "type": "string", + "format": "int64", + "description": "Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget." + }, + "evaluatedDataItemsBigqueryUri": { + "type": "string", + "description": "BigQuery destination uri for exported evaluated examples." + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingMetadata", + "description": "Model metadata specific to TFT Forecasting.", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecasting": { + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecasting", + "properties": { + "metadata": { + "description": "The metadata information.", + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingMetadata" + }, + "inputs": { + "description": "The input parameters of this TrainingJob.", + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputs" + } + }, + "type": "object", + "description": "A TrainingJob that trains and uploads an AutoML Forecasting Model." + }, + "GoogleCloudAiplatformV1NotebookRuntimeTemplate": { + "description": "A template that specifies runtime configurations such as machine type, runtime version, network configurations, etc. Multiple runtimes can be created from a runtime template.", + "properties": { + "serviceAccount": { + "description": "The service account that the runtime workload runs as. You can use any service account within the same project, but you must have the service account user permission to use the instance. If not specified, the [Compute Engine default service account](https://cloud.google.com/compute/docs/access/service-accounts#default_service_account) is used.", + "type": "string" + }, + "notebookRuntimeType": { + "type": "string", + "description": "Optional. Immutable. The type of the notebook runtime template.", + "enum": [ + "NOTEBOOK_RUNTIME_TYPE_UNSPECIFIED", + "USER_DEFINED", + "ONE_CLICK" + ], + "enumDescriptions": [ + "Unspecified notebook runtime type, NotebookRuntimeType will default to USER_DEFINED.", + "runtime or template with coustomized configurations from user.", + "runtime or template with system defined configurations." + ] + }, + "encryptionSpec": { + "description": "Customer-managed encryption key spec for the notebook runtime.", + "$ref": "GoogleCloudAiplatformV1EncryptionSpec" + }, + "name": { + "description": "The resource name of the NotebookRuntimeTemplate.", + "type": "string" + }, + "etag": { + "type": "string", + "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + }, + "machineSpec": { + "$ref": "GoogleCloudAiplatformV1MachineSpec", + "description": "Optional. Immutable. The specification of a single machine for the template." + }, + "dataPersistentDiskSpec": { + "description": "Optional. The specification of persistent disk attached to the runtime as data disk storage.", + "$ref": "GoogleCloudAiplatformV1PersistentDiskSpec" + }, + "updateTime": { + "type": "string", + "format": "google-datetime", + "description": "Output only. Timestamp when this NotebookRuntimeTemplate was most recently updated.", + "readOnly": true + }, + "eucConfig": { + "$ref": "GoogleCloudAiplatformV1NotebookEucConfig", + "description": "EUC configuration of the NotebookRuntimeTemplate." + }, + "networkTags": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Optional. The Compute Engine tags to add to runtime (see [Tagging instances](https://cloud.google.com/vpc/docs/add-remove-network-tags))." + }, + "createTime": { + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Timestamp when this NotebookRuntimeTemplate was created.", + "type": "string" + }, + "idleShutdownConfig": { + "$ref": "GoogleCloudAiplatformV1NotebookIdleShutdownConfig", + "description": "The idle shutdown configuration of NotebookRuntimeTemplate. This config will only be set when idle shutdown is enabled." + }, + "shieldedVmConfig": { + "description": "Optional. Immutable. Runtime Shielded VM spec.", + "$ref": "GoogleCloudAiplatformV1ShieldedVmConfig" + }, + "displayName": { + "type": "string", + "description": "Required. The display name of the NotebookRuntimeTemplate. The name can be up to 128 characters long and can consist of any UTF-8 characters." + }, + "description": { + "type": "string", + "description": "The description of the NotebookRuntimeTemplate." + }, + "isDefault": { + "description": "Output only. The default template to use if not specified.", + "readOnly": true, + "type": "boolean" + }, + "labels": { + "description": "The labels with user-defined metadata to organize the NotebookRuntimeTemplates. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "networkSpec": { + "$ref": "GoogleCloudAiplatformV1NetworkSpec", + "description": "Optional. Network spec." + } + }, + "id": "GoogleCloudAiplatformV1NotebookRuntimeTemplate", + "type": "object" + }, + "GoogleCloudAiplatformV1DedicatedResources": { + "id": "GoogleCloudAiplatformV1DedicatedResources", + "type": "object", + "description": "A description of resources that are dedicated to a DeployedModel, and that need a higher degree of manual configuration.", + "properties": { + "autoscalingMetricSpecs": { + "description": "Immutable. The metric specifications that overrides a resource utilization metric (CPU utilization, accelerator's duty cycle, and so on) target value (default to 60 if not set). At most one entry is allowed per metric. If machine_spec.accelerator_count is above 0, the autoscaling will be based on both CPU utilization and accelerator's duty cycle metrics and scale up when either metrics exceeds its target value while scale down if both metrics are under their target value. The default target value is 60 for both metrics. If machine_spec.accelerator_count is 0, the autoscaling will be based on CPU utilization metric only with default target value 60 if not explicitly set. For example, in the case of Online Prediction, if you want to override target CPU utilization to 80, you should set autoscaling_metric_specs.metric_name to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and autoscaling_metric_specs.target to `80`.", + "items": { + "$ref": "GoogleCloudAiplatformV1AutoscalingMetricSpec" + }, + "type": "array" + }, + "minReplicaCount": { + "format": "int32", + "type": "integer", + "description": "Required. Immutable. The minimum number of machine replicas this DeployedModel will be always deployed on. This value must be greater than or equal to 1. If traffic against the DeployedModel increases, it may dynamically be deployed onto more replicas, and as traffic decreases, some of these extra replicas may be freed." + }, + "machineSpec": { + "description": "Required. Immutable. The specification of a single machine used by the prediction.", + "$ref": "GoogleCloudAiplatformV1MachineSpec" + }, + "maxReplicaCount": { + "type": "integer", + "description": "Immutable. The maximum number of replicas this DeployedModel may be deployed on when the traffic against it increases. If the requested value is too large, the deployment will error, but if deployment succeeds then the ability to scale the model to that many replicas is guaranteed (barring service outages). If traffic against the DeployedModel increases beyond what its replicas at maximum may handle, a portion of the traffic will be dropped. If this value is not provided, will use min_replica_count as the default value. The value of this field impacts the charge against Vertex CPU and GPU quotas. Specifically, you will be charged for (max_replica_count * number of cores in the selected machine type) and (max_replica_count * number of GPUs per replica in the selected machine type).", + "format": "int32" + } + } + }, + "GoogleCloudAiplatformV1ListFeatureViewSyncsResponse": { + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token, which can be sent as ListFeatureViewSyncsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages." + }, + "featureViewSyncs": { + "description": "The FeatureViewSyncs matching the request.", + "items": { + "$ref": "GoogleCloudAiplatformV1FeatureViewSync" + }, + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1ListFeatureViewSyncsResponse", + "description": "Response message for FeatureOnlineStoreAdminService.ListFeatureViewSyncs.", + "type": "object" + }, + "GoogleCloudAiplatformV1UndeployModelRequest": { + "id": "GoogleCloudAiplatformV1UndeployModelRequest", + "description": "Request message for EndpointService.UndeployModel.", + "properties": { + "trafficSplit": { + "type": "object", + "additionalProperties": { + "format": "int32", + "type": "integer" + }, + "description": "If this field is provided, then the Endpoint's traffic_split will be overwritten with it. If last DeployedModel is being undeployed from the Endpoint, the [Endpoint.traffic_split] will always end up empty when this call returns. A DeployedModel will be successfully undeployed only if it doesn't have any traffic assigned to it when this method executes, or if this field unassigns any traffic to it." + }, + "deployedModelId": { + "description": "Required. The ID of the DeployedModel to be undeployed from the Endpoint.", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpecSliceConfig": { + "id": "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpecSliceConfig", + "properties": { + "allValues": { + "type": "boolean", + "description": "If all_values is set to true, then all possible labels of the keyed feature will have another slice computed. Example: `{\"all_values\":{\"value\":true}}`" + }, + "value": { + "$ref": "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpecValue", + "description": "A unique specific value for a given feature. Example: `{ \"value\": { \"string_value\": \"12345\" } }`" + }, + "range": { + "$ref": "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpecRange", + "description": "A range of values for a numerical feature. Example: `{\"range\":{\"low\":10000.0,\"high\":50000.0}}` will capture 12345 and 23334 in the slice." + } + }, + "description": "Specification message containing the config for this SliceSpec. When `kind` is selected as `value` and/or `range`, only a single slice will be computed. When `all_values` is present, a separate slice will be computed for each possible label/value for the corresponding key in `config`. Examples, with feature zip_code with values 12345, 23334, 88888 and feature country with values \"US\", \"Canada\", \"Mexico\" in the dataset: Example 1: { \"zip_code\": { \"value\": { \"float_value\": 12345.0 } } } A single slice for any data with zip_code 12345 in the dataset. Example 2: { \"zip_code\": { \"range\": { \"low\": 12345, \"high\": 20000 } } } A single slice containing data where the zip_codes between 12345 and 20000 For this example, data with the zip_code of 12345 will be in this slice. Example 3: { \"zip_code\": { \"range\": { \"low\": 10000, \"high\": 20000 } }, \"country\": { \"value\": { \"string_value\": \"US\" } } } A single slice containing data where the zip_codes between 10000 and 20000 has the country \"US\". For this example, data with the zip_code of 12345 and country \"US\" will be in this slice. Example 4: { \"country\": {\"all_values\": { \"value\": true } } } Three slices are computed, one for each unique country in the dataset. Example 5: { \"country\": { \"all_values\": { \"value\": true } }, \"zip_code\": { \"value\": { \"float_value\": 12345.0 } } } Three slices are computed, one for each unique country in the dataset where the zip_code is also 12345. For this example, data with zip_code 12345 and country \"US\" will be in one slice, zip_code 12345 and country \"Canada\" in another slice, and zip_code 12345 and country \"Mexico\" in another slice, totaling 3 slices.", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadataBigQuerySource": { + "properties": { + "uri": { + "type": "string", + "description": "The URI of a BigQuery table." + } + }, + "id": "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadataBigQuerySource", + "type": "object" + }, + "GoogleCloudAiplatformV1IndexDatapointRestriction": { + "properties": { + "allowList": { + "items": { + "type": "string" + }, + "description": "The attributes to allow in this namespace. e.g.: 'red'", + "type": "array" + }, + "denyList": { + "description": "The attributes to deny in this namespace. e.g.: 'blue'", + "type": "array", + "items": { + "type": "string" + } + }, + "namespace": { + "type": "string", + "description": "The namespace of this restriction. e.g.: color." + } + }, + "id": "GoogleCloudAiplatformV1IndexDatapointRestriction", + "type": "object", + "description": "Restriction of a datapoint which describe its attributes(tokens) from each of several attribute categories(namespaces)." + }, + "GoogleCloudAiplatformV1FilterSplit": { + "properties": { + "trainingFilter": { + "description": "Required. A filter on DataItems of the Dataset. DataItems that match this filter are used to train the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.", + "type": "string" + }, + "testFilter": { + "description": "Required. A filter on DataItems of the Dataset. DataItems that match this filter are used to test the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.", + "type": "string" + }, + "validationFilter": { + "type": "string", + "description": "Required. A filter on DataItems of the Dataset. DataItems that match this filter are used to validate the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1FilterSplit", + "description": "Assigns input data to training, validation, and test sets based on the given filters, data pieces not matched by any filter are ignored. Currently only supported for Datasets containing DataItems. If any of the filters in this message are to match nothing, then they can be set as '-' (the minus sign). Supported only for unstructured Datasets. " + }, + "GoogleCloudAiplatformV1PublisherModelCallToActionOpenNotebooks": { + "properties": { + "notebooks": { + "description": "Required. Regional resource references to notebooks.", + "items": { + "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences" + }, + "type": "array" + } + }, + "type": "object", + "description": "Open notebooks.", + "id": "GoogleCloudAiplatformV1PublisherModelCallToActionOpenNotebooks" + }, + "GoogleCloudAiplatformV1CreateRegistryFeatureOperationMetadata": { + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "Operation metadata for Feature." + } + }, + "type": "object", + "description": "Details of operations that perform create FeatureGroup.", + "id": "GoogleCloudAiplatformV1CreateRegistryFeatureOperationMetadata" + }, + "GoogleCloudAiplatformV1FeatureViewSyncSyncSummary": { + "description": "Summary from the Sync job. For continuous syncs, the summary is updated periodically. For batch syncs, it gets updated on completion of the sync.", + "properties": { + "totalSlot": { + "description": "Output only. BigQuery slot milliseconds consumed for the sync job.", + "format": "int64", + "readOnly": true, + "type": "string" + }, + "rowSynced": { + "description": "Output only. Total number of rows synced.", + "readOnly": true, + "format": "int64", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1FeatureViewSyncSyncSummary", + "type": "object" + }, + "GoogleCloudAiplatformV1Explanation": { + "properties": { + "attributions": { + "items": { + "$ref": "GoogleCloudAiplatformV1Attribution" + }, + "type": "array", + "description": "Output only. Feature attributions grouped by predicted outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. Attribution.output_index can be used to identify which output this attribution is explaining. By default, we provide Shapley values for the predicted class. However, you can configure the explanation request to generate Shapley values for any other classes too. For example, if a model predicts a probability of `0.4` for approving a loan application, the model's decision is to reject the application since `p(reject) = 0.6 \u003e p(approve) = 0.4`, and the default Shapley values would be computed for rejection decision and not approval, even though the latter might be the positive class. If users set ExplanationParameters.top_k, the attributions are sorted by instance_output_value in descending order. If ExplanationParameters.output_indices is specified, the attributions are stored by Attribution.output_index in the same order as they appear in the output_indices.", + "readOnly": true + }, + "neighbors": { + "description": "Output only. List of the nearest neighbors for example-based explanations. For models deployed with the examples explanations feature enabled, the attributions field is empty and instead the neighbors field is populated.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1Neighbor" + }, + "readOnly": true + } + }, + "type": "object", + "description": "Explanation of a prediction (provided in PredictResponse.predictions) produced by the Model on a given instance.", + "id": "GoogleCloudAiplatformV1Explanation" + }, + "GoogleCloudAiplatformV1WriteTensorboardExperimentDataResponse": { + "description": "Response message for TensorboardService.WriteTensorboardExperimentData.", + "id": "GoogleCloudAiplatformV1WriteTensorboardExperimentDataResponse", + "type": "object", + "properties": {} + }, + "GoogleCloudAiplatformV1SearchNearestEntitiesRequest": { + "type": "object", + "properties": { + "query": { + "$ref": "GoogleCloudAiplatformV1NearestNeighborQuery", + "description": "Required. The query." + }, + "returnFullEntity": { + "description": "Optional. If set to true, the full entities (including all vector values and metadata) of the nearest neighbors are returned; otherwise only entity id of the nearest neighbors will be returned. Note that returning full entities will significantly increase the latency and cost of the query.", + "type": "boolean" + } + }, + "id": "GoogleCloudAiplatformV1SearchNearestEntitiesRequest", + "description": "The request message for FeatureOnlineStoreService.SearchNearestEntities." + }, + "GoogleCloudAiplatformV1ListEndpointsResponse": { + "description": "Response message for EndpointService.ListEndpoints.", + "id": "GoogleCloudAiplatformV1ListEndpointsResponse", + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token to retrieve the next page of results. Pass to ListEndpointsRequest.page_token to obtain that page." + }, + "endpoints": { + "description": "List of Endpoints in the requested page.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1Endpoint" + } + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1AddContextChildrenResponse": { + "description": "Response message for MetadataService.AddContextChildren.", + "type": "object", + "properties": {}, + "id": "GoogleCloudAiplatformV1AddContextChildrenResponse" + }, + "GoogleCloudAiplatformV1FeatureOnlineStoreBigtable": { + "properties": { + "autoScaling": { + "$ref": "GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScaling", + "description": "Required. Autoscaling config applied to Bigtable Instance." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1FeatureOnlineStoreBigtable" + }, + "GoogleCloudAiplatformV1BatchPredictionJobInstanceConfig": { + "properties": { + "includedFields": { + "description": "Fields that will be included in the prediction instance that is sent to the Model. If instance_type is `array`, the order of field names in included_fields also determines the order of the values in the array. When included_fields is populated, excluded_fields must be empty. The input must be JSONL with objects at each line, BigQuery or TfRecord.", + "items": { + "type": "string" + }, + "type": "array" + }, + "excludedFields": { + "type": "array", + "description": "Fields that will be excluded in the prediction instance that is sent to the Model. Excluded will be attached to the batch prediction output if key_field is not specified. When excluded_fields is populated, included_fields must be empty. The input must be JSONL with objects at each line, BigQuery or TfRecord.", + "items": { + "type": "string" + } + }, + "instanceType": { + "type": "string", + "description": "The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format. Supported values are: * `object`: Each input is converted to JSON object format. * For `bigquery`, each row is converted to an object. * For `jsonl`, each line of the JSONL input must be an object. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. * `array`: Each input is converted to JSON array format. * For `bigquery`, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders. * For `jsonl`, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. If not specified, Vertex AI converts the batch prediction input as follows: * For `bigquery` and `csv`, the behavior is the same as `array`. The order of columns is the same as defined in the file or table, unless included_fields is populated. * For `jsonl`, the prediction instance format is determined by each line of the input. * For `tf-record`/`tf-record-gzip`, each record will be converted to an object in the format of `{\"b64\": }`, where `` is the Base64-encoded string of the content of the record. * For `file-list`, each file in the list will be converted to an object in the format of `{\"b64\": }`, where `` is the Base64-encoded string of the content of the file." + }, + "keyField": { + "description": "The name of the field that is considered as a key. The values identified by the key field is not included in the transformed instances that is sent to the Model. This is similar to specifying this name of the field in excluded_fields. In addition, the batch prediction output will not include the instances. Instead the output will only include the value of the key field, in a field named `key` in the output: * For `jsonl` output format, the output will have a `key` field instead of the `instance` field. * For `csv`/`bigquery` output format, the output will have have a `key` column instead of the instance feature columns. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1BatchPredictionJobInstanceConfig", + "description": "Configuration defining how to transform batch prediction input instances to the instances that the Model accepts.", + "type": "object" + }, + "GoogleCloudAiplatformV1UpdateExplanationDatasetRequest": { + "id": "GoogleCloudAiplatformV1UpdateExplanationDatasetRequest", + "type": "object", + "properties": { + "examples": { + "description": "The example config containing the location of the dataset.", + "$ref": "GoogleCloudAiplatformV1Examples" + } + }, + "description": "Request message for ModelService.UpdateExplanationDataset." + }, + "GoogleCloudAiplatformV1GenericOperationMetadata": { + "id": "GoogleCloudAiplatformV1GenericOperationMetadata", + "type": "object", + "description": "Generic Metadata shared by all operations.", + "properties": { + "createTime": { + "description": "Output only. Time when the operation was created.", + "format": "google-datetime", + "readOnly": true, + "type": "string" + }, + "partialFailures": { + "type": "array", + "items": { + "$ref": "GoogleRpcStatus" + }, + "readOnly": true, + "description": "Output only. Partial failures encountered. E.g. single files that couldn't be read. This field should never exceed 20 entries. Status details field will contain standard Google Cloud error details." + }, + "updateTime": { + "readOnly": true, + "format": "google-datetime", + "type": "string", + "description": "Output only. Time when the operation was updated for the last time. If the operation has finished (successfully or not), this is the finish time." + } + } + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextTransformation": { + "type": "object", + "description": "Training pipeline will perform following transformation functions. * The text as is--no change to case, punctuation, spelling, tense, and so on. * Tokenize text to words. Convert each words to a dictionary lookup index and generate an embedding for each index. Combine the embedding of all elements into a single embedding using the mean. * Tokenization is based on unicode script boundaries. * Missing values get their own lookup index and resulting embedding. * Stop-words receive no special treatment and are not removed.", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextTransformation", + "properties": { + "columnName": { + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessSpec": { + "type": "object", + "properties": { + "version": { + "type": "integer", + "description": "Optional. Which version to use for evaluation.", + "format": "int32" + }, + "useReference": { + "type": "boolean", + "description": "Optional. Whether to use instance.reference to compute question answering correctness." + } + }, + "description": "Spec for question answering correctness metric.", + "id": "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessSpec" + }, + "CloudAiLargeModelsVisionImageRAIScores": { + "type": "object", + "id": "CloudAiLargeModelsVisionImageRAIScores", + "description": "RAI scores for generated image returned.", + "properties": { + "agileWatermarkDetectionScore": { + "description": "Agile watermark score for image.", + "format": "double", + "type": "number" + } + } + }, + "GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroup": { + "type": "object", + "description": "Features belonging to a single feature group that will be synced to Online Store.", + "properties": { + "featureIds": { + "description": "Required. Identifiers of features under the feature group.", + "type": "array", + "items": { + "type": "string" + } + }, + "featureGroupId": { + "description": "Required. Identifier of the feature group.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroup" + }, + "GoogleCloudAiplatformV1BatchImportEvaluatedAnnotationsResponse": { + "description": "Response message for ModelService.BatchImportEvaluatedAnnotations", + "id": "GoogleCloudAiplatformV1BatchImportEvaluatedAnnotationsResponse", + "type": "object", + "properties": { + "importedEvaluatedAnnotationsCount": { + "format": "int32", + "type": "integer", + "description": "Output only. Number of EvaluatedAnnotations imported.", + "readOnly": true + } + } + }, + "GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpec": { + "type": "object", + "description": "The median automated stopping rule stops a pending Trial if the Trial's best objective_value is strictly below the median 'performance' of all completed Trials reported up to the Trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the Trial in each measurement.", + "properties": { + "useElapsedDuration": { + "type": "boolean", + "description": "True if median automated stopping rule applies on Measurement.elapsed_duration. It means that elapsed_duration field of latest measurement of current Trial is used to compute median objective value for each completed Trials." + } + }, + "id": "GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpec" + }, + "GoogleCloudAiplatformV1ToolParameterKeyMatchMetricValue": { + "type": "object", + "description": "Tool parameter key match metric value for an instance.", + "id": "GoogleCloudAiplatformV1ToolParameterKeyMatchMetricValue", + "properties": { + "score": { + "description": "Output only. Tool parameter key match score.", + "readOnly": true, + "format": "float", + "type": "number" + } + } + }, + "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessSpec": { + "description": "Spec for question answering helpfulness metric.", + "type": "object", + "id": "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessSpec", + "properties": { + "version": { + "description": "Optional. Which version to use for evaluation.", + "format": "int32", + "type": "integer" + }, + "useReference": { + "description": "Optional. Whether to use instance.reference to compute question answering helpfulness.", + "type": "boolean" + } + } + }, + "GoogleCloudAiplatformV1NearestNeighborQuery": { + "properties": { + "embedding": { + "$ref": "GoogleCloudAiplatformV1NearestNeighborQueryEmbedding", + "description": "Optional. The embedding vector that be used for similar search." + }, + "stringFilters": { + "description": "Optional. The list of string filters.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1NearestNeighborQueryStringFilter" + } + }, + "parameters": { + "$ref": "GoogleCloudAiplatformV1NearestNeighborQueryParameters", + "description": "Optional. Parameters that can be set to tune query on the fly." + }, + "neighborCount": { + "description": "Optional. The number of similar entities to be retrieved from feature view for each query.", + "type": "integer", + "format": "int32" + }, + "entityId": { + "description": "Optional. The entity id whose similar entities should be searched for. If embedding is set, search will use embedding instead of entity_id.", + "type": "string" + }, + "perCrowdingAttributeNeighborCount": { + "type": "integer", + "format": "int32", + "description": "Optional. Crowding is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than sper_crowding_attribute_neighbor_count of the k neighbors returned have the same value of crowding_attribute. It's used for improving result diversity." + }, + "numericFilters": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1NearestNeighborQueryNumericFilter" + }, + "description": "Optional. The list of numeric filters." + } + }, + "description": "A query to find a number of similar entities.", + "type": "object", + "id": "GoogleCloudAiplatformV1NearestNeighborQuery" + }, + "GoogleCloudAiplatformV1TensorboardTimeSeries": { + "type": "object", + "description": "TensorboardTimeSeries maps to times series produced in training runs", + "id": "GoogleCloudAiplatformV1TensorboardTimeSeries", + "properties": { + "pluginData": { + "format": "byte", + "type": "string", + "description": "Data of the current plugin, with the size limited to 65KB." + }, + "displayName": { + "type": "string", + "description": "Required. User provided name of this TensorboardTimeSeries. This value should be unique among all TensorboardTimeSeries resources belonging to the same TensorboardRun resource (parent resource)." + }, + "valueType": { + "enum": [ + "VALUE_TYPE_UNSPECIFIED", + "SCALAR", + "TENSOR", + "BLOB_SEQUENCE" + ], + "enumDescriptions": [ + "The value type is unspecified.", + "Used for TensorboardTimeSeries that is a list of scalars. E.g. accuracy of a model over epochs/time.", + "Used for TensorboardTimeSeries that is a list of tensors. E.g. histograms of weights of layer in a model over epoch/time.", + "Used for TensorboardTimeSeries that is a list of blob sequences. E.g. set of sample images with labels over epochs/time." + ], + "type": "string", + "description": "Required. Immutable. Type of TensorboardTimeSeries value." + }, + "updateTime": { + "description": "Output only. Timestamp when this TensorboardTimeSeries was last updated.", + "readOnly": true, + "format": "google-datetime", + "type": "string" + }, + "etag": { + "type": "string", + "description": "Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + }, + "createTime": { + "format": "google-datetime", + "type": "string", + "readOnly": true, + "description": "Output only. Timestamp when this TensorboardTimeSeries was created." + }, + "description": { + "description": "Description of this TensorboardTimeSeries.", + "type": "string" + }, + "name": { + "type": "string", + "readOnly": true, + "description": "Output only. Name of the TensorboardTimeSeries." + }, + "pluginName": { + "type": "string", + "description": "Immutable. Name of the plugin this time series pertain to. Such as Scalar, Tensor, Blob" + }, + "metadata": { + "$ref": "GoogleCloudAiplatformV1TensorboardTimeSeriesMetadata", + "description": "Output only. Scalar, Tensor, or Blob metadata for this TensorboardTimeSeries.", + "readOnly": true + } + } + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTrackMetrics": { + "description": "UNIMPLEMENTED. Track matching model metrics for a single track match threshold and multiple label match confidence thresholds.", + "type": "object", + "properties": { + "meanMismatchRate": { + "type": "number", + "format": "float", + "description": "The mean mismatch rate over all confidence thresholds." + }, + "iouThreshold": { + "description": "The intersection-over-union threshold value between bounding boxes across frames used to compute this metric entry.", + "format": "float", + "type": "number" + }, + "confidenceMetrics": { + "description": "Metrics for each label-match `confidenceThreshold` from 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is derived from them.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTrackMetricsConfidenceMetrics" + } + }, + "meanBoundingBoxIou": { + "format": "float", + "type": "number", + "description": "The mean bounding box iou over all confidence thresholds." + }, + "meanTrackingAveragePrecision": { + "format": "float", + "description": "The mean average precision over all confidence thresholds.", + "type": "number" + } + }, + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTrackMetrics" + }, + "GoogleCloudAiplatformV1NasTrialDetail": { + "properties": { + "searchTrial": { + "$ref": "GoogleCloudAiplatformV1NasTrial", + "description": "The requested search NasTrial." + }, + "parameters": { + "type": "string", + "description": "The parameters for the NasJob NasTrial." + }, + "trainTrial": { + "$ref": "GoogleCloudAiplatformV1NasTrial", + "description": "The train NasTrial corresponding to search_trial. Only populated if search_trial is used for training." + }, + "name": { + "readOnly": true, + "type": "string", + "description": "Output only. Resource name of the NasTrialDetail." + } + }, + "type": "object", + "description": "Represents a NasTrial details along with its parameters. If there is a corresponding train NasTrial, the train NasTrial is also returned.", + "id": "GoogleCloudAiplatformV1NasTrialDetail" + }, + "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig": { + "type": "object", + "id": "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig", + "properties": { + "value": { + "format": "double", + "type": "number", + "description": "Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature." + } + }, + "description": "The config for Featurestore Monitoring threshold." + }, + "GoogleCloudAiplatformV1UpdateFeatureOperationMetadata": { + "type": "object", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "Operation metadata for Feature Update." + } + }, + "id": "GoogleCloudAiplatformV1UpdateFeatureOperationMetadata", + "description": "Details of operations that perform update Feature." + }, + "GoogleCloudAiplatformV1DataItem": { + "description": "A piece of data in a Dataset. Could be an image, a video, a document or plain text.", + "properties": { + "name": { + "description": "Output only. The resource name of the DataItem.", + "type": "string", + "readOnly": true + }, + "updateTime": { + "format": "google-datetime", + "readOnly": true, + "type": "string", + "description": "Output only. Timestamp when this DataItem was last updated." + }, + "etag": { + "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "labels": { + "type": "object", + "additionalProperties": { + "type": "string" + }, + "description": "Optional. The labels with user-defined metadata to organize your DataItems. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one DataItem(System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." + }, + "createTime": { + "description": "Output only. Timestamp when this DataItem was created.", + "format": "google-datetime", + "type": "string", + "readOnly": true + }, + "payload": { + "type": "any", + "description": "Required. The data that the DataItem represents (for example, an image or a text snippet). The schema of the payload is stored in the parent Dataset's metadata schema's dataItemSchemaUri field." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1DataItem" + }, + "GoogleCloudAiplatformV1FindNeighborsResponse": { + "type": "object", + "id": "GoogleCloudAiplatformV1FindNeighborsResponse", + "properties": { + "nearestNeighbors": { + "items": { + "$ref": "GoogleCloudAiplatformV1FindNeighborsResponseNearestNeighbors" + }, + "type": "array", + "description": "The nearest neighbors of the query datapoints." + } + }, + "description": "The response message for MatchService.FindNeighbors." + }, + "GoogleCloudAiplatformV1AvroSource": { + "properties": { + "gcsSource": { + "$ref": "GoogleCloudAiplatformV1GcsSource", + "description": "Required. Google Cloud Storage location." + } + }, + "id": "GoogleCloudAiplatformV1AvroSource", + "description": "The storage details for Avro input content.", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageClassification": { + "description": "A TrainingJob that trains and uploads an AutoML Image Classification Model.", + "type": "object", + "properties": { + "metadata": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageClassificationMetadata", + "description": "The metadata information." + }, + "inputs": { + "description": "The input parameters of this TrainingJob.", + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageClassification" + }, + "GoogleCloudAiplatformV1ToolParameterKVMatchMetricValue": { + "description": "Tool parameter key value match metric value for an instance.", + "id": "GoogleCloudAiplatformV1ToolParameterKVMatchMetricValue", + "type": "object", + "properties": { + "score": { + "format": "float", + "description": "Output only. Tool parameter key value match score.", + "type": "number", + "readOnly": true + } + } + }, + "GoogleCloudAiplatformV1ListExecutionsResponse": { + "description": "Response message for MetadataService.ListExecutions.", + "type": "object", + "properties": { + "executions": { + "type": "array", + "description": "The Executions retrieved from the MetadataStore.", + "items": { + "$ref": "GoogleCloudAiplatformV1Execution" + } + }, + "nextPageToken": { + "description": "A token, which can be sent as ListExecutionsRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1ListExecutionsResponse" + }, + "GoogleCloudAiplatformV1FluencyInstance": { + "properties": { + "prediction": { + "description": "Required. Output of the evaluated model.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1FluencyInstance", + "type": "object", + "description": "Spec for fluency instance." + }, + "GoogleCloudAiplatformV1ListMetadataSchemasResponse": { + "type": "object", + "description": "Response message for MetadataService.ListMetadataSchemas.", + "id": "GoogleCloudAiplatformV1ListMetadataSchemasResponse", + "properties": { + "nextPageToken": { + "description": "A token, which can be sent as ListMetadataSchemasRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages.", + "type": "string" + }, + "metadataSchemas": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1MetadataSchema" + }, + "description": "The MetadataSchemas found for the MetadataStore." + } + } + }, + "GoogleCloudAiplatformV1SchemaImageClassificationAnnotation": { + "id": "GoogleCloudAiplatformV1SchemaImageClassificationAnnotation", + "properties": { + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that this Annotation pertains to." + }, + "annotationSpecId": { + "type": "string", + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." + } + }, + "description": "Annotation details specific to image classification.", + "type": "object" + }, + "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueCondition": { + "description": "Represents the spec to match integer values from parent parameter.", + "id": "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueCondition", + "type": "object", + "properties": { + "values": { + "type": "array", + "items": { + "format": "int64", + "type": "string" + }, + "description": "Required. Matches values of the parent parameter of 'INTEGER' type. All values must lie in `integer_value_spec` of parent parameter." + } + } + }, + "GoogleCloudAiplatformV1ExportDataConfig": { + "description": "Describes what part of the Dataset is to be exported, the destination of the export and how to export.", + "properties": { + "filterSplit": { + "description": "Split based on the provided filters for each set.", + "$ref": "GoogleCloudAiplatformV1ExportFilterSplit" + }, + "exportUse": { + "enumDescriptions": [ + "Regular user export.", + "Export for custom code training." + ], + "enum": [ + "EXPORT_USE_UNSPECIFIED", + "CUSTOM_CODE_TRAINING" + ], + "type": "string", + "description": "Indicates the usage of the exported files." + }, + "annotationsFilter": { + "type": "string", + "description": "An expression for filtering what part of the Dataset is to be exported. Only Annotations that match this filter will be exported. The filter syntax is the same as in ListAnnotations." + }, + "fractionSplit": { + "$ref": "GoogleCloudAiplatformV1ExportFractionSplit", + "description": "Split based on fractions defining the size of each set." + }, + "gcsDestination": { + "$ref": "GoogleCloudAiplatformV1GcsDestination", + "description": "The Google Cloud Storage location where the output is to be written to. In the given directory a new directory will be created with name: `export-data--` where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All export output will be written into that directory. Inside that directory, annotations with the same schema will be grouped into sub directories which are named with the corresponding annotations' schema title. Inside these sub directories, a schema.yaml will be created to describe the output format." + }, + "savedQueryId": { + "description": "The ID of a SavedQuery (annotation set) under the Dataset specified by dataset_id used for filtering Annotations for training. Only used for custom training data export use cases. Only applicable to Datasets that have SavedQueries. Only Annotations that are associated with this SavedQuery are used in respectively training. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both saved_query_id and annotations_filter. Only one of saved_query_id and annotation_schema_uri should be specified as both of them represent the same thing: problem type.", + "type": "string" + }, + "annotationSchemaUri": { + "type": "string", + "description": "The Cloud Storage URI that points to a YAML file describing the annotation schema. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/annotation/, note that the chosen schema must be consistent with metadata of the Dataset specified by dataset_id. Only used for custom training data export use cases. Only applicable to Datasets that have DataItems and Annotations. Only Annotations that both match this schema and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both annotations_filter and annotation_schema_uri." + } + }, + "id": "GoogleCloudAiplatformV1ExportDataConfig", + "type": "object" + }, + "GoogleCloudAiplatformV1MetadataStoreMetadataStoreState": { + "id": "GoogleCloudAiplatformV1MetadataStoreMetadataStoreState", + "type": "object", + "properties": { + "diskUtilizationBytes": { + "format": "int64", + "type": "string", + "description": "The disk utilization of the MetadataStore in bytes." + } + }, + "description": "Represents state information for a MetadataStore." + }, + "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpec": { + "id": "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpec", + "type": "object", + "properties": { + "parameterSpec": { + "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpec", + "description": "Required. The spec for a conditional parameter." + }, + "parentCategoricalValues": { + "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueCondition", + "description": "The spec for matching values from a parent parameter of `CATEGORICAL` type." + }, + "parentDiscreteValues": { + "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueCondition", + "description": "The spec for matching values from a parent parameter of `DISCRETE` type." + }, + "parentIntValues": { + "description": "The spec for matching values from a parent parameter of `INTEGER` type.", + "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueCondition" + } + }, + "description": "Represents a parameter spec with condition from its parent parameter." + }, + "GoogleLongrunningListOperationsResponse": { + "description": "The response message for Operations.ListOperations.", + "type": "object", + "id": "GoogleLongrunningListOperationsResponse", + "properties": { + "operations": { + "items": { + "$ref": "GoogleLongrunningOperation" + }, + "type": "array", + "description": "A list of operations that matches the specified filter in the request." + }, + "nextPageToken": { + "description": "The standard List next-page token.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1CreateDatasetOperationMetadata": { + "description": "Runtime operation information for DatasetService.CreateDataset.", + "id": "GoogleCloudAiplatformV1CreateDatasetOperationMetadata", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The operation generic information." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1RougeInstance": { + "properties": { + "reference": { + "type": "string", + "description": "Required. Ground truth used to compare against the prediction." + }, + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + } + }, + "id": "GoogleCloudAiplatformV1RougeInstance", + "type": "object", + "description": "Spec for rouge instance." + }, + "GoogleCloudAiplatformV1SchemaTextDataItem": { + "description": "Payload of Text DataItem.", + "properties": { + "gcsUri": { + "description": "Output only. Google Cloud Storage URI points to the original text in user's bucket. The text file is up to 10MB in size.", + "readOnly": true, + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTextDataItem", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaPredictPredictionVideoActionRecognitionPredictionResult": { + "description": "Prediction output format for Video Action Recognition.", + "id": "GoogleCloudAiplatformV1SchemaPredictPredictionVideoActionRecognitionPredictionResult", + "type": "object", + "properties": { + "timeSegmentStart": { + "type": "string", + "format": "google-duration", + "description": "The beginning, inclusive, of the video's time segment in which the AnnotationSpec has been identified. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end." + }, + "id": { + "type": "string", + "description": "The resource ID of the AnnotationSpec that had been identified." + }, + "timeSegmentEnd": { + "type": "string", + "description": "The end, exclusive, of the video's time segment in which the AnnotationSpec has been identified. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end.", + "format": "google-duration" + }, + "confidence": { + "type": "number", + "description": "The Model's confidence in correction of this prediction, higher value means higher confidence.", + "format": "float" + }, + "displayName": { + "description": "The display name of the AnnotationSpec that had been identified.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1ReadIndexDatapointsResponse": { + "id": "GoogleCloudAiplatformV1ReadIndexDatapointsResponse", + "description": "The response message for MatchService.ReadIndexDatapoints.", + "properties": { + "datapoints": { + "items": { + "$ref": "GoogleCloudAiplatformV1IndexDatapoint" + }, + "description": "The result list of datapoints.", + "type": "array" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1FindNeighborsRequest": { + "id": "GoogleCloudAiplatformV1FindNeighborsRequest", + "description": "The request message for MatchService.FindNeighbors.", + "type": "object", + "properties": { + "deployedIndexId": { + "description": "The ID of the DeployedIndex that will serve the request. This request is sent to a specific IndexEndpoint, as per the IndexEndpoint.network. That IndexEndpoint also has IndexEndpoint.deployed_indexes, and each such index has a DeployedIndex.id field. The value of the field below must equal one of the DeployedIndex.id fields of the IndexEndpoint that is being called for this request.", + "type": "string" + }, + "returnFullDatapoint": { + "type": "boolean", + "description": "If set to true, the full datapoints (including all vector values and restricts) of the nearest neighbors are returned. Note that returning full datapoint will significantly increase the latency and cost of the query." + }, + "queries": { + "type": "array", + "description": "The list of queries.", + "items": { + "$ref": "GoogleCloudAiplatformV1FindNeighborsRequestQuery" + } + } + } + }, + "GoogleCloudAiplatformV1AddContextArtifactsAndExecutionsResponse": { + "type": "object", + "id": "GoogleCloudAiplatformV1AddContextArtifactsAndExecutionsResponse", + "description": "Response message for MetadataService.AddContextArtifactsAndExecutions.", + "properties": {} + }, + "GoogleCloudAiplatformV1GroundednessInstance": { + "type": "object", + "description": "Spec for groundedness instance.", + "id": "GoogleCloudAiplatformV1GroundednessInstance", + "properties": { + "context": { + "description": "Required. Background information provided in context used to compare against the prediction.", + "type": "string" + }, + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + } + } + }, + "GoogleCloudAiplatformV1PurgeContextsMetadata": { + "properties": { + "genericMetadata": { + "description": "Operation metadata for purging Contexts.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + }, + "description": "Details of operations that perform MetadataService.PurgeContexts.", + "id": "GoogleCloudAiplatformV1PurgeContextsMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec": { + "description": "Represent spec for search trials.", + "properties": { + "maxTrialCount": { + "format": "int32", + "description": "Required. The maximum number of Neural Architecture Search (NAS) trials to run.", + "type": "integer" + }, + "searchTrialJobSpec": { + "$ref": "GoogleCloudAiplatformV1CustomJobSpec", + "description": "Required. The spec of a search trial job. The same spec applies to all search trials." + }, + "maxParallelTrialCount": { + "format": "int32", + "type": "integer", + "description": "Required. The maximum number of trials to run in parallel." + }, + "maxFailedTrialCount": { + "description": "The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.", + "format": "int32", + "type": "integer" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec" + }, + "GoogleCloudAiplatformV1ResourceRuntimeSpec": { + "id": "GoogleCloudAiplatformV1ResourceRuntimeSpec", + "type": "object", + "properties": { + "raySpec": { + "description": "Optional. Ray cluster configuration. Required when creating a dedicated RayCluster on the PersistentResource.", + "$ref": "GoogleCloudAiplatformV1RaySpec" + }, + "serviceAccountSpec": { + "description": "Optional. Configure the use of workload identity on the PersistentResource", + "$ref": "GoogleCloudAiplatformV1ServiceAccountSpec" + } + }, + "description": "Configuration for the runtime on a PersistentResource instance, including but not limited to: * Service accounts used to run the workloads. * Whether to make it a dedicated Ray Cluster." + }, + "GoogleCloudAiplatformV1ImportFeatureValuesRequest": { + "id": "GoogleCloudAiplatformV1ImportFeatureValuesRequest", + "properties": { + "featureTime": { + "type": "string", + "description": "Single Feature timestamp for all entities being imported. The timestamp must not have higher than millisecond precision.", + "format": "google-datetime" + }, + "featureSpecs": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1ImportFeatureValuesRequestFeatureSpec" + }, + "description": "Required. Specifications defining which Feature values to import from the entity. The request fails if no feature_specs are provided, and having multiple feature_specs for one Feature is not allowed." + }, + "disableOnlineServing": { + "description": "If set, data will not be imported for online serving. This is typically used for backfilling, where Feature generation timestamps are not in the timestamp range needed for online serving.", + "type": "boolean" + }, + "workerCount": { + "description": "Specifies the number of workers that are used to write data to the Featurestore. Consider the online serving capacity that you require to achieve the desired import throughput without interfering with online serving. The value must be positive, and less than or equal to 100. If not set, defaults to using 1 worker. The low count ensures minimal impact on online serving performance.", + "format": "int32", + "type": "integer" + }, + "avroSource": { + "$ref": "GoogleCloudAiplatformV1AvroSource" + }, + "csvSource": { + "$ref": "GoogleCloudAiplatformV1CsvSource" + }, + "entityIdField": { + "type": "string", + "description": "Source column that holds entity IDs. If not provided, entity IDs are extracted from the column named entity_id." + }, + "featureTimeField": { + "description": "Source column that holds the Feature timestamp for all Feature values in each entity.", + "type": "string" + }, + "disableIngestionAnalysis": { + "type": "boolean", + "description": "If true, API doesn't start ingestion analysis pipeline." + }, + "bigquerySource": { + "$ref": "GoogleCloudAiplatformV1BigQuerySource" + } + }, + "description": "Request message for FeaturestoreService.ImportFeatureValues.", + "type": "object" + }, + "GoogleCloudAiplatformV1Part": { + "properties": { + "functionCall": { + "$ref": "GoogleCloudAiplatformV1FunctionCall", + "description": "Optional. A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] with the parameters and their values." + }, + "fileData": { + "$ref": "GoogleCloudAiplatformV1FileData", + "description": "Optional. URI based data." + }, + "text": { + "type": "string", + "description": "Optional. Text part (can be code)." + }, + "videoMetadata": { + "$ref": "GoogleCloudAiplatformV1VideoMetadata", + "description": "Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data." + }, + "inlineData": { + "description": "Optional. Inlined bytes data.", + "$ref": "GoogleCloudAiplatformV1Blob" + }, + "functionResponse": { + "description": "Optional. The result output of a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function call. It is used as context to the model.", + "$ref": "GoogleCloudAiplatformV1FunctionResponse" + } + }, + "id": "GoogleCloudAiplatformV1Part", + "type": "object", + "description": "A datatype containing media that is part of a multi-part `Content` message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. A `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes." + }, + "GoogleCloudAiplatformV1BatchReadFeatureValuesResponse": { + "type": "object", + "properties": {}, + "id": "GoogleCloudAiplatformV1BatchReadFeatureValuesResponse", + "description": "Response message for FeaturestoreService.BatchReadFeatureValues." + }, + "GoogleCloudAiplatformV1SchemaPredictPredictionTabularRegressionPredictionResult": { + "id": "GoogleCloudAiplatformV1SchemaPredictPredictionTabularRegressionPredictionResult", + "description": "Prediction output format for Tabular Regression.", + "type": "object", + "properties": { + "value": { + "format": "float", + "type": "number", + "description": "The regression value." + }, + "quantilePredictions": { + "items": { + "format": "float", + "type": "number" + }, + "type": "array", + "description": "Quantile predictions, in 1-1 correspondence with quantile_values." + }, + "quantileValues": { + "description": "Quantile values.", + "items": { + "type": "number", + "format": "float" + }, + "type": "array" + }, + "lowerBound": { + "description": "The lower bound of the prediction interval.", + "format": "float", + "type": "number" + }, + "upperBound": { + "format": "float", + "type": "number", + "description": "The upper bound of the prediction interval." + } + } + }, + "GoogleCloudAiplatformV1SchemaPredictInstanceVideoClassificationPredictionInstance": { + "type": "object", + "properties": { + "content": { + "type": "string", + "description": "The Google Cloud Storage location of the video on which to perform the prediction." + }, + "mimeType": { + "type": "string", + "description": "The MIME type of the content of the video. Only the following are supported: video/mp4 video/avi video/quicktime" + }, + "timeSegmentEnd": { + "type": "string", + "description": "The end, exclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with \"s\" appended at the end. Fractions are allowed, up to a microsecond precision, and \"inf\" or \"Infinity\" is allowed, which means the end of the video." + }, + "timeSegmentStart": { + "description": "The beginning, inclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with \"s\" appended at the end. Fractions are allowed, up to a microsecond precision.", + "type": "string" + } + }, + "description": "Prediction input format for Video Classification.", + "id": "GoogleCloudAiplatformV1SchemaPredictInstanceVideoClassificationPredictionInstance" + }, + "GoogleCloudAiplatformV1Examples": { + "id": "GoogleCloudAiplatformV1Examples", + "properties": { + "neighborCount": { + "format": "int32", + "type": "integer", + "description": "The number of neighbors to return when querying for examples." + }, + "exampleGcsSource": { + "$ref": "GoogleCloudAiplatformV1ExamplesExampleGcsSource", + "description": "The Cloud Storage input instances." + }, + "nearestNeighborSearchConfig": { + "type": "any", + "description": "The full configuration for the generated index, the semantics are the same as metadata and should match [NearestNeighborSearchConfig](https://cloud.google.com/vertex-ai/docs/explainable-ai/configuring-explanations-example-based#nearest-neighbor-search-config)." + }, + "presets": { + "$ref": "GoogleCloudAiplatformV1Presets", + "description": "Simplified preset configuration, which automatically sets configuration values based on the desired query speed-precision trade-off and modality." + } + }, + "type": "object", + "description": "Example-based explainability that returns the nearest neighbors from the provided dataset." + }, + "GoogleCloudAiplatformV1WriteFeatureValuesPayload": { + "properties": { + "entityId": { + "description": "Required. The ID of the entity.", + "type": "string" + }, + "featureValues": { + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1FeatureValue" + }, + "type": "object", + "description": "Required. Feature values to be written, mapping from Feature ID to value. Up to 100,000 `feature_values` entries may be written across all payloads. The feature generation time, aligned by days, must be no older than five years (1825 days) and no later than one year (366 days) in the future." + } + }, + "description": "Contains Feature values to be written for a specific entity.", + "type": "object", + "id": "GoogleCloudAiplatformV1WriteFeatureValuesPayload" + }, + "GoogleCloudAiplatformV1CreateIndexEndpointOperationMetadata": { + "id": "GoogleCloudAiplatformV1CreateIndexEndpointOperationMetadata", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The operation generic information." + } + }, + "type": "object", + "description": "Runtime operation information for IndexEndpointService.CreateIndexEndpoint." + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformation": { + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformation", + "properties": { + "repeatedText": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextArrayTransformation" + }, + "text": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextTransformation" + }, + "categorical": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalTransformation" + }, + "auto": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationAutoTransformation" + }, + "timestamp": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTimestampTransformation" + }, + "repeatedNumeric": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericArrayTransformation" + }, + "repeatedCategorical": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalArrayTransformation" + }, + "numeric": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericTransformation" + } + } + }, + "GoogleTypeColor": { + "id": "GoogleTypeColor", + "type": "object", + "description": "Represents a color in the RGBA color space. This representation is designed for simplicity of conversion to and from color representations in various languages over compactness. For example, the fields of this representation can be trivially provided to the constructor of `java.awt.Color` in Java; it can also be trivially provided to UIColor's `+colorWithRed:green:blue:alpha` method in iOS; and, with just a little work, it can be easily formatted into a CSS `rgba()` string in JavaScript. This reference page doesn't have information about the absolute color space that should be used to interpret the RGB value—for example, sRGB, Adobe RGB, DCI-P3, and BT.2020. By default, applications should assume the sRGB color space. When color equality needs to be decided, implementations, unless documented otherwise, treat two colors as equal if all their red, green, blue, and alpha values each differ by at most `1e-5`. Example (Java): import com.google.type.Color; // ... public static java.awt.Color fromProto(Color protocolor) { float alpha = protocolor.hasAlpha() ? protocolor.getAlpha().getValue() : 1.0; return new java.awt.Color( protocolor.getRed(), protocolor.getGreen(), protocolor.getBlue(), alpha); } public static Color toProto(java.awt.Color color) { float red = (float) color.getRed(); float green = (float) color.getGreen(); float blue = (float) color.getBlue(); float denominator = 255.0; Color.Builder resultBuilder = Color .newBuilder() .setRed(red / denominator) .setGreen(green / denominator) .setBlue(blue / denominator); int alpha = color.getAlpha(); if (alpha != 255) { result.setAlpha( FloatValue .newBuilder() .setValue(((float) alpha) / denominator) .build()); } return resultBuilder.build(); } // ... Example (iOS / Obj-C): // ... static UIColor* fromProto(Color* protocolor) { float red = [protocolor red]; float green = [protocolor green]; float blue = [protocolor blue]; FloatValue* alpha_wrapper = [protocolor alpha]; float alpha = 1.0; if (alpha_wrapper != nil) { alpha = [alpha_wrapper value]; } return [UIColor colorWithRed:red green:green blue:blue alpha:alpha]; } static Color* toProto(UIColor* color) { CGFloat red, green, blue, alpha; if (![color getRed:&red green:&green blue:&blue alpha:&alpha]) { return nil; } Color* result = [[Color alloc] init]; [result setRed:red]; [result setGreen:green]; [result setBlue:blue]; if (alpha \u003c= 0.9999) { [result setAlpha:floatWrapperWithValue(alpha)]; } [result autorelease]; return result; } // ... Example (JavaScript): // ... var protoToCssColor = function(rgb_color) { var redFrac = rgb_color.red || 0.0; var greenFrac = rgb_color.green || 0.0; var blueFrac = rgb_color.blue || 0.0; var red = Math.floor(redFrac * 255); var green = Math.floor(greenFrac * 255); var blue = Math.floor(blueFrac * 255); if (!('alpha' in rgb_color)) { return rgbToCssColor(red, green, blue); } var alphaFrac = rgb_color.alpha.value || 0.0; var rgbParams = [red, green, blue].join(','); return ['rgba(', rgbParams, ',', alphaFrac, ')'].join(''); }; var rgbToCssColor = function(red, green, blue) { var rgbNumber = new Number((red \u003c\u003c 16) | (green \u003c\u003c 8) | blue); var hexString = rgbNumber.toString(16); var missingZeros = 6 - hexString.length; var resultBuilder = ['#']; for (var i = 0; i \u003c missingZeros; i++) { resultBuilder.push('0'); } resultBuilder.push(hexString); return resultBuilder.join(''); }; // ...", + "properties": { + "red": { + "format": "float", + "type": "number", + "description": "The amount of red in the color as a value in the interval [0, 1]." + }, + "green": { + "description": "The amount of green in the color as a value in the interval [0, 1].", + "format": "float", + "type": "number" + }, + "alpha": { + "format": "float", + "description": "The fraction of this color that should be applied to the pixel. That is, the final pixel color is defined by the equation: `pixel color = alpha * (this color) + (1.0 - alpha) * (background color)` This means that a value of 1.0 corresponds to a solid color, whereas a value of 0.0 corresponds to a completely transparent color. This uses a wrapper message rather than a simple float scalar so that it is possible to distinguish between a default value and the value being unset. If omitted, this color object is rendered as a solid color (as if the alpha value had been explicitly given a value of 1.0).", + "type": "number" + }, + "blue": { + "type": "number", + "format": "float", + "description": "The amount of blue in the color as a value in the interval [0, 1]." + } + } + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionMetadata": { + "properties": { + "successfulStopReason": { + "enumDescriptions": [ + "Should not be set.", + "The inputs.budgetMilliNodeHours had been reached.", + "Further training of the Model ceased to increase its quality, since it already has converged." + ], + "enum": [ + "SUCCESSFUL_STOP_REASON_UNSPECIFIED", + "BUDGET_REACHED", + "MODEL_CONVERGED" + ], + "description": "For successful job completions, this is the reason why the job has finished.", + "type": "string" + }, + "costMilliNodeHours": { + "description": "The actual training cost of creating this model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed inputs.budgetMilliNodeHours.", + "format": "int64", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionMetadata" + }, + "GoogleCloudAiplatformV1PurgeExecutionsMetadata": { + "description": "Details of operations that perform MetadataService.PurgeExecutions.", + "id": "GoogleCloudAiplatformV1PurgeExecutionsMetadata", + "properties": { + "genericMetadata": { + "description": "Operation metadata for purging Executions.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaPredictPredictionTextSentimentPredictionResult": { + "id": "GoogleCloudAiplatformV1SchemaPredictPredictionTextSentimentPredictionResult", + "properties": { + "sentiment": { + "description": "The integer sentiment labels between 0 (inclusive) and sentimentMax label (inclusive), while 0 maps to the least positive sentiment and sentimentMax maps to the most positive one. The higher the score is, the more positive the sentiment in the text snippet is. Note: sentimentMax is an integer value between 1 (inclusive) and 10 (inclusive).", + "format": "int32", + "type": "integer" + } + }, + "description": "Prediction output format for Text Sentiment", + "type": "object" + }, + "GoogleCloudAiplatformV1ListTensorboardExperimentsResponse": { + "description": "Response message for TensorboardService.ListTensorboardExperiments.", + "type": "object", + "id": "GoogleCloudAiplatformV1ListTensorboardExperimentsResponse", + "properties": { + "tensorboardExperiments": { + "items": { + "$ref": "GoogleCloudAiplatformV1TensorboardExperiment" + }, + "description": "The TensorboardExperiments mathching the request.", + "type": "array" + }, + "nextPageToken": { + "type": "string", + "description": "A token, which can be sent as ListTensorboardExperimentsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages." + } + } + }, + "GoogleCloudAiplatformV1CreateTensorboardTimeSeriesRequest": { + "type": "object", + "properties": { + "parent": { + "description": "Required. The resource name of the TensorboardRun to create the TensorboardTimeSeries in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", + "type": "string" + }, + "tensorboardTimeSeriesId": { + "type": "string", + "description": "Optional. The user specified unique ID to use for the TensorboardTimeSeries, which becomes the final component of the TensorboardTimeSeries's resource name. This value should match \"a-z0-9{0, 127}\"" + }, + "tensorboardTimeSeries": { + "$ref": "GoogleCloudAiplatformV1TensorboardTimeSeries", + "description": "Required. The TensorboardTimeSeries to create." + } + }, + "id": "GoogleCloudAiplatformV1CreateTensorboardTimeSeriesRequest", + "description": "Request message for TensorboardService.CreateTensorboardTimeSeries." + }, + "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadata": { + "description": "The metadata of Datasets that contain time series data.", + "properties": { + "timeSeriesIdentifierColumn": { + "type": "string", + "description": "The column name of the time series identifier column that identifies the time series." + }, + "inputConfig": { + "$ref": "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadataInputConfig" + }, + "timeColumn": { + "description": "The column name of the time column that identifies time order in the time series.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1ToolNameMatchInput": { + "description": "Input for tool name match metric.", + "id": "GoogleCloudAiplatformV1ToolNameMatchInput", + "properties": { + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1ToolNameMatchSpec", + "description": "Required. Spec for tool name match metric." + }, + "instances": { + "items": { + "$ref": "GoogleCloudAiplatformV1ToolNameMatchInstance" + }, + "description": "Required. Repeated tool name match instances.", + "type": "array" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1TensorboardExperiment": { + "properties": { + "updateTime": { + "type": "string", + "readOnly": true, + "description": "Output only. Timestamp when this TensorboardExperiment was last updated.", + "format": "google-datetime" + }, + "createTime": { + "description": "Output only. Timestamp when this TensorboardExperiment was created.", + "type": "string", + "format": "google-datetime", + "readOnly": true + }, + "displayName": { + "type": "string", + "description": "User provided name of this TensorboardExperiment." + }, + "name": { + "description": "Output only. Name of the TensorboardExperiment. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", + "type": "string", + "readOnly": true + }, + "etag": { + "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "The labels with user-defined metadata to organize your TensorboardExperiment. Label keys and values cannot be longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with `aiplatform.googleapis.com/` and are immutable. The following system labels exist for each Dataset: * `aiplatform.googleapis.com/dataset_metadata_schema`: output only. Its value is the metadata_schema's title." + }, + "description": { + "description": "Description of this TensorboardExperiment.", + "type": "string" + }, + "source": { + "type": "string", + "description": "Immutable. Source of the TensorboardExperiment. Example: a custom training job." + } + }, + "description": "A TensorboardExperiment is a group of TensorboardRuns, that are typically the results of a training job run, in a Tensorboard.", + "id": "GoogleCloudAiplatformV1TensorboardExperiment", + "type": "object" + }, + "GoogleCloudAiplatformV1StreamingPredictResponse": { + "properties": { + "parameters": { + "description": "The parameters that govern the prediction.", + "$ref": "GoogleCloudAiplatformV1Tensor" + }, + "outputs": { + "type": "array", + "description": "The prediction output.", + "items": { + "$ref": "GoogleCloudAiplatformV1Tensor" + } + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1StreamingPredictResponse", + "description": "Response message for PredictionService.StreamingPredict." + }, + "GoogleCloudAiplatformV1PauseScheduleRequest": { + "id": "GoogleCloudAiplatformV1PauseScheduleRequest", + "type": "object", + "description": "Request message for ScheduleService.PauseSchedule.", + "properties": {} + }, + "GoogleCloudAiplatformV1ListAnnotationsResponse": { + "properties": { + "nextPageToken": { + "type": "string", + "description": "The standard List next-page token." + }, + "annotations": { + "items": { + "$ref": "GoogleCloudAiplatformV1Annotation" + }, + "description": "A list of Annotations that matches the specified filter in the request.", + "type": "array" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1ListAnnotationsResponse", + "description": "Response message for DatasetService.ListAnnotations." + }, + "GoogleCloudAiplatformV1FeatureViewDataKeyCompositeKey": { + "properties": { + "parts": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Parts to construct Entity ID. Should match with the same ID columns as defined in FeatureView in the same order." + } + }, + "id": "GoogleCloudAiplatformV1FeatureViewDataKeyCompositeKey", + "description": "ID that is comprised from several parts (columns).", + "type": "object" + }, + "GoogleCloudAiplatformV1NotebookExecutionJobDataformRepositorySource": { + "description": "The Dataform Repository containing the input notebook.", + "properties": { + "commitSha": { + "type": "string", + "description": "The commit SHA to read repository with. If unset, the file will be read at HEAD." + }, + "dataformRepositoryResourceName": { + "description": "The resource name of the Dataform Repository. Format: `projects/{project_id}/locations/{location}/repositories/{repository_id}`", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1NotebookExecutionJobDataformRepositorySource", + "type": "object" + }, + "GoogleCloudAiplatformV1BatchPredictionJobOutputInfo": { + "type": "object", + "description": "Further describes this job's output. Supplements output_config.", + "id": "GoogleCloudAiplatformV1BatchPredictionJobOutputInfo", + "properties": { + "bigqueryOutputDataset": { + "readOnly": true, + "description": "Output only. The path of the BigQuery dataset created, in `bq://projectId.bqDatasetId` format, into which the prediction output is written.", + "type": "string" + }, + "bigqueryOutputTable": { + "description": "Output only. The name of the BigQuery table created, in `predictions_` format, into which the prediction output is written. Can be used by UI to generate the BigQuery output path, for example.", + "type": "string", + "readOnly": true + }, + "gcsOutputDirectory": { + "type": "string", + "readOnly": true, + "description": "Output only. The full path of the Cloud Storage directory created, into which the prediction output is written." + } + } + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoObjectTracking": { + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoObjectTracking", + "description": "A TrainingJob that trains and uploads an AutoML Video ObjectTracking Model.", + "properties": { + "inputs": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoObjectTrackingInputs", + "description": "The input parameters of this TrainingJob." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1CreateFeatureOnlineStoreOperationMetadata": { + "id": "GoogleCloudAiplatformV1CreateFeatureOnlineStoreOperationMetadata", + "type": "object", + "description": "Details of operations that perform create FeatureOnlineStore.", + "properties": { + "genericMetadata": { + "description": "Operation metadata for FeatureOnlineStore.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + } + }, + "GoogleCloudAiplatformV1BatchReadFeatureValuesRequestPassThroughField": { + "properties": { + "fieldName": { + "description": "Required. The name of the field in the CSV header or the name of the column in BigQuery table. The naming restriction is the same as Feature.name.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1BatchReadFeatureValuesRequestPassThroughField", + "type": "object", + "description": "Describe pass-through fields in read_instance source." + }, + "GoogleCloudAiplatformV1Schedule": { + "properties": { + "state": { + "enumDescriptions": [ + "Unspecified.", + "The Schedule is active. Runs are being scheduled on the user-specified timespec.", + "The schedule is paused. No new runs will be created until the schedule is resumed. Already started runs will be allowed to complete.", + "The Schedule is completed. No new runs will be scheduled. Already started runs will be allowed to complete. Schedules in completed state cannot be paused or resumed." + ], + "readOnly": true, + "type": "string", + "description": "Output only. The state of this Schedule.", + "enum": [ + "STATE_UNSPECIFIED", + "ACTIVE", + "PAUSED", + "COMPLETED" + ] + }, + "createTime": { + "type": "string", + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Timestamp when this Schedule was created." + }, + "lastScheduledRunResponse": { + "$ref": "GoogleCloudAiplatformV1ScheduleRunResponse", + "description": "Output only. Response of the last scheduled run. This is the response for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable). Unset if no run has been scheduled yet.", + "readOnly": true + }, + "maxConcurrentRunCount": { + "type": "string", + "description": "Required. Maximum number of runs that can be started concurrently for this Schedule. This is the limit for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable).", + "format": "int64" + }, + "allowQueueing": { + "description": "Optional. Whether new scheduled runs can be queued when max_concurrent_runs limit is reached. If set to true, new runs will be queued instead of skipped. Default to false.", + "type": "boolean" + }, + "name": { + "type": "string", + "description": "Immutable. The resource name of the Schedule." + }, + "maxRunCount": { + "description": "Optional. Maximum run count of the schedule. If specified, The schedule will be completed when either started_run_count \u003e= max_run_count or when end_time is reached. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.", + "type": "string", + "format": "int64" + }, + "updateTime": { + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Timestamp when this Schedule was updated.", + "type": "string" + }, + "nextRunTime": { + "type": "string", + "description": "Output only. Timestamp when this Schedule should schedule the next run. Having a next_run_time in the past means the runs are being started behind schedule.", + "readOnly": true, + "format": "google-datetime" + }, + "cron": { + "description": "Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: \"CRON_TZ=${IANA_TIME_ZONE}\" or \"TZ=${IANA_TIME_ZONE}\". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, \"CRON_TZ=America/New_York 1 * * * *\", or \"TZ=America/New_York 1 * * * *\".", + "type": "string" + }, + "catchUp": { + "type": "boolean", + "readOnly": true, + "description": "Output only. Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. Default to false." + }, + "endTime": { + "type": "string", + "description": "Optional. Timestamp after which no new runs can be scheduled. If specified, The schedule will be completed when either end_time is reached or when scheduled_run_count \u003e= max_run_count. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.", + "format": "google-datetime" + }, + "lastPauseTime": { + "format": "google-datetime", + "readOnly": true, + "type": "string", + "description": "Output only. Timestamp when this Schedule was last paused. Unset if never paused." + }, + "createPipelineJobRequest": { + "$ref": "GoogleCloudAiplatformV1CreatePipelineJobRequest", + "description": "Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location})." + }, + "startedRunCount": { + "type": "string", + "readOnly": true, + "format": "int64", + "description": "Output only. The number of runs started by this schedule." + }, + "displayName": { + "type": "string", + "description": "Required. User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters." + }, + "startTime": { + "format": "google-datetime", + "description": "Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.", + "type": "string" + }, + "lastResumeTime": { + "type": "string", + "readOnly": true, + "description": "Output only. Timestamp when this Schedule was last resumed. Unset if never resumed from pause.", + "format": "google-datetime" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1Schedule", + "description": "An instance of a Schedule periodically schedules runs to make API calls based on user specified time specification and API request type." + }, + "GoogleCloudAiplatformV1DirectPredictResponse": { + "type": "object", + "properties": { + "parameters": { + "description": "The parameters that govern the prediction.", + "$ref": "GoogleCloudAiplatformV1Tensor" + }, + "outputs": { + "description": "The prediction output.", + "items": { + "$ref": "GoogleCloudAiplatformV1Tensor" + }, + "type": "array" + } + }, + "description": "Response message for PredictionService.DirectPredict.", + "id": "GoogleCloudAiplatformV1DirectPredictResponse" + }, + "GoogleCloudAiplatformV1FeatureValueDestination": { + "description": "A destination location for Feature values and format.", + "type": "object", + "id": "GoogleCloudAiplatformV1FeatureValueDestination", + "properties": { + "csvDestination": { + "description": "Output in CSV format. Array Feature value types are not allowed in CSV format.", + "$ref": "GoogleCloudAiplatformV1CsvDestination" + }, + "bigqueryDestination": { + "description": "Output in BigQuery format. BigQueryDestination.output_uri in FeatureValueDestination.bigquery_destination must refer to a table.", + "$ref": "GoogleCloudAiplatformV1BigQueryDestination" + }, + "tfrecordDestination": { + "description": "Output in TFRecord format. Below are the mapping from Feature value type in Featurestore to Feature value type in TFRecord: Value type in Featurestore | Value type in TFRecord DOUBLE, DOUBLE_ARRAY | FLOAT_LIST INT64, INT64_ARRAY | INT64_LIST STRING, STRING_ARRAY, BYTES | BYTES_LIST true -\u003e byte_string(\"true\"), false -\u003e byte_string(\"false\") BOOL, BOOL_ARRAY (true, false) | BYTES_LIST", + "$ref": "GoogleCloudAiplatformV1TFRecordDestination" + } + } + }, + "GoogleCloudAiplatformV1ExportDataRequest": { + "properties": { + "exportConfig": { + "$ref": "GoogleCloudAiplatformV1ExportDataConfig", + "description": "Required. The desired output location." + } + }, + "description": "Request message for DatasetService.ExportData.", + "type": "object", + "id": "GoogleCloudAiplatformV1ExportDataRequest" + }, + "GoogleCloudAiplatformV1SafetySetting": { + "properties": { + "method": { + "enumDescriptions": [ + "The harm block method is unspecified.", + "The harm block method uses both probability and severity scores.", + "The harm block method uses the probability score." + ], + "type": "string", + "description": "Optional. Specify if the threshold is used for probability or severity score. If not specified, the threshold is used for probability score.", + "enum": [ + "HARM_BLOCK_METHOD_UNSPECIFIED", + "SEVERITY", + "PROBABILITY" + ] + }, + "threshold": { + "type": "string", + "enum": [ + "HARM_BLOCK_THRESHOLD_UNSPECIFIED", + "BLOCK_LOW_AND_ABOVE", + "BLOCK_MEDIUM_AND_ABOVE", + "BLOCK_ONLY_HIGH", + "BLOCK_NONE" + ], + "enumDescriptions": [ + "Unspecified harm block threshold.", + "Block low threshold and above (i.e. block more).", + "Block medium threshold and above.", + "Block only high threshold (i.e. block less).", + "Block none." + ], + "description": "Required. The harm block threshold." + }, + "category": { + "description": "Required. Harm category.", + "type": "string", + "enum": [ + "HARM_CATEGORY_UNSPECIFIED", + "HARM_CATEGORY_HATE_SPEECH", + "HARM_CATEGORY_DANGEROUS_CONTENT", + "HARM_CATEGORY_HARASSMENT", + "HARM_CATEGORY_SEXUALLY_EXPLICIT" + ], + "enumDescriptions": [ + "The harm category is unspecified.", + "The harm category is hate speech.", + "The harm category is dangerous content.", + "The harm category is harassment.", + "The harm category is sexually explicit content." + ] + } + }, + "id": "GoogleCloudAiplatformV1SafetySetting", + "type": "object", + "description": "Safety settings." + }, + "GoogleCloudAiplatformV1SupervisedTuningSpec": { + "id": "GoogleCloudAiplatformV1SupervisedTuningSpec", + "description": "Tuning Spec for Supervised Tuning.", + "type": "object", + "properties": { + "trainingDatasetUri": { + "type": "string", + "description": "Required. Cloud Storage path to file containing training dataset for tuning. The dataset must be formatted as a JSONL file." + }, + "validationDatasetUri": { + "type": "string", + "description": "Optional. Cloud Storage path to file containing validation dataset for tuning. The dataset must be formatted as a JSONL file." + }, + "hyperParameters": { + "description": "Optional. Hyperparameters for SFT.", + "$ref": "GoogleCloudAiplatformV1SupervisedHyperParameters" + } + } + }, + "GoogleCloudAiplatformV1CreateDatasetVersionOperationMetadata": { + "description": "Runtime operation information for DatasetService.CreateDatasetVersion.", + "type": "object", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The common part of the operation metadata." + } + }, + "id": "GoogleCloudAiplatformV1CreateDatasetVersionOperationMetadata" + }, + "GoogleCloudAiplatformV1CreateNotebookRuntimeTemplateOperationMetadata": { + "description": "Metadata information for NotebookService.CreateNotebookRuntimeTemplate.", + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + }, + "id": "GoogleCloudAiplatformV1CreateNotebookRuntimeTemplateOperationMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1Endpoint": { + "type": "object", + "id": "GoogleCloudAiplatformV1Endpoint", + "properties": { + "trafficSplit": { + "additionalProperties": { + "type": "integer", + "format": "int32" + }, + "description": "A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If a DeployedModel's ID is not listed in this map, then it receives no traffic. The traffic percentage values must add up to 100, or map must be empty if the Endpoint is to not accept any traffic at a moment.", + "type": "object" + }, + "displayName": { + "type": "string", + "description": "Required. The display name of the Endpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters." + }, + "dedicatedEndpointEnabled": { + "description": "If true, the endpoint will be exposed through a dedicated DNS [Endpoint.dedicated_endpoint_dns]. Your request to the dedicated DNS will be isolated from other users' traffic and will have better performance and reliability. Note: Once you enabled dedicated endpoint, you won't be able to send request to the shared DNS {region}-aiplatform.googleapis.com. The limitation will be removed soon.", + "type": "boolean" + }, + "modelDeploymentMonitoringJob": { + "description": "Output only. Resource name of the Model Monitoring job associated with this Endpoint if monitoring is enabled by JobService.CreateModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`", + "readOnly": true, + "type": "string" + }, + "enablePrivateServiceConnect": { + "type": "boolean", + "deprecated": true, + "description": "Deprecated: If true, expose the Endpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set." + }, + "createTime": { + "format": "google-datetime", + "description": "Output only. Timestamp when this Endpoint was created.", + "type": "string", + "readOnly": true + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "The labels with user-defined metadata to organize your Endpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels." + }, + "dedicatedEndpointDns": { + "readOnly": true, + "type": "string", + "description": "Output only. DNS of the dedicated endpoint. Will only be populated if dedicated_endpoint_enabled is true. Format: `https://{endpoint_id}.{region}-{project_number}.prediction.vertexai.goog`." + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1EncryptionSpec", + "description": "Customer-managed encryption key spec for an Endpoint. If set, this Endpoint and all sub-resources of this Endpoint will be secured by this key." + }, + "privateServiceConnectConfig": { + "$ref": "GoogleCloudAiplatformV1PrivateServiceConnectConfig", + "description": "Optional. Configuration for private service connect. network and private_service_connect_config are mutually exclusive." + }, + "description": { + "description": "The description of the Endpoint.", + "type": "string" + }, + "name": { + "type": "string", + "readOnly": true, + "description": "Output only. The resource name of the Endpoint." + }, + "predictRequestResponseLoggingConfig": { + "$ref": "GoogleCloudAiplatformV1PredictRequestResponseLoggingConfig", + "description": "Configures the request-response logging for online prediction." + }, + "updateTime": { + "description": "Output only. Timestamp when this Endpoint was last updated.", + "readOnly": true, + "type": "string", + "format": "google-datetime" + }, + "network": { + "type": "string", + "description": "Optional. The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks) to which the Endpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. Only one of the fields, network or enable_private_service_connect, can be set. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert): `projects/{project}/global/networks/{network}`. Where `{project}` is a project number, as in `12345`, and `{network}` is network name." + }, + "deployedModels": { + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1DeployedModel" + }, + "description": "Output only. The models deployed in this Endpoint. To add or remove DeployedModels use EndpointService.DeployModel and EndpointService.UndeployModel respectively.", + "type": "array" + }, + "etag": { + "type": "string", + "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + } + }, + "description": "Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations." + }, + "GoogleCloudAiplatformV1ReadTensorboardSizeResponse": { + "id": "GoogleCloudAiplatformV1ReadTensorboardSizeResponse", + "properties": { + "storageSizeByte": { + "description": "Payload storage size for the TensorBoard", + "type": "string", + "format": "int64" + } + }, + "description": "Response message for TensorboardService.ReadTensorboardSize.", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsImageSegmentationEvaluationMetricsConfidenceMetricsEntry": { + "properties": { + "recall": { + "description": "Recall (True Positive Rate) for the given confidence threshold.", + "format": "float", + "type": "number" + }, + "confusionMatrix": { + "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix", + "description": "Confusion matrix for the given confidence threshold." + }, + "precision": { + "type": "number", + "format": "float", + "description": "Precision for the given confidence threshold." + }, + "iouScore": { + "description": "The intersection-over-union score. The measure of overlap of the annotation's category mask with ground truth category mask on the DataItem.", + "format": "float", + "type": "number" + }, + "diceScoreCoefficient": { + "format": "float", + "description": "DSC or the F1 score, The harmonic mean of recall and precision.", + "type": "number" + }, + "confidenceThreshold": { + "type": "number", + "format": "float", + "description": "Metrics are computed with an assumption that the model never returns predictions with score lower than this value." + } + }, + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsImageSegmentationEvaluationMetricsConfidenceMetricsEntry", + "type": "object" + }, + "GoogleCloudAiplatformV1MigratableResourceAutomlDataset": { + "description": "Represents one Dataset in automl.googleapis.com.", + "type": "object", + "properties": { + "datasetDisplayName": { + "description": "The Dataset's display name in automl.googleapis.com.", + "type": "string" + }, + "dataset": { + "type": "string", + "description": "Full resource name of automl Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`." + } + }, + "id": "GoogleCloudAiplatformV1MigratableResourceAutomlDataset" + }, + "GoogleCloudAiplatformV1FeatureViewSync": { + "id": "GoogleCloudAiplatformV1FeatureViewSync", + "description": "FeatureViewSync is a representation of sync operation which copies data from data source to Feature View in Online Store.", + "properties": { + "syncSummary": { + "description": "Output only. Summary of the sync job.", + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1FeatureViewSyncSyncSummary" + }, + "name": { + "type": "string", + "description": "Identifier. Name of the FeatureViewSync. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}/featureViewSyncs/{feature_view_sync}`" + }, + "createTime": { + "description": "Output only. Time when this FeatureViewSync is created. Creation of a FeatureViewSync means that the job is pending / waiting for sufficient resources but may not have started the actual data transfer yet.", + "readOnly": true, + "format": "google-datetime", + "type": "string" + }, + "runTime": { + "$ref": "GoogleTypeInterval", + "readOnly": true, + "description": "Output only. Time when this FeatureViewSync is finished." + }, + "finalStatus": { + "description": "Output only. Final status of the FeatureViewSync.", + "$ref": "GoogleRpcStatus", + "readOnly": true + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1QuestionAnsweringQualityInput": { + "properties": { + "metricSpec": { + "description": "Required. Spec for question answering quality score metric.", + "$ref": "GoogleCloudAiplatformV1QuestionAnsweringQualitySpec" + }, + "instance": { + "description": "Required. Question answering quality instance.", + "$ref": "GoogleCloudAiplatformV1QuestionAnsweringQualityInstance" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1QuestionAnsweringQualityInput", + "description": "Input for question answering quality metric." + }, + "GoogleCloudAiplatformV1TrainingConfig": { + "type": "object", + "id": "GoogleCloudAiplatformV1TrainingConfig", + "properties": { + "timeoutTrainingMilliHours": { + "description": "The timeout hours for the CMLE training job, expressed in milli hours i.e. 1,000 value in this field means 1 hour.", + "format": "int64", + "type": "string" + } + }, + "description": "CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems." + }, + "GoogleCloudAiplatformV1SchemaPredictInstanceVideoObjectTrackingPredictionInstance": { + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaPredictInstanceVideoObjectTrackingPredictionInstance", + "description": "Prediction input format for Video Object Tracking.", + "properties": { + "timeSegmentEnd": { + "description": "The end, exclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with \"s\" appended at the end. Fractions are allowed, up to a microsecond precision, and \"inf\" or \"Infinity\" is allowed, which means the end of the video.", + "type": "string" + }, + "content": { + "description": "The Google Cloud Storage location of the video on which to perform the prediction.", + "type": "string" + }, + "timeSegmentStart": { + "description": "The beginning, inclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with \"s\" appended at the end. Fractions are allowed, up to a microsecond precision.", + "type": "string" + }, + "mimeType": { + "description": "The MIME type of the content of the video. Only the following are supported: video/mp4 video/avi video/quicktime", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1ListTuningJobsResponse": { + "properties": { + "tuningJobs": { + "type": "array", + "description": "List of TuningJobs in the requested page.", + "items": { + "$ref": "GoogleCloudAiplatformV1TuningJob" + } + }, + "nextPageToken": { + "type": "string", + "description": "A token to retrieve the next page of results. Pass to ListTuningJobsRequest.page_token to obtain that page." + } + }, + "id": "GoogleCloudAiplatformV1ListTuningJobsResponse", + "description": "Response message for GenAiTuningService.ListTuningJobs", + "type": "object" + }, + "GoogleCloudAiplatformV1UpdateIndexOperationMetadata": { + "type": "object", + "description": "Runtime operation information for IndexService.UpdateIndex.", + "id": "GoogleCloudAiplatformV1UpdateIndexOperationMetadata", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The operation generic information." + }, + "nearestNeighborSearchOperationMetadata": { + "description": "The operation metadata with regard to Matching Engine Index operation.", + "$ref": "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadata" + } + } + }, + "GoogleCloudAiplatformV1PipelineTaskDetail": { + "description": "The runtime detail of a task execution.", + "id": "GoogleCloudAiplatformV1PipelineTaskDetail", + "properties": { + "startTime": { + "format": "google-datetime", + "readOnly": true, + "type": "string", + "description": "Output only. Task start time." + }, + "taskId": { + "readOnly": true, + "type": "string", + "format": "int64", + "description": "Output only. The system generated ID of the task." + }, + "execution": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1Execution", + "description": "Output only. The execution metadata of the task." + }, + "inputs": { + "type": "object", + "description": "Output only. The runtime input artifacts of the task.", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1PipelineTaskDetailArtifactList" + }, + "readOnly": true + }, + "error": { + "$ref": "GoogleRpcStatus", + "description": "Output only. The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.", + "readOnly": true + }, + "createTime": { + "description": "Output only. Task create time.", + "type": "string", + "format": "google-datetime", + "readOnly": true + }, + "endTime": { + "readOnly": true, + "type": "string", + "format": "google-datetime", + "description": "Output only. Task end time." + }, + "parentTaskId": { + "description": "Output only. The id of the parent task if the task is within a component scope. Empty if the task is at the root level.", + "format": "int64", + "type": "string", + "readOnly": true + }, + "state": { + "readOnly": true, + "type": "string", + "enumDescriptions": [ + "Unspecified.", + "Specifies pending state for the task.", + "Specifies task is being executed.", + "Specifies task completed successfully.", + "Specifies Task cancel is in pending state.", + "Specifies task is being cancelled.", + "Specifies task was cancelled.", + "Specifies task failed.", + "Specifies task was skipped due to cache hit.", + "Specifies that the task was not triggered because the task's trigger policy is not satisfied. The trigger policy is specified in the `condition` field of PipelineJob.pipeline_spec." + ], + "enum": [ + "STATE_UNSPECIFIED", + "PENDING", + "RUNNING", + "SUCCEEDED", + "CANCEL_PENDING", + "CANCELLING", + "CANCELLED", + "FAILED", + "SKIPPED", + "NOT_TRIGGERED" + ], + "description": "Output only. State of the task." + }, + "executorDetail": { + "description": "Output only. The detailed execution info.", + "$ref": "GoogleCloudAiplatformV1PipelineTaskExecutorDetail", + "readOnly": true + }, + "taskName": { + "readOnly": true, + "description": "Output only. The user specified name of the task that is defined in pipeline_spec.", + "type": "string" + }, + "pipelineTaskStatus": { + "items": { + "$ref": "GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatus" + }, + "type": "array", + "readOnly": true, + "description": "Output only. A list of task status. This field keeps a record of task status evolving over time." + }, + "outputs": { + "type": "object", + "description": "Output only. The runtime output artifacts of the task.", + "readOnly": true, + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1PipelineTaskDetailArtifactList" + } + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1AddExecutionEventsResponse": { + "description": "Response message for MetadataService.AddExecutionEvents.", + "id": "GoogleCloudAiplatformV1AddExecutionEventsResponse", + "type": "object", + "properties": {} + }, + "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadataGcsSource": { + "id": "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadataGcsSource", + "type": "object", + "properties": { + "uri": { + "description": "Cloud Storage URI of one or more files. Only CSV files are supported. The first line of the CSV file is used as the header. If there are multiple files, the header is the first line of the lexicographically first file, the other files must either contain the exact same header or omit the header.", + "type": "array", + "items": { + "type": "string" + } + } + } + }, + "GoogleCloudAiplatformV1PublisherModelCallToActionDeployGke": { + "description": "Configurations for PublisherModel GKE deployment", + "properties": { + "gkeYamlConfigs": { + "description": "Optional. GKE deployment configuration in yaml format.", + "items": { + "type": "string" + }, + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1PublisherModelCallToActionDeployGke", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaImageDataItem": { + "description": "Payload of Image DataItem.", + "type": "object", + "properties": { + "gcsUri": { + "description": "Required. Google Cloud Storage URI points to the original image in user's bucket. The image is up to 30MB in size.", + "type": "string" + }, + "mimeType": { + "readOnly": true, + "description": "Output only. The mime type of the content of the image. Only the images in below listed mime types are supported. - image/jpeg - image/gif - image/png - image/webp - image/bmp - image/tiff - image/vnd.microsoft.icon", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SchemaImageDataItem" + }, + "GoogleCloudAiplatformV1BleuInput": { + "id": "GoogleCloudAiplatformV1BleuInput", + "properties": { + "instances": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1BleuInstance" + }, + "description": "Required. Repeated bleu instances." + }, + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1BleuSpec", + "description": "Required. Spec for bleu score metric." + } + }, + "type": "object", + "description": "Input for bleu metric." + }, + "GoogleCloudAiplatformV1PublisherModelResourceReference": { + "description": "Reference to a resource.", + "id": "GoogleCloudAiplatformV1PublisherModelResourceReference", + "type": "object", + "properties": { + "resourceName": { + "type": "string", + "description": "The resource name of the Google Cloud resource." + }, + "useCase": { + "description": "Use case (CUJ) of the resource.", + "type": "string", + "deprecated": true + }, + "description": { + "description": "Description of the resource.", + "deprecated": true, + "type": "string" + }, + "uri": { + "description": "The URI of the resource.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1BatchCreateTensorboardTimeSeriesResponse": { + "id": "GoogleCloudAiplatformV1BatchCreateTensorboardTimeSeriesResponse", + "properties": { + "tensorboardTimeSeries": { + "items": { + "$ref": "GoogleCloudAiplatformV1TensorboardTimeSeries" + }, + "description": "The created TensorboardTimeSeries.", + "type": "array" + } + }, + "description": "Response message for TensorboardService.BatchCreateTensorboardTimeSeries.", + "type": "object" + }, + "GoogleCloudAiplatformV1NasJobOutput": { + "id": "GoogleCloudAiplatformV1NasJobOutput", + "description": "Represents a uCAIP NasJob output.", + "type": "object", + "properties": { + "multiTrialJobOutput": { + "description": "Output only. The output of this multi-trial Neural Architecture Search (NAS) job.", + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutput" + } + } + }, + "GoogleCloudAiplatformV1UndeployModelOperationMetadata": { + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The operation generic information." + } + }, + "description": "Runtime operation information for EndpointService.UndeployModel.", + "id": "GoogleCloudAiplatformV1UndeployModelOperationMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1UpgradeNotebookRuntimeRequest": { + "description": "Request message for NotebookService.UpgradeNotebookRuntime.", + "id": "GoogleCloudAiplatformV1UpgradeNotebookRuntimeRequest", + "type": "object", + "properties": {} + }, + "GoogleCloudAiplatformV1SchemaTextSegment": { + "description": "The text segment inside of DataItem.", + "properties": { + "content": { + "description": "The text content in the segment for output only.", + "type": "string" + }, + "startOffset": { + "description": "Zero-based character index of the first character of the text segment (counting characters from the beginning of the text).", + "type": "string", + "format": "uint64" + }, + "endOffset": { + "format": "uint64", + "type": "string", + "description": "Zero-based character index of the first character past the end of the text segment (counting character from the beginning of the text). The character at the end_offset is NOT included in the text segment." + } + }, + "id": "GoogleCloudAiplatformV1SchemaTextSegment", + "type": "object" + }, + "GoogleCloudAiplatformV1UpsertDatapointsResponse": { + "properties": {}, + "type": "object", + "id": "GoogleCloudAiplatformV1UpsertDatapointsResponse", + "description": "Response message for IndexService.UpsertDatapoints" + }, + "GoogleCloudAiplatformV1FindNeighborsResponseNearestNeighbors": { + "description": "Nearest neighbors for one query.", + "properties": { + "id": { + "description": "The ID of the query datapoint.", + "type": "string" + }, + "neighbors": { + "items": { + "$ref": "GoogleCloudAiplatformV1FindNeighborsResponseNeighbor" + }, + "type": "array", + "description": "All its neighbors." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1FindNeighborsResponseNearestNeighbors" + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsSummarizationEvaluationMetrics": { + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsSummarizationEvaluationMetrics", + "type": "object", + "properties": { + "rougeLSum": { + "description": "ROUGE-L (Longest Common Subsequence) scoring at summary level.", + "format": "float", + "type": "number" + } + } + }, + "GoogleCloudAiplatformV1ListDataLabelingJobsResponse": { + "type": "object", + "properties": { + "dataLabelingJobs": { + "type": "array", + "description": "A list of DataLabelingJobs that matches the specified filter in the request.", + "items": { + "$ref": "GoogleCloudAiplatformV1DataLabelingJob" + } + }, + "nextPageToken": { + "type": "string", + "description": "The standard List next-page token." + } + }, + "id": "GoogleCloudAiplatformV1ListDataLabelingJobsResponse", + "description": "Response message for JobService.ListDataLabelingJobs." + }, + "GoogleCloudAiplatformV1ExportModelOperationMetadataOutputInfo": { + "description": "Further describes the output of the ExportModel. Supplements ExportModelRequest.OutputConfig.", + "properties": { + "imageOutputUri": { + "readOnly": true, + "type": "string", + "description": "Output only. If the Model image is being exported to Google Container Registry or Artifact Registry this is the full path of the image created." + }, + "artifactOutputUri": { + "readOnly": true, + "description": "Output only. If the Model artifact is being exported to Google Cloud Storage this is the full path of the directory created, into which the Model files are being written to.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1ExportModelOperationMetadataOutputInfo" + }, + "GoogleCloudAiplatformV1SearchMigratableResourcesResponse": { + "id": "GoogleCloudAiplatformV1SearchMigratableResourcesResponse", + "type": "object", + "properties": { + "nextPageToken": { + "description": "The standard next-page token. The migratable_resources may not fill page_size in SearchMigratableResourcesRequest even when there are subsequent pages.", + "type": "string" + }, + "migratableResources": { + "type": "array", + "description": "All migratable resources that can be migrated to the location specified in the request.", + "items": { + "$ref": "GoogleCloudAiplatformV1MigratableResource" + } + } + }, + "description": "Response message for MigrationService.SearchMigratableResources." + }, + "GoogleCloudAiplatformV1CreateEntityTypeOperationMetadata": { + "id": "GoogleCloudAiplatformV1CreateEntityTypeOperationMetadata", + "type": "object", + "properties": { + "genericMetadata": { + "description": "Operation metadata for EntityType.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + }, + "description": "Details of operations that perform create EntityType." + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetrics": { + "type": "object", + "description": "Metrics for forecasting evaluation results.", + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetrics", + "properties": { + "weightedAbsolutePercentageError": { + "format": "float", + "type": "number", + "description": "Weighted Absolute Percentage Error. Does not use weights, this is just what the metric is called. Undefined if actual values sum to zero. Will be very large if actual values sum to a very small number." + }, + "meanAbsoluteError": { + "type": "number", + "format": "float", + "description": "Mean Absolute Error (MAE)." + }, + "quantileMetrics": { + "type": "array", + "description": "The quantile metrics entries for each quantile.", + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetricsQuantileMetricsEntry" + } + }, + "rootMeanSquaredPercentageError": { + "description": "Root Mean Square Percentage Error. Square root of MSPE. Undefined/imaginary when MSPE is negative.", + "format": "float", + "type": "number" + }, + "meanAbsolutePercentageError": { + "type": "number", + "format": "float", + "description": "Mean absolute percentage error. Infinity when there are zeros in the ground truth." + }, + "rootMeanSquaredLogError": { + "type": "number", + "description": "Root mean squared log error. Undefined when there are negative ground truth values or predictions.", + "format": "float" + }, + "rSquared": { + "format": "float", + "description": "Coefficient of determination as Pearson correlation coefficient. Undefined when ground truth or predictions are constant or near constant.", + "type": "number" + }, + "rootMeanSquaredError": { + "type": "number", + "format": "float", + "description": "Root Mean Squared Error (RMSE)." + } + } + }, + "GoogleCloudAiplatformV1FetchFeatureValuesResponseFeatureNameValuePairList": { + "properties": { + "features": { + "description": "List of feature names and values.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1FetchFeatureValuesResponseFeatureNameValuePairListFeatureNameValuePair" + } + } + }, + "type": "object", + "description": "Response structure in the format of key (feature name) and (feature) value pair.", + "id": "GoogleCloudAiplatformV1FetchFeatureValuesResponseFeatureNameValuePairList" + }, + "GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpec": { + "id": "GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpec", + "type": "object", + "description": "Value specification for a parameter in `DOUBLE` type.", + "properties": { + "minValue": { + "type": "number", + "format": "double", + "description": "Required. Inclusive minimum value of the parameter." + }, + "maxValue": { + "type": "number", + "description": "Required. Inclusive maximum value of the parameter.", + "format": "double" + }, + "defaultValue": { + "description": "A default value for a `DOUBLE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.", + "type": "number", + "format": "double" + } + } + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsPairwiseTextGenerationEvaluationMetrics": { + "description": "Metrics for general pairwise text generation evaluation results.", + "properties": { + "humanPreferenceBaselineModelWinRate": { + "format": "float", + "description": "Percentage of time humans decided the baseline model had the better response.", + "type": "number" + }, + "humanPreferenceModelWinRate": { + "description": "Percentage of time humans decided the model had the better response.", + "format": "float", + "type": "number" + }, + "cohensKappa": { + "format": "float", + "type": "number", + "description": "A measurement of agreement between the autorater and human raters that takes the likelihood of random agreement into account." + }, + "falseNegativeCount": { + "type": "string", + "description": "Number of examples where the autorater chose the baseline model, but humans preferred the model.", + "format": "int64" + }, + "modelWinRate": { + "format": "float", + "type": "number", + "description": "Percentage of time the autorater decided the model had the better response." + }, + "recall": { + "format": "float", + "type": "number", + "description": "Fraction of cases where the autorater and humans thought the model had a better response out of all cases where the humans thought the model had a better response." + }, + "baselineModelWinRate": { + "description": "Percentage of time the autorater decided the baseline model had the better response.", + "format": "float", + "type": "number" + }, + "trueNegativeCount": { + "type": "string", + "format": "int64", + "description": "Number of examples where both the autorater and humans decided that the model had the worse response." + }, + "truePositiveCount": { + "description": "Number of examples where both the autorater and humans decided that the model had the better response.", + "type": "string", + "format": "int64" + }, + "accuracy": { + "description": "Fraction of cases where the autorater agreed with the human raters.", + "type": "number", + "format": "float" + }, + "falsePositiveCount": { + "description": "Number of examples where the autorater chose the model, but humans preferred the baseline model.", + "format": "int64", + "type": "string" + }, + "precision": { + "type": "number", + "description": "Fraction of cases where the autorater and humans thought the model had a better response out of all cases where the autorater thought the model had a better response. True positive divided by all positive.", + "format": "float" + }, + "f1Score": { + "description": "Harmonic mean of precision and recall.", + "format": "float", + "type": "number" + } + }, + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsPairwiseTextGenerationEvaluationMetrics", + "type": "object" + }, + "GoogleCloudAiplatformV1ListTensorboardRunsResponse": { + "id": "GoogleCloudAiplatformV1ListTensorboardRunsResponse", + "type": "object", + "description": "Response message for TensorboardService.ListTensorboardRuns.", + "properties": { + "tensorboardRuns": { + "description": "The TensorboardRuns mathching the request.", + "items": { + "$ref": "GoogleCloudAiplatformV1TensorboardRun" + }, + "type": "array" + }, + "nextPageToken": { + "description": "A token, which can be sent as ListTensorboardRunsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter": { + "properties": { + "datasetConfig": { + "additionalProperties": { + "type": "string" + }, + "description": "Customizable dataset settings, used in the `model_garden_trainer`.", + "type": "object" + }, + "studySpec": { + "description": "Optioinal. StudySpec of hyperparameter tuning job. Required for `model_garden_trainer`.", + "$ref": "GoogleCloudAiplatformV1StudySpec" + }, + "trainerType": { + "enum": [ + "TRAINER_TYPE_UNSPECIFIED", + "AUTOML_TRAINER", + "MODEL_GARDEN_TRAINER" + ], + "type": "string", + "enumDescriptions": [ + "Default value.", + "", + "" + ] + }, + "checkpointName": { + "description": "Optional. An unique name of pretrained model checkpoint provided in model garden, it will be mapped to a GCS location internally.", + "type": "string" + }, + "trainerConfig": { + "description": "Customizable trainer settings, used in the `model_garden_trainer`.", + "additionalProperties": { + "type": "string" + }, + "type": "object" + } + }, + "type": "object", + "description": "A wrapper class which contains the tunable parameters in an AutoML Image training job.", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter" + }, + "GoogleCloudAiplatformV1RougeSpec": { + "id": "GoogleCloudAiplatformV1RougeSpec", + "type": "object", + "properties": { + "rougeType": { + "type": "string", + "description": "Optional. Supported rouge types are rougen[1-9], rougeL, and rougeLsum." + }, + "splitSummaries": { + "description": "Optional. Whether to split summaries while using rougeLsum.", + "type": "boolean" + }, + "useStemmer": { + "type": "boolean", + "description": "Optional. Whether to use stemmer to compute rouge score." + } + }, + "description": "Spec for rouge score metric - calculates the recall of n-grams in prediction as compared to reference - returns a score ranging between 0 and 1." + }, + "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualitySpec": { + "type": "object", + "properties": { + "version": { + "format": "int32", + "description": "Optional. Which version to use for evaluation.", + "type": "integer" + }, + "useReference": { + "type": "boolean", + "description": "Optional. Whether to use instance.reference to compute question answering quality." + } + }, + "description": "Spec for pairwise question answering quality score metric.", + "id": "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualitySpec" + }, + "GoogleCloudAiplatformV1ExactMatchInstance": { + "description": "Spec for exact match instance.", + "properties": { + "reference": { + "description": "Required. Ground truth used to compare against the prediction.", + "type": "string" + }, + "prediction": { + "description": "Required. Output of the evaluated model.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1ExactMatchInstance" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputs": { + "type": "object", + "properties": { + "additionalExperiments": { + "description": "Additional experiment flags for the Tables training pipeline.", + "items": { + "type": "string" + }, + "type": "array" + }, + "exportEvaluatedDataItemsConfig": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig", + "description": "Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed." + }, + "predictionType": { + "type": "string", + "description": "The type of prediction the Model is to produce. \"classification\" - Predict one out of multiple target values is picked for each row. \"regression\" - Predict a value based on its relation to other values. This type is available only to columns that contain semantically numeric values, i.e. integers or floating point number, even if stored as e.g. strings." + }, + "disableEarlyStopping": { + "description": "Use the entire training budget. This disables the early stopping feature. By default, the early stopping feature is enabled, which means that AutoML Tables might stop training before the entire training budget has been used.", + "type": "boolean" + }, + "transformations": { + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformation" + }, + "type": "array", + "description": "Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using \".\" as the delimiter." + }, + "targetColumn": { + "description": "The column name of the target column that the model is to predict.", + "type": "string" + }, + "weightColumnName": { + "type": "string", + "description": "Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1." + }, + "optimizationObjectivePrecisionValue": { + "type": "number", + "format": "float", + "description": "Required when optimization_objective is \"maximize-recall-at-precision\". Must be between 0 and 1, inclusive." + }, + "optimizationObjectiveRecallValue": { + "description": "Required when optimization_objective is \"maximize-precision-at-recall\". Must be between 0 and 1, inclusive.", + "type": "number", + "format": "float" + }, + "optimizationObjective": { + "type": "string", + "description": "Objective function the model is optimizing towards. The training process creates a model that maximizes/minimizes the value of the objective function over the validation set. The supported optimization objectives depend on the prediction type. If the field is not set, a default objective function is used. classification (binary): \"maximize-au-roc\" (default) - Maximize the area under the receiver operating characteristic (ROC) curve. \"minimize-log-loss\" - Minimize log loss. \"maximize-au-prc\" - Maximize the area under the precision-recall curve. \"maximize-precision-at-recall\" - Maximize precision for a specified recall value. \"maximize-recall-at-precision\" - Maximize recall for a specified precision value. classification (multi-class): \"minimize-log-loss\" (default) - Minimize log loss. regression: \"minimize-rmse\" (default) - Minimize root-mean-squared error (RMSE). \"minimize-mae\" - Minimize mean-absolute error (MAE). \"minimize-rmsle\" - Minimize root-mean-squared log error (RMSLE)." + }, + "trainBudgetMilliNodeHours": { + "type": "string", + "format": "int64", + "description": "Required. The train budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The training cost of the model will not exceed this budget. The final cost will be attempted to be close to the budget, though may end up being (even) noticeably smaller - at the backend's discretion. This especially may happen when further model training ceases to provide any improvements. If the budget is set to a value known to be insufficient to train a model for the given dataset, the training won't be attempted and will error. The train budget must be between 1,000 and 72,000 milli node hours, inclusive." + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputs" + }, + "GoogleCloudAiplatformV1DirectRawPredictRequest": { + "properties": { + "methodName": { + "type": "string", + "description": "Fully qualified name of the API method being invoked to perform predictions. Format: `/namespace.Service/Method/` Example: `/tensorflow.serving.PredictionService/Predict`" + }, + "input": { + "type": "string", + "format": "byte", + "description": "The prediction input." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1DirectRawPredictRequest", + "description": "Request message for PredictionService.DirectRawPredict." + }, + "GoogleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization": { + "description": "Visualization configurations for image explanation.", + "id": "GoogleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization", + "properties": { + "type": { + "enum": [ + "TYPE_UNSPECIFIED", + "PIXELS", + "OUTLINES" + ], + "type": "string", + "enumDescriptions": [ + "Should not be used.", + "Shows which pixel contributed to the image prediction.", + "Shows which region contributed to the image prediction by outlining the region." + ], + "description": "Type of the image visualization. Only applicable to Integrated Gradients attribution. OUTLINES shows regions of attribution, while PIXELS shows per-pixel attribution. Defaults to OUTLINES." + }, + "overlayType": { + "type": "string", + "enumDescriptions": [ + "Default value. This is the same as NONE.", + "No overlay.", + "The attributions are shown on top of the original image.", + "The attributions are shown on top of grayscaled version of the original image.", + "The attributions are used as a mask to reveal predictive parts of the image and hide the un-predictive parts." + ], + "description": "How the original image is displayed in the visualization. Adjusting the overlay can help increase visual clarity if the original image makes it difficult to view the visualization. Defaults to NONE.", + "enum": [ + "OVERLAY_TYPE_UNSPECIFIED", + "NONE", + "ORIGINAL", + "GRAYSCALE", + "MASK_BLACK" + ] + }, + "clipPercentLowerbound": { + "format": "float", + "type": "number", + "description": "Excludes attributions below the specified percentile, from the highlighted areas. Defaults to 62." + }, + "colorMap": { + "enumDescriptions": [ + "Should not be used.", + "Positive: green. Negative: pink.", + "Viridis color map: A perceptually uniform color mapping which is easier to see by those with colorblindness and progresses from yellow to green to blue. Positive: yellow. Negative: blue.", + "Positive: red. Negative: red.", + "Positive: green. Negative: green.", + "Positive: green. Negative: red.", + "PiYG palette." + ], + "description": "The color scheme used for the highlighted areas. Defaults to PINK_GREEN for Integrated Gradients attribution, which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for XRAI attribution, which highlights the most influential regions in yellow and the least influential in blue.", + "type": "string", + "enum": [ + "COLOR_MAP_UNSPECIFIED", + "PINK_GREEN", + "VIRIDIS", + "RED", + "GREEN", + "RED_GREEN", + "PINK_WHITE_GREEN" + ] + }, + "clipPercentUpperbound": { + "format": "float", + "description": "Excludes attributions above the specified percentile from the highlighted areas. Using the clip_percent_upperbound and clip_percent_lowerbound together can be useful for filtering out noise and making it easier to see areas of strong attribution. Defaults to 99.9.", + "type": "number" + }, + "polarity": { + "enum": [ + "POLARITY_UNSPECIFIED", + "POSITIVE", + "NEGATIVE", + "BOTH" + ], + "enumDescriptions": [ + "Default value. This is the same as POSITIVE.", + "Highlights the pixels/outlines that were most influential to the model's prediction.", + "Setting polarity to negative highlights areas that does not lead to the models's current prediction.", + "Shows both positive and negative attributions." + ], + "type": "string", + "description": "Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecasting": { + "properties": { + "inputs": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputs", + "description": "The input parameters of this TrainingJob." + }, + "metadata": { + "description": "The metadata information.", + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingMetadata" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecasting", + "description": "A TrainingJob that trains and uploads an AutoML Forecasting Model." + }, + "GoogleCloudAiplatformV1StudySpecMetricSpec": { + "properties": { + "goal": { + "type": "string", + "enumDescriptions": [ + "Goal Type will default to maximize.", + "Maximize the goal metric.", + "Minimize the goal metric." + ], + "enum": [ + "GOAL_TYPE_UNSPECIFIED", + "MAXIMIZE", + "MINIMIZE" + ], + "description": "Required. The optimization goal of the metric." + }, + "safetyConfig": { + "description": "Used for safe search. In the case, the metric will be a safety metric. You must provide a separate metric for objective metric.", + "$ref": "GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfig" + }, + "metricId": { + "type": "string", + "description": "Required. The ID of the metric. Must not contain whitespaces and must be unique amongst all MetricSpecs." + } + }, + "description": "Represents a metric to optimize.", + "id": "GoogleCloudAiplatformV1StudySpecMetricSpec", + "type": "object" + }, + "GoogleCloudAiplatformV1ToolNameMatchMetricValue": { + "type": "object", + "id": "GoogleCloudAiplatformV1ToolNameMatchMetricValue", + "properties": { + "score": { + "readOnly": true, + "type": "number", + "format": "float", + "description": "Output only. Tool name match score." + } + }, + "description": "Tool name match metric value for an instance." + }, + "GoogleCloudAiplatformV1ModelMonitoringStatsAnomalies": { + "type": "object", + "properties": { + "anomalyCount": { + "type": "integer", + "format": "int32", + "description": "Number of anomalies within all stats." + }, + "featureStats": { + "items": { + "$ref": "GoogleCloudAiplatformV1ModelMonitoringStatsAnomaliesFeatureHistoricStatsAnomalies" + }, + "description": "A list of historical Stats and Anomalies generated for all Features.", + "type": "array" + }, + "objective": { + "type": "string", + "enum": [ + "MODEL_DEPLOYMENT_MONITORING_OBJECTIVE_TYPE_UNSPECIFIED", + "RAW_FEATURE_SKEW", + "RAW_FEATURE_DRIFT", + "FEATURE_ATTRIBUTION_SKEW", + "FEATURE_ATTRIBUTION_DRIFT" + ], + "enumDescriptions": [ + "Default value, should not be set.", + "Raw feature values' stats to detect skew between Training-Prediction datasets.", + "Raw feature values' stats to detect drift between Serving-Prediction datasets.", + "Feature attribution scores to detect skew between Training-Prediction datasets.", + "Feature attribution scores to detect skew between Prediction datasets collected within different time windows." + ], + "description": "Model Monitoring Objective those stats and anomalies belonging to." + }, + "deployedModelId": { + "description": "Deployed Model ID.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1ModelMonitoringStatsAnomalies", + "description": "Statistics and anomalies generated by Model Monitoring." + }, + "GoogleCloudAiplatformV1CreateTensorboardOperationMetadata": { + "description": "Details of operations that perform create Tensorboard.", + "properties": { + "genericMetadata": { + "description": "Operation metadata for Tensorboard.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1CreateTensorboardOperationMetadata" + }, + "GoogleCloudAiplatformV1SummarizationHelpfulnessResult": { + "properties": { + "score": { + "readOnly": true, + "type": "number", + "description": "Output only. Summarization Helpfulness score.", + "format": "float" + }, + "confidence": { + "format": "float", + "description": "Output only. Confidence for summarization helpfulness score.", + "readOnly": true, + "type": "number" + }, + "explanation": { + "description": "Output only. Explanation for summarization helpfulness score.", + "type": "string", + "readOnly": true + } + }, + "description": "Spec for summarization helpfulness result.", + "type": "object", + "id": "GoogleCloudAiplatformV1SummarizationHelpfulnessResult" + }, + "GoogleCloudAiplatformV1UpdateTensorboardOperationMetadata": { + "properties": { + "genericMetadata": { + "description": "Operation metadata for Tensorboard.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + }, + "description": "Details of operations that perform update Tensorboard.", + "type": "object", + "id": "GoogleCloudAiplatformV1UpdateTensorboardOperationMetadata" + }, + "GoogleCloudAiplatformV1IndexDatapointNumericRestriction": { + "id": "GoogleCloudAiplatformV1IndexDatapointNumericRestriction", + "type": "object", + "properties": { + "valueInt": { + "format": "int64", + "type": "string", + "description": "Represents 64 bit integer." + }, + "op": { + "enum": [ + "OPERATOR_UNSPECIFIED", + "LESS", + "LESS_EQUAL", + "EQUAL", + "GREATER_EQUAL", + "GREATER", + "NOT_EQUAL" + ], + "type": "string", + "enumDescriptions": [ + "Default value of the enum.", + "Datapoints are eligible iff their value is \u003c the query's.", + "Datapoints are eligible iff their value is \u003c= the query's.", + "Datapoints are eligible iff their value is == the query's.", + "Datapoints are eligible iff their value is \u003e= the query's.", + "Datapoints are eligible iff their value is \u003e the query's.", + "Datapoints are eligible iff their value is != the query's." + ], + "description": "This MUST be specified for queries and must NOT be specified for datapoints." + }, + "namespace": { + "description": "The namespace of this restriction. e.g.: cost.", + "type": "string" + }, + "valueFloat": { + "format": "float", + "description": "Represents 32 bit float.", + "type": "number" + }, + "valueDouble": { + "type": "number", + "description": "Represents 64 bit float.", + "format": "double" + } + }, + "description": "This field allows restricts to be based on numeric comparisons rather than categorical tokens." + }, + "GoogleCloudAiplatformV1PublisherModelCallToActionDeployDeployMetadata": { + "id": "GoogleCloudAiplatformV1PublisherModelCallToActionDeployDeployMetadata", + "properties": { + "labels": { + "type": "object", + "description": "Optional. Labels for the deployment. For managing deployment config like verifying, source of deployment config, etc.", + "additionalProperties": { + "type": "string" + } + } + }, + "description": "Metadata information about the deployment for managing deployment config.", + "type": "object" + }, + "GoogleCloudAiplatformV1ModelMonitoringAlertConfig": { + "properties": { + "emailAlertConfig": { + "$ref": "GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfig", + "description": "Email alert config." + }, + "notificationChannels": { + "items": { + "type": "string" + }, + "description": "Resource names of the NotificationChannels to send alert. Must be of the format `projects//notificationChannels/`", + "type": "array" + }, + "enableLogging": { + "description": "Dump the anomalies to Cloud Logging. The anomalies will be put to json payload encoded from proto google.cloud.aiplatform.logging.ModelMonitoringAnomaliesLogEntry. This can be further sinked to Pub/Sub or any other services supported by Cloud Logging.", + "type": "boolean" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1ModelMonitoringAlertConfig", + "description": "The alert config for model monitoring." + }, + "GoogleCloudAiplatformV1CopyModelRequest": { + "properties": { + "sourceModel": { + "description": "Required. The resource name of the Model to copy. That Model must be in the same Project. Format: `projects/{project}/locations/{location}/models/{model}`", + "type": "string" + }, + "modelId": { + "type": "string", + "description": "Optional. Copy source_model into a new Model with this ID. The ID will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen." + }, + "encryptionSpec": { + "description": "Customer-managed encryption key options. If this is set, then the Model copy will be encrypted with the provided encryption key.", + "$ref": "GoogleCloudAiplatformV1EncryptionSpec" + }, + "parentModel": { + "description": "Optional. Specify this field to copy source_model into this existing Model as a new version. Format: `projects/{project}/locations/{location}/models/{model}`", + "type": "string" + } + }, + "type": "object", + "description": "Request message for ModelService.CopyModel.", + "id": "GoogleCloudAiplatformV1CopyModelRequest" + }, + "GoogleCloudAiplatformV1ListSpecialistPoolsResponse": { + "description": "Response message for SpecialistPoolService.ListSpecialistPools.", + "type": "object", + "id": "GoogleCloudAiplatformV1ListSpecialistPoolsResponse", + "properties": { + "nextPageToken": { + "type": "string", + "description": "The standard List next-page token." + }, + "specialistPools": { + "description": "A list of SpecialistPools that matches the specified filter in the request.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1SpecialistPool" + } + } + } + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationCategoricalTransformation": { + "properties": { + "columnName": { + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationCategoricalTransformation", + "type": "object", + "description": "Training pipeline will perform following transformation functions. * The categorical string as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. * Categories that appear less than 5 times in the training dataset are treated as the \"unknown\" category. The \"unknown\" category gets its own special lookup index and resulting embedding." + }, + "GoogleCloudAiplatformV1StreamingPredictRequest": { + "type": "object", + "description": "Request message for PredictionService.StreamingPredict. The first message must contain endpoint field and optionally input. The subsequent messages must contain input.", + "properties": { + "parameters": { + "$ref": "GoogleCloudAiplatformV1Tensor", + "description": "The parameters that govern the prediction." + }, + "inputs": { + "items": { + "$ref": "GoogleCloudAiplatformV1Tensor" + }, + "description": "The prediction input.", + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1StreamingPredictRequest" + }, + "GoogleCloudAiplatformV1CreateMetadataStoreOperationMetadata": { + "description": "Details of operations that perform MetadataService.CreateMetadataStore.", + "id": "GoogleCloudAiplatformV1CreateMetadataStoreOperationMetadata", + "type": "object", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "Operation metadata for creating a MetadataStore." + } + } + }, + "GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScaling": { + "type": "object", + "description": "Online serving scaling configuration. If min_node_count and max_node_count are set to the same value, the cluster will be configured with the fixed number of node (no auto-scaling).", + "properties": { + "minNodeCount": { + "format": "int32", + "description": "Required. The minimum number of nodes to scale down to. Must be greater than or equal to 1.", + "type": "integer" + }, + "maxNodeCount": { + "description": "The maximum number of nodes to scale up to. Must be greater than min_node_count, and less than or equal to 10 times of 'min_node_count'.", + "format": "int32", + "type": "integer" + }, + "cpuUtilizationTarget": { + "type": "integer", + "description": "Optional. The cpu utilization that the Autoscaler should be trying to achieve. This number is on a scale from 0 (no utilization) to 100 (total utilization), and is limited between 10 and 80. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set or set to 0, default to 50.", + "format": "int32" + } + }, + "id": "GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScaling" + }, + "GoogleCloudAiplatformV1ReadFeatureValuesResponseEntityViewData": { + "description": "Container to hold value(s), successive in time, for one Feature from the request.", + "properties": { + "values": { + "$ref": "GoogleCloudAiplatformV1FeatureValueList", + "description": "Feature values list if values, successive in time, are requested. If the requested number of values is greater than the number of existing Feature values, nonexistent values are omitted instead of being returned as empty." + }, + "value": { + "description": "Feature value if a single value is requested.", + "$ref": "GoogleCloudAiplatformV1FeatureValue" + } + }, + "id": "GoogleCloudAiplatformV1ReadFeatureValuesResponseEntityViewData", + "type": "object" + }, + "GoogleCloudAiplatformV1CreateFeatureRequest": { + "id": "GoogleCloudAiplatformV1CreateFeatureRequest", + "type": "object", + "description": "Request message for FeaturestoreService.CreateFeature. Request message for FeatureRegistryService.CreateFeature.", + "properties": { + "parent": { + "type": "string", + "description": "Required. The resource name of the EntityType or FeatureGroup to create a Feature. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`" + }, + "featureId": { + "type": "string", + "description": "Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup." + }, + "feature": { + "$ref": "GoogleCloudAiplatformV1Feature", + "description": "Required. The Feature to create." + } + } + }, + "GoogleCloudAiplatformV1BatchReadFeatureValuesRequestEntityTypeSpec": { + "description": "Selects Features of an EntityType to read values of and specifies read settings.", + "type": "object", + "properties": { + "settings": { + "description": "Per-Feature settings for the batch read.", + "items": { + "$ref": "GoogleCloudAiplatformV1DestinationFeatureSetting" + }, + "type": "array" + }, + "entityTypeId": { + "type": "string", + "description": "Required. ID of the EntityType to select Features. The EntityType id is the entity_type_id specified during EntityType creation." + }, + "featureSelector": { + "$ref": "GoogleCloudAiplatformV1FeatureSelector", + "description": "Required. Selectors choosing which Feature values to read from the EntityType." + } + }, + "id": "GoogleCloudAiplatformV1BatchReadFeatureValuesRequestEntityTypeSpec" + }, + "GoogleCloudAiplatformV1TensorboardRun": { + "description": "TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc", + "properties": { + "labels": { + "type": "object", + "additionalProperties": { + "type": "string" + }, + "description": "The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." + }, + "displayName": { + "description": "Required. User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.", + "type": "string" + }, + "createTime": { + "description": "Output only. Timestamp when this TensorboardRun was created.", + "format": "google-datetime", + "type": "string", + "readOnly": true + }, + "updateTime": { + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Timestamp when this TensorboardRun was last updated.", + "type": "string" + }, + "name": { + "type": "string", + "description": "Output only. Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", + "readOnly": true + }, + "description": { + "description": "Description of this TensorboardRun.", + "type": "string" + }, + "etag": { + "description": "Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1TensorboardRun" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecasting": { + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecasting", + "properties": { + "inputs": { + "description": "The input parameters of this TrainingJob.", + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputs" + }, + "metadata": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingMetadata", + "description": "The metadata information." + } + }, + "type": "object", + "description": "A TrainingJob that trains and uploads an AutoML Forecasting Model." + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingMetadata": { + "properties": { + "evaluatedDataItemsBigqueryUri": { + "type": "string", + "description": "BigQuery destination uri for exported evaluated examples." + }, + "trainCostMilliNodeHours": { + "format": "int64", + "description": "Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget.", + "type": "string" + } + }, + "type": "object", + "description": "Model metadata specific to Seq2Seq Plus Forecasting.", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingMetadata" + }, + "GoogleCloudAiplatformV1ModelGardenSource": { + "description": "Contains information about the source of the models generated from Model Garden.", + "id": "GoogleCloudAiplatformV1ModelGardenSource", + "properties": { + "publicModelName": { + "description": "Required. The model garden source model resource name.", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationNumericTransformation": { + "properties": { + "columnName": { + "type": "string" + } + }, + "description": "Training pipeline will perform following transformation functions. * The value converted to float32. * The z_score of the value. * log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationNumericTransformation", + "type": "object" + }, + "GoogleIamV1SetIamPolicyRequest": { + "properties": { + "policy": { + "description": "REQUIRED: The complete policy to be applied to the `resource`. The size of the policy is limited to a few 10s of KB. An empty policy is a valid policy but certain Google Cloud services (such as Projects) might reject them.", + "$ref": "GoogleIamV1Policy" + } + }, + "id": "GoogleIamV1SetIamPolicyRequest", + "description": "Request message for `SetIamPolicy` method.", + "type": "object" + }, + "GoogleCloudAiplatformV1FeatureSelector": { + "description": "Selector for Features of an EntityType.", + "properties": { + "idMatcher": { + "$ref": "GoogleCloudAiplatformV1IdMatcher", + "description": "Required. Matches Features based on ID." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1FeatureSelector" + }, + "GoogleCloudAiplatformV1RemoveDatapointsResponse": { + "id": "GoogleCloudAiplatformV1RemoveDatapointsResponse", + "properties": {}, + "type": "object", + "description": "Response message for IndexService.RemoveDatapoints" + }, + "GoogleCloudAiplatformV1BatchImportEvaluatedAnnotationsRequest": { + "id": "GoogleCloudAiplatformV1BatchImportEvaluatedAnnotationsRequest", + "description": "Request message for ModelService.BatchImportEvaluatedAnnotations", + "type": "object", + "properties": { + "evaluatedAnnotations": { + "description": "Required. Evaluated annotations resource to be imported.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1EvaluatedAnnotation" + } + } + } + }, + "GoogleCloudAiplatformV1ListDeploymentResourcePoolsResponse": { + "properties": { + "deploymentResourcePools": { + "description": "The DeploymentResourcePools from the specified location.", + "items": { + "$ref": "GoogleCloudAiplatformV1DeploymentResourcePool" + }, + "type": "array" + }, + "nextPageToken": { + "description": "A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1ListDeploymentResourcePoolsResponse", + "description": "Response message for ListDeploymentResourcePools method.", + "type": "object" + }, + "GoogleCloudAiplatformV1LargeModelReference": { + "type": "object", + "properties": { + "name": { + "description": "Required. The unique name of the large Foundation or pre-built model. Like \"chat-bison\", \"text-bison\". Or model name with version ID, like \"chat-bison@001\", \"text-bison@005\", etc.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1LargeModelReference", + "description": "Contains information about the Large Model." + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsBoundingBoxMetrics": { + "properties": { + "confidenceMetrics": { + "type": "array", + "description": "Metrics for each label-match confidence_threshold from 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is derived from them.", + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsBoundingBoxMetricsConfidenceMetrics" + } + }, + "iouThreshold": { + "format": "float", + "description": "The intersection-over-union threshold value used to compute this metrics entry.", + "type": "number" + }, + "meanAveragePrecision": { + "format": "float", + "description": "The mean average precision, most often close to `auPrc`.", + "type": "number" + } + }, + "description": "Bounding box matching model metrics for a single intersection-over-union threshold and multiple label match confidence thresholds.", + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsBoundingBoxMetrics" + }, + "GoogleCloudAiplatformV1PublisherModelCallToActionOpenFineTuningPipelines": { + "type": "object", + "id": "GoogleCloudAiplatformV1PublisherModelCallToActionOpenFineTuningPipelines", + "properties": { + "fineTuningPipelines": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences" + }, + "description": "Required. Regional resource references to fine tuning pipelines." + } + }, + "description": "Open fine tuning pipelines." + }, + "GoogleCloudAiplatformV1CsvSource": { + "type": "object", + "description": "The storage details for CSV input content.", + "id": "GoogleCloudAiplatformV1CsvSource", + "properties": { + "gcsSource": { + "$ref": "GoogleCloudAiplatformV1GcsSource", + "description": "Required. Google Cloud Storage location." + } + } + }, + "GoogleCloudAiplatformV1UpdateFeatureGroupOperationMetadata": { + "id": "GoogleCloudAiplatformV1UpdateFeatureGroupOperationMetadata", + "description": "Details of operations that perform update FeatureGroup.", + "properties": { + "genericMetadata": { + "description": "Operation metadata for FeatureGroup.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1DeleteMetadataStoreOperationMetadata": { + "id": "GoogleCloudAiplatformV1DeleteMetadataStoreOperationMetadata", + "properties": { + "genericMetadata": { + "description": "Operation metadata for deleting a MetadataStore.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + }, + "description": "Details of operations that perform MetadataService.DeleteMetadataStore.", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTextDatasetMetadata": { + "type": "object", + "description": "The metadata of Datasets that contain Text DataItems.", + "properties": { + "dataItemSchemaUri": { + "type": "string", + "description": "Points to a YAML file stored on Google Cloud Storage describing payload of the Text DataItems that belong to this Dataset." + }, + "gcsBucket": { + "description": "Google Cloud Storage Bucket name that contains the blob data of this Dataset.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTextDatasetMetadata" + }, + "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotationPolylineAnnotation": { + "properties": { + "annotationSpecId": { + "type": "string", + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." + }, + "vertexes": { + "description": "The vertexes are connected one by one and the last vertex in not connected to the first one.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaVertex" + } + }, + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that this Annotation pertains to." + } + }, + "id": "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotationPolylineAnnotation", + "description": "Represents a polyline in image.", + "type": "object" + }, + "GoogleCloudAiplatformV1UpdateFeatureViewOperationMetadata": { + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "Operation metadata for FeatureView Update." + } + }, + "description": "Details of operations that perform update FeatureView.", + "type": "object", + "id": "GoogleCloudAiplatformV1UpdateFeatureViewOperationMetadata" + }, + "GoogleIamV1Binding": { + "description": "Associates `members`, or principals, with a `role`.", + "id": "GoogleIamV1Binding", + "properties": { + "members": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Specifies the principals requesting access for a Google Cloud resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. Does not include identities that come from external identity providers (IdPs) through identity federation. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a Google service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `serviceAccount:{projectid}.svc.id.goog[{namespace}/{kubernetes-sa}]`: An identifier for a [Kubernetes service account](https://cloud.google.com/kubernetes-engine/docs/how-to/kubernetes-service-accounts). For example, `my-project.svc.id.goog[my-namespace/my-kubernetes-sa]`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`. * `principal://iam.googleapis.com/locations/global/workforcePools/{pool_id}/subject/{subject_attribute_value}`: A single identity in a workforce identity pool. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/group/{group_id}`: All workforce identities in a group. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/attribute.{attribute_name}/{attribute_value}`: All workforce identities with a specific attribute value. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/*`: All identities in a workforce identity pool. * `principal://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/subject/{subject_attribute_value}`: A single identity in a workload identity pool. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/group/{group_id}`: A workload identity pool group. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/attribute.{attribute_name}/{attribute_value}`: All identities in a workload identity pool with a certain attribute. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/*`: All identities in a workload identity pool. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding. * `deleted:principal://iam.googleapis.com/locations/global/workforcePools/{pool_id}/subject/{subject_attribute_value}`: Deleted single identity in a workforce identity pool. For example, `deleted:principal://iam.googleapis.com/locations/global/workforcePools/my-pool-id/subject/my-subject-attribute-value`." + }, + "role": { + "type": "string", + "description": "Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`. For an overview of the IAM roles and permissions, see the [IAM documentation](https://cloud.google.com/iam/docs/roles-overview). For a list of the available pre-defined roles, see [here](https://cloud.google.com/iam/docs/understanding-roles)." + }, + "condition": { + "description": "The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", + "$ref": "GoogleTypeExpr" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1ListMetadataStoresResponse": { + "id": "GoogleCloudAiplatformV1ListMetadataStoresResponse", + "description": "Response message for MetadataService.ListMetadataStores.", + "type": "object", + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token, which can be sent as ListMetadataStoresRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages." + }, + "metadataStores": { + "description": "The MetadataStores found for the Location.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1MetadataStore" + } + } + } + }, + "GoogleCloudAiplatformV1GroundingChunkWeb": { + "id": "GoogleCloudAiplatformV1GroundingChunkWeb", + "description": "Chunk from the web.", + "properties": { + "title": { + "description": "Title of the chunk.", + "type": "string" + }, + "uri": { + "type": "string", + "description": "URI reference of the chunk." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpec": { + "properties": { + "minMeasurementCount": { + "description": "The minimal number of measurements in a Trial. Early-stopping checks will not trigger if less than min_measurement_count+1 completed trials or pending trials with less than min_measurement_count measurements. If not defined, the default value is 5.", + "format": "int64", + "type": "string" + }, + "minStepCount": { + "type": "string", + "format": "int64", + "description": "Minimum number of steps for a trial to complete. Trials which do not have a measurement with step_count \u003e min_step_count won't be considered for early stopping. It's ok to set it to 0, and a trial can be early stopped at any stage. By default, min_step_count is set to be one-tenth of the max_step_count. When use_elapsed_duration is true, this field is set to the minimum elapsed seconds." + }, + "maxStepCount": { + "format": "int64", + "type": "string", + "description": "Steps used in predicting the final objective for early stopped trials. In general, it's set to be the same as the defined steps in training / tuning. If not defined, it will learn it from the completed trials. When use_steps is false, this field is set to the maximum elapsed seconds." + }, + "updateAllStoppedTrials": { + "type": "boolean", + "description": "ConvexAutomatedStoppingSpec by default only updates the trials that needs to be early stopped using a newly trained auto-regressive model. When this flag is set to True, all stopped trials from the beginning are potentially updated in terms of their `final_measurement`. Also, note that the training logic of autoregressive models is different in this case. Enabling this option has shown better results and this may be the default option in the future." + }, + "useElapsedDuration": { + "description": "This bool determines whether or not the rule is applied based on elapsed_secs or steps. If use_elapsed_duration==false, the early stopping decision is made according to the predicted objective values according to the target steps. If use_elapsed_duration==true, elapsed_secs is used instead of steps. Also, in this case, the parameters max_num_steps and min_num_steps are overloaded to contain max_elapsed_seconds and min_elapsed_seconds.", + "type": "boolean" + }, + "learningRateParameterName": { + "type": "string", + "description": "The hyper-parameter name used in the tuning job that stands for learning rate. Leave it blank if learning rate is not in a parameter in tuning. The learning_rate is used to estimate the objective value of the ongoing trial." + } + }, + "description": "Configuration for ConvexAutomatedStoppingSpec. When there are enough completed trials (configured by min_measurement_count), for pending trials with enough measurements and steps, the policy first computes an overestimate of the objective value at max_num_steps according to the slope of the incomplete objective value curve. No prediction can be made if the curve is completely flat. If the overestimation is worse than the best objective value of the completed trials, this pending trial will be early-stopped, but a last measurement will be added to the pending trial with max_num_steps and predicted objective value from the autoregression model.", + "type": "object", + "id": "GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpec" + }, + "GoogleCloudAiplatformV1MigrateResourceRequestMigrateAutomlDatasetConfig": { + "properties": { + "dataset": { + "description": "Required. Full resource name of automl Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`.", + "type": "string" + }, + "datasetDisplayName": { + "type": "string", + "description": "Required. Display name of the Dataset in Vertex AI. System will pick a display name if unspecified." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateAutomlDatasetConfig", + "description": "Config for migrating Dataset in automl.googleapis.com to Vertex AI's Dataset." + }, + "GoogleCloudAiplatformV1AutomaticResources": { + "properties": { + "maxReplicaCount": { + "format": "int32", + "description": "Immutable. The maximum number of replicas this DeployedModel may be deployed on when the traffic against it increases. If the requested value is too large, the deployment will error, but if deployment succeeds then the ability to scale the model to that many replicas is guaranteed (barring service outages). If traffic against the DeployedModel increases beyond what its replicas at maximum may handle, a portion of the traffic will be dropped. If this value is not provided, a no upper bound for scaling under heavy traffic will be assume, though Vertex AI may be unable to scale beyond certain replica number.", + "type": "integer" + }, + "minReplicaCount": { + "description": "Immutable. The minimum number of replicas this DeployedModel will be always deployed on. If traffic against it increases, it may dynamically be deployed onto more replicas up to max_replica_count, and as traffic decreases, some of these extra replicas may be freed. If the requested value is too large, the deployment will error.", + "type": "integer", + "format": "int32" + } + }, + "id": "GoogleCloudAiplatformV1AutomaticResources", + "description": "A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration. Each Model supporting these resources documents its specific guidelines.", + "type": "object" + }, + "GoogleCloudAiplatformV1EntityType": { + "properties": { + "etag": { + "description": "Optional. Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "labels": { + "description": "Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "updateTime": { + "format": "google-datetime", + "description": "Output only. Timestamp when this EntityType was most recently updated.", + "type": "string", + "readOnly": true + }, + "description": { + "type": "string", + "description": "Optional. Description of the EntityType." + }, + "createTime": { + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Timestamp when this EntityType was created.", + "type": "string" + }, + "monitoringConfig": { + "$ref": "GoogleCloudAiplatformV1FeaturestoreMonitoringConfig", + "description": "Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled." + }, + "name": { + "description": "Immutable. Name of the EntityType. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.", + "type": "string" + }, + "offlineStorageTtlDays": { + "type": "integer", + "format": "int32", + "description": "Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than `offline_storage_ttl_days` since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL." + } + }, + "type": "object", + "description": "An entity type is a type of object in a system that needs to be modeled and have stored information about. For example, driver is an entity type, and driver0 is an instance of an entity type driver.", + "id": "GoogleCloudAiplatformV1EntityType" + }, + "GoogleCloudAiplatformV1StudyTimeConstraint": { + "properties": { + "endTime": { + "description": "Compares the wallclock time to this time. Must use UTC timezone.", + "format": "google-datetime", + "type": "string" + }, + "maxDuration": { + "description": "Counts the wallclock time passed since the creation of this Study.", + "format": "google-duration", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1StudyTimeConstraint", + "type": "object", + "description": "Time-based Constraint for Study" + }, + "GoogleCloudAiplatformV1PrivateEndpoints": { + "type": "object", + "description": "PrivateEndpoints proto is used to provide paths for users to send requests privately. To send request via private service access, use predict_http_uri, explain_http_uri or health_http_uri. To send request via private service connect, use service_attachment.", + "id": "GoogleCloudAiplatformV1PrivateEndpoints", + "properties": { + "explainHttpUri": { + "readOnly": true, + "type": "string", + "description": "Output only. Http(s) path to send explain requests." + }, + "serviceAttachment": { + "readOnly": true, + "type": "string", + "description": "Output only. The name of the service attachment resource. Populated if private service connect is enabled." + }, + "healthHttpUri": { + "description": "Output only. Http(s) path to send health check requests.", + "type": "string", + "readOnly": true + }, + "predictHttpUri": { + "description": "Output only. Http(s) path to send prediction requests.", + "type": "string", + "readOnly": true + } + } + }, + "GoogleCloudAiplatformV1CountTokensResponse": { + "type": "object", + "properties": { + "totalBillableCharacters": { + "format": "int32", + "type": "integer", + "description": "The total number of billable characters counted across all instances from the request." + }, + "totalTokens": { + "format": "int32", + "description": "The total number of tokens counted across all instances from the request.", + "type": "integer" + } + }, + "id": "GoogleCloudAiplatformV1CountTokensResponse", + "description": "Response message for PredictionService.CountTokens." + }, + "GoogleCloudAiplatformV1AddExecutionEventsRequest": { + "description": "Request message for MetadataService.AddExecutionEvents.", + "id": "GoogleCloudAiplatformV1AddExecutionEventsRequest", + "properties": { + "events": { + "description": "The Events to create and add.", + "items": { + "$ref": "GoogleCloudAiplatformV1Event" + }, + "type": "array" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1TensorboardTimeSeriesMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1TensorboardTimeSeriesMetadata", + "description": "Describes metadata for a TensorboardTimeSeries.", + "properties": { + "maxWallTime": { + "format": "google-datetime", + "readOnly": true, + "type": "string", + "description": "Output only. Max wall clock timestamp of all data points within a TensorboardTimeSeries." + }, + "maxBlobSequenceLength": { + "readOnly": true, + "type": "string", + "description": "Output only. The largest blob sequence length (number of blobs) of all data points in this time series, if its ValueType is BLOB_SEQUENCE.", + "format": "int64" + }, + "maxStep": { + "format": "int64", + "type": "string", + "description": "Output only. Max step index of all data points within a TensorboardTimeSeries.", + "readOnly": true + } + } + }, + "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfig": { + "id": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfig", + "properties": { + "trainingDataset": { + "$ref": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDataset", + "description": "Training dataset for models. This field has to be set only if TrainingPredictionSkewDetectionConfig is specified." + }, + "predictionDriftDetectionConfig": { + "$ref": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig", + "description": "The config for drift of prediction data." + }, + "trainingPredictionSkewDetectionConfig": { + "$ref": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig", + "description": "The config for skew between training data and prediction data." + }, + "explanationConfig": { + "$ref": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfig", + "description": "The config for integrating with Vertex Explainable AI." + } + }, + "type": "object", + "description": "The objective configuration for model monitoring, including the information needed to detect anomalies for one particular model." + }, + "CloudAiPlatformCommonCreatePipelineJobApiErrorDetail": { + "id": "CloudAiPlatformCommonCreatePipelineJobApiErrorDetail", + "type": "object", + "description": "Create API error message for Vertex Pipeline. Next Id: 3.", + "properties": { + "publicMessage": { + "description": "Public messages contains actionable items for the error cause.", + "type": "string" + }, + "errorCause": { + "description": "The error root cause returned by CreatePipelineJob API.", + "enum": [ + "ERROR_CAUSE_UNSPECIFIED", + "INVALID_PIPELINE_SPEC_FORMAT", + "INVALID_PIPELINE_SPEC", + "INVALID_DEPLOYMENT_CONFIG", + "INVALID_DEPLOYMENT_SPEC", + "INVALID_INSTANCE_SCHEMA", + "INVALID_CUSTOM_JOB", + "INVALID_CONTAINER_SPEC", + "INVALID_NOTIFICATION_EMAIL_SETUP", + "INVALID_SERVICE_ACCOUNT_SETUP", + "INVALID_KMS_SETUP", + "INVALID_NETWORK_SETUP", + "INVALID_PIPELINE_TASK_SPEC", + "INVALID_PIPELINE_TASK_ARTIFACT", + "INVALID_IMPORTER_SPEC", + "INVALID_RESOLVER_SPEC", + "INVALID_RUNTIME_PARAMETERS", + "CLOUD_API_NOT_ENABLED", + "INVALID_GCS_INPUT_URI", + "INVALID_GCS_OUTPUT_URI", + "INVALID_COMPONENT_SPEC", + "INVALID_DAG_OUTPUTS_SPEC", + "INVALID_DAG_SPEC", + "INSUFFICIENT_QUOTA", + "INTERNAL" + ], + "enumDescriptions": [ + "Should never be used.", + "IR Pipeline Spec can not been parsed to yaml or json format.", + "A pipeline spec is invalid.", + "A deployment config is invalid.", + "A deployment spec is invalid.", + "An instance schema is invalid.", + "A custom job is invalid.", + "A container spec is invalid.", + "Notification email setup is invalid.", + "Service account setup is invalid.", + "KMS setup is invalid.", + "Network setup is invalid.", + "Task spec is invalid.", + "Task artifact is invalid.", + "Importer spec is invalid.", + "Resolver spec is invalid.", + "Runtime Parameters are invalid.", + "Cloud API not enabled.", + "Invalid GCS input uri", + "Invalid GCS output uri", + "Component spec of pipeline is invalid.", + "DagOutputsSpec is invalid.", + "DagSpec is invalid.", + "Project does not have enough quota.", + "An internal error with unknown cause." + ], + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1SchemaTablesDatasetMetadataGcsSource": { + "id": "GoogleCloudAiplatformV1SchemaTablesDatasetMetadataGcsSource", + "properties": { + "uri": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Cloud Storage URI of one or more files. Only CSV files are supported. The first line of the CSV file is used as the header. If there are multiple files, the header is the first line of the lexicographically first file, the other files must either contain the exact same header or omit the header." + } + }, + "type": "object" + }, + "GoogleIamV1Policy": { + "description": "An Identity and Access Management (IAM) policy, which specifies access controls for Google Cloud resources. A `Policy` is a collection of `bindings`. A `binding` binds one or more `members`, or principals, to a single `role`. Principals can be user accounts, service accounts, Google groups, and domains (such as G Suite). A `role` is a named list of permissions; each `role` can be an IAM predefined role or a user-created custom role. For some types of Google Cloud resources, a `binding` can also specify a `condition`, which is a logical expression that allows access to a resource only if the expression evaluates to `true`. A condition can add constraints based on attributes of the request, the resource, or both. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies). **JSON example:** ``` { \"bindings\": [ { \"role\": \"roles/resourcemanager.organizationAdmin\", \"members\": [ \"user:mike@example.com\", \"group:admins@example.com\", \"domain:google.com\", \"serviceAccount:my-project-id@appspot.gserviceaccount.com\" ] }, { \"role\": \"roles/resourcemanager.organizationViewer\", \"members\": [ \"user:eve@example.com\" ], \"condition\": { \"title\": \"expirable access\", \"description\": \"Does not grant access after Sep 2020\", \"expression\": \"request.time \u003c timestamp('2020-10-01T00:00:00.000Z')\", } } ], \"etag\": \"BwWWja0YfJA=\", \"version\": 3 } ``` **YAML example:** ``` bindings: - members: - user:mike@example.com - group:admins@example.com - domain:google.com - serviceAccount:my-project-id@appspot.gserviceaccount.com role: roles/resourcemanager.organizationAdmin - members: - user:eve@example.com role: roles/resourcemanager.organizationViewer condition: title: expirable access description: Does not grant access after Sep 2020 expression: request.time \u003c timestamp('2020-10-01T00:00:00.000Z') etag: BwWWja0YfJA= version: 3 ``` For a description of IAM and its features, see the [IAM documentation](https://cloud.google.com/iam/docs/).", + "properties": { + "etag": { + "type": "string", + "description": "`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.", + "format": "byte" + }, + "bindings": { + "items": { + "$ref": "GoogleIamV1Binding" + }, + "type": "array", + "description": "Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`." + }, + "version": { + "description": "Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", + "type": "integer", + "format": "int32" + } + }, + "type": "object", + "id": "GoogleIamV1Policy" + }, + "GoogleCloudAiplatformV1ImportDataResponse": { + "id": "GoogleCloudAiplatformV1ImportDataResponse", + "type": "object", + "properties": {}, + "description": "Response message for DatasetService.ImportData." + }, + "GoogleCloudAiplatformV1DeployedIndex": { + "properties": { + "id": { + "type": "string", + "description": "Required. The user specified ID of the DeployedIndex. The ID can be up to 128 characters long and must start with a letter and only contain letters, numbers, and underscores. The ID must be unique within the project it is created in." + }, + "enableAccessLogging": { + "type": "boolean", + "description": "Optional. If true, private endpoint's access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each MatchRequest. Note that logs may incur a cost, especially if the deployed index receives a high queries per second rate (QPS). Estimate your costs before enabling this option." + }, + "automaticResources": { + "$ref": "GoogleCloudAiplatformV1AutomaticResources", + "description": "Optional. A description of resources that the DeployedIndex uses, which to large degree are decided by Vertex AI, and optionally allows only a modest additional configuration. If min_replica_count is not set, the default value is 2 (we don't provide SLA when min_replica_count=1). If max_replica_count is not set, the default value is min_replica_count. The max allowed replica count is 1000." + }, + "dedicatedResources": { + "description": "Optional. A description of resources that are dedicated to the DeployedIndex, and that need a higher degree of manual configuration. The field min_replica_count must be set to a value strictly greater than 0, or else validation will fail. We don't provide SLA when min_replica_count=1. If max_replica_count is not set, the default value is min_replica_count. The max allowed replica count is 1000. Available machine types for SMALL shard: e2-standard-2 and all machine types available for MEDIUM and LARGE shard. Available machine types for MEDIUM shard: e2-standard-16 and all machine types available for LARGE shard. Available machine types for LARGE shard: e2-highmem-16, n2d-standard-32. n1-standard-16 and n1-standard-32 are still available, but we recommend e2-standard-16 and e2-highmem-16 for cost efficiency.", + "$ref": "GoogleCloudAiplatformV1DedicatedResources" + }, + "index": { + "type": "string", + "description": "Required. The name of the Index this is the deployment of. We may refer to this Index as the DeployedIndex's \"original\" Index." + }, + "deploymentGroup": { + "description": "Optional. The deployment group can be no longer than 64 characters (eg: 'test', 'prod'). If not set, we will use the 'default' deployment group. Creating `deployment_groups` with `reserved_ip_ranges` is a recommended practice when the peered network has multiple peering ranges. This creates your deployments from predictable IP spaces for easier traffic administration. Also, one deployment_group (except 'default') can only be used with the same reserved_ip_ranges which means if the deployment_group has been used with reserved_ip_ranges: [a, b, c], using it with [a, b] or [d, e] is disallowed. Note: we only support up to 5 deployment groups(not including 'default').", + "type": "string" + }, + "createTime": { + "readOnly": true, + "description": "Output only. Timestamp when the DeployedIndex was created.", + "format": "google-datetime", + "type": "string" + }, + "deployedIndexAuthConfig": { + "$ref": "GoogleCloudAiplatformV1DeployedIndexAuthConfig", + "description": "Optional. If set, the authentication is enabled for the private endpoint." + }, + "displayName": { + "description": "The display name of the DeployedIndex. If not provided upon creation, the Index's display_name is used.", + "type": "string" + }, + "privateEndpoints": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1IndexPrivateEndpoints", + "description": "Output only. Provides paths for users to send requests directly to the deployed index services running on Cloud via private services access. This field is populated if network is configured." + }, + "reservedIpRanges": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Optional. A list of reserved ip ranges under the VPC network that can be used for this DeployedIndex. If set, we will deploy the index within the provided ip ranges. Otherwise, the index might be deployed to any ip ranges under the provided VPC network. The value should be the name of the address (https://cloud.google.com/compute/docs/reference/rest/v1/addresses) Example: ['vertex-ai-ip-range']. For more information about subnets and network IP ranges, please see https://cloud.google.com/vpc/docs/subnets#manually_created_subnet_ip_ranges." + }, + "indexSyncTime": { + "type": "string", + "description": "Output only. The DeployedIndex may depend on various data on its original Index. Additionally when certain changes to the original Index are being done (e.g. when what the Index contains is being changed) the DeployedIndex may be asynchronously updated in the background to reflect these changes. If this timestamp's value is at least the Index.update_time of the original Index, it means that this DeployedIndex and the original Index are in sync. If this timestamp is older, then to see which updates this DeployedIndex already contains (and which it does not), one must list the operations that are running on the original Index. Only the successfully completed Operations with update_time equal or before this sync time are contained in this DeployedIndex.", + "format": "google-datetime", + "readOnly": true + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1DeployedIndex", + "description": "A deployment of an Index. IndexEndpoints contain one or more DeployedIndexes." + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationAutoTransformation": { + "type": "object", + "description": "Training pipeline will infer the proper transformation based on the statistic of dataset.", + "properties": { + "columnName": { + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationAutoTransformation" + }, + "GoogleCloudAiplatformV1ListStudiesResponse": { + "id": "GoogleCloudAiplatformV1ListStudiesResponse", + "description": "Response message for VizierService.ListStudies.", + "type": "object", + "properties": { + "nextPageToken": { + "description": "Passes this token as the `page_token` field of the request for a subsequent call. If this field is omitted, there are no subsequent pages.", + "type": "string" + }, + "studies": { + "items": { + "$ref": "GoogleCloudAiplatformV1Study" + }, + "description": "The studies associated with the project.", + "type": "array" + } + } + }, + "CloudAiLargeModelsVisionRaiInfoDetectedLabels": { + "id": "CloudAiLargeModelsVisionRaiInfoDetectedLabels", + "description": "Filters returning list of deteceted labels, scores, and bounding boxes.", + "type": "object", + "properties": { + "raiCategory": { + "type": "string", + "description": "The RAI category for the deteceted labels." + }, + "entities": { + "items": { + "$ref": "CloudAiLargeModelsVisionRaiInfoDetectedLabelsEntity" + }, + "type": "array", + "description": "The list of detected entities for the rai signal." + } + } + }, + "GoogleCloudAiplatformV1PrivateServiceConnectConfig": { + "properties": { + "projectAllowlist": { + "description": "A list of Projects from which the forwarding rule will target the service attachment.", + "items": { + "type": "string" + }, + "type": "array" + }, + "enablePrivateServiceConnect": { + "type": "boolean", + "description": "Required. If true, expose the IndexEndpoint via private service connect." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1PrivateServiceConnectConfig", + "description": "Represents configuration for private service connect." + }, + "GoogleCloudAiplatformV1SchemaPredictPredictionVideoClassificationPredictionResult": { + "properties": { + "timeSegmentEnd": { + "type": "string", + "format": "google-duration", + "description": "The end, exclusive, of the video's time segment in which the AnnotationSpec has been identified. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end. Note that for 'segment-classification' prediction type, this equals the original 'timeSegmentEnd' from the input instance, for other types it is the end of a shot or a 1 second interval respectively." + }, + "timeSegmentStart": { + "type": "string", + "description": "The beginning, inclusive, of the video's time segment in which the AnnotationSpec has been identified. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end. Note that for 'segment-classification' prediction type, this equals the original 'timeSegmentStart' from the input instance, for other types it is the start of a shot or a 1 second interval respectively.", + "format": "google-duration" + }, + "id": { + "type": "string", + "description": "The resource ID of the AnnotationSpec that had been identified." + }, + "confidence": { + "format": "float", + "type": "number", + "description": "The Model's confidence in correction of this prediction, higher value means higher confidence." + }, + "type": { + "description": "The type of the prediction. The requested types can be configured via parameters. This will be one of - segment-classification - shot-classification - one-sec-interval-classification", + "type": "string" + }, + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that had been identified." + } + }, + "type": "object", + "description": "Prediction output format for Video Classification.", + "id": "GoogleCloudAiplatformV1SchemaPredictPredictionVideoClassificationPredictionResult" + }, + "GoogleCloudLocationLocation": { + "id": "GoogleCloudLocationLocation", + "description": "A resource that represents a Google Cloud location.", + "type": "object", + "properties": { + "labels": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "Cross-service attributes for the location. For example {\"cloud.googleapis.com/region\": \"us-east1\"}" + }, + "metadata": { + "type": "object", + "description": "Service-specific metadata. For example the available capacity at the given location.", + "additionalProperties": { + "description": "Properties of the object. Contains field @type with type URL.", + "type": "any" + } + }, + "displayName": { + "description": "The friendly name for this location, typically a nearby city name. For example, \"Tokyo\".", + "type": "string" + }, + "locationId": { + "description": "The canonical id for this location. For example: `\"us-east1\"`.", + "type": "string" + }, + "name": { + "description": "Resource name for the location, which may vary between implementations. For example: `\"projects/example-project/locations/us-east1\"`", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1ManualBatchTuningParameters": { + "description": "Manual batch tuning parameters.", + "type": "object", + "id": "GoogleCloudAiplatformV1ManualBatchTuningParameters", + "properties": { + "batchSize": { + "format": "int32", + "type": "integer", + "description": "Immutable. The number of the records (e.g. instances) of the operation given in each batch to a machine replica. Machine type, and size of a single record should be considered when setting this parameter, higher value speeds up the batch operation's execution, but too high value will result in a whole batch not fitting in a machine's memory, and the whole operation will fail. The default value is 64." + } + } + }, + "GoogleCloudAiplatformV1UserActionReference": { + "type": "object", + "id": "GoogleCloudAiplatformV1UserActionReference", + "properties": { + "operation": { + "description": "For API calls that return a long running operation. Resource name of the long running operation. Format: `projects/{project}/locations/{location}/operations/{operation}`", + "type": "string" + }, + "method": { + "type": "string", + "description": "The method name of the API RPC call. For example, \"/google.cloud.aiplatform.{apiVersion}.DatasetService.CreateDataset\"" + }, + "dataLabelingJob": { + "description": "For API calls that start a LabelingJob. Resource name of the LabelingJob. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}`", + "type": "string" + } + }, + "description": "References an API call. It contains more information about long running operation and Jobs that are triggered by the API call." + }, + "GoogleCloudAiplatformV1MigratableResourceDataLabelingDataset": { + "properties": { + "datasetDisplayName": { + "type": "string", + "description": "The Dataset's display name in datalabeling.googleapis.com." + }, + "dataset": { + "type": "string", + "description": "Full resource name of data labeling Dataset. Format: `projects/{project}/datasets/{dataset}`." + }, + "dataLabelingAnnotatedDatasets": { + "type": "array", + "description": "The migratable AnnotatedDataset in datalabeling.googleapis.com belongs to the data labeling Dataset.", + "items": { + "$ref": "GoogleCloudAiplatformV1MigratableResourceDataLabelingDatasetDataLabelingAnnotatedDataset" + } + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1MigratableResourceDataLabelingDataset", + "description": "Represents one Dataset in datalabeling.googleapis.com." + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig": { + "description": "Configuration for exporting test set predictions to a BigQuery table.", + "type": "object", + "properties": { + "overrideExistingTable": { + "type": "boolean", + "description": "If true and an export destination is specified, then the contents of the destination are overwritten. Otherwise, if the export destination already exists, then the export operation fails." + }, + "destinationBigqueryUri": { + "type": "string", + "description": "URI of desired destination BigQuery table. Expected format: `bq://{project_id}:{dataset_id}:{table}` If not specified, then results are exported to the following auto-created BigQuery table: `{project_id}:export_evaluated_examples_{model_name}_{yyyy_MM_dd'T'HH_mm_ss_SSS'Z'}.evaluated_examples`" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig" + }, + "GoogleCloudAiplatformV1Citation": { + "description": "Source attributions for content.", + "properties": { + "endIndex": { + "description": "Output only. End index into the content.", + "format": "int32", + "readOnly": true, + "type": "integer" + }, + "uri": { + "type": "string", + "description": "Output only. Url reference of the attribution.", + "readOnly": true + }, + "title": { + "type": "string", + "readOnly": true, + "description": "Output only. Title of the attribution." + }, + "license": { + "description": "Output only. License of the attribution.", + "type": "string", + "readOnly": true + }, + "startIndex": { + "description": "Output only. Start index into the content.", + "format": "int32", + "type": "integer", + "readOnly": true + }, + "publicationDate": { + "description": "Output only. Publication date of the attribution.", + "readOnly": true, + "$ref": "GoogleTypeDate" + } + }, + "id": "GoogleCloudAiplatformV1Citation", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetrics": { + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetrics", + "properties": { + "confusionMatrix": { + "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix", + "description": "Confusion matrix of the evaluation." + }, + "logLoss": { + "type": "number", + "description": "The Log Loss metric.", + "format": "float" + }, + "auPrc": { + "format": "float", + "description": "The Area Under Precision-Recall Curve metric. Micro-averaged for the overall evaluation.", + "type": "number" + }, + "confidenceMetrics": { + "type": "array", + "description": "Metrics for each `confidenceThreshold` in 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and `positionThreshold` = INT32_MAX_VALUE. ROC and precision-recall curves, and other aggregated metrics are derived from them. The confidence metrics entries may also be supplied for additional values of `positionThreshold`, but from these no aggregated metrics are computed.", + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics" + } + }, + "auRoc": { + "format": "float", + "type": "number", + "description": "The Area Under Receiver Operating Characteristic curve metric. Micro-averaged for the overall evaluation." + } + }, + "description": "Metrics for classification evaluation results.", + "type": "object" + }, + "GoogleCloudAiplatformV1DiskSpec": { + "properties": { + "bootDiskSizeGb": { + "type": "integer", + "description": "Size in GB of the boot disk (default is 100GB).", + "format": "int32" + }, + "bootDiskType": { + "description": "Type of the boot disk (default is \"pd-ssd\"). Valid values: \"pd-ssd\" (Persistent Disk Solid State Drive) or \"pd-standard\" (Persistent Disk Hard Disk Drive).", + "type": "string" + } + }, + "type": "object", + "description": "Represents the spec of disk options.", + "id": "GoogleCloudAiplatformV1DiskSpec" + }, + "GoogleCloudAiplatformV1SchemaVisualInspectionClassificationLabelSavedQueryMetadata": { + "id": "GoogleCloudAiplatformV1SchemaVisualInspectionClassificationLabelSavedQueryMetadata", + "properties": { + "multiLabel": { + "description": "Whether or not the classification label is multi_label.", + "type": "boolean" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1Neighbor": { + "properties": { + "neighborDistance": { + "type": "number", + "readOnly": true, + "format": "double", + "description": "Output only. The neighbor distance." + }, + "neighborId": { + "type": "string", + "readOnly": true, + "description": "Output only. The neighbor id." + } + }, + "id": "GoogleCloudAiplatformV1Neighbor", + "description": "Neighbors for example-based explanations.", + "type": "object" + }, + "GoogleCloudAiplatformV1ToolParameterKVMatchResults": { + "type": "object", + "description": "Results for tool parameter key value match metric.", + "id": "GoogleCloudAiplatformV1ToolParameterKVMatchResults", + "properties": { + "toolParameterKvMatchMetricValues": { + "type": "array", + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1ToolParameterKVMatchMetricValue" + }, + "description": "Output only. Tool parameter key value match metric values." + } + } + }, + "GoogleCloudAiplatformV1ListPipelineJobsResponse": { + "properties": { + "pipelineJobs": { + "items": { + "$ref": "GoogleCloudAiplatformV1PipelineJob" + }, + "description": "List of PipelineJobs in the requested page.", + "type": "array" + }, + "nextPageToken": { + "description": "A token to retrieve the next page of results. Pass to ListPipelineJobsRequest.page_token to obtain that page.", + "type": "string" + } + }, + "type": "object", + "description": "Response message for PipelineService.ListPipelineJobs", + "id": "GoogleCloudAiplatformV1ListPipelineJobsResponse" + }, + "GoogleCloudAiplatformV1MigrateResourceResponse": { + "type": "object", + "properties": { + "dataset": { + "description": "Migrated Dataset's resource name.", + "type": "string" + }, + "model": { + "type": "string", + "description": "Migrated Model's resource name." + }, + "migratableResource": { + "description": "Before migration, the identifier in ml.googleapis.com, automl.googleapis.com or datalabeling.googleapis.com.", + "$ref": "GoogleCloudAiplatformV1MigratableResource" + } + }, + "id": "GoogleCloudAiplatformV1MigrateResourceResponse", + "description": "Describes a successfully migrated resource." + }, + "GoogleCloudAiplatformV1CancelDataLabelingJobRequest": { + "description": "Request message for JobService.CancelDataLabelingJob.", + "type": "object", + "id": "GoogleCloudAiplatformV1CancelDataLabelingJobRequest", + "properties": {} + }, + "GoogleCloudAiplatformV1VertexAISearch": { + "description": "Retrieve from Vertex AI Search datastore for grounding. See https://cloud.google.com/vertex-ai-search-and-conversation", + "type": "object", + "properties": { + "datastore": { + "type": "string", + "description": "Required. Fully-qualified Vertex AI Search's datastore resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`" + } + }, + "id": "GoogleCloudAiplatformV1VertexAISearch" + }, + "GoogleCloudAiplatformV1GcsSource": { + "id": "GoogleCloudAiplatformV1GcsSource", + "properties": { + "uris": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Required. Google Cloud Storage URI(-s) to the input file(s). May contain wildcards. For more information on wildcards, see https://cloud.google.com/storage/docs/gsutil/addlhelp/WildcardNames." + } + }, + "description": "The Google Cloud Storage location for the input content.", + "type": "object" + }, + "GoogleCloudAiplatformV1FindNeighborsRequestQueryRRF": { + "description": "Parameters for RRF algorithm that combines search results.", + "id": "GoogleCloudAiplatformV1FindNeighborsRequestQueryRRF", + "properties": { + "alpha": { + "type": "number", + "description": "Required. Users can provide an alpha value to give more weight to dense vs sparse results. For example, if the alpha is 0, we only return sparse and if the alpha is 1, we only return dense.", + "format": "float" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1ToolNameMatchSpec": { + "type": "object", + "properties": {}, + "id": "GoogleCloudAiplatformV1ToolNameMatchSpec", + "description": "Spec for tool name match metric." + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextExtractionEvaluationMetricsConfidenceMetrics": { + "type": "object", + "properties": { + "f1Score": { + "type": "number", + "description": "The harmonic mean of recall and precision.", + "format": "float" + }, + "recall": { + "description": "Recall (True Positive Rate) for the given confidence threshold.", + "format": "float", + "type": "number" + }, + "confidenceThreshold": { + "description": "Metrics are computed with an assumption that the Model never returns predictions with score lower than this value.", + "type": "number", + "format": "float" + }, + "precision": { + "format": "float", + "type": "number", + "description": "Precision for the given confidence threshold." + } + }, + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextExtractionEvaluationMetricsConfidenceMetrics" + }, + "GoogleCloudAiplatformV1MigratableResourceAutomlModel": { + "id": "GoogleCloudAiplatformV1MigratableResourceAutomlModel", + "description": "Represents one Model in automl.googleapis.com.", + "type": "object", + "properties": { + "modelDisplayName": { + "type": "string", + "description": "The Model's display name in automl.googleapis.com." + }, + "model": { + "type": "string", + "description": "Full resource name of automl Model. Format: `projects/{project}/locations/{location}/models/{model}`." + } + } + }, + "GoogleCloudAiplatformV1Attribution": { + "properties": { + "instanceOutputValue": { + "description": "Output only. Model predicted output on the corresponding explanation instance. The field name of the output is determined by the key in ExplanationMetadata.outputs. If the Model predicted output has multiple dimensions, this is the value in the output located by output_index.", + "format": "double", + "type": "number", + "readOnly": true + }, + "approximationError": { + "description": "Output only. Error of feature_attributions caused by approximation used in the explanation method. Lower value means more precise attributions. * For Sampled Shapley attribution, increasing path_count might reduce the error. * For Integrated Gradients attribution, increasing step_count might reduce the error. * For XRAI attribution, increasing step_count might reduce the error. See [this introduction](/vertex-ai/docs/explainable-ai/overview) for more information.", + "type": "number", + "format": "double", + "readOnly": true + }, + "outputIndex": { + "type": "array", + "description": "Output only. The index that locates the explained prediction output. If the prediction output is a scalar value, output_index is not populated. If the prediction output has multiple dimensions, the length of the output_index list is the same as the number of dimensions of the output. The i-th element in output_index is the element index of the i-th dimension of the output vector. Indices start from 0.", + "readOnly": true, + "items": { + "type": "integer", + "format": "int32" + } + }, + "baselineOutputValue": { + "format": "double", + "description": "Output only. Model predicted output if the input instance is constructed from the baselines of all the features defined in ExplanationMetadata.inputs. The field name of the output is determined by the key in ExplanationMetadata.outputs. If the Model's predicted output has multiple dimensions (rank \u003e 1), this is the value in the output located by output_index. If there are multiple baselines, their output values are averaged.", + "type": "number", + "readOnly": true + }, + "featureAttributions": { + "description": "Output only. Attributions of each explained feature. Features are extracted from the prediction instances according to explanation metadata for inputs. The value is a struct, whose keys are the name of the feature. The values are how much the feature in the instance contributed to the predicted result. The format of the value is determined by the feature's input format: * If the feature is a scalar value, the attribution value is a floating number. * If the feature is an array of scalar values, the attribution value is an array. * If the feature is a struct, the attribution value is a struct. The keys in the attribution value struct are the same as the keys in the feature struct. The formats of the values in the attribution struct are determined by the formats of the values in the feature struct. The ExplanationMetadata.feature_attributions_schema_uri field, pointed to by the ExplanationSpec field of the Endpoint.deployed_models object, points to the schema file that describes the features and their attribution values (if it is populated).", + "readOnly": true, + "type": "any" + }, + "outputName": { + "type": "string", + "readOnly": true, + "description": "Output only. Name of the explain output. Specified as the key in ExplanationMetadata.outputs." + }, + "outputDisplayName": { + "description": "Output only. The display name of the output identified by output_index. For example, the predicted class name by a multi-classification Model. This field is only populated iff the Model predicts display names as a separate field along with the explained output. The predicted display name must has the same shape of the explained output, and can be located using output_index.", + "type": "string", + "readOnly": true + } + }, + "type": "object", + "description": "Attribution that explains a particular prediction output.", + "id": "GoogleCloudAiplatformV1Attribution" + }, + "CloudAiLargeModelsVisionRaiInfoDetectedLabelsBoundingBox": { + "properties": { + "x2": { + "description": "The X coordinate of the bottom-right corner, in pixels.", + "type": "integer", + "format": "int32" + }, + "x1": { + "type": "integer", + "format": "int32", + "description": "The X coordinate of the top-left corner, in pixels." + }, + "y2": { + "type": "integer", + "description": "The Y coordinate of the bottom-right corner, in pixels.", + "format": "int32" + }, + "y1": { + "format": "int32", + "description": "The Y coordinate of the top-left corner, in pixels.", + "type": "integer" + } + }, + "id": "CloudAiLargeModelsVisionRaiInfoDetectedLabelsBoundingBox", + "description": "An integer bounding box of original pixels of the image for the detected labels.", + "type": "object" + }, + "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaseline": { + "type": "object", + "properties": { + "gcs": { + "$ref": "GoogleCloudAiplatformV1GcsDestination", + "description": "Cloud Storage location for BatchExplain output." + }, + "bigquery": { + "description": "BigQuery location for BatchExplain output.", + "$ref": "GoogleCloudAiplatformV1BigQueryDestination" + }, + "predictionFormat": { + "enumDescriptions": [ + "Should not be set.", + "Predictions are in JSONL files.", + "Predictions are in BigQuery." + ], + "type": "string", + "enum": [ + "PREDICTION_FORMAT_UNSPECIFIED", + "JSONL", + "BIGQUERY" + ], + "description": "The storage format of the predictions generated BatchPrediction job." + } + }, + "id": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaseline", + "description": "Output from BatchPredictionJob for Model Monitoring baseline dataset, which can be used to generate baseline attribution scores." + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionWindowConfig": { + "description": "Config that contains the strategy used to generate sliding windows in time series training. A window is a series of rows that comprise the context up to the time of prediction, and the horizon following. The corresponding row for each window marks the start of the forecast horizon. Each window is used as an input example for training/evaluation.", + "properties": { + "column": { + "type": "string", + "description": "Name of the column that should be used to generate sliding windows. The column should contain either booleans or string booleans; if the value of the row is True, generate a sliding window with the horizon starting at that row. The column will not be used as a feature in training." + }, + "strideLength": { + "description": "Stride length used to generate input examples. Within one time series, every {$STRIDE_LENGTH} rows will be used to generate a sliding window.", + "format": "int64", + "type": "string" + }, + "maxCount": { + "format": "int64", + "description": "Maximum number of windows that should be generated across all time series.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionWindowConfig" + }, + "GoogleCloudAiplatformV1SearchModelDeploymentMonitoringStatsAnomaliesResponse": { + "id": "GoogleCloudAiplatformV1SearchModelDeploymentMonitoringStatsAnomaliesResponse", + "properties": { + "monitoringStats": { + "items": { + "$ref": "GoogleCloudAiplatformV1ModelMonitoringStatsAnomalies" + }, + "type": "array", + "description": "Stats retrieved for requested objectives. There are at most 1000 ModelMonitoringStatsAnomalies.FeatureHistoricStatsAnomalies.prediction_stats in the response." + }, + "nextPageToken": { + "type": "string", + "description": "The page token that can be used by the next JobService.SearchModelDeploymentMonitoringStatsAnomalies call." + } + }, + "description": "Response message for JobService.SearchModelDeploymentMonitoringStatsAnomalies.", + "type": "object" + }, + "GoogleCloudAiplatformV1GcsDestination": { + "properties": { + "outputUriPrefix": { + "type": "string", + "description": "Required. Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1GcsDestination", + "description": "The Google Cloud Storage location where the output is to be written to." + }, + "GoogleCloudAiplatformV1BatchReadTensorboardTimeSeriesDataResponse": { + "description": "Response message for TensorboardService.BatchReadTensorboardTimeSeriesData.", + "type": "object", + "id": "GoogleCloudAiplatformV1BatchReadTensorboardTimeSeriesDataResponse", + "properties": { + "timeSeriesData": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1TimeSeriesData" + }, + "description": "The returned time series data." + } + } + }, + "GoogleCloudAiplatformV1SummarizationQualityResult": { + "type": "object", + "id": "GoogleCloudAiplatformV1SummarizationQualityResult", + "properties": { + "score": { + "readOnly": true, + "type": "number", + "format": "float", + "description": "Output only. Summarization Quality score." + }, + "explanation": { + "type": "string", + "readOnly": true, + "description": "Output only. Explanation for summarization quality score." + }, + "confidence": { + "description": "Output only. Confidence for summarization quality score.", + "format": "float", + "type": "number", + "readOnly": true + } + }, + "description": "Spec for summarization quality result." + }, + "GoogleCloudAiplatformV1CoherenceResult": { + "description": "Spec for coherence result.", + "type": "object", + "id": "GoogleCloudAiplatformV1CoherenceResult", + "properties": { + "explanation": { + "type": "string", + "readOnly": true, + "description": "Output only. Explanation for coherence score." + }, + "confidence": { + "readOnly": true, + "type": "number", + "format": "float", + "description": "Output only. Confidence for coherence score." + }, + "score": { + "readOnly": true, + "format": "float", + "description": "Output only. Coherence score.", + "type": "number" + } + } + }, + "GoogleCloudAiplatformV1QuestionAnsweringQualitySpec": { + "description": "Spec for question answering quality score metric.", + "id": "GoogleCloudAiplatformV1QuestionAnsweringQualitySpec", + "properties": { + "version": { + "type": "integer", + "format": "int32", + "description": "Optional. Which version to use for evaluation." + }, + "useReference": { + "type": "boolean", + "description": "Optional. Whether to use instance.reference to compute question answering quality." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputs": { + "properties": { + "timeColumn": { + "description": "The name of the column that identifies time order in the time series. This column must be available at forecast.", + "type": "string" + }, + "unavailableAtForecastColumns": { + "items": { + "type": "string" + }, + "description": "Names of columns that are unavailable when a forecast is requested. This column contains information for the given entity (identified by the time_series_identifier_column) that is unknown before the forecast For example, actual weather on a given day.", + "type": "array" + }, + "hierarchyConfig": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHierarchyConfig", + "description": "Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies." + }, + "targetColumn": { + "type": "string", + "description": "The name of the column that the Model is to predict values for. This column must be unavailable at forecast." + }, + "optimizationObjective": { + "description": "Objective function the model is optimizing towards. The training process creates a model that optimizes the value of the objective function over the validation set. The supported optimization objectives: * \"minimize-rmse\" (default) - Minimize root-mean-squared error (RMSE). * \"minimize-mae\" - Minimize mean-absolute error (MAE). * \"minimize-rmsle\" - Minimize root-mean-squared log error (RMSLE). * \"minimize-rmspe\" - Minimize root-mean-squared percentage error (RMSPE). * \"minimize-wape-mae\" - Minimize the combination of weighted absolute percentage error (WAPE) and mean-absolute-error (MAE). * \"minimize-quantile-loss\" - Minimize the quantile loss at the quantiles defined in `quantiles`. * \"minimize-mape\" - Minimize the mean absolute percentage error.", + "type": "string" + }, + "timeSeriesIdentifierColumn": { + "type": "string", + "description": "The name of the column that identifies the time series." + }, + "quantiles": { + "items": { + "format": "double", + "type": "number" + }, + "description": "Quantiles to use for minimize-quantile-loss `optimization_objective`, or for probabilistic inference. Up to 5 quantiles are allowed of values between 0 and 1, exclusive. Required if the value of optimization_objective is minimize-quantile-loss. Represents the percent quantiles to use for that objective. Quantiles must be unique.", + "type": "array" + }, + "enableProbabilisticInference": { + "type": "boolean", + "description": "If probabilistic inference is enabled, the model will fit a distribution that captures the uncertainty of a prediction. At inference time, the predictive distribution is used to make a point prediction that minimizes the optimization objective. For example, the mean of a predictive distribution is the point prediction that minimizes RMSE loss. If quantiles are specified, then the quantiles of the distribution are also returned. The optimization objective cannot be minimize-quantile-loss." + }, + "availableAtForecastColumns": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Names of columns that are available and provided when a forecast is requested. These columns contain information for the given entity (identified by the time_series_identifier_column column) that is known at forecast. For example, predicted weather for a specific day." + }, + "exportEvaluatedDataItemsConfig": { + "description": "Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed.", + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig" + }, + "timeSeriesAttributeColumns": { + "description": "Column names that should be used as attribute columns. The value of these columns does not vary as a function of time. For example, store ID or item color.", + "items": { + "type": "string" + }, + "type": "array" + }, + "dataGranularity": { + "description": "Expected difference in time granularity between rows in the data.", + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsGranularity" + }, + "contextWindow": { + "type": "string", + "format": "int64", + "description": "The amount of time into the past training and prediction data is used for model training and prediction respectively. Expressed in number of units defined by the `data_granularity` field." + }, + "weightColumn": { + "description": "Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1.", + "type": "string" + }, + "validationOptions": { + "description": "Validation options for the data validation component. The available options are: * \"fail-pipeline\" - default, will validate against the validation and fail the pipeline if it fails. * \"ignore-validation\" - ignore the results of the validation and continue", + "type": "string" + }, + "holidayRegions": { + "items": { + "type": "string" + }, + "type": "array", + "description": "The geographical region based on which the holiday effect is applied in modeling by adding holiday categorical array feature that include all holidays matching the date. This option only allowed when data_granularity is day. By default, holiday effect modeling is disabled. To turn it on, specify the holiday region using this option." + }, + "windowConfig": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionWindowConfig", + "description": "Config containing strategy for generating sliding windows." + }, + "additionalExperiments": { + "items": { + "type": "string" + }, + "description": "Additional experiment flags for the time series forcasting training.", + "type": "array" + }, + "trainBudgetMilliNodeHours": { + "format": "int64", + "type": "string", + "description": "Required. The train budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The training cost of the model will not exceed this budget. The final cost will be attempted to be close to the budget, though may end up being (even) noticeably smaller - at the backend's discretion. This especially may happen when further model training ceases to provide any improvements. If the budget is set to a value known to be insufficient to train a model for the given dataset, the training won't be attempted and will error. The train budget must be between 1,000 and 72,000 milli node hours, inclusive." + }, + "transformations": { + "description": "Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using \".\" as the delimiter.", + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation" + }, + "type": "array" + }, + "forecastHorizon": { + "description": "The amount of time into the future for which forecasted values for the target are returned. Expressed in number of units defined by the `data_granularity` field.", + "type": "string", + "format": "int64" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputs", + "type": "object" + }, + "GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpec": { + "description": "Value specification for a parameter in `INTEGER` type.", + "id": "GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpec", + "type": "object", + "properties": { + "defaultValue": { + "type": "string", + "format": "int64", + "description": "A default value for an `INTEGER` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline." + }, + "minValue": { + "format": "int64", + "description": "Required. Inclusive minimum value of the parameter.", + "type": "string" + }, + "maxValue": { + "type": "string", + "format": "int64", + "description": "Required. Inclusive maximum value of the parameter." + } + } + }, + "GoogleCloudAiplatformV1NearestNeighborQueryStringFilter": { + "properties": { + "denyTokens": { + "description": "Optional. The denied tokens.", + "items": { + "type": "string" + }, + "type": "array" + }, + "name": { + "description": "Required. Column names in BigQuery that used as filters.", + "type": "string" + }, + "allowTokens": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Optional. The allowed tokens." + } + }, + "id": "GoogleCloudAiplatformV1NearestNeighborQueryStringFilter", + "description": "String filter is used to search a subset of the entities by using boolean rules on string columns. For example: if a query specifies string filter with 'name = color, allow_tokens = {red, blue}, deny_tokens = {purple}',' then that query will match entities that are red or blue, but if those points are also purple, then they will be excluded even if they are red/blue. Only string filter is supported for now, numeric filter will be supported in the near future.", + "type": "object" + }, + "GoogleCloudAiplatformV1AddContextArtifactsAndExecutionsRequest": { + "id": "GoogleCloudAiplatformV1AddContextArtifactsAndExecutionsRequest", + "type": "object", + "description": "Request message for MetadataService.AddContextArtifactsAndExecutions.", + "properties": { + "executions": { + "type": "array", + "items": { + "type": "string" + }, + "description": "The resource names of the Executions to associate with the Context. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`" + }, + "artifacts": { + "items": { + "type": "string" + }, + "description": "The resource names of the Artifacts to attribute to the Context. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`", + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1ExportDataResponse": { + "id": "GoogleCloudAiplatformV1ExportDataResponse", + "description": "Response message for DatasetService.ExportData.", + "properties": { + "exportedFiles": { + "description": "All of the files that are exported in this export operation. For custom code training export, only three (training, validation and test) Cloud Storage paths in wildcard format are populated (for example, gs://.../training-*).", + "type": "array", + "items": { + "type": "string" + } + }, + "dataStats": { + "$ref": "GoogleCloudAiplatformV1ModelDataStats", + "description": "Only present for custom code training export use case. Records data stats, i.e., train/validation/test item/annotation counts calculated during the export operation." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1BatchCreateTensorboardRunsResponse": { + "description": "Response message for TensorboardService.BatchCreateTensorboardRuns.", + "properties": { + "tensorboardRuns": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1TensorboardRun" + }, + "description": "The created TensorboardRuns." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1BatchCreateTensorboardRunsResponse" + }, + "GoogleCloudAiplatformV1SamplingStrategy": { + "type": "object", + "description": "Sampling Strategy for logging, can be for both training and prediction dataset.", + "properties": { + "randomSampleConfig": { + "description": "Random sample config. Will support more sampling strategies later.", + "$ref": "GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfig" + } + }, + "id": "GoogleCloudAiplatformV1SamplingStrategy" + }, + "GoogleCloudAiplatformV1StudySpecParameterSpec": { + "properties": { + "parameterId": { + "type": "string", + "description": "Required. The ID of the parameter. Must not contain whitespaces and must be unique amongst all ParameterSpecs." + }, + "categoricalValueSpec": { + "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpec", + "description": "The value spec for a 'CATEGORICAL' parameter." + }, + "discreteValueSpec": { + "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpec", + "description": "The value spec for a 'DISCRETE' parameter." + }, + "scaleType": { + "enum": [ + "SCALE_TYPE_UNSPECIFIED", + "UNIT_LINEAR_SCALE", + "UNIT_LOG_SCALE", + "UNIT_REVERSE_LOG_SCALE" + ], + "type": "string", + "description": "How the parameter should be scaled. Leave unset for `CATEGORICAL` parameters.", + "enumDescriptions": [ + "By default, no scaling is applied.", + "Scales the feasible space to (0, 1) linearly.", + "Scales the feasible space logarithmically to (0, 1). The entire feasible space must be strictly positive.", + "Scales the feasible space \"reverse\" logarithmically to (0, 1). The result is that values close to the top of the feasible space are spread out more than points near the bottom. The entire feasible space must be strictly positive." + ] + }, + "integerValueSpec": { + "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpec", + "description": "The value spec for an 'INTEGER' parameter." + }, + "conditionalParameterSpecs": { + "description": "A conditional parameter node is active if the parameter's value matches the conditional node's parent_value_condition. If two items in conditional_parameter_specs have the same name, they must have disjoint parent_value_condition.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpec" + } + }, + "doubleValueSpec": { + "description": "The value spec for a 'DOUBLE' parameter.", + "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpec" + } + }, + "id": "GoogleCloudAiplatformV1StudySpecParameterSpec", + "description": "Represents a single parameter to optimize.", + "type": "object" + }, + "GoogleCloudAiplatformV1FeatureGroup": { + "description": "Vertex AI Feature Group.", + "id": "GoogleCloudAiplatformV1FeatureGroup", + "type": "object", + "properties": { + "description": { + "type": "string", + "description": "Optional. Description of the FeatureGroup." + }, + "createTime": { + "type": "string", + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Timestamp when this FeatureGroup was created." + }, + "updateTime": { + "format": "google-datetime", + "type": "string", + "description": "Output only. Timestamp when this FeatureGroup was last updated.", + "readOnly": true + }, + "bigQuery": { + "$ref": "GoogleCloudAiplatformV1FeatureGroupBigQuery", + "description": "Indicates that features for this group come from BigQuery Table/View. By default treats the source as a sparse time series source. The BigQuery source table or view must have at least one entity ID column and a column named `feature_timestamp`." + }, + "etag": { + "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "Optional. The labels with user-defined metadata to organize your FeatureGroup. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureGroup(System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." + }, + "name": { + "description": "Identifier. Name of the FeatureGroup. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}`", + "type": "string" + } + } + }, + "CloudAiLargeModelsVisionNamedBoundingBox": { + "id": "CloudAiLargeModelsVisionNamedBoundingBox", + "type": "object", + "properties": { + "entities": { + "items": { + "type": "string" + }, + "type": "array" + }, + "x1": { + "format": "float", + "type": "number" + }, + "scores": { + "type": "array", + "items": { + "format": "float", + "type": "number" + } + }, + "y2": { + "format": "float", + "type": "number" + }, + "y1": { + "type": "number", + "format": "float" + }, + "x2": { + "format": "float", + "type": "number" + }, + "classes": { + "items": { + "type": "string" + }, + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1NetworkSpec": { + "type": "object", + "properties": { + "subnetwork": { + "type": "string", + "description": "The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`" + }, + "network": { + "type": "string", + "description": "The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)" + }, + "enableInternetAccess": { + "type": "boolean", + "description": "Whether to enable public internet access. Default false." + } + }, + "id": "GoogleCloudAiplatformV1NetworkSpec", + "description": "Network spec." + }, + "GoogleCloudAiplatformV1MetadataStoreDataplexConfig": { + "description": "Represents Dataplex integration settings.", + "id": "GoogleCloudAiplatformV1MetadataStoreDataplexConfig", + "properties": { + "enabledPipelinesLineage": { + "description": "Optional. Whether or not Data Lineage synchronization is enabled for Vertex Pipelines.", + "type": "boolean" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1DeleteFeatureValuesResponseSelectTimeRangeAndFeature": { + "properties": { + "onlineStorageModifiedEntityCount": { + "description": "The count of modified entities in the online storage. Each entity ID corresponds to one entity. Within each entity, only the features specified in the request are deleted.", + "type": "string", + "format": "int64" + }, + "offlineStorageModifiedEntityRowCount": { + "type": "string", + "format": "int64", + "description": "The count of modified entity rows in the offline storage. Each row corresponds to the combination of an entity ID and a timestamp. One entity ID can have multiple rows in the offline storage. Within each row, only the features specified in the request are deleted." + }, + "impactedFeatureCount": { + "description": "The count of the features or columns impacted. This is the same as the feature count in the request.", + "format": "int64", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1DeleteFeatureValuesResponseSelectTimeRangeAndFeature", + "description": "Response message if the request uses the SelectTimeRangeAndFeature option.", + "type": "object" + }, + "GoogleCloudAiplatformV1UploadModelResponse": { + "id": "GoogleCloudAiplatformV1UploadModelResponse", + "properties": { + "model": { + "type": "string", + "description": "The name of the uploaded Model resource. Format: `projects/{project}/locations/{location}/models/{model}`" + }, + "modelVersionId": { + "readOnly": true, + "description": "Output only. The version ID of the model that is uploaded.", + "type": "string" + } + }, + "description": "Response message of ModelService.UploadModel operation.", + "type": "object" + }, + "GoogleCloudAiplatformV1SupervisedTuningDatasetDistributionDatasetBucket": { + "id": "GoogleCloudAiplatformV1SupervisedTuningDatasetDistributionDatasetBucket", + "description": "Dataset bucket used to create a histogram for the distribution given a population of values.", + "properties": { + "count": { + "description": "Output only. Number of values in the bucket.", + "type": "number", + "readOnly": true, + "format": "double" + }, + "right": { + "format": "double", + "readOnly": true, + "type": "number", + "description": "Output only. Right bound of the bucket." + }, + "left": { + "format": "double", + "type": "number", + "readOnly": true, + "description": "Output only. Left bound of the bucket." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1FeatureViewIndexConfig": { + "type": "object", + "properties": { + "embeddingColumn": { + "type": "string", + "description": "Optional. Column of embedding. This column contains the source data to create index for vector search. embedding_column must be set when using vector search." + }, + "crowdingColumn": { + "type": "string", + "description": "Optional. Column of crowding. This column contains crowding attribute which is a constraint on a neighbor list produced by FeatureOnlineStoreService.SearchNearestEntities to diversify search results. If NearestNeighborQuery.per_crowding_attribute_neighbor_count is set to K in SearchNearestEntitiesRequest, it's guaranteed that no more than K entities of the same crowding attribute are returned in the response." + }, + "distanceMeasureType": { + "type": "string", + "enum": [ + "DISTANCE_MEASURE_TYPE_UNSPECIFIED", + "SQUARED_L2_DISTANCE", + "COSINE_DISTANCE", + "DOT_PRODUCT_DISTANCE" + ], + "description": "Optional. The distance measure used in nearest neighbor search.", + "enumDescriptions": [ + "Should not be set.", + "Euclidean (L_2) Distance.", + "Cosine Distance. Defined as 1 - cosine similarity. We strongly suggest using DOT_PRODUCT_DISTANCE + UNIT_L2_NORM instead of COSINE distance. Our algorithms have been more optimized for DOT_PRODUCT distance which, when combined with UNIT_L2_NORM, is mathematically equivalent to COSINE distance and results in the same ranking.", + "Dot Product Distance. Defined as a negative of the dot product." + ] + }, + "treeAhConfig": { + "description": "Optional. Configuration options for the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396", + "$ref": "GoogleCloudAiplatformV1FeatureViewIndexConfigTreeAHConfig" + }, + "embeddingDimension": { + "format": "int32", + "type": "integer", + "description": "Optional. The number of dimensions of the input embedding." + }, + "filterColumns": { + "description": "Optional. Columns of features that're used to filter vector search results.", + "items": { + "type": "string" + }, + "type": "array" + }, + "bruteForceConfig": { + "description": "Optional. Configuration options for using brute force search, which simply implements the standard linear search in the database for each query. It is primarily meant for benchmarking and to generate the ground truth for approximate search.", + "$ref": "GoogleCloudAiplatformV1FeatureViewIndexConfigBruteForceConfig" + } + }, + "description": "Configuration for vector indexing.", + "id": "GoogleCloudAiplatformV1FeatureViewIndexConfig" + }, + "GoogleCloudAiplatformV1GroundednessResult": { + "description": "Spec for groundedness result.", + "properties": { + "explanation": { + "description": "Output only. Explanation for groundedness score.", + "readOnly": true, + "type": "string" + }, + "score": { + "type": "number", + "description": "Output only. Groundedness score.", + "readOnly": true, + "format": "float" + }, + "confidence": { + "description": "Output only. Confidence for groundedness score.", + "type": "number", + "format": "float", + "readOnly": true + } + }, + "id": "GoogleCloudAiplatformV1GroundednessResult", + "type": "object" + }, + "GoogleCloudAiplatformV1IndexDatapointCrowdingTag": { + "properties": { + "crowdingAttribute": { + "description": "The attribute value used for crowding. The maximum number of neighbors to return per crowding attribute value (per_crowding_attribute_num_neighbors) is configured per-query. This field is ignored if per_crowding_attribute_num_neighbors is larger than the total number of neighbors to return for a given query.", + "type": "string" + } + }, + "type": "object", + "description": "Crowding tag is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than some value k' of the k neighbors returned have the same value of crowding_attribute.", + "id": "GoogleCloudAiplatformV1IndexDatapointCrowdingTag" + }, + "GoogleCloudAiplatformV1ListModelEvaluationsResponse": { + "type": "object", + "properties": { + "modelEvaluations": { + "items": { + "$ref": "GoogleCloudAiplatformV1ModelEvaluation" + }, + "type": "array", + "description": "List of ModelEvaluations in the requested page." + }, + "nextPageToken": { + "type": "string", + "description": "A token to retrieve next page of results. Pass to ListModelEvaluationsRequest.page_token to obtain that page." + } + }, + "description": "Response message for ModelService.ListModelEvaluations.", + "id": "GoogleCloudAiplatformV1ListModelEvaluationsResponse" + }, + "GoogleCloudAiplatformV1CreateFeatureViewOperationMetadata": { + "type": "object", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "Operation metadata for FeatureView Create." + } + }, + "id": "GoogleCloudAiplatformV1CreateFeatureViewOperationMetadata", + "description": "Details of operations that perform create FeatureView." + }, + "GoogleCloudAiplatformV1ExportFeatureValuesRequest": { + "properties": { + "settings": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1DestinationFeatureSetting" + }, + "description": "Per-Feature export settings." + }, + "featureSelector": { + "$ref": "GoogleCloudAiplatformV1FeatureSelector", + "description": "Required. Selects Features to export values of." + }, + "snapshotExport": { + "description": "Exports the latest Feature values of all entities of the EntityType within a time range.", + "$ref": "GoogleCloudAiplatformV1ExportFeatureValuesRequestSnapshotExport" + }, + "destination": { + "$ref": "GoogleCloudAiplatformV1FeatureValueDestination", + "description": "Required. Specifies destination location and format." + }, + "fullExport": { + "$ref": "GoogleCloudAiplatformV1ExportFeatureValuesRequestFullExport", + "description": "Exports all historical values of all entities of the EntityType within a time range" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1ExportFeatureValuesRequest", + "description": "Request message for FeaturestoreService.ExportFeatureValues." + }, + "GoogleCloudAiplatformV1SupervisedTuningDatasetDistribution": { + "id": "GoogleCloudAiplatformV1SupervisedTuningDatasetDistribution", + "type": "object", + "description": "Dataset distribution for Supervised Tuning.", + "properties": { + "min": { + "description": "Output only. The minimum of the population values.", + "format": "double", + "type": "number", + "readOnly": true + }, + "max": { + "type": "number", + "readOnly": true, + "format": "double", + "description": "Output only. The maximum of the population values." + }, + "billableSum": { + "description": "Output only. Sum of a given population of values that are billable.", + "format": "int64", + "type": "string", + "readOnly": true + }, + "p5": { + "readOnly": true, + "type": "number", + "format": "double", + "description": "Output only. The 5th percentile of the values in the population." + }, + "sum": { + "type": "string", + "description": "Output only. Sum of a given population of values.", + "format": "int64", + "readOnly": true + }, + "mean": { + "readOnly": true, + "type": "number", + "description": "Output only. The arithmetic mean of the values in the population.", + "format": "double" + }, + "buckets": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1SupervisedTuningDatasetDistributionDatasetBucket" + }, + "readOnly": true, + "description": "Output only. Defines the histogram bucket." + }, + "p95": { + "format": "double", + "type": "number", + "description": "Output only. The 95th percentile of the values in the population.", + "readOnly": true + }, + "median": { + "format": "double", + "description": "Output only. The median of the values in the population.", + "readOnly": true, + "type": "number" + } + } + }, + "GoogleCloudAiplatformV1MigrateResourceRequestMigrateMlEngineModelVersionConfig": { + "description": "Config for migrating version in ml.googleapis.com to Vertex AI's Model.", + "properties": { + "modelDisplayName": { + "description": "Required. Display name of the model in Vertex AI. System will pick a display name if unspecified.", + "type": "string" + }, + "endpoint": { + "type": "string", + "description": "Required. The ml.googleapis.com endpoint that this model version should be migrated from. Example values: * ml.googleapis.com * us-centrall-ml.googleapis.com * europe-west4-ml.googleapis.com * asia-east1-ml.googleapis.com" + }, + "modelVersion": { + "type": "string", + "description": "Required. Full resource name of ml engine model version. Format: `projects/{project}/models/{model}/versions/{version}`." + } + }, + "id": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateMlEngineModelVersionConfig", + "type": "object" + }, + "GoogleCloudAiplatformV1StreamRawPredictRequest": { + "properties": { + "httpBody": { + "$ref": "GoogleApiHttpBody", + "description": "The prediction input. Supports HTTP headers and arbitrary data payload." + } + }, + "id": "GoogleCloudAiplatformV1StreamRawPredictRequest", + "type": "object", + "description": "Request message for PredictionService.StreamRawPredict." + }, + "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessResult": { + "id": "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessResult", + "description": "Spec for question answering correctness result.", + "properties": { + "explanation": { + "description": "Output only. Explanation for question answering correctness score.", + "readOnly": true, + "type": "string" + }, + "confidence": { + "readOnly": true, + "format": "float", + "description": "Output only. Confidence for question answering correctness score.", + "type": "number" + }, + "score": { + "format": "float", + "type": "number", + "readOnly": true, + "description": "Output only. Question Answering Correctness score." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaPredictionResult": { + "id": "GoogleCloudAiplatformV1SchemaPredictionResult", + "description": "Represents a line of JSONL in the batch prediction output file.", + "properties": { + "key": { + "type": "string", + "description": "Optional user-provided key from the input instance." + }, + "prediction": { + "description": "The prediction result. Value is used here instead of Any so that JsonFormat does not append an extra \"@type\" field when we convert the proto to JSON and so we can represent array of objects. Do not set error if this is set.", + "type": "any" + }, + "error": { + "description": "The error result. Do not set prediction if this is set.", + "$ref": "GoogleCloudAiplatformV1SchemaPredictionResultError" + }, + "instance": { + "additionalProperties": { + "type": "any", + "description": "Properties of the object." + }, + "type": "object", + "description": "User's input instance. Struct is used here instead of Any so that JsonFormat does not append an extra \"@type\" field when we convert the proto to JSON." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1NotebookRuntimeTemplateRef": { + "type": "object", + "id": "GoogleCloudAiplatformV1NotebookRuntimeTemplateRef", + "properties": { + "notebookRuntimeTemplate": { + "description": "Immutable. A resource name of the NotebookRuntimeTemplate.", + "type": "string" + } + }, + "description": "Points to a NotebookRuntimeTemplateRef." + }, + "GoogleCloudAiplatformV1FunctionCall": { + "id": "GoogleCloudAiplatformV1FunctionCall", + "properties": { + "name": { + "type": "string", + "description": "Required. The name of the function to call. Matches [FunctionDeclaration.name]." + }, + "args": { + "type": "object", + "additionalProperties": { + "type": "any", + "description": "Properties of the object." + }, + "description": "Optional. Required. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details." + } + }, + "type": "object", + "description": "A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values." + }, + "GoogleCloudAiplatformV1SchemaPredictInstanceTextSentimentPredictionInstance": { + "description": "Prediction input format for Text Sentiment.", + "properties": { + "mimeType": { + "type": "string", + "description": "The MIME type of the text snippet. The supported MIME types are listed below. - text/plain" + }, + "content": { + "type": "string", + "description": "The text snippet to make the predictions on." + } + }, + "id": "GoogleCloudAiplatformV1SchemaPredictInstanceTextSentimentPredictionInstance", + "type": "object" + }, + "GoogleCloudAiplatformV1PipelineJobRuntimeConfigInputArtifact": { + "type": "object", + "id": "GoogleCloudAiplatformV1PipelineJobRuntimeConfigInputArtifact", + "description": "The type of an input artifact.", + "properties": { + "artifactId": { + "description": "Artifact resource id from MLMD. Which is the last portion of an artifact resource name: `projects/{project}/locations/{location}/metadataStores/default/artifacts/{artifact_id}`. The artifact must stay within the same project, location and default metadatastore as the pipeline.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1ImportModelEvaluationRequest": { + "id": "GoogleCloudAiplatformV1ImportModelEvaluationRequest", + "type": "object", + "properties": { + "modelEvaluation": { + "$ref": "GoogleCloudAiplatformV1ModelEvaluation", + "description": "Required. Model evaluation resource to be imported." + } + }, + "description": "Request message for ModelService.ImportModelEvaluation" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericTransformation": { + "properties": { + "invalidValuesAllowed": { + "type": "boolean", + "description": "If invalid values is allowed, the training pipeline will create a boolean feature that indicated whether the value is valid. Otherwise, the training pipeline will discard the input row from trainining data." + }, + "columnName": { + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericTransformation", + "description": "Training pipeline will perform following transformation functions. * The value converted to float32. * The z_score of the value. * log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * A boolean value that indicates whether the value is valid." + }, + "GoogleCloudAiplatformV1ModelEvaluationModelEvaluationExplanationSpec": { + "properties": { + "explanationSpec": { + "description": "Explanation spec details.", + "$ref": "GoogleCloudAiplatformV1ExplanationSpec" + }, + "explanationType": { + "type": "string", + "description": "Explanation type. For AutoML Image Classification models, possible values are: * `image-integrated-gradients` * `image-xrai`" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1ModelEvaluationModelEvaluationExplanationSpec" + }, + "GoogleCloudAiplatformV1SchemaTimeSegment": { + "description": "A time period inside of a DataItem that has a time dimension (e.g. video).", + "id": "GoogleCloudAiplatformV1SchemaTimeSegment", + "type": "object", + "properties": { + "endTimeOffset": { + "description": "End of the time segment (exclusive), represented as the duration since the start of the DataItem.", + "format": "google-duration", + "type": "string" + }, + "startTimeOffset": { + "format": "google-duration", + "description": "Start of the time segment (inclusive), represented as the duration since the start of the DataItem.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1BatchMigrateResourcesOperationMetadataPartialResult": { + "properties": { + "dataset": { + "description": "Migrated dataset resource name.", + "type": "string" + }, + "model": { + "type": "string", + "description": "Migrated model resource name." + }, + "request": { + "$ref": "GoogleCloudAiplatformV1MigrateResourceRequest", + "description": "It's the same as the value in MigrateResourceRequest.migrate_resource_requests." + }, + "error": { + "description": "The error result of the migration request in case of failure.", + "$ref": "GoogleRpcStatus" + } + }, + "id": "GoogleCloudAiplatformV1BatchMigrateResourcesOperationMetadataPartialResult", + "description": "Represents a partial result in batch migration operation for one MigrateResourceRequest.", + "type": "object" + }, + "GoogleCloudAiplatformV1SyncFeatureViewRequest": { + "type": "object", + "description": "Request message for FeatureOnlineStoreAdminService.SyncFeatureView.", + "properties": {}, + "id": "GoogleCloudAiplatformV1SyncFeatureViewRequest" + }, + "GoogleCloudAiplatformV1CreateTensorboardRunRequest": { + "properties": { + "parent": { + "type": "string", + "description": "Required. The resource name of the TensorboardExperiment to create the TensorboardRun in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`" + }, + "tensorboardRun": { + "description": "Required. The TensorboardRun to create.", + "$ref": "GoogleCloudAiplatformV1TensorboardRun" + }, + "tensorboardRunId": { + "type": "string", + "description": "Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`." + } + }, + "id": "GoogleCloudAiplatformV1CreateTensorboardRunRequest", + "description": "Request message for TensorboardService.CreateTensorboardRun.", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesMetadata": { + "type": "object", + "description": "Model metadata specific to AutoML Tables.", + "properties": { + "trainCostMilliNodeHours": { + "description": "Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget.", + "format": "int64", + "type": "string" + }, + "evaluatedDataItemsBigqueryUri": { + "description": "BigQuery destination uri for exported evaluated examples.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesMetadata" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextClassificationInputs": { + "properties": { + "multiLabel": { + "type": "boolean" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextClassificationInputs", + "type": "object" + }, + "GoogleCloudAiplatformV1ListArtifactsResponse": { + "type": "object", + "properties": { + "nextPageToken": { + "description": "A token, which can be sent as ListArtifactsRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages.", + "type": "string" + }, + "artifacts": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1Artifact" + }, + "description": "The Artifacts retrieved from the MetadataStore." + } + }, + "id": "GoogleCloudAiplatformV1ListArtifactsResponse", + "description": "Response message for MetadataService.ListArtifacts." + }, + "GoogleCloudAiplatformV1ExplanationMetadata": { + "description": "Metadata describing the Model's input and output for explanation.", + "id": "GoogleCloudAiplatformV1ExplanationMetadata", + "properties": { + "latentSpaceSource": { + "type": "string", + "description": "Name of the source to generate embeddings for example based explanations." + }, + "inputs": { + "type": "object", + "description": "Required. Map from feature names to feature input metadata. Keys are the name of the features. Values are the specification of the feature. An empty InputMetadata is valid. It describes a text feature which has the name specified as the key in ExplanationMetadata.inputs. The baseline of the empty feature is chosen by Vertex AI. For Vertex AI-provided Tensorflow images, the key can be any friendly name of the feature. Once specified, featureAttributions are keyed by this key (if not grouped with another feature). For custom images, the key must match with the key in instance.", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1ExplanationMetadataInputMetadata" + } + }, + "outputs": { + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1ExplanationMetadataOutputMetadata" + }, + "type": "object", + "description": "Required. Map from output names to output metadata. For Vertex AI-provided Tensorflow images, keys can be any user defined string that consists of any UTF-8 characters. For custom images, keys are the name of the output field in the prediction to be explained. Currently only one key is allowed." + }, + "featureAttributionsSchemaUri": { + "description": "Points to a YAML file stored on Google Cloud Storage describing the format of the feature attributions. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML tabular Models always have this field populated by Vertex AI. Note: The URI given on output may be different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1ExportModelRequestOutputConfig": { + "type": "object", + "id": "GoogleCloudAiplatformV1ExportModelRequestOutputConfig", + "description": "Output configuration for the Model export.", + "properties": { + "artifactDestination": { + "$ref": "GoogleCloudAiplatformV1GcsDestination", + "description": "The Cloud Storage location where the Model artifact is to be written to. Under the directory given as the destination a new one with name \"`model-export--`\", where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format, will be created. Inside, the Model and any of its supporting files will be written. This field should only be set when the `exportableContent` field of the [Model.supported_export_formats] object contains `ARTIFACT`." + }, + "exportFormatId": { + "description": "The ID of the format in which the Model must be exported. Each Model lists the export formats it supports. If no value is provided here, then the first from the list of the Model's supported formats is used by default.", + "type": "string" + }, + "imageDestination": { + "$ref": "GoogleCloudAiplatformV1ContainerRegistryDestination", + "description": "The Google Container Registry or Artifact Registry uri where the Model container image will be copied to. This field should only be set when the `exportableContent` field of the [Model.supported_export_formats] object contains `IMAGE`." + } + } + }, + "GoogleCloudAiplatformV1SchemaPredictInstanceImageSegmentationPredictionInstance": { + "description": "Prediction input format for Image Segmentation.", + "properties": { + "mimeType": { + "type": "string", + "description": "The MIME type of the content of the image. Only the images in below listed MIME types are supported. - image/jpeg - image/png" + }, + "content": { + "type": "string", + "description": "The image bytes to make the predictions on." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaPredictInstanceImageSegmentationPredictionInstance" + }, + "GoogleCloudAiplatformV1ExplainRequest": { + "properties": { + "parameters": { + "type": "any", + "description": "The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri." + }, + "deployedModelId": { + "type": "string", + "description": "If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split." + }, + "instances": { + "description": "Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.", + "items": { + "type": "any" + }, + "type": "array" + }, + "explanationSpecOverride": { + "$ref": "GoogleCloudAiplatformV1ExplanationSpecOverride", + "description": "If specified, overrides the explanation_spec of the DeployedModel. Can be used for explaining prediction results with different configurations, such as: - Explaining top-5 predictions results as opposed to top-1; - Increasing path count or step count of the attribution methods to reduce approximate errors; - Using different baselines for explaining the prediction results." + } + }, + "type": "object", + "description": "Request message for PredictionService.Explain.", + "id": "GoogleCloudAiplatformV1ExplainRequest" + }, + "GoogleCloudAiplatformV1GroundingMetadata": { + "description": "Metadata returned to client when grounding is enabled.", + "id": "GoogleCloudAiplatformV1GroundingMetadata", + "type": "object", + "properties": { + "webSearchQueries": { + "description": "Optional. Web search queries for the following-up web search.", + "items": { + "type": "string" + }, + "type": "array" + }, + "groundingSupports": { + "description": "Optional. List of grounding support.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1GroundingSupport" + } + }, + "searchEntryPoint": { + "description": "Optional. Google search entry for the following-up web searches.", + "$ref": "GoogleCloudAiplatformV1SearchEntryPoint" + }, + "groundingChunks": { + "type": "array", + "description": "List of supporting references retrieved from specified grounding source.", + "items": { + "$ref": "GoogleCloudAiplatformV1GroundingChunk" + } + } + } + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationCategoricalTransformation": { + "description": "Training pipeline will perform following transformation functions. * The categorical string as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. * Categories that appear less than 5 times in the training dataset are treated as the \"unknown\" category. The \"unknown\" category gets its own special lookup index and resulting embedding.", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationCategoricalTransformation", + "properties": { + "columnName": { + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec": { + "properties": { + "maxParallelTrialCount": { + "description": "Required. The maximum number of trials to run in parallel.", + "format": "int32", + "type": "integer" + }, + "frequency": { + "format": "int32", + "description": "Required. Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.", + "type": "integer" + }, + "trainTrialJobSpec": { + "description": "Required. The spec of a train trial job. The same spec applies to all train trials.", + "$ref": "GoogleCloudAiplatformV1CustomJobSpec" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec", + "description": "Represent spec for train trials." + }, + "GoogleCloudAiplatformV1LookupStudyRequest": { + "properties": { + "displayName": { + "type": "string", + "description": "Required. The user-defined display name of the Study" + } + }, + "description": "Request message for VizierService.LookupStudy.", + "type": "object", + "id": "GoogleCloudAiplatformV1LookupStudyRequest" + }, + "GoogleCloudAiplatformV1CreateEndpointOperationMetadata": { + "id": "GoogleCloudAiplatformV1CreateEndpointOperationMetadata", + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + }, + "description": "Runtime operation information for EndpointService.CreateEndpoint.", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaVisualInspectionMaskSavedQueryMetadata": { + "properties": {}, + "id": "GoogleCloudAiplatformV1SchemaVisualInspectionMaskSavedQueryMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1Port": { + "id": "GoogleCloudAiplatformV1Port", + "type": "object", + "properties": { + "containerPort": { + "type": "integer", + "description": "The number of the port to expose on the pod's IP address. Must be a valid port number, between 1 and 65535 inclusive.", + "format": "int32" + } + }, + "description": "Represents a network port in a container." + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericArrayTransformation": { + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericArrayTransformation", + "type": "object", + "properties": { + "invalidValuesAllowed": { + "description": "If invalid values is allowed, the training pipeline will create a boolean feature that indicated whether the value is valid. Otherwise, the training pipeline will discard the input row from trainining data.", + "type": "boolean" + }, + "columnName": { + "type": "string" + } + }, + "description": "Treats the column as numerical array and performs following transformation functions. * All transformations for Numerical types applied to the average of the all elements. * The average of empty arrays is treated as zero." + }, + "GoogleCloudAiplatformV1PersistentDiskSpec": { + "properties": { + "diskSizeGb": { + "type": "string", + "format": "int64", + "description": "Size in GB of the disk (default is 100GB)." + }, + "diskType": { + "description": "Type of the disk (default is \"pd-standard\"). Valid values: \"pd-ssd\" (Persistent Disk Solid State Drive) \"pd-standard\" (Persistent Disk Hard Disk Drive) \"pd-balanced\" (Balanced Persistent Disk) \"pd-extreme\" (Extreme Persistent Disk)", + "type": "string" + } + }, + "description": "Represents the spec of persistent disk options.", + "type": "object", + "id": "GoogleCloudAiplatformV1PersistentDiskSpec" + }, + "GoogleCloudAiplatformV1SchemaPredictInstanceTextExtractionPredictionInstance": { + "description": "Prediction input format for Text Extraction.", + "id": "GoogleCloudAiplatformV1SchemaPredictInstanceTextExtractionPredictionInstance", + "properties": { + "content": { + "description": "The text snippet to make the predictions on.", + "type": "string" + }, + "key": { + "type": "string", + "description": "This field is only used for batch prediction. If a key is provided, the batch prediction result will by mapped to this key. If omitted, then the batch prediction result will contain the entire input instance. Vertex AI will not check if keys in the request are duplicates, so it is up to the caller to ensure the keys are unique." + }, + "mimeType": { + "description": "The MIME type of the text snippet. The supported MIME types are listed below. - text/plain", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SearchModelDeploymentMonitoringStatsAnomaliesRequestStatsAnomaliesObjective": { + "properties": { + "topFeatureCount": { + "description": "If set, all attribution scores between SearchModelDeploymentMonitoringStatsAnomaliesRequest.start_time and SearchModelDeploymentMonitoringStatsAnomaliesRequest.end_time are fetched, and page token doesn't take effect in this case. Only used to retrieve attribution score for the top Features which has the highest attribution score in the latest monitoring run.", + "format": "int32", + "type": "integer" + }, + "type": { + "enumDescriptions": [ + "Default value, should not be set.", + "Raw feature values' stats to detect skew between Training-Prediction datasets.", + "Raw feature values' stats to detect drift between Serving-Prediction datasets.", + "Feature attribution scores to detect skew between Training-Prediction datasets.", + "Feature attribution scores to detect skew between Prediction datasets collected within different time windows." + ], + "type": "string", + "enum": [ + "MODEL_DEPLOYMENT_MONITORING_OBJECTIVE_TYPE_UNSPECIFIED", + "RAW_FEATURE_SKEW", + "RAW_FEATURE_DRIFT", + "FEATURE_ATTRIBUTION_SKEW", + "FEATURE_ATTRIBUTION_DRIFT" + ] + } + }, + "description": "Stats requested for specific objective.", + "id": "GoogleCloudAiplatformV1SearchModelDeploymentMonitoringStatsAnomaliesRequestStatsAnomaliesObjective", + "type": "object" + }, + "GoogleCloudAiplatformV1EvaluatedAnnotation": { + "description": "True positive, false positive, or false negative. EvaluatedAnnotation is only available under ModelEvaluationSlice with slice of `annotationSpec` dimension.", + "properties": { + "dataItemPayload": { + "type": "any", + "description": "Output only. The data item payload that the Model predicted this EvaluatedAnnotation on.", + "readOnly": true + }, + "explanations": { + "description": "Explanations of predictions. Each element of the explanations indicates the explanation for one explanation Method. The attributions list in the EvaluatedAnnotationExplanation.explanation object corresponds to the predictions list. For example, the second element in the attributions list explains the second element in the predictions list.", + "items": { + "$ref": "GoogleCloudAiplatformV1EvaluatedAnnotationExplanation" + }, + "type": "array" + }, + "groundTruths": { + "items": { + "type": "any" + }, + "description": "Output only. The ground truth Annotations, i.e. the Annotations that exist in the test data the Model is evaluated on. For true positive, there is one and only one ground truth annotation, which matches the only prediction in predictions. For false positive, there are zero or more ground truth annotations that are similar to the only prediction in predictions, but not enough for a match. For false negative, there is one and only one ground truth annotation, which doesn't match any predictions created by the model. The schema of the ground truth is stored in ModelEvaluation.annotation_schema_uri", + "type": "array", + "readOnly": true + }, + "type": { + "enumDescriptions": [ + "Invalid value.", + "The EvaluatedAnnotation is a true positive. It has a prediction created by the Model and a ground truth Annotation which the prediction matches.", + "The EvaluatedAnnotation is false positive. It has a prediction created by the Model which does not match any ground truth annotation.", + "The EvaluatedAnnotation is false negative. It has a ground truth annotation which is not matched by any of the model created predictions." + ], + "enum": [ + "EVALUATED_ANNOTATION_TYPE_UNSPECIFIED", + "TRUE_POSITIVE", + "FALSE_POSITIVE", + "FALSE_NEGATIVE" + ], + "readOnly": true, + "type": "string", + "description": "Output only. Type of the EvaluatedAnnotation." + }, + "errorAnalysisAnnotations": { + "description": "Annotations of model error analysis results.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1ErrorAnalysisAnnotation" + } + }, + "evaluatedDataItemViewId": { + "readOnly": true, + "description": "Output only. ID of the EvaluatedDataItemView under the same ancestor ModelEvaluation. The EvaluatedDataItemView consists of all ground truths and predictions on data_item_payload.", + "type": "string" + }, + "predictions": { + "type": "array", + "readOnly": true, + "items": { + "type": "any" + }, + "description": "Output only. The model predicted annotations. For true positive, there is one and only one prediction, which matches the only one ground truth annotation in ground_truths. For false positive, there is one and only one prediction, which doesn't match any ground truth annotation of the corresponding data_item_view_id. For false negative, there are zero or more predictions which are similar to the only ground truth annotation in ground_truths but not enough for a match. The schema of the prediction is stored in ModelEvaluation.annotation_schema_uri" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1EvaluatedAnnotation" + }, + "GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeature": { + "description": "Noise sigma for a single feature.", + "properties": { + "name": { + "type": "string", + "description": "The name of the input feature for which noise sigma is provided. The features are defined in explanation metadata inputs." + }, + "sigma": { + "description": "This represents the standard deviation of the Gaussian kernel that will be used to add noise to the feature prior to computing gradients. Similar to noise_sigma but represents the noise added to the current feature. Defaults to 0.1.", + "type": "number", + "format": "float" + } + }, + "id": "GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeature", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationNumericTransformation": { + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationNumericTransformation", + "type": "object", + "description": "Training pipeline will perform following transformation functions. * The value converted to float32. * The z_score of the value. * log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.", + "properties": { + "columnName": { + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1FeaturestoreOnlineServingConfig": { + "description": "OnlineServingConfig specifies the details for provisioning online serving resources.", + "id": "GoogleCloudAiplatformV1FeaturestoreOnlineServingConfig", + "properties": { + "scaling": { + "$ref": "GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScaling", + "description": "Online serving scaling configuration. Only one of `fixed_node_count` and `scaling` can be set. Setting one will reset the other." + }, + "fixedNodeCount": { + "format": "int32", + "type": "integer", + "description": "The number of nodes for the online store. The number of nodes doesn't scale automatically, but you can manually update the number of nodes. If set to 0, the featurestore will not have an online store and cannot be used for online serving." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1DirectPredictRequest": { + "type": "object", + "description": "Request message for PredictionService.DirectPredict.", + "id": "GoogleCloudAiplatformV1DirectPredictRequest", + "properties": { + "inputs": { + "items": { + "$ref": "GoogleCloudAiplatformV1Tensor" + }, + "description": "The prediction input.", + "type": "array" + }, + "parameters": { + "description": "The parameters that govern the prediction.", + "$ref": "GoogleCloudAiplatformV1Tensor" + } + } + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTimestampTransformation": { + "type": "object", + "properties": { + "columnName": { + "type": "string" + }, + "timeFormat": { + "type": "string", + "description": "The format in which that time field is expressed. The time_format must either be one of: * `unix-seconds` * `unix-milliseconds` * `unix-microseconds` * `unix-nanoseconds` (for respectively number of seconds, milliseconds, microseconds and nanoseconds since start of the Unix epoch); or be written in `strftime` syntax. If time_format is not set, then the default format is RFC 3339 `date-time` format, where `time-offset` = `\"Z\"` (e.g. 1985-04-12T23:20:50.52Z)" + } + }, + "description": "Training pipeline will perform following transformation functions. * Apply the transformation functions for Numerical columns. * Determine the year, month, day,and weekday. Treat each value from the timestamp as a Categorical column. * Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed.", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTimestampTransformation" + }, + "GoogleCloudAiplatformV1MigratableResourceDataLabelingDatasetDataLabelingAnnotatedDataset": { + "type": "object", + "properties": { + "annotatedDatasetDisplayName": { + "type": "string", + "description": "The AnnotatedDataset's display name in datalabeling.googleapis.com." + }, + "annotatedDataset": { + "type": "string", + "description": "Full resource name of data labeling AnnotatedDataset. Format: `projects/{project}/datasets/{dataset}/annotatedDatasets/{annotated_dataset}`." + } + }, + "description": "Represents one AnnotatedDataset in datalabeling.googleapis.com.", + "id": "GoogleCloudAiplatformV1MigratableResourceDataLabelingDatasetDataLabelingAnnotatedDataset" + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoActionMetrics": { + "properties": { + "meanAveragePrecision": { + "type": "number", + "format": "float", + "description": "The mean average precision." + }, + "precisionWindowLength": { + "format": "google-duration", + "type": "string", + "description": "This VideoActionMetrics is calculated based on this prediction window length. If the predicted action's timestamp is inside the time window whose center is the ground truth action's timestamp with this specific length, the prediction result is treated as a true positive." + }, + "confidenceMetrics": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoActionMetricsConfidenceMetrics" + }, + "description": "Metrics for each label-match confidence_threshold from 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoActionMetrics", + "description": "The Evaluation metrics given a specific precision_window_length." + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoActionRecognition": { + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoActionRecognition", + "properties": { + "inputs": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoActionRecognitionInputs", + "description": "The input parameters of this TrainingJob." + } + }, + "description": "A TrainingJob that trains and uploads an AutoML Video Action Recognition Model." + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrixAnnotationSpecRef": { + "properties": { + "id": { + "description": "ID of the AnnotationSpec.", + "type": "string" + }, + "displayName": { + "description": "Display name of the AnnotationSpec.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrixAnnotationSpecRef", + "type": "object" + }, + "GoogleCloudAiplatformV1SafetyInput": { + "id": "GoogleCloudAiplatformV1SafetyInput", + "properties": { + "instance": { + "$ref": "GoogleCloudAiplatformV1SafetyInstance", + "description": "Required. Safety instance." + }, + "metricSpec": { + "description": "Required. Spec for safety metric.", + "$ref": "GoogleCloudAiplatformV1SafetySpec" + } + }, + "type": "object", + "description": "Input for safety metric." + }, + "GoogleCloudAiplatformV1ResumeModelDeploymentMonitoringJobRequest": { + "properties": {}, + "type": "object", + "description": "Request message for JobService.ResumeModelDeploymentMonitoringJob.", + "id": "GoogleCloudAiplatformV1ResumeModelDeploymentMonitoringJobRequest" + }, + "GoogleCloudAiplatformV1TensorboardTensor": { + "description": "One point viewable on a tensor metric plot.", + "type": "object", + "properties": { + "value": { + "type": "string", + "format": "byte", + "description": "Required. Serialized form of https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/tensor.proto" + }, + "versionNumber": { + "format": "int32", + "description": "Optional. Version number of TensorProto used to serialize value.", + "type": "integer" + } + }, + "id": "GoogleCloudAiplatformV1TensorboardTensor" + }, + "GoogleCloudAiplatformV1Blob": { + "id": "GoogleCloudAiplatformV1Blob", + "description": "Content blob. It's preferred to send as text directly rather than raw bytes.", + "properties": { + "mimeType": { + "description": "Required. The IANA standard MIME type of the source data.", + "type": "string" + }, + "data": { + "description": "Required. Raw bytes.", + "format": "byte", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalArrayTransformation": { + "properties": { + "columnName": { + "type": "string" + } + }, + "type": "object", + "description": "Treats the column as categorical array and performs following transformation functions. * For each element in the array, convert the category name to a dictionary lookup index and generate an embedding for each index. Combine the embedding of all elements into a single embedding using the mean. * Empty arrays treated as an embedding of zeroes.", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalArrayTransformation" + }, + "GoogleCloudAiplatformV1ResourceRuntime": { + "type": "object", + "id": "GoogleCloudAiplatformV1ResourceRuntime", + "properties": { + "accessUris": { + "description": "Output only. URIs for user to connect to the Cluster. Example: { \"RAY_HEAD_NODE_INTERNAL_IP\": \"head-node-IP:10001\" \"RAY_DASHBOARD_URI\": \"ray-dashboard-address:8888\" }", + "readOnly": true, + "additionalProperties": { + "type": "string" + }, + "type": "object" + } + }, + "description": "Persistent Cluster runtime information as output" + }, + "GoogleCloudAiplatformV1ResourcePoolAutoscalingSpec": { + "properties": { + "maxReplicaCount": { + "type": "string", + "description": "Optional. max replicas in the node pool, must be ≥ replica_count and \u003e min_replica_count or will throw error", + "format": "int64" + }, + "minReplicaCount": { + "type": "string", + "description": "Optional. min replicas in the node pool, must be ≤ replica_count and \u003c max_replica_count or will throw error. For autoscaling enabled Ray-on-Vertex, we allow min_replica_count of a resource_pool to be 0 to match the OSS Ray behavior(https://docs.ray.io/en/latest/cluster/vms/user-guides/configuring-autoscaling.html#cluster-config-parameters). As for Persistent Resource, the min_replica_count must be \u003e 0, we added a corresponding validation inside CreatePersistentResourceRequestValidator.java.", + "format": "int64" + } + }, + "id": "GoogleCloudAiplatformV1ResourcePoolAutoscalingSpec", + "description": "The min/max number of replicas allowed if enabling autoscaling", + "type": "object" + }, + "GoogleCloudAiplatformV1ComputeTokensResponse": { + "properties": { + "tokensInfo": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1TokensInfo" + }, + "description": "Lists of tokens info from the input. A ComputeTokensRequest could have multiple instances with a prompt in each instance. We also need to return lists of tokens info for the request with multiple instances." + } + }, + "description": "Response message for ComputeTokens RPC call.", + "type": "object", + "id": "GoogleCloudAiplatformV1ComputeTokensResponse" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextSentiment": { + "properties": { + "inputs": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextSentimentInputs", + "description": "The input parameters of this TrainingJob." + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextSentiment", + "description": "A TrainingJob that trains and uploads an AutoML Text Sentiment Model.", + "type": "object" + }, + "GoogleCloudAiplatformV1ReadTensorboardBlobDataResponse": { + "description": "Response message for TensorboardService.ReadTensorboardBlobData.", + "type": "object", + "id": "GoogleCloudAiplatformV1ReadTensorboardBlobDataResponse", + "properties": { + "blobs": { + "description": "Blob messages containing blob bytes.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1TensorboardBlob" + } + } + } + }, + "GoogleCloudAiplatformV1RemoveContextChildrenResponse": { + "id": "GoogleCloudAiplatformV1RemoveContextChildrenResponse", + "type": "object", + "properties": {}, + "description": "Response message for MetadataService.RemoveContextChildren." + }, + "GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfig": { + "id": "GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfig", + "properties": { + "monitorInterval": { + "description": "Required. The model monitoring job scheduling interval. It will be rounded up to next full hour. This defines how often the monitoring jobs are triggered.", + "type": "string", + "format": "google-duration" + }, + "monitorWindow": { + "format": "google-duration", + "type": "string", + "description": "The time window of the prediction data being included in each prediction dataset. This window specifies how long the data should be collected from historical model results for each run. If not set, ModelDeploymentMonitoringScheduleConfig.monitor_interval will be used. e.g. If currently the cutoff time is 2022-01-08 14:30:00 and the monitor_window is set to be 3600, then data from 2022-01-08 13:30:00 to 2022-01-08 14:30:00 will be retrieved and aggregated to calculate the monitoring statistics." + } + }, + "description": "The config for scheduling monitoring job.", + "type": "object" + }, + "GoogleCloudAiplatformV1ExactMatchResults": { + "id": "GoogleCloudAiplatformV1ExactMatchResults", + "properties": { + "exactMatchMetricValues": { + "readOnly": true, + "description": "Output only. Exact match metric values.", + "items": { + "$ref": "GoogleCloudAiplatformV1ExactMatchMetricValue" + }, + "type": "array" + } + }, + "type": "object", + "description": "Results for exact match metric." + }, + "GoogleCloudAiplatformV1ExplanationMetadataInputMetadataFeatureValueDomain": { + "id": "GoogleCloudAiplatformV1ExplanationMetadataInputMetadataFeatureValueDomain", + "properties": { + "maxValue": { + "format": "float", + "type": "number", + "description": "The maximum permissible value for this feature." + }, + "originalStddev": { + "format": "float", + "type": "number", + "description": "If this input feature has been normalized to a standard deviation of 1.0, the original_stddev specifies the standard deviation of the domain prior to normalization." + }, + "minValue": { + "format": "float", + "description": "The minimum permissible value for this feature.", + "type": "number" + }, + "originalMean": { + "format": "float", + "description": "If this input feature has been normalized to a mean value of 0, the original_mean specifies the mean value of the domain prior to normalization.", + "type": "number" + } + }, + "description": "Domain details of the input feature value. Provides numeric information about the feature, such as its range (min, max). If the feature has been pre-processed, for example with z-scoring, then it provides information about how to recover the original feature. For example, if the input feature is an image and it has been pre-processed to obtain 0-mean and stddev = 1 values, then original_mean, and original_stddev refer to the mean and stddev of the original feature (e.g. image tensor) from which input feature (with mean = 0 and stddev = 1) was obtained.", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTextSentimentSavedQueryMetadata": { + "id": "GoogleCloudAiplatformV1SchemaTextSentimentSavedQueryMetadata", + "properties": { + "sentimentMax": { + "description": "The maximum sentiment of sentiment Anntoation in this SavedQuery.", + "format": "int32", + "type": "integer" + } + }, + "description": "The metadata of SavedQuery contains TextSentiment Annotations.", + "type": "object" + }, + "GoogleCloudAiplatformV1UpsertDatapointsRequest": { + "description": "Request message for IndexService.UpsertDatapoints", + "id": "GoogleCloudAiplatformV1UpsertDatapointsRequest", + "properties": { + "updateMask": { + "format": "google-fieldmask", + "description": "Optional. Update mask is used to specify the fields to be overwritten in the datapoints by the update. The fields specified in the update_mask are relative to each IndexDatapoint inside datapoints, not the full request. Updatable fields: * Use `all_restricts` to update both restricts and numeric_restricts.", + "type": "string" + }, + "datapoints": { + "description": "A list of datapoints to be created/updated.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1IndexDatapoint" + } + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1ListNotebookExecutionJobsResponse": { + "description": "Response message for [NotebookService.CreateNotebookExecutionJob]", + "id": "GoogleCloudAiplatformV1ListNotebookExecutionJobsResponse", + "type": "object", + "properties": { + "nextPageToken": { + "description": "A token to retrieve next page of results. Pass to ListNotebookExecutionJobs.page_token to obtain that page.", + "type": "string" + }, + "notebookExecutionJobs": { + "type": "array", + "description": "List of NotebookExecutionJobs in the requested page.", + "items": { + "$ref": "GoogleCloudAiplatformV1NotebookExecutionJob" + } + } + } + }, + "GoogleCloudAiplatformV1PredictSchemata": { + "id": "GoogleCloudAiplatformV1PredictSchemata", + "properties": { + "instanceSchemaUri": { + "type": "string", + "description": "Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single instance, which are used in PredictRequest.instances, ExplainRequest.instances and BatchPredictionJob.input_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access." + }, + "parametersSchemaUri": { + "description": "Immutable. Points to a YAML file stored on Google Cloud Storage describing the parameters of prediction and explanation via PredictRequest.parameters, ExplainRequest.parameters and BatchPredictionJob.model_parameters. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no parameters are supported, then it is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.", + "type": "string" + }, + "predictionSchemaUri": { + "type": "string", + "description": "Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single prediction produced by this Model, which are returned via PredictResponse.predictions, ExplainResponse.explanations, and BatchPredictionJob.output_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access." + } + }, + "type": "object", + "description": "Contains the schemata used in Model's predictions and explanations via PredictionService.Predict, PredictionService.Explain and BatchPredictionJob." + }, + "GoogleCloudAiplatformV1WriteTensorboardRunDataRequest": { + "description": "Request message for TensorboardService.WriteTensorboardRunData.", + "type": "object", + "properties": { + "tensorboardRun": { + "type": "string", + "description": "Required. The resource name of the TensorboardRun to write data to. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`" + }, + "timeSeriesData": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1TimeSeriesData" + }, + "description": "Required. The TensorboardTimeSeries data to write. Values with in a time series are indexed by their step value. Repeated writes to the same step will overwrite the existing value for that step. The upper limit of data points per write request is 5000." + } + }, + "id": "GoogleCloudAiplatformV1WriteTensorboardRunDataRequest" + }, + "GoogleCloudAiplatformV1ListBatchPredictionJobsResponse": { + "id": "GoogleCloudAiplatformV1ListBatchPredictionJobsResponse", + "type": "object", + "properties": { + "batchPredictionJobs": { + "type": "array", + "description": "List of BatchPredictionJobs in the requested page.", + "items": { + "$ref": "GoogleCloudAiplatformV1BatchPredictionJob" + } + }, + "nextPageToken": { + "description": "A token to retrieve the next page of results. Pass to ListBatchPredictionJobsRequest.page_token to obtain that page.", + "type": "string" + } + }, + "description": "Response message for JobService.ListBatchPredictionJobs" + }, + "GoogleCloudAiplatformV1FunctionCallingConfig": { + "properties": { + "mode": { + "enum": [ + "MODE_UNSPECIFIED", + "AUTO", + "ANY", + "NONE" + ], + "type": "string", + "enumDescriptions": [ + "Unspecified function calling mode. This value should not be used.", + "Default model behavior, model decides to predict either a function call or a natural language repspose.", + "Model is constrained to always predicting a function call only. If \"allowed_function_names\" are set, the predicted function call will be limited to any one of \"allowed_function_names\", else the predicted function call will be any one of the provided \"function_declarations\".", + "Model will not predict any function call. Model behavior is same as when not passing any function declarations." + ], + "description": "Optional. Function calling mode." + }, + "allowedFunctionNames": { + "description": "Optional. Function names to call. Only set when the Mode is ANY. Function names should match [FunctionDeclaration.name]. With mode set to ANY, model will predict a function call from the set of function names provided.", + "items": { + "type": "string" + }, + "type": "array" + } + }, + "description": "Function calling config.", + "id": "GoogleCloudAiplatformV1FunctionCallingConfig", + "type": "object" + }, + "GoogleCloudAiplatformV1ExactMatchSpec": { + "properties": {}, + "type": "object", + "id": "GoogleCloudAiplatformV1ExactMatchSpec", + "description": "Spec for exact match metric - returns 1 if prediction and reference exactly matches, otherwise 0." + }, + "GoogleCloudAiplatformV1Dataset": { + "type": "object", + "id": "GoogleCloudAiplatformV1Dataset", + "description": "A collection of DataItems and Annotations on them.", + "properties": { + "createTime": { + "readOnly": true, + "type": "string", + "format": "google-datetime", + "description": "Output only. Timestamp when this Dataset was created." + }, + "savedQueries": { + "items": { + "$ref": "GoogleCloudAiplatformV1SavedQuery" + }, + "type": "array", + "description": "All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec." + }, + "metadataSchemaUri": { + "type": "string", + "description": "Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/." + }, + "metadataArtifact": { + "description": "Output only. The resource name of the Artifact that was created in MetadataStore when creating the Dataset. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.", + "type": "string", + "readOnly": true + }, + "metadata": { + "type": "any", + "description": "Required. Additional information about the Dataset." + }, + "dataItemCount": { + "description": "Output only. The number of DataItems in this Dataset. Only apply for non-structured Dataset.", + "readOnly": true, + "type": "string", + "format": "int64" + }, + "displayName": { + "type": "string", + "description": "Required. The user-defined name of the Dataset. The name can be up to 128 characters long and can consist of any UTF-8 characters." + }, + "description": { + "description": "The description of the Dataset.", + "type": "string" + }, + "name": { + "readOnly": true, + "type": "string", + "description": "Output only. Identifier. The resource name of the Dataset." + }, + "modelReference": { + "description": "Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets.", + "type": "string" + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1EncryptionSpec", + "description": "Customer-managed encryption key spec for a Dataset. If set, this Dataset and all sub-resources of this Dataset will be secured by this key." + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "description": "The labels with user-defined metadata to organize your Datasets. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable. Following system labels exist for each Dataset: * \"aiplatform.googleapis.com/dataset_metadata_schema\": output only, its value is the metadata_schema's title.", + "type": "object" + }, + "updateTime": { + "description": "Output only. Timestamp when this Dataset was last updated.", + "type": "string", + "format": "google-datetime", + "readOnly": true + }, + "etag": { + "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1PublisherModelCallToAction": { + "id": "GoogleCloudAiplatformV1PublisherModelCallToAction", + "type": "object", + "properties": { + "openGenerationAiStudio": { + "description": "Optional. Open in Generation AI Studio.", + "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences" + }, + "deployGke": { + "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionDeployGke", + "description": "Optional. Deploy PublisherModel to Google Kubernetes Engine." + }, + "createApplication": { + "description": "Optional. Create application using the PublisherModel.", + "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences" + }, + "openGenie": { + "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences", + "description": "Optional. Open Genie / Playground." + }, + "openFineTuningPipelines": { + "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionOpenFineTuningPipelines", + "description": "Optional. Open fine-tuning pipelines of the PublisherModel." + }, + "openFineTuningPipeline": { + "description": "Optional. Open fine-tuning pipeline of the PublisherModel.", + "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences" + }, + "openNotebook": { + "description": "Optional. Open notebook of the PublisherModel.", + "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences" + }, + "openNotebooks": { + "description": "Optional. Open notebooks of the PublisherModel.", + "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionOpenNotebooks" + }, + "openPromptTuningPipeline": { + "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences", + "description": "Optional. Open prompt-tuning pipeline of the PublisherModel." + }, + "openEvaluationPipeline": { + "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences", + "description": "Optional. Open evaluation pipeline of the PublisherModel." + }, + "requestAccess": { + "description": "Optional. Request for access.", + "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences" + }, + "deploy": { + "description": "Optional. Deploy the PublisherModel to Vertex Endpoint.", + "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionDeploy" + }, + "viewRestApi": { + "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionViewRestApi", + "description": "Optional. To view Rest API docs." + } + }, + "description": "Actions could take on this Publisher Model." + }, + "GoogleTypeInterval": { + "description": "Represents a time interval, encoded as a Timestamp start (inclusive) and a Timestamp end (exclusive). The start must be less than or equal to the end. When the start equals the end, the interval is empty (matches no time). When both start and end are unspecified, the interval matches any time.", + "type": "object", + "properties": { + "endTime": { + "description": "Optional. Exclusive end of the interval. If specified, a Timestamp matching this interval will have to be before the end.", + "type": "string", + "format": "google-datetime" + }, + "startTime": { + "type": "string", + "format": "google-datetime", + "description": "Optional. Inclusive start of the interval. If specified, a Timestamp matching this interval will have to be the same or after the start." + } + }, + "id": "GoogleTypeInterval" + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextExtractionEvaluationMetrics": { + "type": "object", + "description": "Metrics for text extraction evaluation results.", + "properties": { + "confusionMatrix": { + "description": "Confusion matrix of the evaluation. Only set for Models where number of AnnotationSpecs is no more than 10. Only set for ModelEvaluations, not for ModelEvaluationSlices.", + "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix" + }, + "confidenceMetrics": { + "description": "Metrics that have confidence thresholds. Precision-recall curve can be derived from them.", + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextExtractionEvaluationMetricsConfidenceMetrics" + }, + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextExtractionEvaluationMetrics" + }, + "GoogleCloudAiplatformV1SearchNearestEntitiesResponse": { + "type": "object", + "description": "Response message for FeatureOnlineStoreService.SearchNearestEntities", + "properties": { + "nearestNeighbors": { + "$ref": "GoogleCloudAiplatformV1NearestNeighbors", + "description": "The nearest neighbors of the query entity." + } + }, + "id": "GoogleCloudAiplatformV1SearchNearestEntitiesResponse" + }, + "GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScaling": { + "id": "GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScaling", + "properties": { + "minNodeCount": { + "type": "integer", + "description": "Required. The minimum number of nodes to scale down to. Must be greater than or equal to 1.", + "format": "int32" + }, + "cpuUtilizationTarget": { + "type": "integer", + "description": "Optional. A percentage of the cluster's CPU capacity. Can be from 10% to 80%. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set will default to 50%.", + "format": "int32" + }, + "maxNodeCount": { + "type": "integer", + "format": "int32", + "description": "Required. The maximum number of nodes to scale up to. Must be greater than or equal to min_node_count, and less than or equal to 10 times of 'min_node_count'." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1DeleteFeatureValuesResponseSelectEntity": { + "id": "GoogleCloudAiplatformV1DeleteFeatureValuesResponseSelectEntity", + "type": "object", + "description": "Response message if the request uses the SelectEntity option.", + "properties": { + "onlineStorageDeletedEntityCount": { + "description": "The count of deleted entities in the online storage. Each entity ID corresponds to one entity.", + "format": "int64", + "type": "string" + }, + "offlineStorageDeletedEntityRowCount": { + "type": "string", + "description": "The count of deleted entity rows in the offline storage. Each row corresponds to the combination of an entity ID and a timestamp. One entity ID can have multiple rows in the offline storage.", + "format": "int64" + } + } + }, + "GoogleCloudAiplatformV1ListFeatureViewsResponse": { + "id": "GoogleCloudAiplatformV1ListFeatureViewsResponse", + "description": "Response message for FeatureOnlineStoreAdminService.ListFeatureViews.", + "properties": { + "nextPageToken": { + "description": "A token, which can be sent as ListFeatureViewsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + }, + "featureViews": { + "description": "The FeatureViews matching the request.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1FeatureView" + } + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationCategoricalTransformation": { + "description": "Training pipeline will perform following transformation functions. * The categorical string as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. * Categories that appear less than 5 times in the training dataset are treated as the \"unknown\" category. The \"unknown\" category gets its own special lookup index and resulting embedding.", + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationCategoricalTransformation", + "properties": { + "columnName": { + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1NearestNeighbors": { + "type": "object", + "properties": { + "neighbors": { + "items": { + "$ref": "GoogleCloudAiplatformV1NearestNeighborsNeighbor" + }, + "description": "All its neighbors.", + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1NearestNeighbors", + "description": "Nearest neighbors for one query." + }, + "GoogleCloudAiplatformV1PurgeContextsResponse": { + "id": "GoogleCloudAiplatformV1PurgeContextsResponse", + "properties": { + "purgeCount": { + "format": "int64", + "type": "string", + "description": "The number of Contexts that this request deleted (or, if `force` is false, the number of Contexts that will be deleted). This can be an estimate." + }, + "purgeSample": { + "description": "A sample of the Context names that will be deleted. Only populated if `force` is set to false. The maximum number of samples is 100 (it is possible to return fewer).", + "items": { + "type": "string" + }, + "type": "array" + } + }, + "type": "object", + "description": "Response message for MetadataService.PurgeContexts." + }, + "GoogleCloudAiplatformV1ListTensorboardTimeSeriesResponse": { + "properties": { + "tensorboardTimeSeries": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1TensorboardTimeSeries" + }, + "description": "The TensorboardTimeSeries mathching the request." + }, + "nextPageToken": { + "description": "A token, which can be sent as ListTensorboardTimeSeriesRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + } + }, + "description": "Response message for TensorboardService.ListTensorboardTimeSeries.", + "type": "object", + "id": "GoogleCloudAiplatformV1ListTensorboardTimeSeriesResponse" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTimestampTransformation": { + "type": "object", + "properties": { + "timeFormat": { + "type": "string", + "description": "The format in which that time field is expressed. The time_format must either be one of: * `unix-seconds` * `unix-milliseconds` * `unix-microseconds` * `unix-nanoseconds` (for respectively number of seconds, milliseconds, microseconds and nanoseconds since start of the Unix epoch); or be written in `strftime` syntax. If time_format is not set, then the default format is RFC 3339 `date-time` format, where `time-offset` = `\"Z\"` (e.g. 1985-04-12T23:20:50.52Z)" + }, + "columnName": { + "type": "string" + } + }, + "description": "Training pipeline will perform following transformation functions. * Apply the transformation functions for Numerical columns. * Determine the year, month, day,and weekday. Treat each value from the timestamp as a Categorical column. * Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed.", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTimestampTransformation" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionCustomJobMetadata": { + "type": "object", + "properties": { + "backingCustomJob": { + "description": "The resource name of the CustomJob that has been created to carry out this custom task.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionCustomJobMetadata" + }, + "GoogleCloudAiplatformV1BleuResults": { + "type": "object", + "id": "GoogleCloudAiplatformV1BleuResults", + "description": "Results for bleu metric.", + "properties": { + "bleuMetricValues": { + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1BleuMetricValue" + }, + "description": "Output only. Bleu metric values.", + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1DeployedIndexAuthConfig": { + "description": "Used to set up the auth on the DeployedIndex's private endpoint.", + "type": "object", + "properties": { + "authProvider": { + "$ref": "GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProvider", + "description": "Defines the authentication provider that the DeployedIndex uses." + } + }, + "id": "GoogleCloudAiplatformV1DeployedIndexAuthConfig" + }, + "GoogleCloudAiplatformV1FeatureViewIndexConfigBruteForceConfig": { + "type": "object", + "description": "Configuration options for using brute force search.", + "properties": {}, + "id": "GoogleCloudAiplatformV1FeatureViewIndexConfigBruteForceConfig" + }, + "GoogleCloudAiplatformV1BatchCreateTensorboardRunsRequest": { + "description": "Request message for TensorboardService.BatchCreateTensorboardRuns.", + "properties": { + "requests": { + "description": "Required. The request message specifying the TensorboardRuns to create. A maximum of 1000 TensorboardRuns can be created in a batch.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1CreateTensorboardRunRequest" + } + } + }, + "id": "GoogleCloudAiplatformV1BatchCreateTensorboardRunsRequest", + "type": "object" + }, + "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadataRecordError": { + "properties": { + "rawRecord": { + "type": "string", + "description": "The original content of this record." + }, + "errorMessage": { + "description": "A human-readable message that is shown to the user to help them fix the error. Note that this message may change from time to time, your code should check against error_type as the source of truth.", + "type": "string" + }, + "errorType": { + "enum": [ + "ERROR_TYPE_UNSPECIFIED", + "EMPTY_LINE", + "INVALID_JSON_SYNTAX", + "INVALID_CSV_SYNTAX", + "INVALID_AVRO_SYNTAX", + "INVALID_EMBEDDING_ID", + "EMBEDDING_SIZE_MISMATCH", + "NAMESPACE_MISSING", + "PARSING_ERROR", + "DUPLICATE_NAMESPACE", + "OP_IN_DATAPOINT", + "MULTIPLE_VALUES", + "INVALID_NUMERIC_VALUE", + "INVALID_ENCODING", + "INVALID_SPARSE_DIMENSIONS", + "INVALID_TOKEN_VALUE", + "INVALID_SPARSE_EMBEDDING", + "INVALID_EMBEDDING" + ], + "type": "string", + "description": "The error type of this record.", + "enumDescriptions": [ + "Default, shall not be used.", + "The record is empty.", + "Invalid json format.", + "Invalid csv format.", + "Invalid avro format.", + "The embedding id is not valid.", + "The size of the dense embedding vectors does not match with the specified dimension.", + "The `namespace` field is missing.", + "Generic catch-all error. Only used for validation failure where the root cause cannot be easily retrieved programmatically.", + "There are multiple restricts with the same `namespace` value.", + "Numeric restrict has operator specified in datapoint.", + "Numeric restrict has multiple values specified.", + "Numeric restrict has invalid numeric value specified.", + "File is not in UTF_8 format.", + "Error parsing sparse dimensions field.", + "Token restrict value is invalid.", + "Invalid sparse embedding.", + "Invalid dense embedding." + ] + }, + "sourceGcsUri": { + "description": "Cloud Storage URI pointing to the original file in user's bucket.", + "type": "string" + }, + "embeddingId": { + "description": "Empty if the embedding id is failed to parse.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadataRecordError", + "type": "object" + }, + "GoogleCloudAiplatformV1NotebookExecutionJobGcsNotebookSource": { + "description": "The Cloud Storage uri for the input notebook.", + "id": "GoogleCloudAiplatformV1NotebookExecutionJobGcsNotebookSource", + "type": "object", + "properties": { + "uri": { + "description": "The Cloud Storage uri pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`", + "type": "string" + }, + "generation": { + "type": "string", + "description": "The version of the Cloud Storage object to read. If unset, the current version of the object is read. See https://cloud.google.com/storage/docs/metadata#generation-number." + } + } + }, + "GoogleCloudAiplatformV1ExportFeatureValuesRequestFullExport": { + "properties": { + "startTime": { + "type": "string", + "description": "Excludes Feature values with feature generation timestamp before this timestamp. If not set, retrieve oldest values kept in Feature Store. Timestamp, if present, must not have higher than millisecond precision.", + "format": "google-datetime" + }, + "endTime": { + "type": "string", + "description": "Exports Feature values as of this timestamp. If not set, retrieve values as of now. Timestamp, if present, must not have higher than millisecond precision.", + "format": "google-datetime" + } + }, + "id": "GoogleCloudAiplatformV1ExportFeatureValuesRequestFullExport", + "type": "object", + "description": "Describes exporting all historical Feature values of all entities of the EntityType between [start_time, end_time]." + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoActionMetricsConfidenceMetrics": { + "type": "object", + "properties": { + "precision": { + "type": "number", + "description": "Output only. Precision for the given confidence threshold.", + "format": "float" + }, + "recall": { + "format": "float", + "type": "number", + "description": "Output only. Recall for the given confidence threshold." + }, + "f1Score": { + "format": "float", + "description": "Output only. The harmonic mean of recall and precision.", + "type": "number" + }, + "confidenceThreshold": { + "format": "float", + "description": "Output only. The confidence threshold value used to compute the metrics.", + "type": "number" + } + }, + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoActionMetricsConfidenceMetrics", + "description": "Metrics for a single confidence threshold." + }, + "GoogleCloudAiplatformV1GenieSource": { + "type": "object", + "description": "Contains information about the source of the models generated from Generative AI Studio.", + "id": "GoogleCloudAiplatformV1GenieSource", + "properties": { + "baseModelUri": { + "type": "string", + "description": "Required. The public base model URI." + } + } + }, + "GoogleCloudAiplatformV1EvaluatedAnnotationExplanation": { + "properties": { + "explanationType": { + "description": "Explanation type. For AutoML Image Classification models, possible values are: * `image-integrated-gradients` * `image-xrai`", + "type": "string" + }, + "explanation": { + "description": "Explanation attribution response details.", + "$ref": "GoogleCloudAiplatformV1Explanation" + } + }, + "type": "object", + "description": "Explanation result of the prediction produced by the Model.", + "id": "GoogleCloudAiplatformV1EvaluatedAnnotationExplanation" + }, + "GoogleCloudAiplatformV1TrialParameter": { + "properties": { + "value": { + "description": "Output only. The value of the parameter. `number_value` will be set if a parameter defined in StudySpec is in type 'INTEGER', 'DOUBLE' or 'DISCRETE'. `string_value` will be set if a parameter defined in StudySpec is in type 'CATEGORICAL'.", + "type": "any", + "readOnly": true + }, + "parameterId": { + "type": "string", + "description": "Output only. The ID of the parameter. The parameter should be defined in StudySpec's Parameters.", + "readOnly": true + } + }, + "description": "A message representing a parameter to be tuned.", + "type": "object", + "id": "GoogleCloudAiplatformV1TrialParameter" + }, + "GoogleCloudAiplatformV1ExplanationMetadataOverride": { + "description": "The ExplanationMetadata entries that can be overridden at online explanation time.", + "type": "object", + "id": "GoogleCloudAiplatformV1ExplanationMetadataOverride", + "properties": { + "inputs": { + "type": "object", + "description": "Required. Overrides the input metadata of the features. The key is the name of the feature to be overridden. The keys specified here must exist in the input metadata to be overridden. If a feature is not specified here, the corresponding feature's input metadata is not overridden.", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1ExplanationMetadataOverrideInputMetadataOverride" + } + } + } + }, + "GoogleCloudAiplatformV1EnvVar": { + "type": "object", + "description": "Represents an environment variable present in a Container or Python Module.", + "properties": { + "name": { + "type": "string", + "description": "Required. Name of the environment variable. Must be a valid C identifier." + }, + "value": { + "description": "Required. Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1EnvVar" + }, + "GoogleCloudAiplatformV1SchemaTablesDatasetMetadata": { + "description": "The metadata of Datasets that contain tables data.", + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTablesDatasetMetadata", + "properties": { + "inputConfig": { + "$ref": "GoogleCloudAiplatformV1SchemaTablesDatasetMetadataInputConfig" + } + } + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationAutoTransformation": { + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationAutoTransformation", + "description": "Training pipeline will infer the proper transformation based on the statistic of dataset.", + "properties": { + "columnName": { + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1BatchImportModelEvaluationSlicesRequest": { + "description": "Request message for ModelService.BatchImportModelEvaluationSlices", + "id": "GoogleCloudAiplatformV1BatchImportModelEvaluationSlicesRequest", + "properties": { + "modelEvaluationSlices": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1ModelEvaluationSlice" + }, + "description": "Required. Model evaluation slice resource to be imported." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1DeleteFeatureValuesOperationMetadata": { + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "Operation metadata for Featurestore delete Features values." + } + }, + "id": "GoogleCloudAiplatformV1DeleteFeatureValuesOperationMetadata", + "type": "object", + "description": "Details of operations that delete Feature values." + }, + "GoogleCloudAiplatformV1ReadTensorboardTimeSeriesDataResponse": { + "properties": { + "timeSeriesData": { + "$ref": "GoogleCloudAiplatformV1TimeSeriesData", + "description": "The returned time series data." + } + }, + "id": "GoogleCloudAiplatformV1ReadTensorboardTimeSeriesDataResponse", + "type": "object", + "description": "Response message for TensorboardService.ReadTensorboardTimeSeriesData." + }, + "GoogleCloudAiplatformV1CoherenceSpec": { + "type": "object", + "id": "GoogleCloudAiplatformV1CoherenceSpec", + "properties": { + "version": { + "description": "Optional. Which version to use for evaluation.", + "format": "int32", + "type": "integer" + } + }, + "description": "Spec for coherence score metric." + }, + "GoogleCloudAiplatformV1UpdateExplanationDatasetResponse": { + "description": "Response message of ModelService.UpdateExplanationDataset operation.", + "properties": {}, + "type": "object", + "id": "GoogleCloudAiplatformV1UpdateExplanationDatasetResponse" + }, + "GoogleCloudAiplatformV1MutateDeployedModelResponse": { + "type": "object", + "description": "Response message for EndpointService.MutateDeployedModel.", + "properties": { + "deployedModel": { + "description": "The DeployedModel that's being mutated.", + "$ref": "GoogleCloudAiplatformV1DeployedModel" + } + }, + "id": "GoogleCloudAiplatformV1MutateDeployedModelResponse" + }, + "GoogleCloudAiplatformV1FindNeighborsResponseNeighbor": { + "properties": { + "datapoint": { + "$ref": "GoogleCloudAiplatformV1IndexDatapoint", + "description": "The datapoint of the neighbor. Note that full datapoints are returned only when \"return_full_datapoint\" is set to true. Otherwise, only the \"datapoint_id\" and \"crowding_tag\" fields are populated." + }, + "distance": { + "description": "The distance between the neighbor and the dense embedding query.", + "format": "double", + "type": "number" + }, + "sparseDistance": { + "type": "number", + "format": "double", + "description": "The distance between the neighbor and the query sparse_embedding." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1FindNeighborsResponseNeighbor", + "description": "A neighbor of the query vector." + }, + "CloudAiLargeModelsVisionSemanticFilterResponse": { + "id": "CloudAiLargeModelsVisionSemanticFilterResponse", + "properties": { + "passedSemanticFilter": { + "type": "boolean", + "description": "This response is added when semantic filter config is turned on in EditConfig. It reports if this image is passed semantic filter response. If passed_semantic_filter is false, the bounding box information will be populated for user to check what caused the semantic filter to fail." + }, + "namedBoundingBoxes": { + "items": { + "$ref": "CloudAiLargeModelsVisionNamedBoundingBox" + }, + "description": "Class labels of the bounding boxes that failed the semantic filtering. Bounding box coordinates.", + "type": "array" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1ExplanationParameters": { + "description": "Parameters to configure explaining for Model's predictions.", + "properties": { + "topK": { + "type": "integer", + "format": "int32", + "description": "If populated, returns attributions for top K indices of outputs (defaults to 1). Only applies to Models that predicts more than one outputs (e,g, multi-class Models). When set to -1, returns explanations for all outputs." + }, + "examples": { + "$ref": "GoogleCloudAiplatformV1Examples", + "description": "Example-based explanations that returns the nearest neighbors from the provided dataset." + }, + "integratedGradientsAttribution": { + "$ref": "GoogleCloudAiplatformV1IntegratedGradientsAttribution", + "description": "An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365" + }, + "sampledShapleyAttribution": { + "$ref": "GoogleCloudAiplatformV1SampledShapleyAttribution", + "description": "An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features. Refer to this paper for model details: https://arxiv.org/abs/1306.4265." + }, + "xraiAttribution": { + "description": "An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 XRAI currently performs better on natural images, like a picture of a house or an animal. If the images are taken in artificial environments, like a lab or manufacturing line, or from diagnostic equipment, like x-rays or quality-control cameras, use Integrated Gradients instead.", + "$ref": "GoogleCloudAiplatformV1XraiAttribution" + }, + "outputIndices": { + "type": "array", + "items": { + "type": "any" + }, + "description": "If populated, only returns attributions that have output_index contained in output_indices. It must be an ndarray of integers, with the same shape of the output it's explaining. If not populated, returns attributions for top_k indices of outputs. If neither top_k nor output_indices is populated, returns the argmax index of the outputs. Only applicable to Models that predict multiple outputs (e,g, multi-class Models that predict multiple classes)." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1ExplanationParameters" + }, + "GoogleCloudAiplatformV1MigrateResourceRequestMigrateDataLabelingDatasetConfigMigrateDataLabelingAnnotatedDatasetConfig": { + "type": "object", + "id": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateDataLabelingDatasetConfigMigrateDataLabelingAnnotatedDatasetConfig", + "properties": { + "annotatedDataset": { + "type": "string", + "description": "Required. Full resource name of data labeling AnnotatedDataset. Format: `projects/{project}/datasets/{dataset}/annotatedDatasets/{annotated_dataset}`." + } + }, + "description": "Config for migrating AnnotatedDataset in datalabeling.googleapis.com to Vertex AI's SavedQuery." + }, + "GoogleCloudAiplatformV1SpecialistPool": { + "id": "GoogleCloudAiplatformV1SpecialistPool", + "description": "SpecialistPool represents customers' own workforce to work on their data labeling jobs. It includes a group of specialist managers and workers. Managers are responsible for managing the workers in this pool as well as customers' data labeling jobs associated with this pool. Customers create specialist pool as well as start data labeling jobs on Cloud, managers and workers handle the jobs using CrowdCompute console.", + "type": "object", + "properties": { + "specialistManagerEmails": { + "items": { + "type": "string" + }, + "description": "The email addresses of the managers in the SpecialistPool.", + "type": "array" + }, + "specialistWorkerEmails": { + "items": { + "type": "string" + }, + "description": "The email addresses of workers in the SpecialistPool.", + "type": "array" + }, + "displayName": { + "description": "Required. The user-defined name of the SpecialistPool. The name can be up to 128 characters long and can consist of any UTF-8 characters. This field should be unique on project-level.", + "type": "string" + }, + "pendingDataLabelingJobs": { + "type": "array", + "readOnly": true, + "description": "Output only. The resource name of the pending data labeling jobs.", + "items": { + "type": "string" + } + }, + "name": { + "type": "string", + "description": "Required. The resource name of the SpecialistPool." + }, + "specialistManagersCount": { + "readOnly": true, + "description": "Output only. The number of managers in this SpecialistPool.", + "format": "int32", + "type": "integer" + } + } + }, + "GoogleTypeDate": { + "id": "GoogleTypeDate", + "type": "object", + "properties": { + "month": { + "format": "int32", + "type": "integer", + "description": "Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day." + }, + "year": { + "description": "Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.", + "type": "integer", + "format": "int32" + }, + "day": { + "type": "integer", + "description": "Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn't significant.", + "format": "int32" + } + }, + "description": "Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values. * A month and day, with a zero year (for example, an anniversary). * A year on its own, with a zero month and a zero day. * A year and month, with a zero day (for example, a credit card expiration date). Related types: * google.type.TimeOfDay * google.type.DateTime * google.protobuf.Timestamp" + }, + "GoogleCloudAiplatformV1FeatureView": { + "id": "GoogleCloudAiplatformV1FeatureView", + "description": "FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig.", + "properties": { + "updateTime": { + "description": "Output only. Timestamp when this FeatureView was last updated.", + "format": "google-datetime", + "type": "string", + "readOnly": true + }, + "syncConfig": { + "$ref": "GoogleCloudAiplatformV1FeatureViewSyncConfig", + "description": "Configures when data is to be synced/updated for this FeatureView. At the end of the sync the latest featureValues for each entityId of this FeatureView are made ready for online serving." + }, + "labels": { + "type": "object", + "additionalProperties": { + "type": "string" + }, + "description": "Optional. The labels with user-defined metadata to organize your FeatureViews. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." + }, + "createTime": { + "format": "google-datetime", + "type": "string", + "readOnly": true, + "description": "Output only. Timestamp when this FeatureView was created." + }, + "bigQuerySource": { + "description": "Optional. Configures how data is supposed to be extracted from a BigQuery source to be loaded onto the FeatureOnlineStore.", + "$ref": "GoogleCloudAiplatformV1FeatureViewBigQuerySource" + }, + "featureRegistrySource": { + "$ref": "GoogleCloudAiplatformV1FeatureViewFeatureRegistrySource", + "description": "Optional. Configures the features from a Feature Registry source that need to be loaded onto the FeatureOnlineStore." + }, + "indexConfig": { + "$ref": "GoogleCloudAiplatformV1FeatureViewIndexConfig", + "description": "Optional. Configuration for index preparation for vector search. It contains the required configurations to create an index from source data, so that approximate nearest neighbor (a.k.a ANN) algorithms search can be performed during online serving." + }, + "name": { + "description": "Identifier. Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`", + "type": "string" + }, + "etag": { + "type": "string", + "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1ExportTensorboardTimeSeriesDataResponse": { + "id": "GoogleCloudAiplatformV1ExportTensorboardTimeSeriesDataResponse", + "description": "Response message for TensorboardService.ExportTensorboardTimeSeriesData.", + "properties": { + "timeSeriesDataPoints": { + "items": { + "$ref": "GoogleCloudAiplatformV1TimeSeriesDataPoint" + }, + "description": "The returned time series data points.", + "type": "array" + }, + "nextPageToken": { + "description": "A token, which can be sent as page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsGeneralTextGenerationEvaluationMetrics": { + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsGeneralTextGenerationEvaluationMetrics", + "type": "object", + "properties": { + "bleu": { + "format": "float", + "description": "BLEU (bilingual evaluation understudy) scores based on sacrebleu implementation.", + "type": "number" + }, + "rougeLSum": { + "description": "ROUGE-L (Longest Common Subsequence) scoring at summary level.", + "format": "float", + "type": "number" + } + } + }, + "GoogleCloudAiplatformV1ListPersistentResourcesResponse": { + "id": "GoogleCloudAiplatformV1ListPersistentResourcesResponse", + "description": "Response message for PersistentResourceService.ListPersistentResources", + "type": "object", + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token to retrieve next page of results. Pass to ListPersistentResourcesRequest.page_token to obtain that page." + }, + "persistentResources": { + "items": { + "$ref": "GoogleCloudAiplatformV1PersistentResource" + }, + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1WriteFeatureValuesResponse": { + "properties": {}, + "id": "GoogleCloudAiplatformV1WriteFeatureValuesResponse", + "description": "Response message for FeaturestoreOnlineServingService.WriteFeatureValues.", + "type": "object" + }, + "GoogleCloudAiplatformV1MergeVersionAliasesRequest": { + "description": "Request message for ModelService.MergeVersionAliases.", + "type": "object", + "id": "GoogleCloudAiplatformV1MergeVersionAliasesRequest", + "properties": { + "versionAliases": { + "description": "Required. The set of version aliases to merge. The alias should be at most 128 characters, and match `a-z{0,126}[a-z-0-9]`. Add the `-` prefix to an alias means removing that alias from the version. `-` is NOT counted in the 128 characters. Example: `-golden` means removing the `golden` alias from the version. There is NO ordering in aliases, which means 1) The aliases returned from GetModel API might not have the exactly same order from this MergeVersionAliases API. 2) Adding and deleting the same alias in the request is not recommended, and the 2 operations will be cancelled out.", + "items": { + "type": "string" + }, + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsQuestionAnsweringEvaluationMetrics": { + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsQuestionAnsweringEvaluationMetrics", + "type": "object", + "properties": { + "exactMatch": { + "type": "number", + "format": "float", + "description": "The rate at which the input predicted strings exactly match their references." + } + } + }, + "GoogleCloudAiplatformV1FulfillmentInput": { + "properties": { + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1FulfillmentSpec", + "description": "Required. Spec for fulfillment score metric." + }, + "instance": { + "description": "Required. Fulfillment instance.", + "$ref": "GoogleCloudAiplatformV1FulfillmentInstance" + } + }, + "type": "object", + "description": "Input for fulfillment metric.", + "id": "GoogleCloudAiplatformV1FulfillmentInput" + }, + "GoogleCloudAiplatformV1PairwiseSummarizationQualityResult": { + "type": "object", + "id": "GoogleCloudAiplatformV1PairwiseSummarizationQualityResult", + "properties": { + "pairwiseChoice": { + "type": "string", + "enumDescriptions": [ + "Unspecified prediction choice.", + "Baseline prediction wins", + "Candidate prediction wins", + "Winner cannot be determined" + ], + "readOnly": true, + "description": "Output only. Pairwise summarization prediction choice.", + "enum": [ + "PAIRWISE_CHOICE_UNSPECIFIED", + "BASELINE", + "CANDIDATE", + "TIE" + ] + }, + "explanation": { + "description": "Output only. Explanation for summarization quality score.", + "type": "string", + "readOnly": true + }, + "confidence": { + "format": "float", + "type": "number", + "readOnly": true, + "description": "Output only. Confidence for summarization quality score." + } + }, + "description": "Spec for pairwise summarization quality result." + }, + "GoogleCloudAiplatformV1FeatureOnlineStoreOptimized": { + "properties": {}, + "description": "Optimized storage type", + "id": "GoogleCloudAiplatformV1FeatureOnlineStoreOptimized", + "type": "object" + }, + "GoogleCloudAiplatformV1SafetyResult": { + "id": "GoogleCloudAiplatformV1SafetyResult", + "description": "Spec for safety result.", + "properties": { + "score": { + "type": "number", + "format": "float", + "readOnly": true, + "description": "Output only. Safety score." + }, + "explanation": { + "description": "Output only. Explanation for safety score.", + "readOnly": true, + "type": "string" + }, + "confidence": { + "type": "number", + "format": "float", + "description": "Output only. Confidence for safety score.", + "readOnly": true + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaVideoActionRecognitionAnnotation": { + "id": "GoogleCloudAiplatformV1SchemaVideoActionRecognitionAnnotation", + "type": "object", + "description": "Annotation details specific to video action recognition.", + "properties": { + "timeSegment": { + "description": "This Annotation applies to the time period represented by the TimeSegment. If it's not set, the Annotation applies to the whole video.", + "$ref": "GoogleCloudAiplatformV1SchemaTimeSegment" + }, + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that this Annotation pertains to." + }, + "annotationSpecId": { + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1ListModelEvaluationSlicesResponse": { + "id": "GoogleCloudAiplatformV1ListModelEvaluationSlicesResponse", + "properties": { + "nextPageToken": { + "description": "A token to retrieve next page of results. Pass to ListModelEvaluationSlicesRequest.page_token to obtain that page.", + "type": "string" + }, + "modelEvaluationSlices": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1ModelEvaluationSlice" + }, + "description": "List of ModelEvaluations in the requested page." + } + }, + "description": "Response message for ModelService.ListModelEvaluationSlices.", + "type": "object" + }, + "GoogleCloudAiplatformV1GenerateContentResponseUsageMetadata": { + "properties": { + "candidatesTokenCount": { + "description": "Number of tokens in the response(s).", + "type": "integer", + "format": "int32" + }, + "promptTokenCount": { + "format": "int32", + "description": "Number of tokens in the request.", + "type": "integer" + }, + "totalTokenCount": { + "type": "integer", + "format": "int32" + } + }, + "id": "GoogleCloudAiplatformV1GenerateContentResponseUsageMetadata", + "description": "Usage metadata about response(s).", + "type": "object" + }, + "GoogleCloudAiplatformV1DeployIndexOperationMetadata": { + "type": "object", + "properties": { + "deployedIndexId": { + "description": "The unique index id specified by user", + "type": "string" + }, + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + }, + "id": "GoogleCloudAiplatformV1DeployIndexOperationMetadata", + "description": "Runtime operation information for IndexEndpointService.DeployIndex." + }, + "GoogleCloudAiplatformV1ExportFeatureValuesResponse": { + "properties": {}, + "description": "Response message for FeaturestoreService.ExportFeatureValues.", + "type": "object", + "id": "GoogleCloudAiplatformV1ExportFeatureValuesResponse" + }, + "GoogleCloudAiplatformV1PairwiseSummarizationQualitySpec": { + "id": "GoogleCloudAiplatformV1PairwiseSummarizationQualitySpec", + "type": "object", + "description": "Spec for pairwise summarization quality score metric.", + "properties": { + "version": { + "type": "integer", + "description": "Optional. Which version to use for evaluation.", + "format": "int32" + }, + "useReference": { + "type": "boolean", + "description": "Optional. Whether to use instance.reference to compute pairwise summarization quality." + } + } + }, + "GoogleCloudAiplatformV1CheckTrialEarlyStoppingStateRequest": { + "properties": {}, + "type": "object", + "id": "GoogleCloudAiplatformV1CheckTrialEarlyStoppingStateRequest", + "description": "Request message for VizierService.CheckTrialEarlyStoppingState." + }, + "GoogleCloudAiplatformV1GroundingChunk": { + "description": "Grounding chunk.", + "type": "object", + "properties": { + "web": { + "$ref": "GoogleCloudAiplatformV1GroundingChunkWeb", + "description": "Grounding chunk from the web." + }, + "retrievedContext": { + "description": "Grounding chunk from context retrieved by the retrieval tools.", + "$ref": "GoogleCloudAiplatformV1GroundingChunkRetrievedContext" + } + }, + "id": "GoogleCloudAiplatformV1GroundingChunk" + }, + "GoogleCloudAiplatformV1ListDatasetsResponse": { + "id": "GoogleCloudAiplatformV1ListDatasetsResponse", + "description": "Response message for DatasetService.ListDatasets.", + "type": "object", + "properties": { + "nextPageToken": { + "type": "string", + "description": "The standard List next-page token." + }, + "datasets": { + "items": { + "$ref": "GoogleCloudAiplatformV1Dataset" + }, + "description": "A list of Datasets that matches the specified filter in the request.", + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1TrialContext": { + "id": "GoogleCloudAiplatformV1TrialContext", + "type": "object", + "description": "Next ID: 3", + "properties": { + "parameters": { + "type": "array", + "description": "If/when a Trial is generated or selected from this Context, its Parameters will match any parameters specified here. (I.e. if this context specifies parameter name:'a' int_value:3, then a resulting Trial will have int_value:3 for its parameter named 'a'.) Note that we first attempt to match existing REQUESTED Trials with contexts, and if there are no matches, we generate suggestions in the subspace defined by the parameters specified here. NOTE: a Context without any Parameters matches the entire feasible search space.", + "items": { + "$ref": "GoogleCloudAiplatformV1TrialParameter" + } + }, + "description": { + "description": "A human-readable field which can store a description of this context. This will become part of the resulting Trial's description field.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1ListHyperparameterTuningJobsResponse": { + "id": "GoogleCloudAiplatformV1ListHyperparameterTuningJobsResponse", + "type": "object", + "properties": { + "hyperparameterTuningJobs": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1HyperparameterTuningJob" + }, + "description": "List of HyperparameterTuningJobs in the requested page. HyperparameterTuningJob.trials of the jobs will be not be returned." + }, + "nextPageToken": { + "type": "string", + "description": "A token to retrieve the next page of results. Pass to ListHyperparameterTuningJobsRequest.page_token to obtain that page." + } + }, + "description": "Response message for JobService.ListHyperparameterTuningJobs" + }, + "GoogleCloudAiplatformV1CustomJob": { + "description": "Represents a job that runs custom workloads such as a Docker container or a Python package. A CustomJob can have multiple worker pools and each worker pool can have its own machine and input spec. A CustomJob will be cleaned up once the job enters terminal state (failed or succeeded).", + "type": "object", + "properties": { + "state": { + "type": "string", + "enum": [ + "JOB_STATE_UNSPECIFIED", + "JOB_STATE_QUEUED", + "JOB_STATE_PENDING", + "JOB_STATE_RUNNING", + "JOB_STATE_SUCCEEDED", + "JOB_STATE_FAILED", + "JOB_STATE_CANCELLING", + "JOB_STATE_CANCELLED", + "JOB_STATE_PAUSED", + "JOB_STATE_EXPIRED", + "JOB_STATE_UPDATING", + "JOB_STATE_PARTIALLY_SUCCEEDED" + ], + "readOnly": true, + "enumDescriptions": [ + "The job state is unspecified.", + "The job has been just created or resumed and processing has not yet begun.", + "The service is preparing to run the job.", + "The job is in progress.", + "The job completed successfully.", + "The job failed.", + "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "The job has been cancelled.", + "The job has been stopped, and can be resumed.", + "The job has expired.", + "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", + "The job is partially succeeded, some results may be missing due to errors." + ], + "description": "Output only. The detailed state of the job." + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1EncryptionSpec", + "description": "Customer-managed encryption key options for a CustomJob. If this is set, then all resources created by the CustomJob will be encrypted with the provided encryption key." + }, + "webAccessUris": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "Output only. URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) (one URI for each training node). Only available if job_spec.enable_web_access is `true`. The keys are names of each node in the training job; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell.", + "readOnly": true + }, + "labels": { + "description": "The labels with user-defined metadata to organize CustomJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", + "additionalProperties": { + "type": "string" + }, + "type": "object" + }, + "updateTime": { + "type": "string", + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Time when the CustomJob was most recently updated." + }, + "jobSpec": { + "$ref": "GoogleCloudAiplatformV1CustomJobSpec", + "description": "Required. Job spec." + }, + "startTime": { + "readOnly": true, + "type": "string", + "description": "Output only. Time when the CustomJob for the first time entered the `JOB_STATE_RUNNING` state.", + "format": "google-datetime" + }, + "displayName": { + "description": "Required. The display name of the CustomJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + }, + "error": { + "$ref": "GoogleRpcStatus", + "description": "Output only. Only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "readOnly": true + }, + "createTime": { + "description": "Output only. Time when the CustomJob was created.", + "format": "google-datetime", + "readOnly": true, + "type": "string" + }, + "endTime": { + "type": "string", + "format": "google-datetime", + "description": "Output only. Time when the CustomJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.", + "readOnly": true + }, + "name": { + "description": "Output only. Resource name of a CustomJob.", + "readOnly": true, + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1CustomJob" + }, + "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessInput": { + "properties": { + "instance": { + "$ref": "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessInstance", + "description": "Required. Question answering correctness instance." + }, + "metricSpec": { + "description": "Required. Spec for question answering correctness score metric.", + "$ref": "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessSpec" + } + }, + "type": "object", + "description": "Input for question answering correctness metric.", + "id": "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessInput" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageSegmentation": { + "type": "object", + "properties": { + "inputs": { + "description": "The input parameters of this TrainingJob.", + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageSegmentationInputs" + }, + "metadata": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageSegmentationMetadata", + "description": "The metadata information." + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageSegmentation", + "description": "A TrainingJob that trains and uploads an AutoML Image Segmentation Model." + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics": { + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics", + "properties": { + "falsePositiveRateAt1": { + "type": "number", + "format": "float", + "description": "The False Positive Rate when only considering the label that has the highest prediction score and not below the confidence threshold for each DataItem." + }, + "recallAt1": { + "format": "float", + "type": "number", + "description": "The Recall (True Positive Rate) when only considering the label that has the highest prediction score and not below the confidence threshold for each DataItem." + }, + "precision": { + "description": "Precision for the given confidence threshold.", + "type": "number", + "format": "float" + }, + "f1ScoreAt1": { + "description": "The harmonic mean of recallAt1 and precisionAt1.", + "format": "float", + "type": "number" + }, + "confidenceThreshold": { + "format": "float", + "description": "Metrics are computed with an assumption that the Model never returns predictions with score lower than this value.", + "type": "number" + }, + "falsePositiveRate": { + "format": "float", + "type": "number", + "description": "False Positive Rate for the given confidence threshold." + }, + "precisionAt1": { + "format": "float", + "type": "number", + "description": "The precision when only considering the label that has the highest prediction score and not below the confidence threshold for each DataItem." + }, + "maxPredictions": { + "type": "integer", + "format": "int32", + "description": "Metrics are computed with an assumption that the Model always returns at most this many predictions (ordered by their score, descendingly), but they all still need to meet the `confidenceThreshold`." + }, + "confusionMatrix": { + "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix", + "description": "Confusion matrix of the evaluation for this confidence_threshold." + }, + "falsePositiveCount": { + "type": "string", + "format": "int64", + "description": "The number of Model created labels that do not match a ground truth label." + }, + "trueNegativeCount": { + "type": "string", + "description": "The number of labels that were not created by the Model, but if they would, they would not match a ground truth label.", + "format": "int64" + }, + "truePositiveCount": { + "description": "The number of Model created labels that match a ground truth label.", + "format": "int64", + "type": "string" + }, + "f1Score": { + "format": "float", + "type": "number", + "description": "The harmonic mean of recall and precision. For summary metrics, it computes the micro-averaged F1 score." + }, + "f1ScoreMicro": { + "type": "number", + "format": "float", + "description": "Micro-averaged F1 Score." + }, + "falseNegativeCount": { + "description": "The number of ground truth labels that are not matched by a Model created label.", + "format": "int64", + "type": "string" + }, + "f1ScoreMacro": { + "description": "Macro-averaged F1 Score.", + "type": "number", + "format": "float" + }, + "recall": { + "description": "Recall (True Positive Rate) for the given confidence threshold.", + "type": "number", + "format": "float" + } + } + }, + "GoogleCloudAiplatformV1BleuMetricValue": { + "type": "object", + "properties": { + "score": { + "type": "number", + "description": "Output only. Bleu score.", + "readOnly": true, + "format": "float" + } + }, + "id": "GoogleCloudAiplatformV1BleuMetricValue", + "description": "Bleu metric value for an instance." + }, + "GoogleCloudAiplatformV1ExportFractionSplit": { + "id": "GoogleCloudAiplatformV1ExportFractionSplit", + "type": "object", + "properties": { + "testFraction": { + "format": "double", + "description": "The fraction of the input data that is to be used to evaluate the Model.", + "type": "number" + }, + "validationFraction": { + "description": "The fraction of the input data that is to be used to validate the Model.", + "format": "double", + "type": "number" + }, + "trainingFraction": { + "type": "number", + "description": "The fraction of the input data that is to be used to train the Model.", + "format": "double" + } + }, + "description": "Assigns the input data to training, validation, and test sets as per the given fractions. Any of `training_fraction`, `validation_fraction` and `test_fraction` may optionally be provided, they must sum to up to 1. If the provided ones sum to less than 1, the remainder is assigned to sets as decided by Vertex AI. If none of the fractions are set, by default roughly 80% of data is used for training, 10% for validation, and 10% for test." + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTextTransformation": { + "properties": { + "columnName": { + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTextTransformation", + "type": "object", + "description": "Training pipeline will perform following transformation functions. * The text as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index." + }, + "GoogleCloudAiplatformV1TimeSeriesData": { + "properties": { + "tensorboardTimeSeriesId": { + "type": "string", + "description": "Required. The ID of the TensorboardTimeSeries, which will become the final component of the TensorboardTimeSeries' resource name" + }, + "values": { + "type": "array", + "description": "Required. Data points in this time series.", + "items": { + "$ref": "GoogleCloudAiplatformV1TimeSeriesDataPoint" + } + }, + "valueType": { + "enumDescriptions": [ + "The value type is unspecified.", + "Used for TensorboardTimeSeries that is a list of scalars. E.g. accuracy of a model over epochs/time.", + "Used for TensorboardTimeSeries that is a list of tensors. E.g. histograms of weights of layer in a model over epoch/time.", + "Used for TensorboardTimeSeries that is a list of blob sequences. E.g. set of sample images with labels over epochs/time." + ], + "description": "Required. Immutable. The value type of this time series. All the values in this time series data must match this value type.", + "enum": [ + "VALUE_TYPE_UNSPECIFIED", + "SCALAR", + "TENSOR", + "BLOB_SEQUENCE" + ], + "type": "string" + } + }, + "description": "All the data stored in a TensorboardTimeSeries.", + "type": "object", + "id": "GoogleCloudAiplatformV1TimeSeriesData" + }, + "GoogleCloudAiplatformV1Execution": { + "properties": { + "description": { + "description": "Description of the Execution", + "type": "string" + }, + "labels": { + "type": "object", + "description": "The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded).", + "additionalProperties": { + "type": "string" + } + }, + "schemaVersion": { + "description": "The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.", + "type": "string" + }, + "metadata": { + "additionalProperties": { + "type": "any", + "description": "Properties of the object." + }, + "description": "Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.", + "type": "object" + }, + "etag": { + "type": "string", + "description": "An eTag used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + }, + "updateTime": { + "description": "Output only. Timestamp when this Execution was last updated.", + "readOnly": true, + "format": "google-datetime", + "type": "string" + }, + "createTime": { + "description": "Output only. Timestamp when this Execution was created.", + "format": "google-datetime", + "readOnly": true, + "type": "string" + }, + "state": { + "enum": [ + "STATE_UNSPECIFIED", + "NEW", + "RUNNING", + "COMPLETE", + "FAILED", + "CACHED", + "CANCELLED" + ], + "description": "The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.", + "enumDescriptions": [ + "Unspecified Execution state", + "The Execution is new", + "The Execution is running", + "The Execution has finished running", + "The Execution has failed", + "The Execution completed through Cache hit.", + "The Execution was cancelled." + ], + "type": "string" + }, + "name": { + "description": "Output only. The resource name of the Execution.", + "type": "string", + "readOnly": true + }, + "schemaTitle": { + "type": "string", + "description": "The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store." + }, + "displayName": { + "type": "string", + "description": "User provided display name of the Execution. May be up to 128 Unicode characters." + } + }, + "id": "GoogleCloudAiplatformV1Execution", + "type": "object", + "description": "Instance of a general execution." + }, + "GoogleCloudAiplatformV1SummarizationHelpfulnessInstance": { + "properties": { + "context": { + "type": "string", + "description": "Required. Text to be summarized." + }, + "instruction": { + "description": "Optional. Summarization prompt for LLM.", + "type": "string" + }, + "reference": { + "description": "Optional. Ground truth used to compare against the prediction.", + "type": "string" + }, + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + } + }, + "description": "Spec for summarization helpfulness instance.", + "type": "object", + "id": "GoogleCloudAiplatformV1SummarizationHelpfulnessInstance" + }, + "GoogleCloudAiplatformV1ExportFeatureValuesOperationMetadata": { + "id": "GoogleCloudAiplatformV1ExportFeatureValuesOperationMetadata", + "properties": { + "genericMetadata": { + "description": "Operation metadata for Featurestore export Feature values.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + }, + "type": "object", + "description": "Details of operations that exports Features values." + }, + "GoogleCloudAiplatformV1SummarizationQualityInstance": { + "description": "Spec for summarization quality instance.", + "properties": { + "reference": { + "type": "string", + "description": "Optional. Ground truth used to compare against the prediction." + }, + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + }, + "instruction": { + "type": "string", + "description": "Required. Summarization prompt for LLM." + }, + "context": { + "type": "string", + "description": "Required. Text to be summarized." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SummarizationQualityInstance" + }, + "GoogleCloudAiplatformV1FulfillmentResult": { + "description": "Spec for fulfillment result.", + "id": "GoogleCloudAiplatformV1FulfillmentResult", + "properties": { + "score": { + "type": "number", + "description": "Output only. Fulfillment score.", + "format": "float", + "readOnly": true + }, + "confidence": { + "format": "float", + "readOnly": true, + "type": "number", + "description": "Output only. Confidence for fulfillment score." + }, + "explanation": { + "readOnly": true, + "description": "Output only. Explanation for fulfillment score.", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1StringArray": { + "description": "A list of string values.", + "id": "GoogleCloudAiplatformV1StringArray", + "type": "object", + "properties": { + "values": { + "description": "A list of string values.", + "items": { + "type": "string" + }, + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1IndexDatapoint": { + "description": "A datapoint of Index.", + "properties": { + "sparseEmbedding": { + "description": "Optional. Feature embedding vector for sparse index.", + "$ref": "GoogleCloudAiplatformV1IndexDatapointSparseEmbedding" + }, + "crowdingTag": { + "$ref": "GoogleCloudAiplatformV1IndexDatapointCrowdingTag", + "description": "Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query." + }, + "numericRestricts": { + "description": "Optional. List of Restrict of the datapoint, used to perform \"restricted searches\" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.", + "items": { + "$ref": "GoogleCloudAiplatformV1IndexDatapointNumericRestriction" + }, + "type": "array" + }, + "datapointId": { + "type": "string", + "description": "Required. Unique identifier of the datapoint." + }, + "restricts": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1IndexDatapointRestriction" + }, + "description": "Optional. List of Restrict of the datapoint, used to perform \"restricted searches\" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering" + }, + "featureVector": { + "description": "Required. Feature embedding vector for dense index. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].", + "items": { + "format": "float", + "type": "number" + }, + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1IndexDatapoint", + "type": "object" + }, + "GoogleCloudAiplatformV1BatchImportModelEvaluationSlicesResponse": { + "properties": { + "importedModelEvaluationSlices": { + "items": { + "type": "string" + }, + "readOnly": true, + "description": "Output only. List of imported ModelEvaluationSlice.name.", + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1BatchImportModelEvaluationSlicesResponse", + "type": "object", + "description": "Response message for ModelService.BatchImportModelEvaluationSlices" + }, + "GoogleCloudAiplatformV1Schema": { + "properties": { + "minimum": { + "type": "number", + "description": "Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER Minimum value of the Type.INTEGER and Type.NUMBER", + "format": "double" + }, + "pattern": { + "type": "string", + "description": "Optional. Pattern of the Type.STRING to restrict a string to a regular expression." + }, + "nullable": { + "type": "boolean", + "description": "Optional. Indicates if the value may be null." + }, + "maxProperties": { + "type": "string", + "description": "Optional. Maximum number of the properties for Type.OBJECT.", + "format": "int64" + }, + "properties": { + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1Schema" + }, + "type": "object", + "description": "Optional. SCHEMA FIELDS FOR TYPE OBJECT Properties of Type.OBJECT." + }, + "maxItems": { + "type": "string", + "format": "int64", + "description": "Optional. Maximum number of the elements for Type.ARRAY." + }, + "items": { + "description": "Optional. SCHEMA FIELDS FOR TYPE ARRAY Schema of the elements of Type.ARRAY.", + "$ref": "GoogleCloudAiplatformV1Schema" + }, + "format": { + "type": "string", + "description": "Optional. The format of the data. Supported formats: for NUMBER type: \"float\", \"double\" for INTEGER type: \"int32\", \"int64\" for STRING type: \"email\", \"byte\", etc" + }, + "minItems": { + "format": "int64", + "description": "Optional. Minimum number of the elements for Type.ARRAY.", + "type": "string" + }, + "maximum": { + "description": "Optional. Maximum value of the Type.INTEGER and Type.NUMBER", + "type": "number", + "format": "double" + }, + "title": { + "type": "string", + "description": "Optional. The title of the Schema." + }, + "type": { + "type": "string", + "enum": [ + "TYPE_UNSPECIFIED", + "STRING", + "NUMBER", + "INTEGER", + "BOOLEAN", + "ARRAY", + "OBJECT" + ], + "description": "Optional. The type of the data.", + "enumDescriptions": [ + "Not specified, should not be used.", + "OpenAPI string type", + "OpenAPI number type", + "OpenAPI integer type", + "OpenAPI boolean type", + "OpenAPI array type", + "OpenAPI object type" + ] + }, + "minProperties": { + "description": "Optional. Minimum number of the properties for Type.OBJECT.", + "type": "string", + "format": "int64" + }, + "maxLength": { + "description": "Optional. Maximum length of the Type.STRING", + "format": "int64", + "type": "string" + }, + "required": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Optional. Required properties of Type.OBJECT." + }, + "minLength": { + "description": "Optional. SCHEMA FIELDS FOR TYPE STRING Minimum length of the Type.STRING", + "type": "string", + "format": "int64" + }, + "enum": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Optional. Possible values of the element of Type.STRING with enum format. For example we can define an Enum Direction as : {type:STRING, format:enum, enum:[\"EAST\", NORTH\", \"SOUTH\", \"WEST\"]}" + }, + "description": { + "type": "string", + "description": "Optional. The description of the data." + }, + "default": { + "description": "Optional. Default value of the data.", + "type": "any" + }, + "example": { + "type": "any", + "description": "Optional. Example of the object. Will only populated when the object is the root." + } + }, + "description": "Schema is used to define the format of input/output data. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema). More fields may be added in the future as needed.", + "type": "object", + "id": "GoogleCloudAiplatformV1Schema" + }, + "GoogleCloudAiplatformV1Candidate": { + "properties": { + "score": { + "format": "double", + "description": "Output only. Confidence score of the candidate.", + "type": "number", + "readOnly": true + }, + "finishMessage": { + "readOnly": true, + "type": "string", + "description": "Output only. Describes the reason the mode stopped generating tokens in more detail. This is only filled when `finish_reason` is set." + }, + "citationMetadata": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1CitationMetadata", + "description": "Output only. Source attribution of the generated content." + }, + "groundingMetadata": { + "$ref": "GoogleCloudAiplatformV1GroundingMetadata", + "readOnly": true, + "description": "Output only. Metadata specifies sources used to ground generated content." + }, + "safetyRatings": { + "type": "array", + "description": "Output only. List of ratings for the safety of a response candidate. There is at most one rating per category.", + "items": { + "$ref": "GoogleCloudAiplatformV1SafetyRating" + }, + "readOnly": true + }, + "content": { + "$ref": "GoogleCloudAiplatformV1Content", + "readOnly": true, + "description": "Output only. Content parts of the candidate." + }, + "finishReason": { + "description": "Output only. The reason why the model stopped generating tokens. If empty, the model has not stopped generating the tokens.", + "readOnly": true, + "enumDescriptions": [ + "The finish reason is unspecified.", + "Natural stop point of the model or provided stop sequence.", + "The maximum number of tokens as specified in the request was reached.", + "The token generation was stopped as the response was flagged for safety reasons. NOTE: When streaming the Candidate.content will be empty if content filters blocked the output.", + "The token generation was stopped as the response was flagged for unauthorized citations.", + "All other reasons that stopped the token generation", + "The token generation was stopped as the response was flagged for the terms which are included from the terminology blocklist.", + "The token generation was stopped as the response was flagged for the prohibited contents.", + "The token generation was stopped as the response was flagged for Sensitive Personally Identifiable Information (SPII) contents.", + "The function call generated by the model is invalid." + ], + "enum": [ + "FINISH_REASON_UNSPECIFIED", + "STOP", + "MAX_TOKENS", + "SAFETY", + "RECITATION", + "OTHER", + "BLOCKLIST", + "PROHIBITED_CONTENT", + "SPII", + "MALFORMED_FUNCTION_CALL" + ], + "type": "string" + }, + "index": { + "format": "int32", + "description": "Output only. Index of the candidate.", + "type": "integer", + "readOnly": true + } + }, + "description": "A response candidate generated from the model.", + "id": "GoogleCloudAiplatformV1Candidate", + "type": "object" + }, + "GoogleCloudAiplatformV1MetadataSchema": { + "type": "object", + "description": "Instance of a general MetadataSchema.", + "id": "GoogleCloudAiplatformV1MetadataSchema", + "properties": { + "description": { + "description": "Description of the Metadata Schema", + "type": "string" + }, + "schema": { + "type": "string", + "description": "Required. The raw YAML string representation of the MetadataSchema. The combination of [MetadataSchema.version] and the schema name given by `title` in [MetadataSchema.schema] must be unique within a MetadataStore. The schema is defined as an OpenAPI 3.0.2 [MetadataSchema Object](https://github.com/OAI/OpenAPI-Specification/blob/master/versions/3.0.2.md#schemaObject)" + }, + "name": { + "readOnly": true, + "type": "string", + "description": "Output only. The resource name of the MetadataSchema." + }, + "schemaVersion": { + "description": "The version of the MetadataSchema. The version's format must match the following regular expression: `^[0-9]+.+.+$`, which would allow to order/compare different versions. Example: 1.0.0, 1.0.1, etc.", + "type": "string" + }, + "createTime": { + "readOnly": true, + "description": "Output only. Timestamp when this MetadataSchema was created.", + "format": "google-datetime", + "type": "string" + }, + "schemaType": { + "enumDescriptions": [ + "Unspecified type for the MetadataSchema.", + "A type indicating that the MetadataSchema will be used by Artifacts.", + "A typee indicating that the MetadataSchema will be used by Executions.", + "A state indicating that the MetadataSchema will be used by Contexts." + ], + "enum": [ + "METADATA_SCHEMA_TYPE_UNSPECIFIED", + "ARTIFACT_TYPE", + "EXECUTION_TYPE", + "CONTEXT_TYPE" + ], + "type": "string", + "description": "The type of the MetadataSchema. This is a property that identifies which metadata types will use the MetadataSchema." + } + } + }, + "GoogleCloudAiplatformV1UndeployIndexResponse": { + "id": "GoogleCloudAiplatformV1UndeployIndexResponse", + "type": "object", + "properties": {}, + "description": "Response message for IndexEndpointService.UndeployIndex." + }, + "GoogleTypeExpr": { + "type": "object", + "description": "Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: \"Summary size limit\" description: \"Determines if a summary is less than 100 chars\" expression: \"document.summary.size() \u003c 100\" Example (Equality): title: \"Requestor is owner\" description: \"Determines if requestor is the document owner\" expression: \"document.owner == request.auth.claims.email\" Example (Logic): title: \"Public documents\" description: \"Determine whether the document should be publicly visible\" expression: \"document.type != 'private' && document.type != 'internal'\" Example (Data Manipulation): title: \"Notification string\" description: \"Create a notification string with a timestamp.\" expression: \"'New message received at ' + string(document.create_time)\" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.", + "id": "GoogleTypeExpr", + "properties": { + "expression": { + "type": "string", + "description": "Textual representation of an expression in Common Expression Language syntax." + }, + "title": { + "type": "string", + "description": "Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression." + }, + "location": { + "description": "Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.", + "type": "string" + }, + "description": { + "description": "Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoClassificationInputs": { + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoClassificationInputs", + "properties": { + "modelType": { + "enumDescriptions": [ + "Should not be set.", + "A model best tailored to be used within Google Cloud, and which cannot be exported. Default.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as a TensorFlow or TensorFlow Lite model and used on a mobile or edge device afterwards.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) to a Jetson device afterwards." + ], + "type": "string", + "enum": [ + "MODEL_TYPE_UNSPECIFIED", + "CLOUD", + "MOBILE_VERSATILE_1", + "MOBILE_JETSON_VERSATILE_1" + ] + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1GoogleSearchRetrieval": { + "description": "Tool to retrieve public web data for grounding, powered by Google.", + "id": "GoogleCloudAiplatformV1GoogleSearchRetrieval", + "properties": {}, + "type": "object" + }, + "GoogleCloudAiplatformV1CreateDeploymentResourcePoolOperationMetadata": { + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The operation generic information." + } + }, + "description": "Runtime operation information for CreateDeploymentResourcePool method.", + "id": "GoogleCloudAiplatformV1CreateDeploymentResourcePoolOperationMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1CreateDeploymentResourcePoolRequest": { + "properties": { + "deploymentResourcePool": { + "$ref": "GoogleCloudAiplatformV1DeploymentResourcePool", + "description": "Required. The DeploymentResourcePool to create." + }, + "deploymentResourcePoolId": { + "description": "Required. The ID to use for the DeploymentResourcePool, which will become the final component of the DeploymentResourcePool's resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1CreateDeploymentResourcePoolRequest", + "description": "Request message for CreateDeploymentResourcePool method." + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingMetadata", + "properties": { + "evaluatedDataItemsBigqueryUri": { + "type": "string", + "description": "BigQuery destination uri for exported evaluated examples." + }, + "trainCostMilliNodeHours": { + "description": "Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget.", + "type": "string", + "format": "int64" + } + }, + "description": "Model metadata specific to AutoML Forecasting." + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsGranularity": { + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsGranularity", + "properties": { + "quantity": { + "type": "string", + "format": "int64", + "description": "The number of granularity_units between data points in the training data. If `granularity_unit` is `minute`, can be 1, 5, 10, 15, or 30. For all other values of `granularity_unit`, must be 1." + }, + "unit": { + "description": "The time granularity unit of this time period. The supported units are: * \"minute\" * \"hour\" * \"day\" * \"week\" * \"month\" * \"year\"", + "type": "string" + } + }, + "description": "A duration of time expressed in time granularity units." + }, + "GoogleCloudAiplatformV1BatchCancelPipelineJobsRequest": { + "type": "object", + "id": "GoogleCloudAiplatformV1BatchCancelPipelineJobsRequest", + "description": "Request message for PipelineService.BatchCancelPipelineJobs.", + "properties": { + "names": { + "items": { + "type": "string" + }, + "description": "Required. The names of the PipelineJobs to cancel. A maximum of 32 PipelineJobs can be cancelled in a batch. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipelineJob}`", + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1PairwiseSummarizationQualityInput": { + "description": "Input for pairwise summarization quality metric.", + "properties": { + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1PairwiseSummarizationQualitySpec", + "description": "Required. Spec for pairwise summarization quality score metric." + }, + "instance": { + "$ref": "GoogleCloudAiplatformV1PairwiseSummarizationQualityInstance", + "description": "Required. Pairwise summarization quality instance." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1PairwiseSummarizationQualityInput" + }, + "GoogleCloudAiplatformV1ListSchedulesResponse": { + "type": "object", + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token to retrieve the next page of results. Pass to ListSchedulesRequest.page_token to obtain that page." + }, + "schedules": { + "items": { + "$ref": "GoogleCloudAiplatformV1Schedule" + }, + "description": "List of Schedules in the requested page.", + "type": "array" + } + }, + "description": "Response message for ScheduleService.ListSchedules", + "id": "GoogleCloudAiplatformV1ListSchedulesResponse" + }, + "GoogleCloudAiplatformV1PublisherModel": { + "id": "GoogleCloudAiplatformV1PublisherModel", + "properties": { + "versionState": { + "type": "string", + "enum": [ + "VERSION_STATE_UNSPECIFIED", + "VERSION_STATE_STABLE", + "VERSION_STATE_UNSTABLE" + ], + "description": "Optional. Indicates the state of the model version.", + "enumDescriptions": [ + "The version state is unspecified.", + "Used to indicate the version is stable.", + "Used to indicate the version is unstable." + ] + }, + "openSourceCategory": { + "enum": [ + "OPEN_SOURCE_CATEGORY_UNSPECIFIED", + "PROPRIETARY", + "GOOGLE_OWNED_OSS_WITH_GOOGLE_CHECKPOINT", + "THIRD_PARTY_OWNED_OSS_WITH_GOOGLE_CHECKPOINT", + "GOOGLE_OWNED_OSS", + "THIRD_PARTY_OWNED_OSS" + ], + "description": "Required. Indicates the open source category of the publisher model.", + "type": "string", + "enumDescriptions": [ + "The open source category is unspecified, which should not be used.", + "Used to indicate the PublisherModel is not open sourced.", + "Used to indicate the PublisherModel is a Google-owned open source model w/ Google checkpoint.", + "Used to indicate the PublisherModel is a 3p-owned open source model w/ Google checkpoint.", + "Used to indicate the PublisherModel is a Google-owned pure open source model.", + "Used to indicate the PublisherModel is a 3p-owned pure open source model." + ] + }, + "supportedActions": { + "$ref": "GoogleCloudAiplatformV1PublisherModelCallToAction", + "description": "Optional. Supported call-to-action options." + }, + "frameworks": { + "items": { + "type": "string" + }, + "description": "Optional. Additional information about the model's Frameworks.", + "type": "array" + }, + "predictSchemata": { + "$ref": "GoogleCloudAiplatformV1PredictSchemata", + "description": "Optional. The schemata that describes formats of the PublisherModel's predictions and explanations as given and returned via PredictionService.Predict." + }, + "versionId": { + "type": "string", + "readOnly": true, + "description": "Output only. Immutable. The version ID of the PublisherModel. A new version is committed when a new model version is uploaded under an existing model id. It is an auto-incrementing decimal number in string representation." + }, + "name": { + "readOnly": true, + "type": "string", + "description": "Output only. The resource name of the PublisherModel." + }, + "launchStage": { + "enumDescriptions": [ + "The model launch stage is unspecified.", + "Used to indicate the PublisherModel is at Experimental launch stage, available to a small set of customers.", + "Used to indicate the PublisherModel is at Private Preview launch stage, only available to a small set of customers, although a larger set of customers than an Experimental launch. Previews are the first launch stage used to get feedback from customers.", + "Used to indicate the PublisherModel is at Public Preview launch stage, available to all customers, although not supported for production workloads.", + "Used to indicate the PublisherModel is at GA launch stage, available to all customers and ready for production workload." + ], + "enum": [ + "LAUNCH_STAGE_UNSPECIFIED", + "EXPERIMENTAL", + "PRIVATE_PREVIEW", + "PUBLIC_PREVIEW", + "GA" + ], + "description": "Optional. Indicates the launch stage of the model.", + "type": "string" + }, + "publisherModelTemplate": { + "readOnly": true, + "type": "string", + "description": "Optional. Output only. Immutable. Used to indicate this model has a publisher model and provide the template of the publisher model resource name." + } + }, + "type": "object", + "description": "A Model Garden Publisher Model." + }, + "GoogleCloudAiplatformV1AssignNotebookRuntimeRequest": { + "type": "object", + "description": "Request message for NotebookService.AssignNotebookRuntime.", + "id": "GoogleCloudAiplatformV1AssignNotebookRuntimeRequest", + "properties": { + "notebookRuntime": { + "$ref": "GoogleCloudAiplatformV1NotebookRuntime", + "description": "Required. Provide runtime specific information (e.g. runtime owner, notebook id) used for NotebookRuntime assignment." + }, + "notebookRuntimeId": { + "type": "string", + "description": "Optional. User specified ID for the notebook runtime." + }, + "notebookRuntimeTemplate": { + "type": "string", + "description": "Required. The resource name of the NotebookRuntimeTemplate based on which a NotebookRuntime will be assigned (reuse or create a new one)." + } + } + }, + "GoogleCloudAiplatformV1NotebookExecutionJob": { + "id": "GoogleCloudAiplatformV1NotebookExecutionJob", + "description": "NotebookExecutionJob represents an instance of a notebook execution.", + "type": "object", + "properties": { + "status": { + "readOnly": true, + "$ref": "GoogleRpcStatus", + "description": "Output only. Populated when the NotebookExecutionJob is completed. When there is an error during notebook execution, the error details are populated." + }, + "serviceAccount": { + "description": "The service account to run the execution as.", + "type": "string" + }, + "scheduleResourceName": { + "type": "string", + "description": "Output only. The Schedule resource name if this job is triggered by one. Format: `projects/{project_id}/locations/{location}/schedules/{schedule_id}`", + "readOnly": true + }, + "executionUser": { + "type": "string", + "description": "The user email to run the execution as. Only supported by Colab runtimes." + }, + "updateTime": { + "description": "Output only. Timestamp when this NotebookExecutionJob was most recently updated.", + "type": "string", + "format": "google-datetime", + "readOnly": true + }, + "jobState": { + "enum": [ + "JOB_STATE_UNSPECIFIED", + "JOB_STATE_QUEUED", + "JOB_STATE_PENDING", + "JOB_STATE_RUNNING", + "JOB_STATE_SUCCEEDED", + "JOB_STATE_FAILED", + "JOB_STATE_CANCELLING", + "JOB_STATE_CANCELLED", + "JOB_STATE_PAUSED", + "JOB_STATE_EXPIRED", + "JOB_STATE_UPDATING", + "JOB_STATE_PARTIALLY_SUCCEEDED" + ], + "type": "string", + "description": "Output only. The state of the NotebookExecutionJob.", + "readOnly": true, + "enumDescriptions": [ + "The job state is unspecified.", + "The job has been just created or resumed and processing has not yet begun.", + "The service is preparing to run the job.", + "The job is in progress.", + "The job completed successfully.", + "The job failed.", + "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "The job has been cancelled.", + "The job has been stopped, and can be resumed.", + "The job has expired.", + "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", + "The job is partially succeeded, some results may be missing due to errors." + ] + }, + "name": { + "type": "string", + "readOnly": true, + "description": "Output only. The resource name of this NotebookExecutionJob. Format: `projects/{project_id}/locations/{location}/notebookExecutionJobs/{job_id}`" + }, + "labels": { + "description": "The labels with user-defined metadata to organize NotebookExecutionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "notebookRuntimeTemplateResourceName": { + "type": "string", + "description": "The NotebookRuntimeTemplate to source compute configuration from." + }, + "displayName": { + "description": "The display name of the NotebookExecutionJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + }, + "executionTimeout": { + "type": "string", + "format": "google-duration", + "description": "Max running time of the execution job in seconds (default 86400s / 24 hrs)." + }, + "directNotebookSource": { + "$ref": "GoogleCloudAiplatformV1NotebookExecutionJobDirectNotebookSource", + "description": "The contents of an input notebook file." + }, + "dataformRepositorySource": { + "$ref": "GoogleCloudAiplatformV1NotebookExecutionJobDataformRepositorySource", + "description": "The Dataform Repository pointing to a single file notebook repository." + }, + "createTime": { + "readOnly": true, + "description": "Output only. Timestamp when this NotebookExecutionJob was created.", + "type": "string", + "format": "google-datetime" + }, + "gcsNotebookSource": { + "$ref": "GoogleCloudAiplatformV1NotebookExecutionJobGcsNotebookSource", + "description": "The Cloud Storage url pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`" + }, + "gcsOutputUri": { + "description": "The Cloud Storage location to upload the result to. Format: `gs://bucket-name`", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationAutoTransformation": { + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationAutoTransformation", + "properties": { + "columnName": { + "type": "string" + } + }, + "description": "Training pipeline will infer the proper transformation based on the statistic of dataset.", + "type": "object" + }, + "GoogleCloudAiplatformV1GroundednessInput": { + "description": "Input for groundedness metric.", + "type": "object", + "id": "GoogleCloudAiplatformV1GroundednessInput", + "properties": { + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1GroundednessSpec", + "description": "Required. Spec for groundedness metric." + }, + "instance": { + "description": "Required. Groundedness instance.", + "$ref": "GoogleCloudAiplatformV1GroundednessInstance" + } + } + }, + "GoogleCloudAiplatformV1BatchPredictionJobOutputConfig": { + "description": "Configures the output of BatchPredictionJob. See Model.supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them.", + "properties": { + "predictionsFormat": { + "type": "string", + "description": "Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats." + }, + "gcsDestination": { + "$ref": "GoogleCloudAiplatformV1GcsDestination", + "description": "The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is `prediction--`, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files `predictions_0001.`, `predictions_0002.`, ..., `predictions_N.` are created where `` depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional `errors_0001.`, `errors_0002.`,..., `errors_N.` files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional `error` field which as value has google.rpc.Status containing only `code` and `message` fields." + }, + "bigqueryDestination": { + "description": "The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name `prediction__` where is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ \"based on ISO-8601\" format. In the dataset two tables will be created, `predictions`, and `errors`. If the Model has both instance and prediction schemata defined then the tables have columns as follows: The `predictions` table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The `errors` table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single \"errors\" column, which as values has google.rpc.Status represented as a STRUCT, and containing only `code` and `message`.", + "$ref": "GoogleCloudAiplatformV1BigQueryDestination" + } + }, + "id": "GoogleCloudAiplatformV1BatchPredictionJobOutputConfig", + "type": "object" + }, + "GoogleCloudAiplatformV1MetadataStore": { + "id": "GoogleCloudAiplatformV1MetadataStore", + "type": "object", + "description": "Instance of a metadata store. Contains a set of metadata that can be queried.", + "properties": { + "name": { + "description": "Output only. The resource name of the MetadataStore instance.", + "type": "string", + "readOnly": true + }, + "dataplexConfig": { + "description": "Optional. Dataplex integration settings.", + "$ref": "GoogleCloudAiplatformV1MetadataStoreDataplexConfig" + }, + "createTime": { + "description": "Output only. Timestamp when this MetadataStore was created.", + "type": "string", + "readOnly": true, + "format": "google-datetime" + }, + "description": { + "type": "string", + "description": "Description of the MetadataStore." + }, + "updateTime": { + "format": "google-datetime", + "type": "string", + "description": "Output only. Timestamp when this MetadataStore was last updated.", + "readOnly": true + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1EncryptionSpec", + "description": "Customer-managed encryption key spec for a Metadata Store. If set, this Metadata Store and all sub-resources of this Metadata Store are secured using this key." + }, + "state": { + "description": "Output only. State information of the MetadataStore.", + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1MetadataStoreMetadataStoreState" + } + } + }, + "CloudAiLargeModelsVisionRaiInfo": { + "id": "CloudAiLargeModelsVisionRaiInfo", + "type": "object", + "properties": { + "modelName": { + "description": "The model name used to indexing into the RaiFilterConfig map. Would either be one of imagegeneration@002-006, imagen-3.0-... api endpoint names, or internal names used for mapping to different filter configs (genselfie, ai_watermark) than its api endpoint.", + "type": "string" + }, + "scores": { + "items": { + "format": "float", + "type": "number" + }, + "description": "List of rai scores mapping to the rai categories. Rounded to 1 decimal place.", + "type": "array" + }, + "detectedLabels": { + "description": "The list of detected labels for different rai categories.", + "type": "array", + "items": { + "$ref": "CloudAiLargeModelsVisionRaiInfoDetectedLabels" + } + }, + "raiCategories": { + "description": "List of rai categories' information to return", + "type": "array", + "items": { + "type": "string" + } + } + } + }, + "GoogleCloudAiplatformV1CoherenceInput": { + "description": "Input for coherence metric.", + "id": "GoogleCloudAiplatformV1CoherenceInput", + "type": "object", + "properties": { + "instance": { + "description": "Required. Coherence instance.", + "$ref": "GoogleCloudAiplatformV1CoherenceInstance" + }, + "metricSpec": { + "description": "Required. Spec for coherence score metric.", + "$ref": "GoogleCloudAiplatformV1CoherenceSpec" + } + } + }, + "GoogleApiHttpBody": { + "type": "object", + "description": "Message that represents an arbitrary HTTP body. It should only be used for payload formats that can't be represented as JSON, such as raw binary or an HTML page. This message can be used both in streaming and non-streaming API methods in the request as well as the response. It can be used as a top-level request field, which is convenient if one wants to extract parameters from either the URL or HTTP template into the request fields and also want access to the raw HTTP body. Example: message GetResourceRequest { // A unique request id. string request_id = 1; // The raw HTTP body is bound to this field. google.api.HttpBody http_body = 2; } service ResourceService { rpc GetResource(GetResourceRequest) returns (google.api.HttpBody); rpc UpdateResource(google.api.HttpBody) returns (google.protobuf.Empty); } Example with streaming methods: service CaldavService { rpc GetCalendar(stream google.api.HttpBody) returns (stream google.api.HttpBody); rpc UpdateCalendar(stream google.api.HttpBody) returns (stream google.api.HttpBody); } Use of this type only changes how the request and response bodies are handled, all other features will continue to work unchanged.", + "id": "GoogleApiHttpBody", + "properties": { + "data": { + "format": "byte", + "description": "The HTTP request/response body as raw binary.", + "type": "string" + }, + "extensions": { + "description": "Application specific response metadata. Must be set in the first response for streaming APIs.", + "items": { + "additionalProperties": { + "type": "any", + "description": "Properties of the object. Contains field @type with type URL." + }, + "type": "object" + }, + "type": "array" + }, + "contentType": { + "type": "string", + "description": "The HTTP Content-Type header value specifying the content type of the body." + } + } + }, + "GoogleCloudAiplatformV1Model": { + "description": "A trained machine learning Model.", + "id": "GoogleCloudAiplatformV1Model", + "type": "object", + "properties": { + "etag": { + "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "satisfiesPzi": { + "description": "Output only. Reserved for future use.", + "type": "boolean", + "readOnly": true + }, + "versionId": { + "description": "Output only. Immutable. The version ID of the model. A new version is committed when a new model version is uploaded or trained under an existing model id. It is an auto-incrementing decimal number in string representation.", + "type": "string", + "readOnly": true + }, + "metadataArtifact": { + "readOnly": true, + "type": "string", + "description": "Output only. The resource name of the Artifact that was created in MetadataStore when creating the Model. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`." + }, + "name": { + "description": "The resource name of the Model.", + "type": "string" + }, + "metadataSchemaUri": { + "type": "string", + "description": "Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access." + }, + "supportedExportFormats": { + "description": "Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.", + "items": { + "$ref": "GoogleCloudAiplatformV1ModelExportFormat" + }, + "type": "array", + "readOnly": true + }, + "satisfiesPzs": { + "readOnly": true, + "type": "boolean", + "description": "Output only. Reserved for future use." + }, + "deployedModels": { + "readOnly": true, + "type": "array", + "description": "Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.", + "items": { + "$ref": "GoogleCloudAiplatformV1DeployedModelRef" + } + }, + "baseModelSource": { + "$ref": "GoogleCloudAiplatformV1ModelBaseModelSource", + "description": "Optional. User input field to specify the base model source. Currently it only supports specifing the Model Garden models and Genie models." + }, + "dataStats": { + "description": "Stats of data used for training or evaluating the Model. Only populated when the Model is trained by a TrainingPipeline with data_input_config.", + "$ref": "GoogleCloudAiplatformV1ModelDataStats" + }, + "metadata": { + "description": "Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.", + "type": "any" + }, + "pipelineJob": { + "description": "Optional. This field is populated if the model is produced by a pipeline job.", + "type": "string" + }, + "displayName": { + "description": "Required. The display name of the Model. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + }, + "supportedInputStorageFormats": { + "description": "Output only. The formats this Model supports in BatchPredictionJob.input_config. If PredictSchemata.instance_schema_uri exists, the instances should be given as per that schema. The possible formats are: * `jsonl` The JSON Lines format, where each instance is a single line. Uses GcsSource. * `csv` The CSV format, where each instance is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses GcsSource. * `tf-record` The TFRecord format, where each instance is a single record in tfrecord syntax. Uses GcsSource. * `tf-record-gzip` Similar to `tf-record`, but the file is gzipped. Uses GcsSource. * `bigquery` Each instance is a single row in BigQuery. Uses BigQuerySource. * `file-list` Each line of the file is the location of an instance to process, uses `gcs_source` field of the InputConfig object. If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.", + "items": { + "type": "string" + }, + "type": "array", + "readOnly": true + }, + "trainingPipeline": { + "readOnly": true, + "description": "Output only. The resource name of the TrainingPipeline that uploaded this Model, if any.", + "type": "string" + }, + "versionCreateTime": { + "readOnly": true, + "description": "Output only. Timestamp when this version was created.", + "format": "google-datetime", + "type": "string" + }, + "description": { + "type": "string", + "description": "The description of the Model." + }, + "artifactUri": { + "description": "Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not required for AutoML Models.", + "type": "string" + }, + "createTime": { + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Timestamp when this Model was uploaded into Vertex AI.", + "type": "string" + }, + "originalModelInfo": { + "readOnly": true, + "description": "Output only. If this Model is a copy of another Model, this contains info about the original.", + "$ref": "GoogleCloudAiplatformV1ModelOriginalModelInfo" + }, + "predictSchemata": { + "$ref": "GoogleCloudAiplatformV1PredictSchemata", + "description": "The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain." + }, + "labels": { + "description": "The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "versionAliases": { + "type": "array", + "description": "User provided version aliases so that a model version can be referenced via alias (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_alias}` instead of auto-generated version id (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_id})`. The format is a-z{0,126}[a-z0-9] to distinguish from version_id. A default version alias will be created for the first version of the model, and there must be exactly one default version alias for a model.", + "items": { + "type": "string" + } + }, + "supportedOutputStorageFormats": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Output only. The formats this Model supports in BatchPredictionJob.output_config. If both PredictSchemata.instance_schema_uri and PredictSchemata.prediction_schema_uri exist, the predictions are returned together with their instances. In other words, the prediction has the original instance data first, followed by the actual prediction content (as per the schema). The possible formats are: * `jsonl` The JSON Lines format, where each prediction is a single line. Uses GcsDestination. * `csv` The CSV format, where each prediction is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses GcsDestination. * `bigquery` Each prediction is a single row in a BigQuery table, uses BigQueryDestination . If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.", + "readOnly": true + }, + "modelSourceInfo": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1ModelSourceInfo", + "description": "Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or saved and tuned from Genie or Model Garden." + }, + "updateTime": { + "format": "google-datetime", + "type": "string", + "description": "Output only. Timestamp when this Model was most recently updated.", + "readOnly": true + }, + "explanationSpec": { + "description": "The default explanation specification for this Model. The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated. All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob. If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob.", + "$ref": "GoogleCloudAiplatformV1ExplanationSpec" + }, + "versionUpdateTime": { + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Timestamp when this version was most recently updated.", + "type": "string" + }, + "containerSpec": { + "description": "Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not required for AutoML Models.", + "$ref": "GoogleCloudAiplatformV1ModelContainerSpec" + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1EncryptionSpec", + "description": "Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key." + }, + "versionDescription": { + "description": "The description of this version.", + "type": "string" + }, + "supportedDeploymentResourcesTypes": { + "description": "Output only. When this Model is deployed, its prediction resources are described by the `prediction_resources` field of the Endpoint.deployed_models object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an Endpoint and does not support online predictions (PredictionService.Predict or PredictionService.Explain). Such a Model can serve predictions by using a BatchPredictionJob, if it has at least one entry each in supported_input_storage_formats and supported_output_storage_formats.", + "items": { + "enumDescriptions": [ + "Should not be used.", + "Resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.", + "Resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.", + "Resources that can be shared by multiple DeployedModels. A pre-configured DeploymentResourcePool is required." + ], + "enum": [ + "DEPLOYMENT_RESOURCES_TYPE_UNSPECIFIED", + "DEDICATED_RESOURCES", + "AUTOMATIC_RESOURCES", + "SHARED_RESOURCES" + ], + "type": "string" + }, + "readOnly": true, + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProvider": { + "properties": { + "audiences": { + "description": "The list of JWT [audiences](https://tools.ietf.org/html/draft-ietf-oauth-json-web-token-32#section-4.1.3). that are allowed to access. A JWT containing any of these audiences will be accepted.", + "items": { + "type": "string" + }, + "type": "array" + }, + "allowedIssuers": { + "type": "array", + "items": { + "type": "string" + }, + "description": "A list of allowed JWT issuers. Each entry must be a valid Google service account, in the following format: `service-account-name@project-id.iam.gserviceaccount.com`" + } + }, + "type": "object", + "description": "Configuration for an authentication provider, including support for [JSON Web Token (JWT)](https://tools.ietf.org/html/draft-ietf-oauth-json-web-token-32).", + "id": "GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProvider" + }, + "GoogleCloudAiplatformV1BatchMigrateResourcesOperationMetadata": { + "description": "Runtime operation information for MigrationService.BatchMigrateResources.", + "id": "GoogleCloudAiplatformV1BatchMigrateResourcesOperationMetadata", + "type": "object", + "properties": { + "partialResults": { + "items": { + "$ref": "GoogleCloudAiplatformV1BatchMigrateResourcesOperationMetadataPartialResult" + }, + "type": "array", + "description": "Partial results that reflect the latest migration operation progress." + }, + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The common part of the operation metadata." + } + } + }, + "GoogleCloudAiplatformV1ExplanationMetadataInputMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1ExplanationMetadataInputMetadata", + "properties": { + "featureValueDomain": { + "$ref": "GoogleCloudAiplatformV1ExplanationMetadataInputMetadataFeatureValueDomain", + "description": "The domain details of the input feature value. Like min/max, original mean or standard deviation if normalized." + }, + "inputTensorName": { + "description": "Name of the input tensor for this feature. Required and is only applicable to Vertex AI-provided images for Tensorflow.", + "type": "string" + }, + "denseShapeTensorName": { + "type": "string", + "description": "Specifies the shape of the values of the input if the input is a sparse representation. Refer to Tensorflow documentation for more details: https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor." + }, + "encoding": { + "enum": [ + "ENCODING_UNSPECIFIED", + "IDENTITY", + "BAG_OF_FEATURES", + "BAG_OF_FEATURES_SPARSE", + "INDICATOR", + "COMBINED_EMBEDDING", + "CONCAT_EMBEDDING" + ], + "description": "Defines how the feature is encoded into the input tensor. Defaults to IDENTITY.", + "enumDescriptions": [ + "Default value. This is the same as IDENTITY.", + "The tensor represents one feature.", + "The tensor represents a bag of features where each index maps to a feature. InputMetadata.index_feature_mapping must be provided for this encoding. For example: ``` input = [27, 6.0, 150] index_feature_mapping = [\"age\", \"height\", \"weight\"] ```", + "The tensor represents a bag of features where each index maps to a feature. Zero values in the tensor indicates feature being non-existent. InputMetadata.index_feature_mapping must be provided for this encoding. For example: ``` input = [2, 0, 5, 0, 1] index_feature_mapping = [\"a\", \"b\", \"c\", \"d\", \"e\"] ```", + "The tensor is a list of binaries representing whether a feature exists or not (1 indicates existence). InputMetadata.index_feature_mapping must be provided for this encoding. For example: ``` input = [1, 0, 1, 0, 1] index_feature_mapping = [\"a\", \"b\", \"c\", \"d\", \"e\"] ```", + "The tensor is encoded into a 1-dimensional array represented by an encoded tensor. InputMetadata.encoded_tensor_name must be provided for this encoding. For example: ``` input = [\"This\", \"is\", \"a\", \"test\", \".\"] encoded = [0.1, 0.2, 0.3, 0.4, 0.5] ```", + "Select this encoding when the input tensor is encoded into a 2-dimensional array represented by an encoded tensor. InputMetadata.encoded_tensor_name must be provided for this encoding. The first dimension of the encoded tensor's shape is the same as the input tensor's shape. For example: ``` input = [\"This\", \"is\", \"a\", \"test\", \".\"] encoded = [[0.1, 0.2, 0.3, 0.4, 0.5], [0.2, 0.1, 0.4, 0.3, 0.5], [0.5, 0.1, 0.3, 0.5, 0.4], [0.5, 0.3, 0.1, 0.2, 0.4], [0.4, 0.3, 0.2, 0.5, 0.1]] ```" + ], + "type": "string" + }, + "modality": { + "type": "string", + "description": "Modality of the feature. Valid values are: numeric, image. Defaults to numeric." + }, + "inputBaselines": { + "description": "Baseline inputs for this feature. If no baseline is specified, Vertex AI chooses the baseline for this feature. If multiple baselines are specified, Vertex AI returns the average attributions across them in Attribution.feature_attributions. For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape of each baseline must match the shape of the input tensor. If a scalar is provided, we broadcast to the same shape as the input tensor. For custom images, the element of the baselines must be in the same format as the feature's input in the instance[]. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.", + "items": { + "type": "any" + }, + "type": "array" + }, + "encodedBaselines": { + "type": "array", + "description": "A list of baselines for the encoded tensor. The shape of each baseline should match the shape of the encoded tensor. If a scalar is provided, Vertex AI broadcasts to the same shape as the encoded tensor.", + "items": { + "type": "any" + } + }, + "groupName": { + "description": "Name of the group that the input belongs to. Features with the same group name will be treated as one feature when computing attributions. Features grouped together can have different shapes in value. If provided, there will be one single attribution generated in Attribution.feature_attributions, keyed by the group name.", + "type": "string" + }, + "indexFeatureMapping": { + "items": { + "type": "string" + }, + "description": "A list of feature names for each index in the input tensor. Required when the input InputMetadata.encoding is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.", + "type": "array" + }, + "visualization": { + "$ref": "GoogleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization", + "description": "Visualization configurations for image explanation." + }, + "encodedTensorName": { + "type": "string", + "description": "Encoded tensor is a transformation of the input tensor. Must be provided if choosing Integrated Gradients attribution or XRAI attribution and the input tensor is not differentiable. An encoded tensor is generated if the input tensor is encoded by a lookup table." + }, + "indicesTensorName": { + "type": "string", + "description": "Specifies the index of the values of the input tensor. Required when the input tensor is a sparse representation. Refer to Tensorflow documentation for more details: https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor." + } + }, + "description": "Metadata of the input of a feature. Fields other than InputMetadata.input_baselines are applicable only for Models that are using Vertex AI-provided images for Tensorflow." + }, + "GoogleCloudAiplatformV1IndexStats": { + "description": "Stats of the Index.", + "properties": { + "vectorsCount": { + "description": "Output only. The number of dense vectors in the Index.", + "readOnly": true, + "format": "int64", + "type": "string" + }, + "sparseVectorsCount": { + "type": "string", + "description": "Output only. The number of sparse vectors in the Index.", + "format": "int64", + "readOnly": true + }, + "shardsCount": { + "format": "int32", + "description": "Output only. The number of shards in the Index.", + "type": "integer", + "readOnly": true + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1IndexStats" + }, + "GoogleCloudAiplatformV1PersistentResource": { + "type": "object", + "properties": { + "resourcePools": { + "description": "Required. The spec of the pools of different resources.", + "items": { + "$ref": "GoogleCloudAiplatformV1ResourcePool" + }, + "type": "array" + }, + "pscInterfaceConfig": { + "$ref": "GoogleCloudAiplatformV1PscInterfaceConfig", + "description": "Optional. Configuration for PSC-I for PersistentResource." + }, + "createTime": { + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Time when the PersistentResource was created.", + "type": "string" + }, + "updateTime": { + "description": "Output only. Time when the PersistentResource was most recently updated.", + "type": "string", + "format": "google-datetime", + "readOnly": true + }, + "error": { + "$ref": "GoogleRpcStatus", + "description": "Output only. Only populated when persistent resource's state is `STOPPING` or `ERROR`.", + "readOnly": true + }, + "resourceRuntime": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1ResourceRuntime", + "description": "Output only. Runtime information of the Persistent Resource." + }, + "resourceRuntimeSpec": { + "$ref": "GoogleCloudAiplatformV1ResourceRuntimeSpec", + "description": "Optional. Persistent Resource runtime spec. For example, used for Ray cluster configuration." + }, + "name": { + "description": "Immutable. Resource name of a PersistentResource.", + "type": "string" + }, + "startTime": { + "description": "Output only. Time when the PersistentResource for the first time entered the `RUNNING` state.", + "format": "google-datetime", + "readOnly": true, + "type": "string" + }, + "displayName": { + "type": "string", + "description": "Optional. The display name of the PersistentResource. The name can be up to 128 characters long and can consist of any UTF-8 characters." + }, + "state": { + "enum": [ + "STATE_UNSPECIFIED", + "PROVISIONING", + "RUNNING", + "STOPPING", + "ERROR", + "REBOOTING", + "UPDATING" + ], + "description": "Output only. The detailed state of a Study.", + "enumDescriptions": [ + "Not set.", + "The PROVISIONING state indicates the persistent resources is being created.", + "The RUNNING state indicates the persistent resource is healthy and fully usable.", + "The STOPPING state indicates the persistent resource is being deleted.", + "The ERROR state indicates the persistent resource may be unusable. Details can be found in the `error` field.", + "The REBOOTING state indicates the persistent resource is being rebooted (PR is not available right now but is expected to be ready again later).", + "The UPDATING state indicates the persistent resource is being updated." + ], + "readOnly": true, + "type": "string" + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1EncryptionSpec", + "description": "Optional. Customer-managed encryption key spec for a PersistentResource. If set, this PersistentResource and all sub-resources of this PersistentResource will be secured by this key." + }, + "network": { + "type": "string", + "description": "Optional. The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to peered with Vertex AI to host the persistent resources. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. To specify this field, you must have already [configured VPC Network Peering for Vertex AI](https://cloud.google.com/vertex-ai/docs/general/vpc-peering). If this field is left unspecified, the resources aren't peered with any network." + }, + "labels": { + "type": "object", + "description": "Optional. The labels with user-defined metadata to organize PersistentResource. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", + "additionalProperties": { + "type": "string" + } + }, + "reservedIpRanges": { + "description": "Optional. A list of names for the reserved IP ranges under the VPC network that can be used for this persistent resource. If set, we will deploy the persistent resource within the provided IP ranges. Otherwise, the persistent resource is deployed to any IP ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].", + "items": { + "type": "string" + }, + "type": "array" + } + }, + "description": "Represents long-lasting resources that are dedicated to users to runs custom workloads. A PersistentResource can have multiple node pools and each node pool can have its own machine spec.", + "id": "GoogleCloudAiplatformV1PersistentResource" + }, + "GoogleRpcStatus": { + "properties": { + "code": { + "description": "The status code, which should be an enum value of google.rpc.Code.", + "format": "int32", + "type": "integer" + }, + "message": { + "description": "A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.", + "type": "string" + }, + "details": { + "items": { + "additionalProperties": { + "description": "Properties of the object. Contains field @type with type URL.", + "type": "any" + }, + "type": "object" + }, + "type": "array", + "description": "A list of messages that carry the error details. There is a common set of message types for APIs to use." + } + }, + "id": "GoogleRpcStatus", + "description": "The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors).", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTablesDatasetMetadataInputConfig": { + "description": "The tables Dataset's data source. The Dataset doesn't store the data directly, but only pointer(s) to its data.", + "type": "object", + "properties": { + "bigquerySource": { + "$ref": "GoogleCloudAiplatformV1SchemaTablesDatasetMetadataBigQuerySource" + }, + "gcsSource": { + "$ref": "GoogleCloudAiplatformV1SchemaTablesDatasetMetadataGcsSource" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTablesDatasetMetadataInputConfig" + }, + "GoogleCloudAiplatformV1BoolArray": { + "description": "A list of boolean values.", + "type": "object", + "properties": { + "values": { + "type": "array", + "items": { + "type": "boolean" + }, + "description": "A list of bool values." + } + }, + "id": "GoogleCloudAiplatformV1BoolArray" + }, + "GoogleCloudAiplatformV1IndexPrivateEndpoints": { + "description": "IndexPrivateEndpoints proto is used to provide paths for users to send requests via private endpoints (e.g. private service access, private service connect). To send request via private service access, use match_grpc_address. To send request via private service connect, use service_attachment.", + "id": "GoogleCloudAiplatformV1IndexPrivateEndpoints", + "properties": { + "serviceAttachment": { + "readOnly": true, + "description": "Output only. The name of the service attachment resource. Populated if private service connect is enabled.", + "type": "string" + }, + "pscAutomatedEndpoints": { + "type": "array", + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1PscAutomatedEndpoints" + }, + "description": "Output only. PscAutomatedEndpoints is populated if private service connect is enabled if PscAutomatedConfig is set." + }, + "matchGrpcAddress": { + "description": "Output only. The ip address used to send match gRPC requests.", + "type": "string", + "readOnly": true + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsImageObjectDetectionEvaluationMetrics": { + "properties": { + "evaluatedBoundingBoxCount": { + "description": "The total number of bounding boxes (i.e. summed over all images) the ground truth used to create this evaluation had.", + "type": "integer", + "format": "int32" + }, + "boundingBoxMeanAveragePrecision": { + "type": "number", + "description": "The single metric for bounding boxes evaluation: the `meanAveragePrecision` averaged over all `boundingBoxMetricsEntries`.", + "format": "float" + }, + "boundingBoxMetrics": { + "description": "The bounding boxes match metrics for each intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.", + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsBoundingBoxMetrics" + }, + "type": "array" + } + }, + "description": "Metrics for image object detection evaluation results.", + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsImageObjectDetectionEvaluationMetrics" + }, + "GoogleCloudAiplatformV1ToolCallValidInstance": { + "description": "Spec for tool call valid instance.", + "properties": { + "prediction": { + "description": "Required. Output of the evaluated model.", + "type": "string" + }, + "reference": { + "type": "string", + "description": "Required. Ground truth used to compare against the prediction." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1ToolCallValidInstance" + }, + "GoogleCloudAiplatformV1DatasetVersion": { + "properties": { + "createTime": { + "readOnly": true, + "description": "Output only. Timestamp when this DatasetVersion was created.", + "type": "string", + "format": "google-datetime" + }, + "updateTime": { + "description": "Output only. Timestamp when this DatasetVersion was last updated.", + "format": "google-datetime", + "readOnly": true, + "type": "string" + }, + "displayName": { + "description": "The user-defined name of the DatasetVersion. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + }, + "bigQueryDatasetName": { + "readOnly": true, + "type": "string", + "description": "Output only. Name of the associated BigQuery dataset." + }, + "metadata": { + "type": "any", + "readOnly": true, + "description": "Required. Output only. Additional information about the DatasetVersion." + }, + "etag": { + "type": "string", + "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + }, + "modelReference": { + "readOnly": true, + "description": "Output only. Reference to the public base model last used by the dataset version. Only set for prompt dataset versions.", + "type": "string" + }, + "name": { + "type": "string", + "description": "Output only. Identifier. The resource name of the DatasetVersion.", + "readOnly": true + } + }, + "type": "object", + "description": "Describes the dataset version.", + "id": "GoogleCloudAiplatformV1DatasetVersion" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHyperparameterTuningTask": { + "description": "A TrainingJob that tunes Hypererparameters of a custom code Model.", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHyperparameterTuningTask", + "properties": { + "inputs": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHyperparameterTuningJobSpec", + "description": "The input parameters of this HyperparameterTuningTask." + }, + "metadata": { + "description": "The metadata information.", + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHyperparameterTuningJobMetadata" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1DataItemView": { + "properties": { + "hasTruncatedAnnotations": { + "type": "boolean", + "description": "True if and only if the Annotations field has been truncated. It happens if more Annotations for this DataItem met the request's annotation_filter than are allowed to be returned by annotations_limit. Note that if Annotations field is not being returned due to field mask, then this field will not be set to true no matter how many Annotations are there." + }, + "annotations": { + "type": "array", + "description": "The Annotations on the DataItem. If too many Annotations should be returned for the DataItem, this field will be truncated per annotations_limit in request. If it was, then the has_truncated_annotations will be set to true.", + "items": { + "$ref": "GoogleCloudAiplatformV1Annotation" + } + }, + "dataItem": { + "$ref": "GoogleCloudAiplatformV1DataItem", + "description": "The DataItem." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1DataItemView", + "description": "A container for a single DataItem and Annotations on it." + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoClassification": { + "type": "object", + "description": "A TrainingJob that trains and uploads an AutoML Video Classification Model.", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoClassification", + "properties": { + "inputs": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoClassificationInputs", + "description": "The input parameters of this TrainingJob." + } + } + }, + "GoogleCloudAiplatformV1ImportFeatureValuesRequestFeatureSpec": { + "properties": { + "id": { + "type": "string", + "description": "Required. ID of the Feature to import values of. This Feature must exist in the target EntityType, or the request will fail." + }, + "sourceField": { + "type": "string", + "description": "Source column to get the Feature values from. If not set, uses the column with the same name as the Feature ID." + } + }, + "type": "object", + "description": "Defines the Feature value(s) to import.", + "id": "GoogleCloudAiplatformV1ImportFeatureValuesRequestFeatureSpec" + }, + "GoogleCloudAiplatformV1PscAutomatedEndpoints": { + "type": "object", + "id": "GoogleCloudAiplatformV1PscAutomatedEndpoints", + "description": "PscAutomatedEndpoints defines the output of the forwarding rule automatically created by each PscAutomationConfig.", + "properties": { + "projectId": { + "type": "string", + "description": "Corresponding project_id in pscAutomationConfigs" + }, + "network": { + "description": "Corresponding network in pscAutomationConfigs.", + "type": "string" + }, + "matchAddress": { + "description": "Ip Address created by the automated forwarding rule.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1UpdatePersistentResourceOperationMetadata": { + "description": "Details of operations that perform update PersistentResource.", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "Operation metadata for PersistentResource." + }, + "progressMessage": { + "type": "string", + "description": "Progress Message for Update LRO" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1UpdatePersistentResourceOperationMetadata" + }, + "GoogleCloudAiplatformV1ListIndexesResponse": { + "id": "GoogleCloudAiplatformV1ListIndexesResponse", + "type": "object", + "description": "Response message for IndexService.ListIndexes.", + "properties": { + "indexes": { + "items": { + "$ref": "GoogleCloudAiplatformV1Index" + }, + "description": "List of indexes in the requested page.", + "type": "array" + }, + "nextPageToken": { + "description": "A token to retrieve next page of results. Pass to ListIndexesRequest.page_token to obtain that page.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueCondition": { + "id": "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueCondition", + "description": "Represents the spec to match discrete values from parent parameter.", + "type": "object", + "properties": { + "values": { + "items": { + "format": "double", + "type": "number" + }, + "description": "Required. Matches values of the parent parameter of 'DISCRETE' type. All values must exist in `discrete_value_spec` of parent parameter. The Epsilon of the value matching is 1e-10.", + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1RawPredictRequest": { + "description": "Request message for PredictionService.RawPredict.", + "type": "object", + "id": "GoogleCloudAiplatformV1RawPredictRequest", + "properties": { + "httpBody": { + "$ref": "GoogleApiHttpBody", + "description": "The prediction input. Supports HTTP headers and arbitrary data payload. A DeployedModel may have an upper limit on the number of instances it supports per request. When this limit it is exceeded for an AutoML model, the RawPredict method returns an error. When this limit is exceeded for a custom-trained model, the behavior varies depending on the model. You can specify the schema for each instance in the predict_schemata.instance_schema_uri field when you create a Model. This schema applies when you deploy the `Model` as a `DeployedModel` to an Endpoint and use the `RawPredict` method." + } + } + }, + "GoogleCloudAiplatformV1PipelineJob": { + "type": "object", + "description": "An instance of a machine learning PipelineJob.", + "properties": { + "error": { + "$ref": "GoogleRpcStatus", + "description": "Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.", + "readOnly": true + }, + "createTime": { + "format": "google-datetime", + "description": "Output only. Pipeline creation time.", + "type": "string", + "readOnly": true + }, + "scheduleName": { + "readOnly": true, + "description": "Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API.", + "type": "string" + }, + "updateTime": { + "description": "Output only. Timestamp when this PipelineJob was most recently updated.", + "readOnly": true, + "type": "string", + "format": "google-datetime" + }, + "displayName": { + "type": "string", + "description": "The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters." + }, + "pipelineSpec": { + "description": "The spec of the pipeline.", + "type": "object", + "additionalProperties": { + "description": "Properties of the object.", + "type": "any" + } + }, + "endTime": { + "format": "google-datetime", + "description": "Output only. Pipeline end time.", + "readOnly": true, + "type": "string" + }, + "serviceAccount": { + "type": "string", + "description": "The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account." + }, + "runtimeConfig": { + "description": "Runtime config of the pipeline.", + "$ref": "GoogleCloudAiplatformV1PipelineJobRuntimeConfig" + }, + "reservedIpRanges": { + "type": "array", + "items": { + "type": "string" + }, + "description": "A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range']." + }, + "templateUri": { + "description": "A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.", + "type": "string" + }, + "startTime": { + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Pipeline start time.", + "type": "string" + }, + "network": { + "type": "string", + "description": "The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network." + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1EncryptionSpec", + "description": "Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key." + }, + "labels": { + "description": "The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.", + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "preflightValidations": { + "description": "Optional. Whether to do component level validations before job creation.", + "type": "boolean" + }, + "state": { + "readOnly": true, + "description": "Output only. The detailed state of the job.", + "enumDescriptions": [ + "The pipeline state is unspecified.", + "The pipeline has been created or resumed, and processing has not yet begun.", + "The service is preparing to run the pipeline.", + "The pipeline is in progress.", + "The pipeline completed successfully.", + "The pipeline failed.", + "The pipeline is being cancelled. From this state, the pipeline may only go to either PIPELINE_STATE_SUCCEEDED, PIPELINE_STATE_FAILED or PIPELINE_STATE_CANCELLED.", + "The pipeline has been cancelled.", + "The pipeline has been stopped, and can be resumed." + ], + "type": "string", + "enum": [ + "PIPELINE_STATE_UNSPECIFIED", + "PIPELINE_STATE_QUEUED", + "PIPELINE_STATE_PENDING", + "PIPELINE_STATE_RUNNING", + "PIPELINE_STATE_SUCCEEDED", + "PIPELINE_STATE_FAILED", + "PIPELINE_STATE_CANCELLING", + "PIPELINE_STATE_CANCELLED", + "PIPELINE_STATE_PAUSED" + ] + }, + "jobDetail": { + "readOnly": true, + "description": "Output only. The details of pipeline run. Not available in the list view.", + "$ref": "GoogleCloudAiplatformV1PipelineJobDetail" + }, + "name": { + "description": "Output only. The resource name of the PipelineJob.", + "readOnly": true, + "type": "string" + }, + "templateMetadata": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1PipelineTemplateMetadata", + "description": "Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry." + } + }, + "id": "GoogleCloudAiplatformV1PipelineJob" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTables": { + "properties": { + "inputs": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputs", + "description": "The input parameters of this TrainingJob." + }, + "metadata": { + "description": "The metadata information.", + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesMetadata" + } + }, + "type": "object", + "description": "A TrainingJob that trains and uploads an AutoML Tables Model.", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTables" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoObjectTrackingInputs": { + "type": "object", + "properties": { + "modelType": { + "enum": [ + "MODEL_TYPE_UNSPECIFIED", + "CLOUD", + "MOBILE_VERSATILE_1", + "MOBILE_CORAL_VERSATILE_1", + "MOBILE_CORAL_LOW_LATENCY_1", + "MOBILE_JETSON_VERSATILE_1", + "MOBILE_JETSON_LOW_LATENCY_1" + ], + "enumDescriptions": [ + "Should not be set.", + "A model best tailored to be used within Google Cloud, and which c annot be exported. Default.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as a TensorFlow or TensorFlow Lite model and used on a mobile or edge device afterwards.", + "A versatile model that is meant to be exported (see ModelService.ExportModel) and used on a Google Coral device.", + "A model that trades off quality for low latency, to be exported (see ModelService.ExportModel) and used on a Google Coral device.", + "A versatile model that is meant to be exported (see ModelService.ExportModel) and used on an NVIDIA Jetson device.", + "A model that trades off quality for low latency, to be exported (see ModelService.ExportModel) and used on an NVIDIA Jetson device." + ], + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoObjectTrackingInputs" + }, + "GoogleCloudAiplatformV1EvaluateInstancesRequest": { + "description": "Request message for EvaluationService.EvaluateInstances.", + "properties": { + "safetyInput": { + "$ref": "GoogleCloudAiplatformV1SafetyInput", + "description": "Input for safety metric." + }, + "toolNameMatchInput": { + "description": "Input for tool name match metric.", + "$ref": "GoogleCloudAiplatformV1ToolNameMatchInput" + }, + "bleuInput": { + "description": "Instances and metric spec for bleu metric.", + "$ref": "GoogleCloudAiplatformV1BleuInput" + }, + "questionAnsweringQualityInput": { + "$ref": "GoogleCloudAiplatformV1QuestionAnsweringQualityInput", + "description": "Input for question answering quality metric." + }, + "questionAnsweringRelevanceInput": { + "$ref": "GoogleCloudAiplatformV1QuestionAnsweringRelevanceInput", + "description": "Input for question answering relevance metric." + }, + "toolParameterKvMatchInput": { + "$ref": "GoogleCloudAiplatformV1ToolParameterKVMatchInput", + "description": "Input for tool parameter key value match metric." + }, + "summarizationQualityInput": { + "$ref": "GoogleCloudAiplatformV1SummarizationQualityInput", + "description": "Input for summarization quality metric." + }, + "coherenceInput": { + "description": "Input for coherence metric.", + "$ref": "GoogleCloudAiplatformV1CoherenceInput" + }, + "questionAnsweringHelpfulnessInput": { + "$ref": "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessInput", + "description": "Input for question answering helpfulness metric." + }, + "fluencyInput": { + "description": "LLM-based metric instance. General text generation metrics, applicable to other categories. Input for fluency metric.", + "$ref": "GoogleCloudAiplatformV1FluencyInput" + }, + "pairwiseQuestionAnsweringQualityInput": { + "description": "Input for pairwise question answering quality metric.", + "$ref": "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualityInput" + }, + "pairwiseSummarizationQualityInput": { + "$ref": "GoogleCloudAiplatformV1PairwiseSummarizationQualityInput", + "description": "Input for pairwise summarization quality metric." + }, + "summarizationVerbosityInput": { + "description": "Input for summarization verbosity metric.", + "$ref": "GoogleCloudAiplatformV1SummarizationVerbosityInput" + }, + "toolParameterKeyMatchInput": { + "description": "Input for tool parameter key match metric.", + "$ref": "GoogleCloudAiplatformV1ToolParameterKeyMatchInput" + }, + "toolCallValidInput": { + "description": "Tool call metric instances. Input for tool call valid metric.", + "$ref": "GoogleCloudAiplatformV1ToolCallValidInput" + }, + "fulfillmentInput": { + "$ref": "GoogleCloudAiplatformV1FulfillmentInput", + "description": "Input for fulfillment metric." + }, + "rougeInput": { + "description": "Instances and metric spec for rouge metric.", + "$ref": "GoogleCloudAiplatformV1RougeInput" + }, + "exactMatchInput": { + "$ref": "GoogleCloudAiplatformV1ExactMatchInput", + "description": "Auto metric instances. Instances and metric spec for exact match metric." + }, + "summarizationHelpfulnessInput": { + "$ref": "GoogleCloudAiplatformV1SummarizationHelpfulnessInput", + "description": "Input for summarization helpfulness metric." + }, + "questionAnsweringCorrectnessInput": { + "$ref": "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessInput", + "description": "Input for question answering correctness metric." + }, + "groundednessInput": { + "description": "Input for groundedness metric.", + "$ref": "GoogleCloudAiplatformV1GroundednessInput" + } + }, + "id": "GoogleCloudAiplatformV1EvaluateInstancesRequest", + "type": "object" + }, + "GoogleCloudAiplatformV1SampledShapleyAttribution": { + "description": "An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.", + "id": "GoogleCloudAiplatformV1SampledShapleyAttribution", + "properties": { + "pathCount": { + "type": "integer", + "description": "Required. The number of feature permutations to consider when approximating the Shapley values. Valid range of its value is [1, 50], inclusively.", + "format": "int32" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix": { + "properties": { + "annotationSpecs": { + "description": "AnnotationSpecs used in the confusion matrix. For AutoML Text Extraction, a special negative AnnotationSpec with empty `id` and `displayName` of \"NULL\" will be added as the last element.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrixAnnotationSpecRef" + } + }, + "rows": { + "items": { + "type": "array", + "items": { + "type": "any" + } + }, + "description": "Rows in the confusion matrix. The number of rows is equal to the size of `annotationSpecs`. `rowsi` is the number of DataItems that have ground truth of the `annotationSpecs[i]` and are predicted as `annotationSpecs[j]` by the Model being evaluated. For Text Extraction, when `annotationSpecs[i]` is the last element in `annotationSpecs`, i.e. the special negative AnnotationSpec, `rowsi` is the number of predicted entities of `annoatationSpec[j]` that are not labeled as any of the ground truth AnnotationSpec. When annotationSpecs[j] is the special negative AnnotationSpec, `rowsi` is the number of entities have ground truth of `annotationSpec[i]` that are not predicted as an entity by the Model. The value of the last cell, i.e. `rowi` where i == j and `annotationSpec[i]` is the special negative AnnotationSpec, is always 0.", + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix", + "type": "object" + }, + "GoogleCloudAiplatformV1IntegratedGradientsAttribution": { + "type": "object", + "description": "An attribution method that computes the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365", + "properties": { + "blurBaselineConfig": { + "$ref": "GoogleCloudAiplatformV1BlurBaselineConfig", + "description": "Config for IG with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383" + }, + "smoothGradConfig": { + "description": "Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf", + "$ref": "GoogleCloudAiplatformV1SmoothGradConfig" + }, + "stepCount": { + "format": "int32", + "type": "integer", + "description": "Required. The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is within the desired error range. Valid range of its value is [1, 100], inclusively." + } + }, + "id": "GoogleCloudAiplatformV1IntegratedGradientsAttribution" + }, + "GoogleCloudAiplatformV1FeatureValue": { + "id": "GoogleCloudAiplatformV1FeatureValue", + "properties": { + "doubleArrayValue": { + "description": "A list of double type feature value.", + "$ref": "GoogleCloudAiplatformV1DoubleArray" + }, + "int64Value": { + "description": "Int64 feature value.", + "type": "string", + "format": "int64" + }, + "boolValue": { + "type": "boolean", + "description": "Bool type feature value." + }, + "metadata": { + "description": "Metadata of feature value.", + "$ref": "GoogleCloudAiplatformV1FeatureValueMetadata" + }, + "stringValue": { + "type": "string", + "description": "String feature value." + }, + "doubleValue": { + "description": "Double type feature value.", + "type": "number", + "format": "double" + }, + "boolArrayValue": { + "$ref": "GoogleCloudAiplatformV1BoolArray", + "description": "A list of bool type feature value." + }, + "structValue": { + "$ref": "GoogleCloudAiplatformV1StructValue", + "description": "A struct type feature value." + }, + "bytesValue": { + "type": "string", + "format": "byte", + "description": "Bytes feature value." + }, + "stringArrayValue": { + "$ref": "GoogleCloudAiplatformV1StringArray", + "description": "A list of string type feature value." + }, + "int64ArrayValue": { + "$ref": "GoogleCloudAiplatformV1Int64Array", + "description": "A list of int64 type feature value." + } + }, + "type": "object", + "description": "Value for a feature." + }, + "GoogleCloudAiplatformV1Content": { + "description": "The base structured datatype containing multi-part content of a message. A `Content` includes a `role` field designating the producer of the `Content` and a `parts` field containing multi-part data that contains the content of the message turn.", + "id": "GoogleCloudAiplatformV1Content", + "type": "object", + "properties": { + "parts": { + "description": "Required. Ordered `Parts` that constitute a single message. Parts may have different IANA MIME types.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1Part" + } + }, + "role": { + "description": "Optional. The producer of the content. Must be either 'user' or 'model'. Useful to set for multi-turn conversations, otherwise can be left blank or unset.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1BleuInstance": { + "description": "Spec for bleu instance.", + "properties": { + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + }, + "reference": { + "type": "string", + "description": "Required. Ground truth used to compare against the prediction." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1BleuInstance" + }, + "GoogleCloudAiplatformV1ListTensorboardsResponse": { + "properties": { + "nextPageToken": { + "description": "A token, which can be sent as ListTensorboardsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + }, + "tensorboards": { + "description": "The Tensorboards mathching the request.", + "items": { + "$ref": "GoogleCloudAiplatformV1Tensorboard" + }, + "type": "array" + } + }, + "description": "Response message for TensorboardService.ListTensorboards.", + "id": "GoogleCloudAiplatformV1ListTensorboardsResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics": { + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics", + "properties": { + "linearKappa": { + "format": "float", + "type": "number", + "description": "Linear weighted kappa. Only set for ModelEvaluations, not for ModelEvaluationSlices." + }, + "meanSquaredError": { + "format": "float", + "description": "Mean squared error. Only set for ModelEvaluations, not for ModelEvaluationSlices.", + "type": "number" + }, + "quadraticKappa": { + "description": "Quadratic weighted kappa. Only set for ModelEvaluations, not for ModelEvaluationSlices.", + "type": "number", + "format": "float" + }, + "f1Score": { + "type": "number", + "format": "float", + "description": "The harmonic mean of recall and precision." + }, + "confusionMatrix": { + "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix", + "description": "Confusion matrix of the evaluation. Only set for ModelEvaluations, not for ModelEvaluationSlices." + }, + "recall": { + "type": "number", + "description": "Recall.", + "format": "float" + }, + "meanAbsoluteError": { + "type": "number", + "format": "float", + "description": "Mean absolute error. Only set for ModelEvaluations, not for ModelEvaluationSlices." + }, + "precision": { + "description": "Precision.", + "format": "float", + "type": "number" + } + }, + "description": "Model evaluation metrics for text sentiment problems.", + "type": "object" + }, + "GoogleCloudAiplatformV1FeatureOnlineStore": { + "type": "object", + "id": "GoogleCloudAiplatformV1FeatureOnlineStore", + "description": "Vertex AI Feature Online Store provides a centralized repository for serving ML features and embedding indexes at low latency. The Feature Online Store is a top-level container.", + "properties": { + "labels": { + "description": "Optional. The labels with user-defined metadata to organize your FeatureOnlineStore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", + "additionalProperties": { + "type": "string" + }, + "type": "object" + }, + "name": { + "description": "Identifier. Name of the FeatureOnlineStore. Format: `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}`", + "type": "string" + }, + "state": { + "description": "Output only. State of the featureOnlineStore.", + "enumDescriptions": [ + "Default value. This value is unused.", + "State when the featureOnlineStore configuration is not being updated and the fields reflect the current configuration of the featureOnlineStore. The featureOnlineStore is usable in this state.", + "The state of the featureOnlineStore configuration when it is being updated. During an update, the fields reflect either the original configuration or the updated configuration of the featureOnlineStore. The featureOnlineStore is still usable in this state." + ], + "enum": [ + "STATE_UNSPECIFIED", + "STABLE", + "UPDATING" + ], + "type": "string", + "readOnly": true + }, + "updateTime": { + "readOnly": true, + "description": "Output only. Timestamp when this FeatureOnlineStore was last updated.", + "type": "string", + "format": "google-datetime" + }, + "etag": { + "type": "string", + "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1EncryptionSpec", + "description": "Optional. Customer-managed encryption key spec for data storage. If set, online store will be secured by this key." + }, + "dedicatedServingEndpoint": { + "description": "Optional. The dedicated serving endpoint for this FeatureOnlineStore, which is different from common Vertex service endpoint.", + "$ref": "GoogleCloudAiplatformV1FeatureOnlineStoreDedicatedServingEndpoint" + }, + "createTime": { + "description": "Output only. Timestamp when this FeatureOnlineStore was created.", + "readOnly": true, + "type": "string", + "format": "google-datetime" + }, + "optimized": { + "$ref": "GoogleCloudAiplatformV1FeatureOnlineStoreOptimized", + "description": "Contains settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. When choose Optimized storage type, need to set PrivateServiceConnectConfig.enable_private_service_connect to use private endpoint. Otherwise will use public endpoint by default." + }, + "bigtable": { + "$ref": "GoogleCloudAiplatformV1FeatureOnlineStoreBigtable", + "description": "Contains settings for the Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore." + } + } + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation": { + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation", + "properties": { + "numeric": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationNumericTransformation" + }, + "categorical": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationCategoricalTransformation" + }, + "text": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTextTransformation" + }, + "auto": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationAutoTransformation" + }, + "timestamp": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTimestampTransformation" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1AnnotationSpec": { + "id": "GoogleCloudAiplatformV1AnnotationSpec", + "description": "Identifies a concept with which DataItems may be annotated with.", + "properties": { + "name": { + "description": "Output only. Resource name of the AnnotationSpec.", + "readOnly": true, + "type": "string" + }, + "updateTime": { + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Timestamp when AnnotationSpec was last updated.", + "type": "string" + }, + "createTime": { + "description": "Output only. Timestamp when this AnnotationSpec was created.", + "type": "string", + "format": "google-datetime", + "readOnly": true + }, + "displayName": { + "type": "string", + "description": "Required. The user-defined name of the AnnotationSpec. The name can be up to 128 characters long and can consist of any UTF-8 characters." + }, + "etag": { + "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTimestampTransformation": { + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTimestampTransformation", + "properties": { + "timeFormat": { + "description": "The format in which that time field is expressed. The time_format must either be one of: * `unix-seconds` * `unix-milliseconds` * `unix-microseconds` * `unix-nanoseconds` (for respectively number of seconds, milliseconds, microseconds and nanoseconds since start of the Unix epoch); or be written in `strftime` syntax. If time_format is not set, then the default format is RFC 3339 `date-time` format, where `time-offset` = `\"Z\"` (e.g. 1985-04-12T23:20:50.52Z)", + "type": "string" + }, + "columnName": { + "type": "string" + } + }, + "description": "Training pipeline will perform following transformation functions. * Apply the transformation functions for Numerical columns. * Determine the year, month, day,and weekday. Treat each value from the timestamp as a Categorical column. * Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed." + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTextTransformation": { + "properties": { + "columnName": { + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTextTransformation", + "description": "Training pipeline will perform following transformation functions. * The text as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index." + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoActionRecognitionInputs": { + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoActionRecognitionInputs", + "properties": { + "modelType": { + "enum": [ + "MODEL_TYPE_UNSPECIFIED", + "CLOUD", + "MOBILE_VERSATILE_1", + "MOBILE_JETSON_VERSATILE_1", + "MOBILE_CORAL_VERSATILE_1" + ], + "enumDescriptions": [ + "Should not be set.", + "A model best tailored to be used within Google Cloud, and which c annot be exported. Default.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as a TensorFlow or TensorFlow Lite model and used on a mobile or edge device afterwards.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) to a Jetson device afterwards.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as a TensorFlow or TensorFlow Lite model and used on a Coral device afterwards." + ], + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1TimeSeriesDataPoint": { + "properties": { + "scalar": { + "$ref": "GoogleCloudAiplatformV1Scalar", + "description": "A scalar value." + }, + "wallTime": { + "format": "google-datetime", + "type": "string", + "description": "Wall clock timestamp when this data point is generated by the end user." + }, + "step": { + "format": "int64", + "description": "Step index of this data point within the run.", + "type": "string" + }, + "blobs": { + "$ref": "GoogleCloudAiplatformV1TensorboardBlobSequence", + "description": "A blob sequence value." + }, + "tensor": { + "$ref": "GoogleCloudAiplatformV1TensorboardTensor", + "description": "A tensor value." + } + }, + "type": "object", + "description": "A TensorboardTimeSeries data point.", + "id": "GoogleCloudAiplatformV1TimeSeriesDataPoint" + }, + "GoogleCloudAiplatformV1MigrateResourceRequestMigrateDataLabelingDatasetConfig": { + "description": "Config for migrating Dataset in datalabeling.googleapis.com to Vertex AI's Dataset.", + "id": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateDataLabelingDatasetConfig", + "properties": { + "dataset": { + "type": "string", + "description": "Required. Full resource name of data labeling Dataset. Format: `projects/{project}/datasets/{dataset}`." + }, + "datasetDisplayName": { + "description": "Optional. Display name of the Dataset in Vertex AI. System will pick a display name if unspecified.", + "type": "string" + }, + "migrateDataLabelingAnnotatedDatasetConfigs": { + "description": "Optional. Configs for migrating AnnotatedDataset in datalabeling.googleapis.com to Vertex AI's SavedQuery. The specified AnnotatedDatasets have to belong to the datalabeling Dataset.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateDataLabelingDatasetConfigMigrateDataLabelingAnnotatedDatasetConfig" + } + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTimestampTransformation": { + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTimestampTransformation", + "properties": { + "timeFormat": { + "description": "The format in which that time field is expressed. The time_format must either be one of: * `unix-seconds` * `unix-milliseconds` * `unix-microseconds` * `unix-nanoseconds` (for respectively number of seconds, milliseconds, microseconds and nanoseconds since start of the Unix epoch); or be written in `strftime` syntax. If time_format is not set, then the default format is RFC 3339 `date-time` format, where `time-offset` = `\"Z\"` (e.g. 1985-04-12T23:20:50.52Z)", + "type": "string" + }, + "columnName": { + "type": "string" + }, + "invalidValuesAllowed": { + "description": "If invalid values is allowed, the training pipeline will create a boolean feature that indicated whether the value is valid. Otherwise, the training pipeline will discard the input row from trainining data.", + "type": "boolean" + } + }, + "description": "Training pipeline will perform following transformation functions. * Apply the transformation functions for Numerical columns. * Determine the year, month, day,and weekday. Treat each value from the * timestamp as a Categorical column. * Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed.", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputs": { + "type": "object", + "properties": { + "quantiles": { + "items": { + "format": "double", + "type": "number" + }, + "type": "array", + "description": "Quantiles to use for minimize-quantile-loss `optimization_objective`. Up to 5 quantiles are allowed of values between 0 and 1, exclusive. Required if the value of optimization_objective is minimize-quantile-loss. Represents the percent quantiles to use for that objective. Quantiles must be unique." + }, + "holidayRegions": { + "description": "The geographical region based on which the holiday effect is applied in modeling by adding holiday categorical array feature that include all holidays matching the date. This option only allowed when data_granularity is day. By default, holiday effect modeling is disabled. To turn it on, specify the holiday region using this option.", + "type": "array", + "items": { + "type": "string" + } + }, + "windowConfig": { + "description": "Config containing strategy for generating sliding windows.", + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionWindowConfig" + }, + "hierarchyConfig": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHierarchyConfig", + "description": "Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies." + }, + "timeSeriesAttributeColumns": { + "items": { + "type": "string" + }, + "description": "Column names that should be used as attribute columns. The value of these columns does not vary as a function of time. For example, store ID or item color.", + "type": "array" + }, + "unavailableAtForecastColumns": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Names of columns that are unavailable when a forecast is requested. This column contains information for the given entity (identified by the time_series_identifier_column) that is unknown before the forecast For example, actual weather on a given day." + }, + "timeColumn": { + "description": "The name of the column that identifies time order in the time series. This column must be available at forecast.", + "type": "string" + }, + "targetColumn": { + "description": "The name of the column that the Model is to predict values for. This column must be unavailable at forecast.", + "type": "string" + }, + "availableAtForecastColumns": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Names of columns that are available and provided when a forecast is requested. These columns contain information for the given entity (identified by the time_series_identifier_column column) that is known at forecast. For example, predicted weather for a specific day." + }, + "validationOptions": { + "description": "Validation options for the data validation component. The available options are: * \"fail-pipeline\" - default, will validate against the validation and fail the pipeline if it fails. * \"ignore-validation\" - ignore the results of the validation and continue", + "type": "string" + }, + "timeSeriesIdentifierColumn": { + "type": "string", + "description": "The name of the column that identifies the time series." + }, + "forecastHorizon": { + "description": "The amount of time into the future for which forecasted values for the target are returned. Expressed in number of units defined by the `data_granularity` field.", + "type": "string", + "format": "int64" + }, + "exportEvaluatedDataItemsConfig": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig", + "description": "Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed." + }, + "contextWindow": { + "format": "int64", + "type": "string", + "description": "The amount of time into the past training and prediction data is used for model training and prediction respectively. Expressed in number of units defined by the `data_granularity` field." + }, + "additionalExperiments": { + "description": "Additional experiment flags for the time series forcasting training.", + "items": { + "type": "string" + }, + "type": "array" + }, + "transformations": { + "description": "Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using \".\" as the delimiter.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformation" + } + }, + "weightColumn": { + "type": "string", + "description": "Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1. This column must be available at forecast." + }, + "trainBudgetMilliNodeHours": { + "type": "string", + "description": "Required. The train budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The training cost of the model will not exceed this budget. The final cost will be attempted to be close to the budget, though may end up being (even) noticeably smaller - at the backend's discretion. This especially may happen when further model training ceases to provide any improvements. If the budget is set to a value known to be insufficient to train a model for the given dataset, the training won't be attempted and will error. The train budget must be between 1,000 and 72,000 milli node hours, inclusive.", + "format": "int64" + }, + "dataGranularity": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsGranularity", + "description": "Expected difference in time granularity between rows in the data." + }, + "optimizationObjective": { + "description": "Objective function the model is optimizing towards. The training process creates a model that optimizes the value of the objective function over the validation set. The supported optimization objectives: * \"minimize-rmse\" (default) - Minimize root-mean-squared error (RMSE). * \"minimize-mae\" - Minimize mean-absolute error (MAE). * \"minimize-rmsle\" - Minimize root-mean-squared log error (RMSLE). * \"minimize-rmspe\" - Minimize root-mean-squared percentage error (RMSPE). * \"minimize-wape-mae\" - Minimize the combination of weighted absolute percentage error (WAPE) and mean-absolute-error (MAE). * \"minimize-quantile-loss\" - Minimize the quantile loss at the quantiles defined in `quantiles`. * \"minimize-mape\" - Minimize the mean absolute percentage error.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputs" + }, + "GoogleCloudAiplatformV1SavedQuery": { + "type": "object", + "id": "GoogleCloudAiplatformV1SavedQuery", + "description": "A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.", + "properties": { + "annotationSpecCount": { + "format": "int32", + "description": "Output only. Number of AnnotationSpecs in the context of the SavedQuery.", + "type": "integer", + "readOnly": true + }, + "updateTime": { + "description": "Output only. Timestamp when SavedQuery was last updated.", + "readOnly": true, + "type": "string", + "format": "google-datetime" + }, + "name": { + "readOnly": true, + "description": "Output only. Resource name of the SavedQuery.", + "type": "string" + }, + "createTime": { + "format": "google-datetime", + "type": "string", + "description": "Output only. Timestamp when this SavedQuery was created.", + "readOnly": true + }, + "displayName": { + "description": "Required. The user-defined name of the SavedQuery. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + }, + "annotationFilter": { + "type": "string", + "readOnly": true, + "description": "Output only. Filters on the Annotations in the dataset." + }, + "metadata": { + "description": "Some additional information about the SavedQuery.", + "type": "any" + }, + "supportAutomlTraining": { + "type": "boolean", + "readOnly": true, + "description": "Output only. If the Annotations belonging to the SavedQuery can be used for AutoML training." + }, + "etag": { + "description": "Used to perform a consistent read-modify-write update. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "problemType": { + "type": "string", + "description": "Required. Problem type of the SavedQuery. Allowed values: * IMAGE_CLASSIFICATION_SINGLE_LABEL * IMAGE_CLASSIFICATION_MULTI_LABEL * IMAGE_BOUNDING_POLY * IMAGE_BOUNDING_BOX * TEXT_CLASSIFICATION_SINGLE_LABEL * TEXT_CLASSIFICATION_MULTI_LABEL * TEXT_EXTRACTION * TEXT_SENTIMENT * VIDEO_CLASSIFICATION * VIDEO_OBJECT_TRACKING" + } + } + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTrackMetricsConfidenceMetrics": { + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTrackMetricsConfidenceMetrics", + "properties": { + "trackingRecall": { + "format": "float", + "description": "Tracking recall.", + "type": "number" + }, + "mismatchRate": { + "format": "float", + "description": "Mismatch rate, which measures the tracking consistency, i.e. correctness of instance ID continuity.", + "type": "number" + }, + "boundingBoxIou": { + "description": "Bounding box intersection-over-union precision. Measures how well the bounding boxes overlap between each other (e.g. complete overlap or just barely above iou_threshold).", + "format": "float", + "type": "number" + }, + "confidenceThreshold": { + "format": "float", + "type": "number", + "description": "The confidence threshold value used to compute the metrics." + }, + "trackingPrecision": { + "type": "number", + "description": "Tracking precision.", + "format": "float" + } + }, + "description": "Metrics for a single confidence threshold." + }, + "GoogleCloudAiplatformV1SchemaVideoClassificationAnnotation": { + "properties": { + "annotationSpecId": { + "type": "string", + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." + }, + "timeSegment": { + "description": "This Annotation applies to the time period represented by the TimeSegment. If it's not set, the Annotation applies to the whole video.", + "$ref": "GoogleCloudAiplatformV1SchemaTimeSegment" + }, + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that this Annotation pertains to." + } + }, + "type": "object", + "description": "Annotation details specific to video classification.", + "id": "GoogleCloudAiplatformV1SchemaVideoClassificationAnnotation" + }, + "GoogleCloudAiplatformV1ComputeTokensRequest": { + "description": "Request message for ComputeTokens RPC call.", + "properties": { + "contents": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1Content" + }, + "description": "Optional. Input content." + }, + "instances": { + "type": "array", + "description": "Optional. The instances that are the input to token computing API call. Schema is identical to the prediction schema of the text model, even for the non-text models, like chat models, or Codey models.", + "items": { + "type": "any" + } + }, + "model": { + "description": "Optional. The name of the publisher model requested to serve the prediction. Format: projects/{project}/locations/{location}/publishers/*/models/*", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1ComputeTokensRequest" + }, + "GoogleCloudAiplatformV1MigrateResourceRequest": { + "properties": { + "migrateAutomlModelConfig": { + "$ref": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateAutomlModelConfig", + "description": "Config for migrating Model in automl.googleapis.com to Vertex AI's Model." + }, + "migrateMlEngineModelVersionConfig": { + "description": "Config for migrating Version in ml.googleapis.com to Vertex AI's Model.", + "$ref": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateMlEngineModelVersionConfig" + }, + "migrateAutomlDatasetConfig": { + "$ref": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateAutomlDatasetConfig", + "description": "Config for migrating Dataset in automl.googleapis.com to Vertex AI's Dataset." + }, + "migrateDataLabelingDatasetConfig": { + "$ref": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateDataLabelingDatasetConfig", + "description": "Config for migrating Dataset in datalabeling.googleapis.com to Vertex AI's Dataset." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1MigrateResourceRequest", + "description": "Config of migrating one resource from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI." + }, + "GoogleCloudAiplatformV1SchemaPredictParamsVideoActionRecognitionPredictionParams": { + "description": "Prediction model parameters for Video Action Recognition.", + "properties": { + "maxPredictions": { + "description": "The model only returns up to that many top, by confidence score, predictions per frame of the video. If this number is very high, the Model may return fewer predictions per frame. Default value is 50.", + "format": "int32", + "type": "integer" + }, + "confidenceThreshold": { + "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0", + "format": "float", + "type": "number" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaPredictParamsVideoActionRecognitionPredictionParams" + }, + "GoogleCloudAiplatformV1TunedModel": { + "id": "GoogleCloudAiplatformV1TunedModel", + "description": "The Model Registry Model and Online Prediction Endpoint assiociated with this TuningJob.", + "type": "object", + "properties": { + "model": { + "readOnly": true, + "description": "Output only. The resource name of the TunedModel. Format: `projects/{project}/locations/{location}/models/{model}`.", + "type": "string" + }, + "endpoint": { + "readOnly": true, + "description": "Output only. A resource name of an Endpoint. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1SchemaPredictParamsVideoObjectTrackingPredictionParams": { + "description": "Prediction model parameters for Video Object Tracking.", + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaPredictParamsVideoObjectTrackingPredictionParams", + "properties": { + "minBoundingBoxSize": { + "format": "float", + "description": "Only bounding boxes with shortest edge at least that long as a relative value of video frame size are returned. Default value is 0.0.", + "type": "number" + }, + "maxPredictions": { + "type": "integer", + "format": "int32", + "description": "The model only returns up to that many top, by confidence score, predictions per frame of the video. If this number is very high, the Model may return fewer predictions per frame. Default value is 50." + }, + "confidenceThreshold": { + "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0", + "type": "number", + "format": "float" + } + } + }, + "GoogleCloudAiplatformV1MigratableResource": { + "type": "object", + "properties": { + "dataLabelingDataset": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1MigratableResourceDataLabelingDataset", + "description": "Output only. Represents one Dataset in datalabeling.googleapis.com." + }, + "automlModel": { + "$ref": "GoogleCloudAiplatformV1MigratableResourceAutomlModel", + "readOnly": true, + "description": "Output only. Represents one Model in automl.googleapis.com." + }, + "automlDataset": { + "$ref": "GoogleCloudAiplatformV1MigratableResourceAutomlDataset", + "description": "Output only. Represents one Dataset in automl.googleapis.com.", + "readOnly": true + }, + "lastUpdateTime": { + "description": "Output only. Timestamp when this MigratableResource was last updated.", + "type": "string", + "readOnly": true, + "format": "google-datetime" + }, + "lastMigrateTime": { + "description": "Output only. Timestamp when the last migration attempt on this MigratableResource started. Will not be set if there's no migration attempt on this MigratableResource.", + "readOnly": true, + "format": "google-datetime", + "type": "string" + }, + "mlEngineModelVersion": { + "$ref": "GoogleCloudAiplatformV1MigratableResourceMlEngineModelVersion", + "readOnly": true, + "description": "Output only. Represents one Version in ml.googleapis.com." + } + }, + "id": "GoogleCloudAiplatformV1MigratableResource", + "description": "Represents one resource that exists in automl.googleapis.com, datalabeling.googleapis.com or ml.googleapis.com." + }, + "GoogleCloudAiplatformV1ExamplesRestrictionsNamespace": { + "description": "Restrictions namespace for example-based explanations overrides.", + "properties": { + "namespaceName": { + "type": "string", + "description": "The namespace name." + }, + "deny": { + "items": { + "type": "string" + }, + "description": "The list of deny tags.", + "type": "array" + }, + "allow": { + "items": { + "type": "string" + }, + "description": "The list of allowed tags.", + "type": "array" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1ExamplesRestrictionsNamespace" + }, + "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotationPolygonAnnotation": { + "id": "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotationPolygonAnnotation", + "properties": { + "displayName": { + "description": "The display name of the AnnotationSpec that this Annotation pertains to.", + "type": "string" + }, + "vertexes": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaVertex" + }, + "description": "The vertexes are connected one by one and the last vertex is connected to the first one to represent a polygon." + }, + "annotationSpecId": { + "type": "string", + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." + } + }, + "description": "Represents a polygon in image.", + "type": "object" + }, + "GoogleCloudAiplatformV1FindNeighborsRequestQuery": { + "id": "GoogleCloudAiplatformV1FindNeighborsRequestQuery", + "type": "object", + "properties": { + "approximateNeighborCount": { + "format": "int32", + "type": "integer", + "description": "The number of neighbors to find via approximate search before exact reordering is performed. If not set, the default value from scam config is used; if set, this value must be \u003e 0." + }, + "fractionLeafNodesToSearchOverride": { + "description": "The fraction of the number of leaves to search, set at query time allows user to tune search performance. This value increase result in both search accuracy and latency increase. The value should be between 0.0 and 1.0. If not set or set to 0.0, query uses the default value specified in NearestNeighborSearchConfig.TreeAHConfig.fraction_leaf_nodes_to_search.", + "format": "double", + "type": "number" + }, + "rrf": { + "$ref": "GoogleCloudAiplatformV1FindNeighborsRequestQueryRRF", + "description": "Optional. Represents RRF algorithm that combines search results." + }, + "datapoint": { + "$ref": "GoogleCloudAiplatformV1IndexDatapoint", + "description": "Required. The datapoint/vector whose nearest neighbors should be searched for." + }, + "perCrowdingAttributeNeighborCount": { + "type": "integer", + "format": "int32", + "description": "Crowding is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than some value k' of the k neighbors returned have the same value of crowding_attribute. It's used for improving result diversity. This field is the maximum number of matches with the same crowding tag." + }, + "neighborCount": { + "type": "integer", + "format": "int32", + "description": "The number of nearest neighbors to be retrieved from database for each query. If not set, will use the default from the service configuration (https://cloud.google.com/vertex-ai/docs/matching-engine/configuring-indexes#nearest-neighbor-search-config)." + } + }, + "description": "A query to find a number of the nearest neighbors (most similar vectors) of a vector." + }, + "GoogleCloudAiplatformV1StudySpecStudyStoppingConfig": { + "id": "GoogleCloudAiplatformV1StudySpecStudyStoppingConfig", + "description": "The configuration (stopping conditions) for automated stopping of a Study. Conditions include trial budgets, time budgets, and convergence detection.", + "properties": { + "shouldStopAsap": { + "description": "If true, a Study enters STOPPING_ASAP whenever it would normally enters STOPPING state. The bottom line is: set to true if you want to interrupt on-going evaluations of Trials as soon as the study stopping condition is met. (Please see Study.State documentation for the source of truth).", + "type": "boolean" + }, + "minNumTrials": { + "description": "If there are fewer than this many COMPLETED trials, do not stop the study.", + "format": "int32", + "type": "integer" + }, + "minimumRuntimeConstraint": { + "$ref": "GoogleCloudAiplatformV1StudyTimeConstraint", + "description": "Each \"stopping rule\" in this proto specifies an \"if\" condition. Before Vizier would generate a new suggestion, it first checks each specified stopping rule, from top to bottom in this list. Note that the first few rules (e.g. minimum_runtime_constraint, min_num_trials) will prevent other stopping rules from being evaluated until they are met. For example, setting `min_num_trials=5` and `always_stop_after= 1 hour` means that the Study will ONLY stop after it has 5 COMPLETED trials, even if more than an hour has passed since its creation. It follows the first applicable rule (whose \"if\" condition is satisfied) to make a stopping decision. If none of the specified rules are applicable, then Vizier decides that the study should not stop. If Vizier decides that the study should stop, the study enters STOPPING state (or STOPPING_ASAP if should_stop_asap = true). IMPORTANT: The automatic study state transition happens precisely as described above; that is, deleting trials or updating StudyConfig NEVER automatically moves the study state back to ACTIVE. If you want to _resume_ a Study that was stopped, 1) change the stopping conditions if necessary, 2) activate the study, and then 3) ask for suggestions. If the specified time or duration has not passed, do not stop the study." + }, + "maxDurationNoProgress": { + "type": "string", + "format": "google-duration", + "description": "If the objective value has not improved for this much time, stop the study. WARNING: Effective only for single-objective studies." + }, + "maxNumTrialsNoProgress": { + "description": "If the objective value has not improved for this many consecutive trials, stop the study. WARNING: Effective only for single-objective studies.", + "format": "int32", + "type": "integer" + }, + "maxNumTrials": { + "format": "int32", + "type": "integer", + "description": "If there are more than this many trials, stop the study." + }, + "maximumRuntimeConstraint": { + "description": "If the specified time or duration has passed, stop the study.", + "$ref": "GoogleCloudAiplatformV1StudyTimeConstraint" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1ExportModelResponse": { + "type": "object", + "id": "GoogleCloudAiplatformV1ExportModelResponse", + "description": "Response message of ModelService.ExportModel operation.", + "properties": {} + }, + "GoogleCloudAiplatformV1ToolConfig": { + "id": "GoogleCloudAiplatformV1ToolConfig", + "description": "Tool config. This config is shared for all tools provided in the request.", + "properties": { + "functionCallingConfig": { + "description": "Optional. Function calling config.", + "$ref": "GoogleCloudAiplatformV1FunctionCallingConfig" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata": { + "type": "object", + "description": "All metadata of most recent monitoring pipelines.", + "properties": { + "status": { + "$ref": "GoogleRpcStatus", + "description": "The status of the most recent monitoring pipeline." + }, + "runTime": { + "type": "string", + "description": "The time that most recent monitoring pipelines that is related to this run.", + "format": "google-datetime" + } + }, + "id": "GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata" + }, + "GoogleCloudAiplatformV1ExplanationSpec": { + "type": "object", + "properties": { + "metadata": { + "$ref": "GoogleCloudAiplatformV1ExplanationMetadata", + "description": "Optional. Metadata describing the Model's input and output for explanation." + }, + "parameters": { + "$ref": "GoogleCloudAiplatformV1ExplanationParameters", + "description": "Required. Parameters that configure explaining of the Model's predictions." + } + }, + "id": "GoogleCloudAiplatformV1ExplanationSpec", + "description": "Specification of Model explanation." + }, + "GoogleCloudAiplatformV1ToolParameterKVMatchSpec": { + "properties": { + "useStrictStringMatch": { + "type": "boolean", + "description": "Optional. Whether to use STRCIT string match on parameter values." + } + }, + "type": "object", + "description": "Spec for tool parameter key value match metric.", + "id": "GoogleCloudAiplatformV1ToolParameterKVMatchSpec" + }, + "GoogleCloudAiplatformV1CreateSpecialistPoolOperationMetadata": { + "id": "GoogleCloudAiplatformV1CreateSpecialistPoolOperationMetadata", + "description": "Runtime operation information for SpecialistPoolService.CreateSpecialistPool.", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The operation generic information." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1PipelineTaskExecutorDetail": { + "id": "GoogleCloudAiplatformV1PipelineTaskExecutorDetail", + "type": "object", + "properties": { + "customJobDetail": { + "$ref": "GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetail", + "description": "Output only. The detailed info for a custom job executor.", + "readOnly": true + }, + "containerDetail": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetail", + "description": "Output only. The detailed info for a container executor." + } + }, + "description": "The runtime detail of a pipeline executor." + }, + "GoogleCloudAiplatformV1FeatureGroupBigQuery": { + "id": "GoogleCloudAiplatformV1FeatureGroupBigQuery", + "type": "object", + "properties": { + "entityIdColumns": { + "type": "array", + "description": "Optional. Columns to construct entity_id / row keys. If not provided defaults to `entity_id`.", + "items": { + "type": "string" + } + }, + "bigQuerySource": { + "$ref": "GoogleCloudAiplatformV1BigQuerySource", + "description": "Required. Immutable. The BigQuery source URI that points to either a BigQuery Table or View." + } + }, + "description": "Input source type for BigQuery Tables and Views." + }, + "GoogleCloudAiplatformV1TimestampSplit": { + "properties": { + "validationFraction": { + "format": "double", + "description": "The fraction of the input data that is to be used to validate the Model.", + "type": "number" + }, + "testFraction": { + "type": "number", + "format": "double", + "description": "The fraction of the input data that is to be used to evaluate the Model." + }, + "trainingFraction": { + "description": "The fraction of the input data that is to be used to train the Model.", + "type": "number", + "format": "double" + }, + "key": { + "description": "Required. The key is a name of one of the Dataset's data columns. The values of the key (the values in the column) must be in RFC 3339 `date-time` format, where `time-offset` = `\"Z\"` (e.g. 1985-04-12T23:20:50.52Z). If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1TimestampSplit", + "description": "Assigns input data to training, validation, and test sets based on a provided timestamps. The youngest data pieces are assigned to training set, next to validation set, and the oldest to the test set. Supported only for tabular Datasets.", + "type": "object" + }, + "GoogleCloudAiplatformV1CancelHyperparameterTuningJobRequest": { + "properties": {}, + "type": "object", + "id": "GoogleCloudAiplatformV1CancelHyperparameterTuningJobRequest", + "description": "Request message for JobService.CancelHyperparameterTuningJob." + }, + "GoogleCloudAiplatformV1PauseModelDeploymentMonitoringJobRequest": { + "type": "object", + "properties": {}, + "description": "Request message for JobService.PauseModelDeploymentMonitoringJob.", + "id": "GoogleCloudAiplatformV1PauseModelDeploymentMonitoringJobRequest" + }, + "GoogleCloudAiplatformV1NearestNeighborsNeighbor": { + "description": "A neighbor of the query vector.", + "type": "object", + "id": "GoogleCloudAiplatformV1NearestNeighborsNeighbor", + "properties": { + "entityKeyValues": { + "$ref": "GoogleCloudAiplatformV1FetchFeatureValuesResponse", + "description": "The attributes of the neighbor, e.g. filters, crowding and metadata Note that full entities are returned only when \"return_full_entity\" is set to true. Otherwise, only the \"entity_id\" and \"distance\" fields are populated." + }, + "entityId": { + "type": "string", + "description": "The id of the similar entity." + }, + "distance": { + "description": "The distance between the neighbor and the query vector.", + "format": "double", + "type": "number" + } + } + }, + "GoogleCloudAiplatformV1DeleteFeatureValuesResponse": { + "properties": { + "selectTimeRangeAndFeature": { + "$ref": "GoogleCloudAiplatformV1DeleteFeatureValuesResponseSelectTimeRangeAndFeature", + "description": "Response for request specifying time range and feature" + }, + "selectEntity": { + "description": "Response for request specifying the entities to delete", + "$ref": "GoogleCloudAiplatformV1DeleteFeatureValuesResponseSelectEntity" + } + }, + "id": "GoogleCloudAiplatformV1DeleteFeatureValuesResponse", + "description": "Response message for FeaturestoreService.DeleteFeatureValues.", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTextExtractionAnnotation": { + "properties": { + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that this Annotation pertains to." + }, + "annotationSpecId": { + "type": "string", + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." + }, + "textSegment": { + "description": "The segment of the text content.", + "$ref": "GoogleCloudAiplatformV1SchemaTextSegment" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTextExtractionAnnotation", + "description": "Annotation details specific to text extraction.", + "type": "object" + }, + "GoogleCloudAiplatformV1ListOptimalTrialsResponse": { + "id": "GoogleCloudAiplatformV1ListOptimalTrialsResponse", + "type": "object", + "description": "Response message for VizierService.ListOptimalTrials.", + "properties": { + "optimalTrials": { + "items": { + "$ref": "GoogleCloudAiplatformV1Trial" + }, + "description": "The pareto-optimal Trials for multiple objective Study or the optimal trial for single objective Study. The definition of pareto-optimal can be checked in wiki page. https://en.wikipedia.org/wiki/Pareto_efficiency", + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1GenerateContentRequest": { + "id": "GoogleCloudAiplatformV1GenerateContentRequest", + "type": "object", + "description": "Request message for [PredictionService.GenerateContent].", + "properties": { + "generationConfig": { + "description": "Optional. Generation config.", + "$ref": "GoogleCloudAiplatformV1GenerationConfig" + }, + "safetySettings": { + "description": "Optional. Per request settings for blocking unsafe content. Enforced on GenerateContentResponse.candidates.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1SafetySetting" + } + }, + "systemInstruction": { + "description": "Optional. The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph.", + "$ref": "GoogleCloudAiplatformV1Content" + }, + "contents": { + "items": { + "$ref": "GoogleCloudAiplatformV1Content" + }, + "type": "array", + "description": "Required. The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request." + }, + "toolConfig": { + "$ref": "GoogleCloudAiplatformV1ToolConfig", + "description": "Optional. Tool config. This config is shared for all tools provided in the request." + }, + "tools": { + "description": "Optional. A list of `Tools` the model may use to generate the next response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model.", + "items": { + "$ref": "GoogleCloudAiplatformV1Tool" + }, + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1ExplanationMetadataOverrideInputMetadataOverride": { + "id": "GoogleCloudAiplatformV1ExplanationMetadataOverrideInputMetadataOverride", + "description": "The input metadata entries to be overridden.", + "type": "object", + "properties": { + "inputBaselines": { + "items": { + "type": "any" + }, + "type": "array", + "description": "Baseline inputs for this feature. This overrides the `input_baseline` field of the ExplanationMetadata.InputMetadata object of the corresponding feature's input metadata. If it's not specified, the original baselines are not overridden." + } + } + }, + "GoogleCloudAiplatformV1PscInterfaceConfig": { + "type": "object", + "properties": { + "networkAttachment": { + "type": "string", + "description": "Optional. The full name of the Compute Engine [network attachment](https://cloud.google.com/vpc/docs/about-network-attachments) to attach to the resource. For example, `projects/12345/regions/us-central1/networkAttachments/myNA`. is of the form `projects/{project}/regions/{region}/networkAttachments/{networkAttachment}`. Where {project} is a project number, as in `12345`, and {networkAttachment} is a network attachment name. To specify this field, you must have already [created a network attachment] (https://cloud.google.com/vpc/docs/create-manage-network-attachments#create-network-attachments). This field is only used for resources using PSC-I." + } + }, + "description": "Configuration for PSC-I.", + "id": "GoogleCloudAiplatformV1PscInterfaceConfig" + }, + "GoogleCloudAiplatformV1UploadModelOperationMetadata": { + "description": "Details of ModelService.UploadModel operation.", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The common part of the operation metadata." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1UploadModelOperationMetadata" + }, + "GoogleCloudAiplatformV1UpdateModelDeploymentMonitoringJobOperationMetadata": { + "id": "GoogleCloudAiplatformV1UpdateModelDeploymentMonitoringJobOperationMetadata", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The operation generic information." + } + }, + "type": "object", + "description": "Runtime operation information for JobService.UpdateModelDeploymentMonitoringJob." + }, + "GoogleCloudAiplatformV1DeleteFeatureValuesRequestSelectTimeRangeAndFeature": { + "description": "Message to select time range and feature. Values of the selected feature generated within an inclusive time range will be deleted. Using this option permanently deletes the feature values from the specified feature IDs within the specified time range. This might include data from the online storage. If you want to retain any deleted historical data in the online storage, you must re-ingest it.", + "type": "object", + "id": "GoogleCloudAiplatformV1DeleteFeatureValuesRequestSelectTimeRangeAndFeature", + "properties": { + "timeRange": { + "$ref": "GoogleTypeInterval", + "description": "Required. Select feature generated within a half-inclusive time range. The time range is lower inclusive and upper exclusive." + }, + "featureSelector": { + "description": "Required. Selectors choosing which feature values to be deleted from the EntityType.", + "$ref": "GoogleCloudAiplatformV1FeatureSelector" + }, + "skipOnlineStorageDelete": { + "type": "boolean", + "description": "If set, data will not be deleted from online storage. When time range is older than the data in online storage, setting this to be true will make the deletion have no impact on online serving." + } + } + }, + "GoogleCloudAiplatformV1FractionSplit": { + "description": "Assigns the input data to training, validation, and test sets as per the given fractions. Any of `training_fraction`, `validation_fraction` and `test_fraction` may optionally be provided, they must sum to up to 1. If the provided ones sum to less than 1, the remainder is assigned to sets as decided by Vertex AI. If none of the fractions are set, by default roughly 80% of data is used for training, 10% for validation, and 10% for test.", + "properties": { + "validationFraction": { + "format": "double", + "description": "The fraction of the input data that is to be used to validate the Model.", + "type": "number" + }, + "trainingFraction": { + "type": "number", + "description": "The fraction of the input data that is to be used to train the Model.", + "format": "double" + }, + "testFraction": { + "type": "number", + "format": "double", + "description": "The fraction of the input data that is to be used to evaluate the Model." + } + }, + "id": "GoogleCloudAiplatformV1FractionSplit", + "type": "object" + }, + "GoogleCloudAiplatformV1Tensor": { + "id": "GoogleCloudAiplatformV1Tensor", + "type": "object", + "description": "A tensor value type.", + "properties": { + "doubleVal": { + "type": "array", + "description": "DOUBLE", + "items": { + "format": "double", + "type": "number" + } + }, + "shape": { + "type": "array", + "description": "Shape of the tensor.", + "items": { + "format": "int64", + "type": "string" + } + }, + "intVal": { + "type": "array", + "description": "INT_8 INT_16 INT_32", + "items": { + "format": "int32", + "type": "integer" + } + }, + "uint64Val": { + "items": { + "format": "uint64", + "type": "string" + }, + "description": "UINT64", + "type": "array" + }, + "tensorVal": { + "format": "byte", + "type": "string", + "description": "Serialized raw tensor content." + }, + "bytesVal": { + "items": { + "type": "string", + "format": "byte" + }, + "description": "STRING", + "type": "array" + }, + "stringVal": { + "type": "array", + "items": { + "type": "string" + }, + "description": "STRING" + }, + "floatVal": { + "items": { + "type": "number", + "format": "float" + }, + "description": "FLOAT", + "type": "array" + }, + "int64Val": { + "type": "array", + "items": { + "format": "int64", + "type": "string" + }, + "description": "INT64" + }, + "dtype": { + "type": "string", + "enum": [ + "DATA_TYPE_UNSPECIFIED", + "BOOL", + "STRING", + "FLOAT", + "DOUBLE", + "INT8", + "INT16", + "INT32", + "INT64", + "UINT8", + "UINT16", + "UINT32", + "UINT64" + ], + "description": "The data type of tensor.", + "enumDescriptions": [ + "Not a legal value for DataType. Used to indicate a DataType field has not been set.", + "Data types that all computation devices are expected to be capable to support.", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "" + ] + }, + "listVal": { + "items": { + "$ref": "GoogleCloudAiplatformV1Tensor" + }, + "description": "A list of tensor values.", + "type": "array" + }, + "boolVal": { + "items": { + "type": "boolean" + }, + "type": "array", + "description": "Type specific representations that make it easy to create tensor protos in all languages. Only the representation corresponding to \"dtype\" can be set. The values hold the flattened representation of the tensor in row major order. BOOL" + }, + "uintVal": { + "description": "UINT8 UINT16 UINT32", + "type": "array", + "items": { + "type": "integer", + "format": "uint32" + } + }, + "structVal": { + "description": "A map of string to tensor.", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1Tensor" + }, + "type": "object" + } + } + }, + "GoogleCloudAiplatformV1SchemaPredictPredictionImageObjectDetectionPredictionResult": { + "type": "object", + "description": "Prediction output format for Image Object Detection.", + "properties": { + "ids": { + "type": "array", + "description": "The resource IDs of the AnnotationSpecs that had been identified, ordered by the confidence score descendingly.", + "items": { + "type": "string", + "format": "int64" + } + }, + "displayNames": { + "description": "The display names of the AnnotationSpecs that had been identified, order matches the IDs.", + "type": "array", + "items": { + "type": "string" + } + }, + "bboxes": { + "items": { + "type": "array", + "items": { + "type": "any" + } + }, + "description": "Bounding boxes, i.e. the rectangles over the image, that pinpoint the found AnnotationSpecs. Given in order that matches the IDs. Each bounding box is an array of 4 numbers `xMin`, `xMax`, `yMin`, and `yMax`, which represent the extremal coordinates of the box. They are relative to the image size, and the point 0,0 is in the top left of the image.", + "type": "array" + }, + "confidences": { + "items": { + "format": "float", + "type": "number" + }, + "type": "array", + "description": "The Model's confidences in correctness of the predicted IDs, higher value means higher confidence. Order matches the Ids." + } + }, + "id": "GoogleCloudAiplatformV1SchemaPredictPredictionImageObjectDetectionPredictionResult" + }, + "GoogleCloudAiplatformV1SearchModelDeploymentMonitoringStatsAnomaliesRequest": { + "type": "object", + "properties": { + "endTime": { + "type": "string", + "description": "The latest timestamp of stats being generated. If not set, indicates feching stats till the latest possible one.", + "format": "google-datetime" + }, + "startTime": { + "type": "string", + "format": "google-datetime", + "description": "The earliest timestamp of stats being generated. If not set, indicates fetching stats till the earliest possible one." + }, + "pageSize": { + "format": "int32", + "type": "integer", + "description": "The standard list page size." + }, + "deployedModelId": { + "type": "string", + "description": "Required. The DeployedModel ID of the [ModelDeploymentMonitoringObjectiveConfig.deployed_model_id]." + }, + "featureDisplayName": { + "type": "string", + "description": "The feature display name. If specified, only return the stats belonging to this feature. Format: ModelMonitoringStatsAnomalies.FeatureHistoricStatsAnomalies.feature_display_name, example: \"user_destination\"." + }, + "objectives": { + "items": { + "$ref": "GoogleCloudAiplatformV1SearchModelDeploymentMonitoringStatsAnomaliesRequestStatsAnomaliesObjective" + }, + "type": "array", + "description": "Required. Objectives of the stats to retrieve." + }, + "pageToken": { + "type": "string", + "description": "A page token received from a previous JobService.SearchModelDeploymentMonitoringStatsAnomalies call." + } + }, + "description": "Request message for JobService.SearchModelDeploymentMonitoringStatsAnomalies.", + "id": "GoogleCloudAiplatformV1SearchModelDeploymentMonitoringStatsAnomaliesRequest" + }, + "GoogleCloudAiplatformV1ToolCallValidMetricValue": { + "type": "object", + "description": "Tool call valid metric value for an instance.", + "properties": { + "score": { + "format": "float", + "description": "Output only. Tool call valid score.", + "type": "number", + "readOnly": true + } + }, + "id": "GoogleCloudAiplatformV1ToolCallValidMetricValue" + }, + "GoogleCloudAiplatformV1CompletionStats": { + "id": "GoogleCloudAiplatformV1CompletionStats", + "type": "object", + "properties": { + "successfulForecastPointCount": { + "readOnly": true, + "type": "string", + "format": "int64", + "description": "Output only. The number of the successful forecast points that are generated by the forecasting model. This is ONLY used by the forecasting batch prediction." + }, + "successfulCount": { + "format": "int64", + "readOnly": true, + "description": "Output only. The number of entities that had been processed successfully.", + "type": "string" + }, + "failedCount": { + "description": "Output only. The number of entities for which any error was encountered.", + "format": "int64", + "readOnly": true, + "type": "string" + }, + "incompleteCount": { + "type": "string", + "readOnly": true, + "format": "int64", + "description": "Output only. In cases when enough errors are encountered a job, pipeline, or operation may be failed as a whole. Below is the number of entities for which the processing had not been finished (either in successful or failed state). Set to -1 if the number is unknown (for example, the operation failed before the total entity number could be collected)." + } + }, + "description": "Success and error statistics of processing multiple entities (for example, DataItems or structured data rows) in batch." + }, + "GoogleCloudAiplatformV1NearestNeighborQueryEmbedding": { + "description": "The embedding vector.", + "properties": { + "value": { + "description": "Optional. Individual value in the embedding.", + "items": { + "format": "float", + "type": "number" + }, + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1NearestNeighborQueryEmbedding", + "type": "object" + }, + "GoogleCloudAiplatformV1CoherenceInstance": { + "properties": { + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + } + }, + "description": "Spec for coherence instance.", + "id": "GoogleCloudAiplatformV1CoherenceInstance", + "type": "object" + }, + "GoogleCloudAiplatformV1SuggestTrialsMetadata": { + "properties": { + "genericMetadata": { + "description": "Operation metadata for suggesting Trials.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + }, + "clientId": { + "description": "The identifier of the client that is requesting the suggestion. If multiple SuggestTrialsRequests have the same `client_id`, the service will return the identical suggested Trial if the Trial is pending, and provide a new Trial if the last suggested Trial was completed.", + "type": "string" + } + }, + "description": "Details of operations that perform Trials suggestion.", + "id": "GoogleCloudAiplatformV1SuggestTrialsMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1SummarizationHelpfulnessInput": { + "id": "GoogleCloudAiplatformV1SummarizationHelpfulnessInput", + "description": "Input for summarization helpfulness metric.", + "properties": { + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1SummarizationHelpfulnessSpec", + "description": "Required. Spec for summarization helpfulness score metric." + }, + "instance": { + "$ref": "GoogleCloudAiplatformV1SummarizationHelpfulnessInstance", + "description": "Required. Summarization helpfulness instance." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaImageBoundingBoxAnnotation": { + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaImageBoundingBoxAnnotation", + "description": "Annotation details specific to image object detection.", + "properties": { + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that this Annotation pertains to." + }, + "xMax": { + "type": "number", + "format": "double", + "description": "The rightmost coordinate of the bounding box." + }, + "yMin": { + "description": "The topmost coordinate of the bounding box.", + "type": "number", + "format": "double" + }, + "annotationSpecId": { + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", + "type": "string" + }, + "yMax": { + "description": "The bottommost coordinate of the bounding box.", + "type": "number", + "format": "double" + }, + "xMin": { + "type": "number", + "description": "The leftmost coordinate of the bounding box.", + "format": "double" + } + } + }, + "GoogleCloudAiplatformV1FeaturestoreMonitoringConfig": { + "description": "Configuration of how features in Featurestore are monitored.", + "type": "object", + "id": "GoogleCloudAiplatformV1FeaturestoreMonitoringConfig", + "properties": { + "numericalThresholdConfig": { + "$ref": "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig", + "description": "Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64)." + }, + "snapshotAnalysis": { + "$ref": "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis", + "description": "The config for Snapshot Analysis Based Feature Monitoring." + }, + "categoricalThresholdConfig": { + "description": "Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).", + "$ref": "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig" + }, + "importFeaturesAnalysis": { + "$ref": "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis", + "description": "The config for ImportFeatures Analysis Based Feature Monitoring." + } + } + }, + "GoogleCloudAiplatformV1ErrorAnalysisAnnotation": { + "type": "object", + "id": "GoogleCloudAiplatformV1ErrorAnalysisAnnotation", + "description": "Model error analysis for each annotation.", + "properties": { + "attributedItems": { + "items": { + "$ref": "GoogleCloudAiplatformV1ErrorAnalysisAnnotationAttributedItem" + }, + "type": "array", + "description": "Attributed items for a given annotation, typically representing neighbors from the training sets constrained by the query type." + }, + "queryType": { + "type": "string", + "enumDescriptions": [ + "Unspecified query type for model error analysis.", + "Query similar samples across all classes in the dataset.", + "Query similar samples from the same class of the input sample.", + "Query dissimilar samples from the same class of the input sample." + ], + "enum": [ + "QUERY_TYPE_UNSPECIFIED", + "ALL_SIMILAR", + "SAME_CLASS_SIMILAR", + "SAME_CLASS_DISSIMILAR" + ], + "description": "The query type used for finding the attributed items." + }, + "outlierScore": { + "format": "double", + "description": "The outlier score of this annotated item. Usually defined as the min of all distances from attributed items.", + "type": "number" + }, + "outlierThreshold": { + "format": "double", + "type": "number", + "description": "The threshold used to determine if this annotation is an outlier or not." + } + } + }, + "GoogleCloudAiplatformV1TuningDataStats": { + "description": "The tuning data statistic values for TuningJob.", + "type": "object", + "id": "GoogleCloudAiplatformV1TuningDataStats", + "properties": { + "supervisedTuningDataStats": { + "description": "The SFT Tuning data stats.", + "$ref": "GoogleCloudAiplatformV1SupervisedTuningDataStats" + } + } + }, + "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpecValue": { + "type": "object", + "id": "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpecValue", + "properties": { + "stringValue": { + "type": "string", + "description": "String type." + }, + "floatValue": { + "format": "float", + "type": "number", + "description": "Float type." + } + }, + "description": "Single value that supports strings and floats." + }, + "GoogleCloudAiplatformV1GenerationConfig": { + "type": "object", + "id": "GoogleCloudAiplatformV1GenerationConfig", + "properties": { + "responseMimeType": { + "description": "Optional. Output response mimetype of the generated candidate text. Supported mimetype: - `text/plain`: (default) Text output. - `application/json`: JSON response in the candidates. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. This is a preview feature.", + "type": "string" + }, + "topK": { + "type": "number", + "description": "Optional. If specified, top-k sampling will be used.", + "format": "float" + }, + "topP": { + "description": "Optional. If specified, nucleus sampling will be used.", + "format": "float", + "type": "number" + }, + "temperature": { + "format": "float", + "description": "Optional. Controls the randomness of predictions.", + "type": "number" + }, + "maxOutputTokens": { + "type": "integer", + "description": "Optional. The maximum number of output tokens to generate per message.", + "format": "int32" + }, + "responseSchema": { + "$ref": "GoogleCloudAiplatformV1Schema", + "description": "Optional. The `Schema` object allows the definition of input and output data types. These types can be objects, but also primitives and arrays. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema). If set, a compatible response_mime_type must also be set. Compatible mimetypes: `application/json`: Schema for JSON response." + }, + "presencePenalty": { + "type": "number", + "format": "float", + "description": "Optional. Positive penalties." + }, + "candidateCount": { + "format": "int32", + "type": "integer", + "description": "Optional. Number of candidates to generate." + }, + "stopSequences": { + "description": "Optional. Stop sequences.", + "items": { + "type": "string" + }, + "type": "array" + }, + "frequencyPenalty": { + "description": "Optional. Frequency penalties.", + "type": "number", + "format": "float" + } + }, + "description": "Generation config." + }, + "GoogleCloudAiplatformV1ListContextsResponse": { + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token, which can be sent as ListContextsRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages." + }, + "contexts": { + "type": "array", + "description": "The Contexts retrieved from the MetadataStore.", + "items": { + "$ref": "GoogleCloudAiplatformV1Context" + } + } + }, + "type": "object", + "description": "Response message for MetadataService.ListContexts.", + "id": "GoogleCloudAiplatformV1ListContextsResponse" + }, + "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpec": { + "properties": { + "goal": { + "type": "string", + "description": "Required. The optimization goal of the metric.", + "enumDescriptions": [ + "Goal Type will default to maximize.", + "Maximize the goal metric.", + "Minimize the goal metric." + ], + "enum": [ + "GOAL_TYPE_UNSPECIFIED", + "MAXIMIZE", + "MINIMIZE" + ] + }, + "metricId": { + "type": "string", + "description": "Required. The ID of the metric. Must not contain whitespaces." + } + }, + "id": "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpec", + "description": "Represents a metric to optimize.", + "type": "object" + }, + "GoogleCloudAiplatformV1NotebookRuntime": { + "id": "GoogleCloudAiplatformV1NotebookRuntime", + "type": "object", + "description": "A runtime is a virtual machine allocated to a particular user for a particular Notebook file on temporary basis with lifetime limited to 24 hours.", + "properties": { + "updateTime": { + "readOnly": true, + "description": "Output only. Timestamp when this NotebookRuntime was most recently updated.", + "format": "google-datetime", + "type": "string" + }, + "runtimeUser": { + "description": "Required. The user email of the NotebookRuntime.", + "type": "string" + }, + "idleShutdownConfig": { + "$ref": "GoogleCloudAiplatformV1NotebookIdleShutdownConfig", + "readOnly": true, + "description": "Output only. The idle shutdown configuration of the notebook runtime." + }, + "notebookRuntimeType": { + "enum": [ + "NOTEBOOK_RUNTIME_TYPE_UNSPECIFIED", + "USER_DEFINED", + "ONE_CLICK" + ], + "enumDescriptions": [ + "Unspecified notebook runtime type, NotebookRuntimeType will default to USER_DEFINED.", + "runtime or template with coustomized configurations from user.", + "runtime or template with system defined configurations." + ], + "readOnly": true, + "type": "string", + "description": "Output only. The type of the notebook runtime." + }, + "expirationTime": { + "type": "string", + "description": "Output only. Timestamp when this NotebookRuntime will be expired: 1. System Predefined NotebookRuntime: 24 hours after creation. After expiration, system predifined runtime will be deleted. 2. User created NotebookRuntime: 6 months after last upgrade. After expiration, user created runtime will be stopped and allowed for upgrade.", + "readOnly": true, + "format": "google-datetime" + }, + "notebookRuntimeTemplateRef": { + "description": "Output only. The pointer to NotebookRuntimeTemplate this NotebookRuntime is created from.", + "$ref": "GoogleCloudAiplatformV1NotebookRuntimeTemplateRef", + "readOnly": true + }, + "encryptionSpec": { + "readOnly": true, + "description": "Output only. Customer-managed encryption key spec for the notebook runtime.", + "$ref": "GoogleCloudAiplatformV1EncryptionSpec" + }, + "description": { + "type": "string", + "description": "The description of the NotebookRuntime." + }, + "createTime": { + "type": "string", + "description": "Output only. Timestamp when this NotebookRuntime was created.", + "readOnly": true, + "format": "google-datetime" + }, + "proxyUri": { + "type": "string", + "readOnly": true, + "description": "Output only. The proxy endpoint used to access the NotebookRuntime." + }, + "version": { + "readOnly": true, + "type": "string", + "description": "Output only. The VM os image version of NotebookRuntime." + }, + "satisfiesPzs": { + "readOnly": true, + "type": "boolean", + "description": "Output only. Reserved for future use." + }, + "isUpgradable": { + "readOnly": true, + "description": "Output only. Whether NotebookRuntime is upgradable.", + "type": "boolean" + }, + "satisfiesPzi": { + "description": "Output only. Reserved for future use.", + "type": "boolean", + "readOnly": true + }, + "displayName": { + "description": "Required. The display name of the NotebookRuntime. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + }, + "serviceAccount": { + "type": "string", + "description": "Output only. The service account that the NotebookRuntime workload runs as.", + "readOnly": true + }, + "healthState": { + "description": "Output only. The health state of the NotebookRuntime.", + "type": "string", + "enumDescriptions": [ + "Unspecified health state.", + "NotebookRuntime is in healthy state. Applies to ACTIVE state.", + "NotebookRuntime is in unhealthy state. Applies to ACTIVE state." + ], + "readOnly": true, + "enum": [ + "HEALTH_STATE_UNSPECIFIED", + "HEALTHY", + "UNHEALTHY" + ] + }, + "labels": { + "description": "The labels with user-defined metadata to organize your NotebookRuntime. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one NotebookRuntime (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable. Following system labels exist for NotebookRuntime: * \"aiplatform.googleapis.com/notebook_runtime_gce_instance_id\": output only, its value is the Compute Engine instance id. * \"aiplatform.googleapis.com/colab_enterprise_entry_service\": its value is either \"bigquery\" or \"vertex\"; if absent, it should be \"vertex\". This is to describe the entry service, either BigQuery or Vertex.", + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "runtimeState": { + "readOnly": true, + "type": "string", + "enum": [ + "RUNTIME_STATE_UNSPECIFIED", + "RUNNING", + "BEING_STARTED", + "BEING_STOPPED", + "STOPPED", + "BEING_UPGRADED", + "ERROR", + "INVALID" + ], + "description": "Output only. The runtime (instance) state of the NotebookRuntime.", + "enumDescriptions": [ + "Unspecified runtime state.", + "NotebookRuntime is in running state.", + "NotebookRuntime is in starting state.", + "NotebookRuntime is in stopping state.", + "NotebookRuntime is in stopped state.", + "NotebookRuntime is in upgrading state. It is in the middle of upgrading process.", + "NotebookRuntime was unable to start/stop properly.", + "NotebookRuntime is in invalid state. Cannot be recovered." + ] + }, + "networkTags": { + "description": "Optional. The Compute Engine tags to add to runtime (see [Tagging instances](https://cloud.google.com/vpc/docs/add-remove-network-tags)).", + "items": { + "type": "string" + }, + "type": "array" + }, + "name": { + "description": "Output only. The resource name of the NotebookRuntime.", + "readOnly": true, + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfig": { + "type": "object", + "description": "Requests are randomly selected.", + "id": "GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfig", + "properties": { + "sampleRate": { + "description": "Sample rate (0, 1]", + "type": "number", + "format": "double" + } + } + }, + "GoogleCloudAiplatformV1ServiceAccountSpec": { + "id": "GoogleCloudAiplatformV1ServiceAccountSpec", + "properties": { + "enableCustomServiceAccount": { + "description": "Required. If true, custom user-managed service account is enforced to run any workloads (for example, Vertex Jobs) on the resource. Otherwise, uses the [Vertex AI Custom Code Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).", + "type": "boolean" + }, + "serviceAccount": { + "description": "Optional. Required when all below conditions are met * `enable_custom_service_account` is true; * any runtime is specified via `ResourceRuntimeSpec` on creation time, for example, Ray The users must have `iam.serviceAccounts.actAs` permission on this service account and then the specified runtime containers will run as it. Do not set this field if you want to submit jobs using custom service account to this PersistentResource after creation, but only specify the `service_account` inside the job.", + "type": "string" + } + }, + "description": "Configuration for the use of custom service account to run the workloads.", + "type": "object" + }, + "GoogleCloudAiplatformV1Presets": { + "properties": { + "query": { + "description": "Preset option controlling parameters for speed-precision trade-off when querying for examples. If omitted, defaults to `PRECISE`.", + "type": "string", + "enum": [ + "PRECISE", + "FAST" + ], + "enumDescriptions": [ + "More precise neighbors as a trade-off against slower response.", + "Faster response as a trade-off against less precise neighbors." + ] + }, + "modality": { + "enum": [ + "MODALITY_UNSPECIFIED", + "IMAGE", + "TEXT", + "TABULAR" + ], + "enumDescriptions": [ + "Should not be set. Added as a recommended best practice for enums", + "IMAGE modality", + "TEXT modality", + "TABULAR modality" + ], + "description": "The modality of the uploaded model, which automatically configures the distance measurement and feature normalization for the underlying example index and queries. If your model does not precisely fit one of these types, it is okay to choose the closest type.", + "type": "string" + } + }, + "description": "Preset configuration for example-based explanations", + "id": "GoogleCloudAiplatformV1Presets", + "type": "object" + }, + "GoogleCloudAiplatformV1WriteTensorboardRunDataResponse": { + "description": "Response message for TensorboardService.WriteTensorboardRunData.", + "type": "object", + "properties": {}, + "id": "GoogleCloudAiplatformV1WriteTensorboardRunDataResponse" + }, + "GoogleCloudAiplatformV1Scalar": { + "description": "One point viewable on a scalar metric plot.", + "id": "GoogleCloudAiplatformV1Scalar", + "type": "object", + "properties": { + "value": { + "type": "number", + "format": "double", + "description": "Value of the point at this step / timestamp." + } + } + }, + "GoogleCloudAiplatformV1ToolNameMatchInstance": { + "properties": { + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + }, + "reference": { + "type": "string", + "description": "Required. Ground truth used to compare against the prediction." + } + }, + "type": "object", + "description": "Spec for tool name match instance.", + "id": "GoogleCloudAiplatformV1ToolNameMatchInstance" + }, + "GoogleCloudAiplatformV1ListIndexEndpointsResponse": { + "id": "GoogleCloudAiplatformV1ListIndexEndpointsResponse", + "properties": { + "indexEndpoints": { + "items": { + "$ref": "GoogleCloudAiplatformV1IndexEndpoint" + }, + "type": "array", + "description": "List of IndexEndpoints in the requested page." + }, + "nextPageToken": { + "type": "string", + "description": "A token to retrieve next page of results. Pass to ListIndexEndpointsRequest.page_token to obtain that page." + } + }, + "description": "Response message for IndexEndpointService.ListIndexEndpoints.", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationAutoTransformation": { + "properties": { + "columnName": { + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationAutoTransformation", + "type": "object", + "description": "Training pipeline will infer the proper transformation based on the statistic of dataset." + }, + "GoogleCloudAiplatformV1ReadTensorboardUsageResponsePerMonthUsageData": { + "properties": { + "userUsageData": { + "items": { + "$ref": "GoogleCloudAiplatformV1ReadTensorboardUsageResponsePerUserUsageData" + }, + "description": "Usage data for each user in the given month.", + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1ReadTensorboardUsageResponsePerMonthUsageData", + "type": "object", + "description": "Per month usage data" + }, + "GoogleCloudAiplatformV1DeployModelOperationMetadata": { + "description": "Runtime operation information for EndpointService.DeployModel.", + "id": "GoogleCloudAiplatformV1DeployModelOperationMetadata", + "type": "object", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The operation generic information." + } + } + }, + "GoogleCloudAiplatformV1RayMetricSpec": { + "id": "GoogleCloudAiplatformV1RayMetricSpec", + "type": "object", + "description": "Configuration for the Ray metrics.", + "properties": { + "disabled": { + "type": "boolean", + "description": "Optional. Flag to disable the Ray metrics collection." + } + } + }, + "GoogleCloudAiplatformV1ReadFeatureValuesResponseEntityView": { + "type": "object", + "id": "GoogleCloudAiplatformV1ReadFeatureValuesResponseEntityView", + "description": "Entity view with Feature values.", + "properties": { + "entityId": { + "type": "string", + "description": "ID of the requested entity." + }, + "data": { + "description": "Each piece of data holds the k requested values for one requested Feature. If no values for the requested Feature exist, the corresponding cell will be empty. This has the same size and is in the same order as the features from the header ReadFeatureValuesResponse.header.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1ReadFeatureValuesResponseEntityViewData" + } + } + } + }, + "GoogleCloudAiplatformV1ImportDataOperationMetadata": { + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The common part of the operation metadata." + } + }, + "type": "object", + "description": "Runtime operation information for DatasetService.ImportData.", + "id": "GoogleCloudAiplatformV1ImportDataOperationMetadata" + }, + "GoogleCloudAiplatformV1CheckTrialEarlyStoppingStateResponse": { + "properties": { + "shouldStop": { + "description": "True if the Trial should stop.", + "type": "boolean" + } + }, + "description": "Response message for VizierService.CheckTrialEarlyStoppingState.", + "type": "object", + "id": "GoogleCloudAiplatformV1CheckTrialEarlyStoppingStateResponse" + }, + "GoogleCloudAiplatformV1AddTrialMeasurementRequest": { + "description": "Request message for VizierService.AddTrialMeasurement.", + "id": "GoogleCloudAiplatformV1AddTrialMeasurementRequest", + "type": "object", + "properties": { + "measurement": { + "description": "Required. The measurement to be added to a Trial.", + "$ref": "GoogleCloudAiplatformV1Measurement" + } + } + }, + "GoogleCloudAiplatformV1RemoveContextChildrenRequest": { + "id": "GoogleCloudAiplatformV1RemoveContextChildrenRequest", + "description": "Request message for MetadataService.DeleteContextChildrenRequest.", + "type": "object", + "properties": { + "childContexts": { + "type": "array", + "items": { + "type": "string" + }, + "description": "The resource names of the child Contexts." + } + } + }, + "GoogleCloudAiplatformV1Trial": { + "id": "GoogleCloudAiplatformV1Trial", + "type": "object", + "properties": { + "parameters": { + "items": { + "$ref": "GoogleCloudAiplatformV1TrialParameter" + }, + "readOnly": true, + "description": "Output only. The parameters of the Trial.", + "type": "array" + }, + "name": { + "readOnly": true, + "type": "string", + "description": "Output only. Resource name of the Trial assigned by the service." + }, + "state": { + "description": "Output only. The detailed state of the Trial.", + "readOnly": true, + "enum": [ + "STATE_UNSPECIFIED", + "REQUESTED", + "ACTIVE", + "STOPPING", + "SUCCEEDED", + "INFEASIBLE" + ], + "enumDescriptions": [ + "The Trial state is unspecified.", + "Indicates that a specific Trial has been requested, but it has not yet been suggested by the service.", + "Indicates that the Trial has been suggested.", + "Indicates that the Trial should stop according to the service.", + "Indicates that the Trial is completed successfully.", + "Indicates that the Trial should not be attempted again. The service will set a Trial to INFEASIBLE when it's done but missing the final_measurement." + ], + "type": "string" + }, + "customJob": { + "type": "string", + "readOnly": true, + "description": "Output only. The CustomJob name linked to the Trial. It's set for a HyperparameterTuningJob's Trial." + }, + "clientId": { + "readOnly": true, + "type": "string", + "description": "Output only. The identifier of the client that originally requested this Trial. Each client is identified by a unique client_id. When a client asks for a suggestion, Vertex AI Vizier will assign it a Trial. The client should evaluate the Trial, complete it, and report back to Vertex AI Vizier. If suggestion is asked again by same client_id before the Trial is completed, the same Trial will be returned. Multiple clients with different client_ids can ask for suggestions simultaneously, each of them will get their own Trial." + }, + "startTime": { + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Time when the Trial was started.", + "type": "string" + }, + "measurements": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1Measurement" + }, + "description": "Output only. A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_duration). These are used for early stopping computations.", + "readOnly": true + }, + "infeasibleReason": { + "readOnly": true, + "type": "string", + "description": "Output only. A human readable string describing why the Trial is infeasible. This is set only if Trial state is `INFEASIBLE`." + }, + "id": { + "description": "Output only. The identifier of the Trial assigned by the service.", + "readOnly": true, + "type": "string" + }, + "finalMeasurement": { + "description": "Output only. The final measurement containing the objective value.", + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1Measurement" + }, + "endTime": { + "type": "string", + "format": "google-datetime", + "description": "Output only. Time when the Trial's status changed to `SUCCEEDED` or `INFEASIBLE`.", + "readOnly": true + }, + "webAccessUris": { + "additionalProperties": { + "type": "string" + }, + "readOnly": true, + "description": "Output only. URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) (one URI for each training node). Only available if this trial is part of a HyperparameterTuningJob and the job's trial_job_spec.enable_web_access field is `true`. The keys are names of each node used for the trial; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell.", + "type": "object" + } + }, + "description": "A message representing a Trial. A Trial contains a unique set of Parameters that has been or will be evaluated, along with the objective metrics got by running the Trial." + }, + "GoogleCloudAiplatformV1ModelDataStats": { + "id": "GoogleCloudAiplatformV1ModelDataStats", + "properties": { + "testDataItemsCount": { + "type": "string", + "format": "int64", + "description": "Number of DataItems that were used for evaluating this Model. If the Model is evaluated multiple times, this will be the number of test DataItems used by the first evaluation. If the Model is not evaluated, the number is 0." + }, + "trainingDataItemsCount": { + "format": "int64", + "description": "Number of DataItems that were used for training this Model.", + "type": "string" + }, + "validationAnnotationsCount": { + "description": "Number of Annotations that are used for validating this Model during training.", + "type": "string", + "format": "int64" + }, + "trainingAnnotationsCount": { + "type": "string", + "format": "int64", + "description": "Number of Annotations that are used for training this Model." + }, + "testAnnotationsCount": { + "format": "int64", + "description": "Number of Annotations that are used for evaluating this Model. If the Model is evaluated multiple times, this will be the number of test Annotations used by the first evaluation. If the Model is not evaluated, the number is 0.", + "type": "string" + }, + "validationDataItemsCount": { + "type": "string", + "description": "Number of DataItems that were used for validating this Model during training.", + "format": "int64" + } + }, + "description": "Stats of data used for train or evaluate the Model.", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformation": { + "properties": { + "timestamp": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTimestampTransformation" + }, + "text": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTextTransformation" + }, + "auto": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationAutoTransformation" + }, + "numeric": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationNumericTransformation" + }, + "categorical": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationCategoricalTransformation" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformation", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTablesDatasetMetadataBigQuerySource": { + "properties": { + "uri": { + "description": "The URI of a BigQuery table. e.g. bq://projectId.bqDatasetId.bqTableId", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1SchemaTablesDatasetMetadataBigQuerySource", + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs": { + "type": "object", + "properties": { + "baseModelId": { + "type": "string", + "description": "The ID of the `base` model. If it is specified, the new model will be trained based on the `base` model. Otherwise, the new model will be trained from scratch. The `base` model must be in the same Project and Location as the new Model to train, and have the same modelType." + }, + "uptrainBaseModelId": { + "type": "string", + "description": "The ID of `base` model for upTraining. If it is specified, the new model will be upTrained based on the `base` model for upTraining. Otherwise, the new model will be trained from scratch. The `base` model for upTraining must be in the same Project and Location as the new Model to train, and have the same modelType." + }, + "modelType": { + "enumDescriptions": [ + "Should not be set.", + "A Model best tailored to be used within Google Cloud, and which cannot be exported. Default.", + "A model type best tailored to be used within Google Cloud, which cannot be exported externally. Compared to the CLOUD model above, it is expected to have higher prediction accuracy.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow or Core ML model and used on a mobile or edge device afterwards. Expected to have low latency, but may have lower prediction quality than other mobile models.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow or Core ML model and used on a mobile or edge device with afterwards.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow or Core ML model and used on a mobile or edge device afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other mobile models.", + "EfficientNet model for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally.", + "MaxViT model for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally.", + "ViT model for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally.", + "CoCa model for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally." + ], + "enum": [ + "MODEL_TYPE_UNSPECIFIED", + "CLOUD", + "CLOUD_1", + "MOBILE_TF_LOW_LATENCY_1", + "MOBILE_TF_VERSATILE_1", + "MOBILE_TF_HIGH_ACCURACY_1", + "EFFICIENTNET", + "MAXVIT", + "VIT", + "COCA" + ], + "type": "string" + }, + "multiLabel": { + "type": "boolean", + "description": "If false, a single-label (multi-class) Model will be trained (i.e. assuming that for each image just up to one annotation may be applicable). If true, a multi-label Model will be trained (i.e. assuming that for each image multiple annotations may be applicable)." + }, + "tunableParameter": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter", + "description": "Trainer type for Vision TrainRequest." + }, + "disableEarlyStopping": { + "type": "boolean", + "description": "Use the entire training budget. This disables the early stopping feature. When false the early stopping feature is enabled, which means that AutoML Image Classification might stop training before the entire training budget has been used." + }, + "budgetMilliNodeHours": { + "format": "int64", + "type": "string", + "description": "The training budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The actual metadata.costMilliNodeHours will be equal or less than this value. If further model training ceases to provide any improvements, it will stop without using the full budget and the metadata.successfulStopReason will be `model-converged`. Note, node_hour = actual_hour * number_of_nodes_involved. For modelType `cloud`(default), the budget must be between 8,000 and 800,000 milli node hours, inclusive. The default value is 192,000 which represents one day in wall time, considering 8 nodes are used. For model types `mobile-tf-low-latency-1`, `mobile-tf-versatile-1`, `mobile-tf-high-accuracy-1`, the training budget must be between 1,000 and 100,000 milli node hours, inclusive. The default value is 24,000 which represents one day in wall time on a single node that is used." + } + }, + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs" + }, + "GoogleCloudAiplatformV1Study": { + "type": "object", + "properties": { + "state": { + "description": "Output only. The detailed state of a Study.", + "type": "string", + "readOnly": true, + "enum": [ + "STATE_UNSPECIFIED", + "ACTIVE", + "INACTIVE", + "COMPLETED" + ], + "enumDescriptions": [ + "The study state is unspecified.", + "The study is active.", + "The study is stopped due to an internal error.", + "The study is done when the service exhausts the parameter search space or max_trial_count is reached." + ] + }, + "createTime": { + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Time at which the study was created.", + "type": "string" + }, + "inactiveReason": { + "description": "Output only. A human readable reason why the Study is inactive. This should be empty if a study is ACTIVE or COMPLETED.", + "type": "string", + "readOnly": true + }, + "name": { + "description": "Output only. The name of a study. The study's globally unique identifier. Format: `projects/{project}/locations/{location}/studies/{study}`", + "type": "string", + "readOnly": true + }, + "studySpec": { + "$ref": "GoogleCloudAiplatformV1StudySpec", + "description": "Required. Configuration of the Study." + }, + "displayName": { + "type": "string", + "description": "Required. Describes the Study, default value is empty string." + } + }, + "description": "A message representing a Study.", + "id": "GoogleCloudAiplatformV1Study" + }, + "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoActionRecognitionMetrics": { + "description": "Model evaluation metrics for video action recognition.", + "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoActionRecognitionMetrics", + "type": "object", + "properties": { + "evaluatedActionCount": { + "description": "The number of ground truth actions used to create this evaluation.", + "type": "integer", + "format": "int32" + }, + "videoActionMetrics": { + "description": "The metric entries for precision window lengths: 1s,2s,3s.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoActionMetrics" + } + } + } + }, + "GoogleCloudAiplatformV1SchemaVideoDataItem": { + "properties": { + "mimeType": { + "readOnly": true, + "description": "Output only. The mime type of the content of the video. Only the videos in below listed mime types are supported. Supported mime_type: - video/mp4 - video/avi - video/quicktime", + "type": "string" + }, + "gcsUri": { + "type": "string", + "description": "Required. Google Cloud Storage URI points to the original video in user's bucket. The video is up to 50 GB in size and up to 3 hour in duration." + } + }, + "id": "GoogleCloudAiplatformV1SchemaVideoDataItem", + "description": "Payload of Video DataItem.", + "type": "object" + }, + "GoogleCloudAiplatformV1IdMatcher": { + "properties": { + "ids": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Required. The following are accepted as `ids`: * A single-element list containing only `*`, which selects all Features in the target EntityType, or * A list containing only Feature IDs, which selects only Features with those IDs in the target EntityType." + } + }, + "description": "Matcher for Features of an EntityType by Feature ID.", + "id": "GoogleCloudAiplatformV1IdMatcher", + "type": "object" + }, + "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis": { + "id": "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis", + "properties": { + "disabled": { + "type": "boolean", + "description": "The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring." + }, + "stalenessDays": { + "description": "Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.", + "format": "int32", + "type": "integer" + }, + "monitoringIntervalDays": { + "type": "integer", + "format": "int32", + "description": "Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days." + } + }, + "description": "Configuration of the Featurestore's Snapshot Analysis Based Monitoring. This type of analysis generates statistics for each Feature based on a snapshot of the latest feature value of each entities every monitoring_interval.", + "type": "object" + }, + "GoogleCloudAiplatformV1FeatureViewBigQuerySource": { + "properties": { + "uri": { + "description": "Required. The BigQuery view URI that will be materialized on each sync trigger based on FeatureView.SyncConfig.", + "type": "string" + }, + "entityIdColumns": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Required. Columns to construct entity_id / row keys." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1FeatureViewBigQuerySource" + }, + "GoogleCloudAiplatformV1AddContextChildrenRequest": { + "properties": { + "childContexts": { + "items": { + "type": "string" + }, + "description": "The resource names of the child Contexts.", + "type": "array" + } + }, + "type": "object", + "description": "Request message for MetadataService.AddContextChildren.", + "id": "GoogleCloudAiplatformV1AddContextChildrenRequest" + }, + "GoogleCloudAiplatformV1ListCustomJobsResponse": { + "description": "Response message for JobService.ListCustomJobs", + "type": "object", + "id": "GoogleCloudAiplatformV1ListCustomJobsResponse", + "properties": { + "customJobs": { + "type": "array", + "description": "List of CustomJobs in the requested page.", + "items": { + "$ref": "GoogleCloudAiplatformV1CustomJob" + } + }, + "nextPageToken": { + "type": "string", + "description": "A token to retrieve the next page of results. Pass to ListCustomJobsRequest.page_token to obtain that page." + } + } + }, + "GoogleCloudAiplatformV1UpdateExplanationDatasetOperationMetadata": { + "description": "Runtime operation information for ModelService.UpdateExplanationDataset.", + "type": "object", + "id": "GoogleCloudAiplatformV1UpdateExplanationDatasetOperationMetadata", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The common part of the operation metadata." + } + } + }, + "GoogleCloudAiplatformV1FulfillmentSpec": { + "type": "object", + "properties": { + "version": { + "type": "integer", + "description": "Optional. Which version to use for evaluation.", + "format": "int32" + } + }, + "id": "GoogleCloudAiplatformV1FulfillmentSpec", + "description": "Spec for fulfillment metric." + }, + "GoogleCloudAiplatformV1Event": { + "description": "An edge describing the relationship between an Artifact and an Execution in a lineage graph.", + "type": "object", + "id": "GoogleCloudAiplatformV1Event", + "properties": { + "type": { + "type": "string", + "enum": [ + "TYPE_UNSPECIFIED", + "INPUT", + "OUTPUT" + ], + "enumDescriptions": [ + "Unspecified whether input or output of the Execution.", + "An input of the Execution.", + "An output of the Execution." + ], + "description": "Required. The type of the Event." + }, + "artifact": { + "description": "Required. The relative resource name of the Artifact in the Event.", + "type": "string" + }, + "execution": { + "readOnly": true, + "type": "string", + "description": "Output only. The relative resource name of the Execution in the Event." + }, + "eventTime": { + "description": "Output only. Time the Event occurred.", + "type": "string", + "readOnly": true, + "format": "google-datetime" + }, + "labels": { + "type": "object", + "additionalProperties": { + "type": "string" + }, + "description": "The labels with user-defined metadata to annotate Events. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Event (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." + } + } + }, + "GoogleCloudAiplatformV1UpdateDeploymentResourcePoolOperationMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1UpdateDeploymentResourcePoolOperationMetadata", + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + }, + "description": "Runtime operation information for UpdateDeploymentResourcePool method." + }, + "GoogleCloudAiplatformV1TokensInfo": { + "id": "GoogleCloudAiplatformV1TokensInfo", + "description": "Tokens info with a list of tokens and the corresponding list of token ids.", + "properties": { + "tokenIds": { + "description": "A list of token ids from the input.", + "type": "array", + "items": { + "type": "string", + "format": "int64" + } + }, + "tokens": { + "items": { + "type": "string", + "format": "byte" + }, + "type": "array", + "description": "A list of tokens from the input." + }, + "role": { + "description": "Optional. Optional fields for the role from the corresponding Content.", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1TuningJob": { + "properties": { + "supervisedTuningSpec": { + "description": "Tuning Spec for Supervised Fine Tuning.", + "$ref": "GoogleCloudAiplatformV1SupervisedTuningSpec" + }, + "endTime": { + "format": "google-datetime", + "type": "string", + "readOnly": true, + "description": "Output only. Time when the TuningJob entered any of the following JobStates: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`, `JOB_STATE_EXPIRED`." + }, + "tunedModelDisplayName": { + "type": "string", + "description": "Optional. The display name of the TunedModel. The name can be up to 128 characters long and can consist of any UTF-8 characters." + }, + "createTime": { + "format": "google-datetime", + "description": "Output only. Time when the TuningJob was created.", + "type": "string", + "readOnly": true + }, + "updateTime": { + "readOnly": true, + "type": "string", + "description": "Output only. Time when the TuningJob was most recently updated.", + "format": "google-datetime" + }, + "error": { + "readOnly": true, + "$ref": "GoogleRpcStatus", + "description": "Output only. Only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`." + }, + "description": { + "type": "string", + "description": "Optional. The description of the TuningJob." + }, + "startTime": { + "format": "google-datetime", + "description": "Output only. Time when the TuningJob for the first time entered the `JOB_STATE_RUNNING` state.", + "readOnly": true, + "type": "string" + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1EncryptionSpec", + "description": "Customer-managed encryption key options for a TuningJob. If this is set, then all resources created by the TuningJob will be encrypted with the provided encryption key." + }, + "experiment": { + "readOnly": true, + "type": "string", + "description": "Output only. The Experiment associated with this TuningJob." + }, + "labels": { + "description": "Optional. The labels with user-defined metadata to organize TuningJob and generated resources such as Model and Endpoint. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "baseModel": { + "description": "The base model that is being tuned, e.g., \"gemini-1.0-pro-002\".", + "type": "string" + }, + "name": { + "description": "Output only. Identifier. Resource name of a TuningJob. Format: `projects/{project}/locations/{location}/tuningJobs/{tuning_job}`", + "type": "string", + "readOnly": true + }, + "state": { + "readOnly": true, + "description": "Output only. The detailed state of the job.", + "enumDescriptions": [ + "The job state is unspecified.", + "The job has been just created or resumed and processing has not yet begun.", + "The service is preparing to run the job.", + "The job is in progress.", + "The job completed successfully.", + "The job failed.", + "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "The job has been cancelled.", + "The job has been stopped, and can be resumed.", + "The job has expired.", + "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", + "The job is partially succeeded, some results may be missing due to errors." + ], + "type": "string", + "enum": [ + "JOB_STATE_UNSPECIFIED", + "JOB_STATE_QUEUED", + "JOB_STATE_PENDING", + "JOB_STATE_RUNNING", + "JOB_STATE_SUCCEEDED", + "JOB_STATE_FAILED", + "JOB_STATE_CANCELLING", + "JOB_STATE_CANCELLED", + "JOB_STATE_PAUSED", + "JOB_STATE_EXPIRED", + "JOB_STATE_UPDATING", + "JOB_STATE_PARTIALLY_SUCCEEDED" + ] + }, + "tunedModel": { + "$ref": "GoogleCloudAiplatformV1TunedModel", + "readOnly": true, + "description": "Output only. The tuned model resources assiociated with this TuningJob." + }, + "tuningDataStats": { + "readOnly": true, + "description": "Output only. The tuning data statistics associated with this TuningJob.", + "$ref": "GoogleCloudAiplatformV1TuningDataStats" + } + }, + "id": "GoogleCloudAiplatformV1TuningJob", + "type": "object", + "description": "Represents a TuningJob that runs with Google owned models." + }, + "GoogleCloudAiplatformV1PurgeExecutionsResponse": { + "id": "GoogleCloudAiplatformV1PurgeExecutionsResponse", + "properties": { + "purgeCount": { + "type": "string", + "format": "int64", + "description": "The number of Executions that this request deleted (or, if `force` is false, the number of Executions that will be deleted). This can be an estimate." + }, + "purgeSample": { + "items": { + "type": "string" + }, + "type": "array", + "description": "A sample of the Execution names that will be deleted. Only populated if `force` is set to false. The maximum number of samples is 100 (it is possible to return fewer)." + } + }, + "type": "object", + "description": "Response message for MetadataService.PurgeExecutions." + }, + "GoogleCloudAiplatformV1FluencySpec": { + "properties": { + "version": { + "format": "int32", + "description": "Optional. Which version to use for evaluation.", + "type": "integer" + } + }, + "id": "GoogleCloudAiplatformV1FluencySpec", + "type": "object", + "description": "Spec for fluency score metric." + }, + "GoogleCloudAiplatformV1FetchFeatureValuesResponse": { + "id": "GoogleCloudAiplatformV1FetchFeatureValuesResponse", + "description": "Response message for FeatureOnlineStoreService.FetchFeatureValues", + "type": "object", + "properties": { + "dataKey": { + "description": "The data key associated with this response. Will only be populated for FeatureOnlineStoreService.StreamingFetchFeatureValues RPCs.", + "$ref": "GoogleCloudAiplatformV1FeatureViewDataKey" + }, + "keyValues": { + "description": "Feature values in KeyValue format.", + "$ref": "GoogleCloudAiplatformV1FetchFeatureValuesResponseFeatureNameValuePairList" + }, + "protoStruct": { + "type": "object", + "description": "Feature values in proto Struct format.", + "additionalProperties": { + "type": "any", + "description": "Properties of the object." + } + } + } + }, + "GoogleCloudAiplatformV1QueryDeployedModelsResponse": { + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages." + }, + "deployedModels": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1DeployedModel" + }, + "deprecated": true, + "description": "DEPRECATED Use deployed_model_refs instead." + }, + "deployedModelRefs": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1DeployedModelRef" + }, + "description": "References to the DeployedModels that share the specified deploymentResourcePool." + }, + "totalDeployedModelCount": { + "format": "int32", + "description": "The total number of DeployedModels on this DeploymentResourcePool.", + "type": "integer" + }, + "totalEndpointCount": { + "description": "The total number of Endpoints that have DeployedModels on this DeploymentResourcePool.", + "type": "integer", + "format": "int32" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1QueryDeployedModelsResponse", + "description": "Response message for QueryDeployedModels method." + }, + "GoogleCloudAiplatformV1FileData": { + "id": "GoogleCloudAiplatformV1FileData", + "properties": { + "fileUri": { + "type": "string", + "description": "Required. URI." + }, + "mimeType": { + "description": "Required. The IANA standard MIME type of the source data.", + "type": "string" + } + }, + "description": "URI based data.", + "type": "object" + }, + "GoogleCloudAiplatformV1DoubleArray": { + "type": "object", + "properties": { + "values": { + "type": "array", + "items": { + "type": "number", + "format": "double" + }, + "description": "A list of double values." + } + }, + "id": "GoogleCloudAiplatformV1DoubleArray", + "description": "A list of double values." + }, + "GoogleCloudAiplatformV1UpgradeNotebookRuntimeOperationMetadata": { + "properties": { + "progressMessage": { + "type": "string", + "description": "A human-readable message that shows the intermediate progress details of NotebookRuntime." + }, + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1UpgradeNotebookRuntimeOperationMetadata", + "description": "Metadata information for NotebookService.UpgradeNotebookRuntime." + }, + "GoogleCloudAiplatformV1ListFeaturesResponse": { + "properties": { + "features": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1Feature" + }, + "description": "The Features matching the request." + }, + "nextPageToken": { + "type": "string", + "description": "A token, which can be sent as ListFeaturesRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages." + } + }, + "description": "Response message for FeaturestoreService.ListFeatures. Response message for FeatureRegistryService.ListFeatures.", + "id": "GoogleCloudAiplatformV1ListFeaturesResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpec": { + "id": "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpec", + "type": "object", + "description": "The spec of multi-trial Neural Architecture Search (NAS).", + "properties": { + "searchTrialSpec": { + "$ref": "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec", + "description": "Required. Spec for search trials." + }, + "trainTrialSpec": { + "$ref": "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec", + "description": "Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched." + }, + "metric": { + "description": "Metric specs for the NAS job. Validation for this field is done at `multi_trial_algorithm_spec` field.", + "$ref": "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpec" + }, + "multiTrialAlgorithm": { + "description": "The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to `REINFORCEMENT_LEARNING`.", + "enumDescriptions": [ + "Defaults to `REINFORCEMENT_LEARNING`.", + "The Reinforcement Learning Algorithm for Multi-trial Neural Architecture Search (NAS).", + "The Grid Search Algorithm for Multi-trial Neural Architecture Search (NAS)." + ], + "enum": [ + "MULTI_TRIAL_ALGORITHM_UNSPECIFIED", + "REINFORCEMENT_LEARNING", + "GRID_SEARCH" + ], + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1MutateDeployedModelRequest": { + "properties": { + "deployedModel": { + "$ref": "GoogleCloudAiplatformV1DeployedModel", + "description": "Required. The DeployedModel to be mutated within the Endpoint. Only the following fields can be mutated: * `min_replica_count` in either DedicatedResources or AutomaticResources * `max_replica_count` in either DedicatedResources or AutomaticResources * autoscaling_metric_specs * `disable_container_logging` (v1 only) * `enable_container_logging` (v1beta1 only)" + }, + "updateMask": { + "format": "google-fieldmask", + "type": "string", + "description": "Required. The update mask applies to the resource. See google.protobuf.FieldMask." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1MutateDeployedModelRequest", + "description": "Request message for EndpointService.MutateDeployedModel." + }, + "GoogleCloudAiplatformV1QuestionAnsweringQualityInstance": { + "description": "Spec for question answering quality instance.", + "properties": { + "instruction": { + "type": "string", + "description": "Required. Question Answering prompt for LLM." + }, + "reference": { + "type": "string", + "description": "Optional. Ground truth used to compare against the prediction." + }, + "context": { + "type": "string", + "description": "Required. Text to answer the question." + }, + "prediction": { + "description": "Required. Output of the evaluated model.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1QuestionAnsweringQualityInstance" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTextTransformation": { + "properties": { + "columnName": { + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTextTransformation", + "description": "Training pipeline will perform following transformation functions. * The text as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index." + }, + "GoogleCloudAiplatformV1ExplanationMetadataOutputMetadata": { + "properties": { + "displayNameMappingKey": { + "description": "Specify a field name in the prediction to look for the display name. Use this if the prediction contains the display names for the outputs. The display names in the prediction must have the same shape of the outputs, so that it can be located by Attribution.output_index for a specific output.", + "type": "string" + }, + "outputTensorName": { + "description": "Name of the output tensor. Required and is only applicable to Vertex AI provided images for Tensorflow.", + "type": "string" + }, + "indexDisplayNameMapping": { + "type": "any", + "description": "Static mapping between the index and display name. Use this if the outputs are a deterministic n-dimensional array, e.g. a list of scores of all the classes in a pre-defined order for a multi-classification Model. It's not feasible if the outputs are non-deterministic, e.g. the Model produces top-k classes or sort the outputs by their values. The shape of the value must be an n-dimensional array of strings. The number of dimensions must match that of the outputs to be explained. The Attribution.output_display_name is populated by locating in the mapping with Attribution.output_index." + } + }, + "description": "Metadata of the prediction output to be explained.", + "type": "object", + "id": "GoogleCloudAiplatformV1ExplanationMetadataOutputMetadata" + }, + "GoogleCloudAiplatformV1FeatureValueList": { + "type": "object", + "id": "GoogleCloudAiplatformV1FeatureValueList", + "description": "Container for list of values.", + "properties": { + "values": { + "description": "A list of feature values. All of them should be the same data type.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1FeatureValue" + } + } + } + }, + "GoogleCloudAiplatformV1DeployIndexRequest": { + "type": "object", + "description": "Request message for IndexEndpointService.DeployIndex.", + "properties": { + "deployedIndex": { + "$ref": "GoogleCloudAiplatformV1DeployedIndex", + "description": "Required. The DeployedIndex to be created within the IndexEndpoint." + } + }, + "id": "GoogleCloudAiplatformV1DeployIndexRequest" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetection": { + "properties": { + "inputs": { + "description": "The input parameters of this TrainingJob.", + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionInputs" + }, + "metadata": { + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionMetadata", + "description": "The metadata information" + } + }, + "type": "object", + "description": "A TrainingJob that trains and uploads an AutoML Image Object Detection Model.", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetection" + }, + "GoogleCloudAiplatformV1IndexDatapointSparseEmbedding": { + "type": "object", + "description": "Feature embedding vector for sparse index. An array of numbers whose values are located in the specified dimensions.", + "id": "GoogleCloudAiplatformV1IndexDatapointSparseEmbedding", + "properties": { + "values": { + "items": { + "type": "number", + "format": "float" + }, + "type": "array", + "description": "Required. The list of embedding values of the sparse vector." + }, + "dimensions": { + "description": "Required. The list of indexes for the embedding values of the sparse vector.", + "items": { + "format": "int64", + "type": "string" + }, + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences": { + "properties": { + "references": { + "type": "object", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1PublisherModelResourceReference" + }, + "description": "Required." + }, + "resourceUseCase": { + "type": "string", + "description": "Optional. Use case (CUJ) of the resource." + }, + "resourceDescription": { + "description": "Optional. Description of the resource.", + "type": "string" + }, + "resourceTitle": { + "type": "string", + "description": "Optional. Title of the resource." + }, + "title": { + "description": "Required. ", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences", + "type": "object", + "description": "The regional resource name or the URI. Key is region, e.g., us-central1, europe-west2, global, etc.." + }, + "GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfig": { + "type": "object", + "id": "GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfig", + "description": "Used in safe optimization to specify threshold levels and risk tolerance.", + "properties": { + "safetyThreshold": { + "format": "double", + "type": "number", + "description": "Safety threshold (boundary value between safe and unsafe). NOTE that if you leave SafetyMetricConfig unset, a default value of 0 will be used." + }, + "desiredMinSafeTrialsFraction": { + "description": "Desired minimum fraction of safe trials (over total number of trials) that should be targeted by the algorithm at any time during the study (best effort). This should be between 0.0 and 1.0 and a value of 0.0 means that there is no minimum and an algorithm proceeds without targeting any specific fraction. A value of 1.0 means that the algorithm attempts to only Suggest safe Trials.", + "format": "double", + "type": "number" + } + } + }, + "GoogleCloudAiplatformV1GroundingChunkRetrievedContext": { + "description": "Chunk from context retrieved by the retrieval tools.", + "type": "object", + "properties": { + "uri": { + "description": "URI reference of the attribution.", + "type": "string" + }, + "title": { + "type": "string", + "description": "Title of the attribution." + } + }, + "id": "GoogleCloudAiplatformV1GroundingChunkRetrievedContext" + }, + "GoogleCloudAiplatformV1MigratableResourceMlEngineModelVersion": { + "id": "GoogleCloudAiplatformV1MigratableResourceMlEngineModelVersion", + "type": "object", + "description": "Represents one model Version in ml.googleapis.com.", + "properties": { + "version": { + "description": "Full resource name of ml engine model Version. Format: `projects/{project}/models/{model}/versions/{version}`.", + "type": "string" + }, + "endpoint": { + "description": "The ml.googleapis.com endpoint that this model Version currently lives in. Example values: * ml.googleapis.com * us-centrall-ml.googleapis.com * europe-west4-ml.googleapis.com * asia-east1-ml.googleapis.com", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1CountTokensRequest": { + "id": "GoogleCloudAiplatformV1CountTokensRequest", + "description": "Request message for PredictionService.CountTokens.", + "properties": { + "model": { + "description": "Optional. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`", + "type": "string" + }, + "instances": { + "items": { + "type": "any" + }, + "description": "Optional. The instances that are the input to token counting call. Schema is identical to the prediction schema of the underlying model.", + "type": "array" + }, + "tools": { + "items": { + "$ref": "GoogleCloudAiplatformV1Tool" + }, + "description": "Optional. A list of `Tools` the model may use to generate the next response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model.", + "type": "array" + }, + "contents": { + "items": { + "$ref": "GoogleCloudAiplatformV1Content" + }, + "description": "Optional. Input content.", + "type": "array" + }, + "systemInstruction": { + "description": "Optional. The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph.", + "$ref": "GoogleCloudAiplatformV1Content" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1SchemaTextClassificationAnnotation": { + "type": "object", + "properties": { + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that this Annotation pertains to." + }, + "annotationSpecId": { + "type": "string", + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." + } + }, + "id": "GoogleCloudAiplatformV1SchemaTextClassificationAnnotation", + "description": "Annotation details specific to text classification." + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextClassification": { + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextClassification", + "type": "object", + "description": "A TrainingJob that trains and uploads an AutoML Text Classification Model.", + "properties": { + "inputs": { + "description": "The input parameters of this TrainingJob.", + "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextClassificationInputs" + } + } + }, + "GoogleCloudAiplatformV1Context": { + "properties": { + "createTime": { + "readOnly": true, + "type": "string", + "description": "Output only. Timestamp when this Context was created.", + "format": "google-datetime" + }, + "displayName": { + "type": "string", + "description": "User provided display name of the Context. May be up to 128 Unicode characters." + }, + "parentContexts": { + "type": "array", + "description": "Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.", + "readOnly": true, + "items": { + "type": "string" + } + }, + "metadata": { + "additionalProperties": { + "description": "Properties of the object.", + "type": "any" + }, + "description": "Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.", + "type": "object" + }, + "description": { + "description": "Description of the Context", + "type": "string" + }, + "schemaTitle": { + "type": "string", + "description": "The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store." + }, + "etag": { + "description": "An eTag used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "updateTime": { + "type": "string", + "format": "google-datetime", + "description": "Output only. Timestamp when this Context was last updated.", + "readOnly": true + }, + "schemaVersion": { + "description": "The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.", + "type": "string" + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "description": "The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).", + "type": "object" + }, + "name": { + "type": "string", + "description": "Immutable. The resource name of the Context." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1Context", + "description": "Instance of a general context." + }, + "GoogleCloudAiplatformV1BatchReadFeatureValuesRequest": { + "id": "GoogleCloudAiplatformV1BatchReadFeatureValuesRequest", + "type": "object", + "properties": { + "destination": { + "description": "Required. Specifies output location and format.", + "$ref": "GoogleCloudAiplatformV1FeatureValueDestination" + }, + "bigqueryReadInstances": { + "$ref": "GoogleCloudAiplatformV1BigQuerySource", + "description": "Similar to csv_read_instances, but from BigQuery source." + }, + "passThroughFields": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1BatchReadFeatureValuesRequestPassThroughField" + }, + "description": "When not empty, the specified fields in the *_read_instances source will be joined as-is in the output, in addition to those fields from the Featurestore Entity. For BigQuery source, the type of the pass-through values will be automatically inferred. For CSV source, the pass-through values will be passed as opaque bytes." + }, + "csvReadInstances": { + "$ref": "GoogleCloudAiplatformV1CsvSource", + "description": "Each read instance consists of exactly one read timestamp and one or more entity IDs identifying entities of the corresponding EntityTypes whose Features are requested. Each output instance contains Feature values of requested entities concatenated together as of the read time. An example read instance may be `foo_entity_id, bar_entity_id, 2020-01-01T10:00:00.123Z`. An example output instance may be `foo_entity_id, bar_entity_id, 2020-01-01T10:00:00.123Z, foo_entity_feature1_value, bar_entity_feature2_value`. Timestamp in each read instance must be millisecond-aligned. `csv_read_instances` are read instances stored in a plain-text CSV file. The header should be: [ENTITY_TYPE_ID1], [ENTITY_TYPE_ID2], ..., timestamp The columns can be in any order. Values in the timestamp column must use the RFC 3339 format, e.g. `2012-07-30T10:43:17.123Z`." + }, + "startTime": { + "description": "Optional. Excludes Feature values with feature generation timestamp before this timestamp. If not set, retrieve oldest values kept in Feature Store. Timestamp, if present, must not have higher than millisecond precision.", + "format": "google-datetime", + "type": "string" + }, + "entityTypeSpecs": { + "items": { + "$ref": "GoogleCloudAiplatformV1BatchReadFeatureValuesRequestEntityTypeSpec" + }, + "description": "Required. Specifies EntityType grouping Features to read values of and settings.", + "type": "array" + } + }, + "description": "Request message for FeaturestoreService.BatchReadFeatureValues." + }, + "GoogleCloudAiplatformV1SummarizationVerbositySpec": { + "description": "Spec for summarization verbosity score metric.", + "type": "object", + "properties": { + "version": { + "description": "Optional. Which version to use for evaluation.", + "type": "integer", + "format": "int32" + }, + "useReference": { + "type": "boolean", + "description": "Optional. Whether to use instance.reference to compute summarization verbosity." + } + }, + "id": "GoogleCloudAiplatformV1SummarizationVerbositySpec" + }, + "GoogleCloudAiplatformV1NfsMount": { + "description": "Represents a mount configuration for Network File System (NFS) to mount.", + "properties": { + "path": { + "type": "string", + "description": "Required. Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of `server:path`" + }, + "server": { + "type": "string", + "description": "Required. IP address of the NFS server." + }, + "mountPoint": { + "type": "string", + "description": "Required. Destination mount path. The NFS will be mounted for the user under /mnt/nfs/" + } + }, + "id": "GoogleCloudAiplatformV1NfsMount", + "type": "object" + }, + "GoogleCloudAiplatformV1ListSavedQueriesResponse": { + "type": "object", + "id": "GoogleCloudAiplatformV1ListSavedQueriesResponse", + "description": "Response message for DatasetService.ListSavedQueries.", + "properties": { + "nextPageToken": { + "type": "string", + "description": "The standard List next-page token." + }, + "savedQueries": { + "items": { + "$ref": "GoogleCloudAiplatformV1SavedQuery" + }, + "description": "A list of SavedQueries that match the specified filter in the request.", + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1NearestNeighborQueryNumericFilter": { + "type": "object", + "properties": { + "valueDouble": { + "type": "number", + "description": "double value type.", + "format": "double" + }, + "name": { + "description": "Required. Column name in BigQuery that used as filters.", + "type": "string" + }, + "valueFloat": { + "type": "number", + "description": "float value type.", + "format": "float" + }, + "op": { + "enumDescriptions": [ + "Unspecified operator.", + "Entities are eligible if their value is \u003c the query's.", + "Entities are eligible if their value is \u003c= the query's.", + "Entities are eligible if their value is == the query's.", + "Entities are eligible if their value is \u003e= the query's.", + "Entities are eligible if their value is \u003e the query's.", + "Entities are eligible if their value is != the query's." + ], + "enum": [ + "OPERATOR_UNSPECIFIED", + "LESS", + "LESS_EQUAL", + "EQUAL", + "GREATER_EQUAL", + "GREATER", + "NOT_EQUAL" + ], + "description": "Optional. This MUST be specified for queries and must NOT be specified for database points.", + "type": "string" + }, + "valueInt": { + "type": "string", + "format": "int64", + "description": "int value type." + } + }, + "id": "GoogleCloudAiplatformV1NearestNeighborQueryNumericFilter", + "description": "Numeric filter is used to search a subset of the entities by using boolean rules on numeric columns. For example: Database Point 0: {name: “a” value_int: 42} {name: “b” value_float: 1.0} Database Point 1: {name: “a” value_int: 10} {name: “b” value_float: 2.0} Database Point 2: {name: “a” value_int: -1} {name: “b” value_float: 3.0} Query: {name: “a” value_int: 12 operator: LESS} // Matches Point 1, 2 {name: “b” value_float: 2.0 operator: EQUAL} // Matches Point 1" + }, + "GoogleProtobufEmpty": { + "description": "A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }", + "properties": {}, + "type": "object", + "id": "GoogleProtobufEmpty" + }, + "GoogleCloudAiplatformV1DeployedModelRef": { + "properties": { + "deployedModelId": { + "description": "Immutable. An ID of a DeployedModel in the above Endpoint.", + "type": "string" + }, + "endpoint": { + "description": "Immutable. A resource name of an Endpoint.", + "type": "string" + } + }, + "description": "Points to a DeployedModel.", + "type": "object", + "id": "GoogleCloudAiplatformV1DeployedModelRef" + }, + "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalTransformation": { + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalTransformation", + "properties": { + "columnName": { + "type": "string" + } + }, + "description": "Training pipeline will perform following transformation functions. * The categorical string as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. * Categories that appear less than 5 times in the training dataset are treated as the \"unknown\" category. The \"unknown\" category gets its own special lookup index and resulting embedding." + }, + "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig": { + "description": "The config for Training & Prediction data skew detection. It specifies the training dataset sources and the skew detection parameters.", + "properties": { + "skewThresholds": { + "type": "object", + "description": "Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature.", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1ThresholdConfig" + } + }, + "defaultSkewThreshold": { + "$ref": "GoogleCloudAiplatformV1ThresholdConfig", + "description": "Skew anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features." + }, + "attributionScoreSkewThresholds": { + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1ThresholdConfig" + }, + "type": "object", + "description": "Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig" + }, + "GoogleCloudAiplatformV1CompleteTrialRequest": { + "type": "object", + "description": "Request message for VizierService.CompleteTrial.", + "id": "GoogleCloudAiplatformV1CompleteTrialRequest", + "properties": { + "trialInfeasible": { + "type": "boolean", + "description": "Optional. True if the Trial cannot be run with the given Parameter, and final_measurement will be ignored." + }, + "finalMeasurement": { + "$ref": "GoogleCloudAiplatformV1Measurement", + "description": "Optional. If provided, it will be used as the completed Trial's final_measurement; Otherwise, the service will auto-select a previously reported measurement as the final-measurement" + }, + "infeasibleReason": { + "description": "Optional. A human readable reason why the trial was infeasible. This should only be provided if `trial_infeasible` is true.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1FeatureViewFeatureRegistrySource": { + "description": "A Feature Registry source for features that need to be synced to Online Store.", + "type": "object", + "id": "GoogleCloudAiplatformV1FeatureViewFeatureRegistrySource", + "properties": { + "featureGroups": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroup" + }, + "description": "Required. List of features that need to be synced to Online Store." + }, + "projectNumber": { + "description": "Optional. The project number of the parent project of the Feature Groups.", + "type": "string", + "format": "int64" + } + } + }, + "GoogleCloudAiplatformV1ReadIndexDatapointsRequest": { + "description": "The request message for MatchService.ReadIndexDatapoints.", + "type": "object", + "id": "GoogleCloudAiplatformV1ReadIndexDatapointsRequest", + "properties": { + "ids": { + "type": "array", + "items": { + "type": "string" + }, + "description": "IDs of the datapoints to be searched for." + }, + "deployedIndexId": { + "description": "The ID of the DeployedIndex that will serve the request.", + "type": "string" + } + } + }, + "GoogleIamV1TestIamPermissionsResponse": { + "properties": { + "permissions": { + "description": "A subset of `TestPermissionsRequest.permissions` that the caller is allowed.", + "items": { + "type": "string" + }, + "type": "array" + } + }, + "description": "Response message for `TestIamPermissions` method.", + "id": "GoogleIamV1TestIamPermissionsResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfig": { + "type": "object", + "properties": { + "explanationBaseline": { + "description": "Predictions generated by the BatchPredictionJob using baseline dataset.", + "$ref": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaseline" + }, + "enableFeatureAttributes": { + "type": "boolean", + "description": "If want to analyze the Vertex Explainable AI feature attribute scores or not. If set to true, Vertex AI will log the feature attributions from explain response and do the skew/drift detection for them." + } + }, + "description": "The config for integrating with Vertex Explainable AI. Only applicable if the Model has explanation_spec populated.", + "id": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfig" + }, + "GoogleCloudAiplatformV1SchemaPredictPredictionTextExtractionPredictionResult": { + "properties": { + "confidences": { + "type": "array", + "items": { + "format": "float", + "type": "number" + }, + "description": "The Model's confidences in correctness of the predicted IDs, higher value means higher confidence. Order matches the Ids." + }, + "ids": { + "type": "array", + "items": { + "format": "int64", + "type": "string" + }, + "description": "The resource IDs of the AnnotationSpecs that had been identified, ordered by the confidence score descendingly." + }, + "textSegmentEndOffsets": { + "type": "array", + "items": { + "type": "string", + "format": "int64" + }, + "description": "The end offsets, inclusive, of the text segment in which the AnnotationSpec has been identified. Expressed as a zero-based number of characters as measured from the start of the text snippet." + }, + "textSegmentStartOffsets": { + "type": "array", + "items": { + "format": "int64", + "type": "string" + }, + "description": "The start offsets, inclusive, of the text segment in which the AnnotationSpec has been identified. Expressed as a zero-based number of characters as measured from the start of the text snippet." + }, + "displayNames": { + "items": { + "type": "string" + }, + "type": "array", + "description": "The display names of the AnnotationSpecs that had been identified, order matches the IDs." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1SchemaPredictPredictionTextExtractionPredictionResult", + "description": "Prediction output format for Text Extraction." + }, + "GoogleCloudAiplatformV1StartNotebookRuntimeOperationMetadata": { + "type": "object", + "description": "Metadata information for NotebookService.StartNotebookRuntime.", + "properties": { + "progressMessage": { + "description": "A human-readable message that shows the intermediate progress details of NotebookRuntime.", + "type": "string" + }, + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", + "description": "The operation generic information." + } + }, + "id": "GoogleCloudAiplatformV1StartNotebookRuntimeOperationMetadata" + }, + "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis": { + "type": "object", + "description": "Configuration of the Featurestore's ImportFeature Analysis Based Monitoring. This type of analysis generates statistics for values of each Feature imported by every ImportFeatureValues operation.", + "properties": { + "anomalyDetectionBaseline": { + "description": "The baseline used to do anomaly detection for the statistics generated by import features analysis.", + "enum": [ + "BASELINE_UNSPECIFIED", + "LATEST_STATS", + "MOST_RECENT_SNAPSHOT_STATS", + "PREVIOUS_IMPORT_FEATURES_STATS" + ], + "type": "string", + "enumDescriptions": [ + "Should not be used.", + "Choose the later one statistics generated by either most recent snapshot analysis or previous import features analysis. If non of them exists, skip anomaly detection and only generate a statistics.", + "Use the statistics generated by the most recent snapshot analysis if exists.", + "Use the statistics generated by the previous import features analysis if exists." + ] + }, + "state": { + "enumDescriptions": [ + "Should not be used.", + "The default behavior of whether to enable the monitoring. EntityType-level config: disabled. Feature-level config: inherited from the configuration of EntityType this Feature belongs to.", + "Explicitly enables import features analysis. EntityType-level config: by default enables import features analysis for all Features under it. Feature-level config: enables import features analysis regardless of the EntityType-level config.", + "Explicitly disables import features analysis. EntityType-level config: by default disables import features analysis for all Features under it. Feature-level config: disables import features analysis regardless of the EntityType-level config." + ], + "type": "string", + "enum": [ + "STATE_UNSPECIFIED", + "DEFAULT", + "ENABLED", + "DISABLED" + ], + "description": "Whether to enable / disable / inherite default hebavior for import features analysis." + } + }, + "id": "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis" + }, + "GoogleCloudAiplatformV1ModelEvaluation": { + "id": "GoogleCloudAiplatformV1ModelEvaluation", + "type": "object", + "description": "A collection of metrics calculated by comparing Model's predictions on all of the test data against annotations from the test data.", + "properties": { + "dataItemSchemaUri": { + "type": "string", + "description": "Points to a YAML file stored on Google Cloud Storage describing EvaluatedDataItemView.data_item_payload and EvaluatedAnnotation.data_item_payload. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). This field is not populated if there are neither EvaluatedDataItemViews nor EvaluatedAnnotations under this ModelEvaluation." + }, + "name": { + "description": "Output only. The resource name of the ModelEvaluation.", + "readOnly": true, + "type": "string" + }, + "explanationSpecs": { + "description": "Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.", + "items": { + "$ref": "GoogleCloudAiplatformV1ModelEvaluationModelEvaluationExplanationSpec" + }, + "type": "array" + }, + "createTime": { + "type": "string", + "format": "google-datetime", + "description": "Output only. Timestamp when this ModelEvaluation was created.", + "readOnly": true + }, + "metrics": { + "description": "Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri", + "type": "any" + }, + "sliceDimensions": { + "description": "All possible dimensions of ModelEvaluationSlices. The dimensions can be used as the filter of the ModelService.ListModelEvaluationSlices request, in the form of `slice.dimension = `.", + "items": { + "type": "string" + }, + "type": "array" + }, + "metadata": { + "description": "The metadata of the ModelEvaluation. For the ModelEvaluation uploaded from Managed Pipeline, metadata contains a structured value with keys of \"pipeline_job_id\", \"evaluation_dataset_type\", \"evaluation_dataset_path\", \"row_based_metrics_path\".", + "type": "any" + }, + "modelExplanation": { + "description": "Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for AutoML tabular Models. ", + "$ref": "GoogleCloudAiplatformV1ModelExplanation" + }, + "metricsSchemaUri": { + "type": "string", + "description": "Points to a YAML file stored on Google Cloud Storage describing the metrics of this ModelEvaluation. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject)." + }, + "annotationSchemaUri": { + "description": "Points to a YAML file stored on Google Cloud Storage describing EvaluatedDataItemView.predictions, EvaluatedDataItemView.ground_truths, EvaluatedAnnotation.predictions, and EvaluatedAnnotation.ground_truths. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). This field is not populated if there are neither EvaluatedDataItemViews nor EvaluatedAnnotations under this ModelEvaluation.", + "type": "string" + }, + "displayName": { + "type": "string", + "description": "The display name of the ModelEvaluation." + } + } + } + }, + "mtlsRootUrl": "https://aiplatform.mtls.googleapis.com/", + "endpoints": [ + { + "location": "africa-south1", + "endpointUrl": "https://africa-south1-aiplatform.googleapis.com/", + "description": "Locational Endpoint" + }, + { + "endpointUrl": "https://asia-east1-aiplatform.googleapis.com/", + "description": "Locational Endpoint", + "location": "asia-east1" + }, + { + "location": "asia-east2", + "description": "Locational Endpoint", + "endpointUrl": "https://asia-east2-aiplatform.googleapis.com/" + }, + { + "location": "asia-northeast1", + "description": "Locational Endpoint", + "endpointUrl": "https://asia-northeast1-aiplatform.googleapis.com/" + }, + { + "location": "asia-northeast2", + "description": "Locational Endpoint", + "endpointUrl": "https://asia-northeast2-aiplatform.googleapis.com/" + }, + { + "description": "Locational Endpoint", + "endpointUrl": "https://asia-northeast3-aiplatform.googleapis.com/", + "location": "asia-northeast3" + }, + { + "endpointUrl": "https://asia-south1-aiplatform.googleapis.com/", + "location": "asia-south1", + "description": "Locational Endpoint" + }, + { + "location": "asia-southeast1", + "endpointUrl": "https://asia-southeast1-aiplatform.googleapis.com/", + "description": "Locational Endpoint" + }, + { + "location": "asia-southeast2", + "description": "Locational Endpoint", + "endpointUrl": "https://asia-southeast2-aiplatform.googleapis.com/" + }, + { + "description": "Locational Endpoint", + "location": "australia-southeast1", + "endpointUrl": "https://australia-southeast1-aiplatform.googleapis.com/" + }, + { + "endpointUrl": "https://australia-southeast2-aiplatform.googleapis.com/", + "description": "Locational Endpoint", + "location": "australia-southeast2" + }, + { + "description": "Locational Endpoint", + "location": "europe-central2", + "endpointUrl": "https://europe-central2-aiplatform.googleapis.com/" + }, + { + "location": "europe-north1", + "endpointUrl": "https://europe-north1-aiplatform.googleapis.com/", + "description": "Locational Endpoint" + }, + { + "location": "europe-southwest1", + "endpointUrl": "https://europe-southwest1-aiplatform.googleapis.com/", + "description": "Locational Endpoint" + }, + { + "description": "Locational Endpoint", + "location": "europe-west1", + "endpointUrl": "https://europe-west1-aiplatform.googleapis.com/" + }, + { + "location": "europe-west2", + "endpointUrl": "https://europe-west2-aiplatform.googleapis.com/", + "description": "Locational Endpoint" + }, + { + "description": "Locational Endpoint", + "location": "europe-west3", + "endpointUrl": "https://europe-west3-aiplatform.googleapis.com/" + }, + { + "description": "Locational Endpoint", + "location": "europe-west4", + "endpointUrl": "https://europe-west4-aiplatform.googleapis.com/" + }, + { + "location": "europe-west6", + "description": "Locational Endpoint", + "endpointUrl": "https://europe-west6-aiplatform.googleapis.com/" + }, + { + "description": "Locational Endpoint", + "endpointUrl": "https://europe-west8-aiplatform.googleapis.com/", + "location": "europe-west8" + }, + { + "description": "Locational Endpoint", + "endpointUrl": "https://europe-west9-aiplatform.googleapis.com/", + "location": "europe-west9" + }, + { + "endpointUrl": "https://europe-west12-aiplatform.googleapis.com/", + "description": "Locational Endpoint", + "location": "europe-west12" + }, + { + "endpointUrl": "https://me-central1-aiplatform.googleapis.com/", + "description": "Locational Endpoint", + "location": "me-central1" + }, + { + "location": "me-central2", + "description": "Locational Endpoint", + "endpointUrl": "https://me-central2-aiplatform.googleapis.com/" + }, + { + "location": "me-west1", + "endpointUrl": "https://me-west1-aiplatform.googleapis.com/", + "description": "Locational Endpoint" + }, + { + "location": "northamerica-northeast1", + "description": "Locational Endpoint", + "endpointUrl": "https://northamerica-northeast1-aiplatform.googleapis.com/" + }, + { + "description": "Locational Endpoint", + "location": "northamerica-northeast2", + "endpointUrl": "https://northamerica-northeast2-aiplatform.googleapis.com/" + }, + { + "endpointUrl": "https://southamerica-east1-aiplatform.googleapis.com/", + "description": "Locational Endpoint", + "location": "southamerica-east1" + }, + { + "location": "southamerica-west1", + "description": "Locational Endpoint", + "endpointUrl": "https://southamerica-west1-aiplatform.googleapis.com/" + }, + { + "endpointUrl": "https://us-central1-aiplatform.googleapis.com/", + "description": "Locational Endpoint", + "location": "us-central1" + }, + { + "location": "us-central2", + "endpointUrl": "https://us-central2-aiplatform.googleapis.com/", + "description": "Locational Endpoint" + }, + { + "description": "Locational Endpoint", + "endpointUrl": "https://us-east1-aiplatform.googleapis.com/", + "location": "us-east1" + }, + { + "description": "Locational Endpoint", + "endpointUrl": "https://us-east4-aiplatform.googleapis.com/", + "location": "us-east4" + }, + { + "location": "us-south1", + "endpointUrl": "https://us-south1-aiplatform.googleapis.com/", + "description": "Locational Endpoint" + }, + { + "description": "Locational Endpoint", + "endpointUrl": "https://us-west1-aiplatform.googleapis.com/", + "location": "us-west1" + }, + { + "location": "us-west2", + "endpointUrl": "https://us-west2-aiplatform.googleapis.com/", + "description": "Locational Endpoint" + }, + { + "endpointUrl": "https://us-west3-aiplatform.googleapis.com/", + "description": "Locational Endpoint", + "location": "us-west3" + }, + { + "endpointUrl": "https://us-west4-aiplatform.googleapis.com/", + "location": "us-west4", + "description": "Locational Endpoint" + }, + { + "endpointUrl": "https://us-east5-aiplatform.googleapis.com/", + "location": "us-east5", + "description": "Locational Endpoint" + } + ], + "discoveryVersion": "v1" +} diff --git a/etc/api/aiplatform/v1beta1/aiplatform-api.json b/etc/api/aiplatform/v1beta1/aiplatform-api.json new file mode 100644 index 0000000000..0be9389c82 --- /dev/null +++ b/etc/api/aiplatform/v1beta1/aiplatform-api.json @@ -0,0 +1,45192 @@ +{ + "name": "aiplatform", + "fullyEncodeReservedExpansion": true, + "revision": "20240715", + "baseUrl": "https://aiplatform.googleapis.com/", + "schemas": { + "GoogleCloudAiplatformV1beta1ToolNameMatchResults": { + "id": "GoogleCloudAiplatformV1beta1ToolNameMatchResults", + "description": "Results for tool name match metric.", + "properties": { + "toolNameMatchMetricValues": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ToolNameMatchMetricValue" + }, + "type": "array", + "description": "Output only. Tool name match metric values.", + "readOnly": true + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1RagContextsContext": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1RagContextsContext", + "properties": { + "distance": { + "format": "double", + "type": "number", + "description": "The distance between the query vector and the context text vector." + }, + "sourceUri": { + "type": "string", + "description": "For vertex RagStore, if the file is imported from Cloud Storage or Google Drive, source_uri will be original file URI in Cloud Storage or Google Drive; if file is uploaded, source_uri will be file display name." + }, + "text": { + "type": "string", + "description": "The text chunk." + } + }, + "description": "A context of the query." + }, + "GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoObjectTrackingPredictionResult": { + "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoObjectTrackingPredictionResult", + "type": "object", + "properties": { + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that had been identified." + }, + "confidence": { + "description": "The Model's confidence in correction of this prediction, higher value means higher confidence.", + "type": "number", + "format": "float" + }, + "frames": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoObjectTrackingPredictionResultFrame" + }, + "description": "All of the frames of the video in which a single object instance has been detected. The bounding boxes in the frames identify the same object." + }, + "timeSegmentStart": { + "description": "The beginning, inclusive, of the video's time segment in which the object instance has been detected. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end.", + "format": "google-duration", + "type": "string" + }, + "timeSegmentEnd": { + "description": "The end, inclusive, of the video's time segment in which the object instance has been detected. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end.", + "format": "google-duration", + "type": "string" + }, + "id": { + "type": "string", + "description": "The resource ID of the AnnotationSpec that had been identified." + } + }, + "description": "Prediction output format for Video Object Tracking." + }, + "GoogleCloudAiplatformV1beta1Explanation": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1Explanation", + "description": "Explanation of a prediction (provided in PredictResponse.predictions) produced by the Model on a given instance.", + "properties": { + "neighbors": { + "description": "Output only. List of the nearest neighbors for example-based explanations. For models deployed with the examples explanations feature enabled, the attributions field is empty and instead the neighbors field is populated.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Neighbor" + }, + "readOnly": true + }, + "attributions": { + "type": "array", + "description": "Output only. Feature attributions grouped by predicted outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. Attribution.output_index can be used to identify which output this attribution is explaining. By default, we provide Shapley values for the predicted class. However, you can configure the explanation request to generate Shapley values for any other classes too. For example, if a model predicts a probability of `0.4` for approving a loan application, the model's decision is to reject the application since `p(reject) = 0.6 \u003e p(approve) = 0.4`, and the default Shapley values would be computed for rejection decision and not approval, even though the latter might be the positive class. If users set ExplanationParameters.top_k, the attributions are sorted by instance_output_value in descending order. If ExplanationParameters.output_indices is specified, the attributions are stored by Attribution.output_index in the same order as they appear in the output_indices.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Attribution" + }, + "readOnly": true + } + } + }, + "GoogleCloudAiplatformV1beta1Tensor": { + "properties": { + "tensorVal": { + "type": "string", + "format": "byte", + "description": "Serialized raw tensor content." + }, + "stringVal": { + "type": "array", + "description": "STRING", + "items": { + "type": "string" + } + }, + "uint64Val": { + "items": { + "format": "uint64", + "type": "string" + }, + "type": "array", + "description": "UINT64" + }, + "doubleVal": { + "type": "array", + "description": "DOUBLE", + "items": { + "format": "double", + "type": "number" + } + }, + "dtype": { + "description": "The data type of tensor.", + "enum": [ + "DATA_TYPE_UNSPECIFIED", + "BOOL", + "STRING", + "FLOAT", + "DOUBLE", + "INT8", + "INT16", + "INT32", + "INT64", + "UINT8", + "UINT16", + "UINT32", + "UINT64" + ], + "enumDescriptions": [ + "Not a legal value for DataType. Used to indicate a DataType field has not been set.", + "Data types that all computation devices are expected to be capable to support.", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "" + ], + "type": "string" + }, + "uintVal": { + "items": { + "type": "integer", + "format": "uint32" + }, + "description": "UINT8 UINT16 UINT32", + "type": "array" + }, + "structVal": { + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1Tensor" + }, + "description": "A map of string to tensor.", + "type": "object" + }, + "listVal": { + "type": "array", + "description": "A list of tensor values.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Tensor" + } + }, + "boolVal": { + "type": "array", + "items": { + "type": "boolean" + }, + "description": "Type specific representations that make it easy to create tensor protos in all languages. Only the representation corresponding to \"dtype\" can be set. The values hold the flattened representation of the tensor in row major order. BOOL" + }, + "int64Val": { + "items": { + "type": "string", + "format": "int64" + }, + "type": "array", + "description": "INT64" + }, + "floatVal": { + "items": { + "type": "number", + "format": "float" + }, + "type": "array", + "description": "FLOAT" + }, + "intVal": { + "items": { + "format": "int32", + "type": "integer" + }, + "description": "INT_8 INT_16 INT_32", + "type": "array" + }, + "bytesVal": { + "items": { + "type": "string", + "format": "byte" + }, + "type": "array", + "description": "STRING" + }, + "shape": { + "description": "Shape of the tensor.", + "type": "array", + "items": { + "format": "int64", + "type": "string" + } + } + }, + "type": "object", + "description": "A tensor value type.", + "id": "GoogleCloudAiplatformV1beta1Tensor" + }, + "GoogleCloudAiplatformV1beta1ToolParameterKVMatchMetricValue": { + "properties": { + "score": { + "format": "float", + "type": "number", + "description": "Output only. Tool parameter key value match score.", + "readOnly": true + } + }, + "type": "object", + "description": "Tool parameter key value match metric value for an instance.", + "id": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchMetricValue" + }, + "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob": { + "properties": { + "samplePredictInstance": { + "type": "any", + "description": "Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests." + }, + "bigqueryTables": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringBigQueryTable" + }, + "type": "array", + "readOnly": true, + "description": "Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum: 1. Training data logging predict request/response 2. Serving data logging predict request/response" + }, + "predictInstanceSchemaUri": { + "description": "YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation). If not set, we will generate predict schema from collected predict requests.", + "type": "string" + }, + "endpoint": { + "type": "string", + "description": "Required. Endpoint resource name. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" + }, + "error": { + "description": "Output only. Only populated when the job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "$ref": "GoogleRpcStatus", + "readOnly": true + }, + "analysisInstanceSchemaUri": { + "type": "string", + "description": "YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze. If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string." + }, + "labels": { + "type": "object", + "additionalProperties": { + "type": "string" + }, + "description": "The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels." + }, + "updateTime": { + "readOnly": true, + "format": "google-datetime", + "type": "string", + "description": "Output only. Timestamp when this ModelDeploymentMonitoringJob was updated most recently." + }, + "modelDeploymentMonitoringScheduleConfig": { + "description": "Required. Schedule config for running the monitoring job.", + "$ref": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringScheduleConfig" + }, + "state": { + "type": "string", + "description": "Output only. The detailed state of the monitoring job. When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'.", + "readOnly": true, + "enum": [ + "JOB_STATE_UNSPECIFIED", + "JOB_STATE_QUEUED", + "JOB_STATE_PENDING", + "JOB_STATE_RUNNING", + "JOB_STATE_SUCCEEDED", + "JOB_STATE_FAILED", + "JOB_STATE_CANCELLING", + "JOB_STATE_CANCELLED", + "JOB_STATE_PAUSED", + "JOB_STATE_EXPIRED", + "JOB_STATE_UPDATING", + "JOB_STATE_PARTIALLY_SUCCEEDED" + ], + "enumDescriptions": [ + "The job state is unspecified.", + "The job has been just created or resumed and processing has not yet begun.", + "The service is preparing to run the job.", + "The job is in progress.", + "The job completed successfully.", + "The job failed.", + "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "The job has been cancelled.", + "The job has been stopped, and can be resumed.", + "The job has expired.", + "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", + "The job is partially succeeded, some results may be missing due to errors." + ] + }, + "enableMonitoringPipelineLogs": { + "type": "boolean", + "description": "If true, the scheduled monitoring pipeline logs are sent to Google Cloud Logging, including pipeline status and anomalies detected. Please note the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging#pricing)." + }, + "modelMonitoringAlertConfig": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfig", + "description": "Alert config for model monitoring." + }, + "loggingSamplingStrategy": { + "$ref": "GoogleCloudAiplatformV1beta1SamplingStrategy", + "description": "Required. Sample Strategy for logging." + }, + "nextScheduleTime": { + "description": "Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.", + "readOnly": true, + "type": "string", + "format": "google-datetime" + }, + "latestMonitoringPipelineMetadata": { + "description": "Output only. Latest triggered monitoring pipeline metadata.", + "$ref": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata", + "readOnly": true + }, + "logTtl": { + "format": "google-duration", + "type": "string", + "description": "The TTL of BigQuery tables in user projects which stores logs. A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day." + }, + "name": { + "readOnly": true, + "description": "Output only. Resource name of a ModelDeploymentMonitoringJob.", + "type": "string" + }, + "displayName": { + "type": "string", + "description": "Required. The user-defined name of the ModelDeploymentMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob." + }, + "statsAnomaliesBaseDirectory": { + "$ref": "GoogleCloudAiplatformV1beta1GcsDestination", + "description": "Stats anomalies base folder path." + }, + "scheduleState": { + "description": "Output only. Schedule state when the monitoring job is in Running state.", + "enumDescriptions": [ + "Unspecified state.", + "The pipeline is picked up and wait to run.", + "The pipeline is offline and will be scheduled for next run.", + "The pipeline is running." + ], + "readOnly": true, + "enum": [ + "MONITORING_SCHEDULE_STATE_UNSPECIFIED", + "PENDING", + "OFFLINE", + "RUNNING" + ], + "type": "string" + }, + "createTime": { + "readOnly": true, + "description": "Output only. Timestamp when this ModelDeploymentMonitoringJob was created.", + "format": "google-datetime", + "type": "string" + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", + "description": "Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key." + }, + "modelDeploymentMonitoringObjectiveConfigs": { + "description": "Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringObjectiveConfig" + } + } + }, + "id": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob", + "description": "Represents a job that runs periodically to monitor the deployed models in an endpoint. It will analyze the logged training & prediction data to detect any abnormal behaviors.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1MigratableResourceAutomlModel": { + "properties": { + "model": { + "type": "string", + "description": "Full resource name of automl Model. Format: `projects/{project}/locations/{location}/models/{model}`." + }, + "modelDisplayName": { + "type": "string", + "description": "The Model's display name in automl.googleapis.com." + } + }, + "type": "object", + "description": "Represents one Model in automl.googleapis.com.", + "id": "GoogleCloudAiplatformV1beta1MigratableResourceAutomlModel" + }, + "GoogleCloudAiplatformV1beta1SchemaPredictInstanceImageClassificationPredictionInstance": { + "type": "object", + "properties": { + "mimeType": { + "type": "string", + "description": "The MIME type of the content of the image. Only the images in below listed MIME types are supported. - image/jpeg - image/gif - image/png - image/webp - image/bmp - image/tiff - image/vnd.microsoft.icon" + }, + "content": { + "description": "The image bytes or Cloud Storage URI to make the prediction on.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaPredictInstanceImageClassificationPredictionInstance", + "description": "Prediction input format for Image Classification." + }, + "GoogleCloudAiplatformV1beta1FeatureOnlineStoreEmbeddingManagement": { + "properties": { + "enabled": { + "description": "Optional. Immutable. Whether to enable embedding management in this FeatureOnlineStore. It's immutable after creation to ensure the FeatureOnlineStore availability.", + "type": "boolean" + } + }, + "id": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreEmbeddingManagement", + "description": "Deprecated: This sub message is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type. Contains settings for embedding management.", + "deprecated": true, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDatasetModelMonitoringBigQuerySource": { + "type": "object", + "description": "Dataset spec for data sotred in BigQuery.", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDatasetModelMonitoringBigQuerySource", + "properties": { + "query": { + "description": "Standard SQL to be used instead of the `table_uri`.", + "type": "string" + }, + "tableUri": { + "description": "BigQuery URI to a table, up to 2000 characters long. All the columns in the table will be selected. Accepted forms: * BigQuery path. For example: `bq://projectId.bqDatasetId.bqTableId`.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1AddContextArtifactsAndExecutionsResponse": { + "properties": {}, + "description": "Response message for MetadataService.AddContextArtifactsAndExecutions.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1AddContextArtifactsAndExecutionsResponse" + }, + "GoogleCloudLocationListLocationsResponse": { + "description": "The response message for Locations.ListLocations.", + "type": "object", + "properties": { + "locations": { + "items": { + "$ref": "GoogleCloudLocationLocation" + }, + "description": "A list of locations that matches the specified filter in the request.", + "type": "array" + }, + "nextPageToken": { + "description": "The standard List next-page token.", + "type": "string" + } + }, + "id": "GoogleCloudLocationListLocationsResponse" + }, + "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigVertexPredictionEndpoint": { + "properties": { + "model": { + "type": "string", + "description": "Output only. The resource name of the model that is deployed on the endpoint. Present only when the endpoint is not a publisher model. Pattern: `projects/{project}/locations/{location}/models/{model}`", + "readOnly": true + }, + "endpoint": { + "type": "string", + "description": "Required. The endpoint resource name. Format: `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}` or `projects/{project}/locations/{location}/endpoints/{endpoint}`" + }, + "modelVersionId": { + "readOnly": true, + "description": "Output only. Version ID of the model that is deployed on the endpoint. Present only when the endpoint is not a publisher model.", + "type": "string" + } + }, + "type": "object", + "description": "Config representing a model hosted on Vertex Prediction Endpoint.", + "id": "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigVertexPredictionEndpoint" + }, + "GoogleCloudAiplatformV1beta1GroundednessInput": { + "description": "Input for groundedness metric.", + "id": "GoogleCloudAiplatformV1beta1GroundednessInput", + "type": "object", + "properties": { + "instance": { + "$ref": "GoogleCloudAiplatformV1beta1GroundednessInstance", + "description": "Required. Groundedness instance." + }, + "metricSpec": { + "description": "Required. Spec for groundedness metric.", + "$ref": "GoogleCloudAiplatformV1beta1GroundednessSpec" + } + } + }, + "GoogleCloudAiplatformV1beta1SlackSource": { + "description": "The Slack source for the ImportRagFilesRequest.", + "properties": { + "channels": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SlackSourceSlackChannels" + }, + "description": "Required. The Slack channels.", + "type": "array" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SlackSource" + }, + "GoogleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsResponse": { + "description": "Response message for ModelService.BatchImportEvaluatedAnnotations", + "properties": { + "importedEvaluatedAnnotationsCount": { + "type": "integer", + "readOnly": true, + "format": "int32", + "description": "Output only. Number of EvaluatedAnnotations imported." + } + }, + "id": "GoogleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SamplingStrategy": { + "properties": { + "randomSampleConfig": { + "$ref": "GoogleCloudAiplatformV1beta1SamplingStrategyRandomSampleConfig", + "description": "Random sample config. Will support more sampling strategies later." + } + }, + "description": "Sampling Strategy for logging, can be for both training and prediction dataset.", + "id": "GoogleCloudAiplatformV1beta1SamplingStrategy", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaPredictPredictionClassificationPredictionResult": { + "description": "Prediction output format for Image and Text Classification.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionClassificationPredictionResult", + "properties": { + "ids": { + "description": "The resource IDs of the AnnotationSpecs that had been identified.", + "type": "array", + "items": { + "type": "string", + "format": "int64" + } + }, + "displayNames": { + "description": "The display names of the AnnotationSpecs that had been identified, order matches the IDs.", + "type": "array", + "items": { + "type": "string" + } + }, + "confidences": { + "items": { + "type": "number", + "format": "float" + }, + "description": "The Model's confidences in correctness of the predicted IDs, higher value means higher confidence. Order matches the Ids.", + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1beta1StreamingReadFeatureValuesRequest": { + "description": "Request message for FeaturestoreOnlineServingService.StreamingFeatureValuesRead.", + "id": "GoogleCloudAiplatformV1beta1StreamingReadFeatureValuesRequest", + "type": "object", + "properties": { + "entityIds": { + "items": { + "type": "string" + }, + "description": "Required. IDs of entities to read Feature values of. The maximum number of IDs is 100. For example, for a machine learning model predicting user clicks on a website, an entity ID could be `user_123`.", + "type": "array" + }, + "featureSelector": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureSelector", + "description": "Required. Selector choosing Features of the target EntityType. Feature IDs will be deduplicated." + } + } + }, + "GoogleCloudAiplatformV1beta1CancelCustomJobRequest": { + "properties": {}, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1CancelCustomJobRequest", + "description": "Request message for JobService.CancelCustomJob." + }, + "GoogleCloudAiplatformV1beta1CreateDeploymentResourcePoolRequest": { + "type": "object", + "properties": { + "deploymentResourcePoolId": { + "description": "Required. The ID to use for the DeploymentResourcePool, which will become the final component of the DeploymentResourcePool's resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`.", + "type": "string" + }, + "deploymentResourcePool": { + "description": "Required. The DeploymentResourcePool to create.", + "$ref": "GoogleCloudAiplatformV1beta1DeploymentResourcePool" + } + }, + "id": "GoogleCloudAiplatformV1beta1CreateDeploymentResourcePoolRequest", + "description": "Request message for CreateDeploymentResourcePool method." + }, + "GoogleCloudAiplatformV1beta1CancelHyperparameterTuningJobRequest": { + "description": "Request message for JobService.CancelHyperparameterTuningJob.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1CancelHyperparameterTuningJobRequest", + "properties": {} + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionMetadata": { + "properties": { + "successfulStopReason": { + "type": "string", + "enumDescriptions": [ + "Should not be set.", + "The inputs.budgetMilliNodeHours had been reached.", + "Further training of the Model ceased to increase its quality, since it already has converged." + ], + "enum": [ + "SUCCESSFUL_STOP_REASON_UNSPECIFIED", + "BUDGET_REACHED", + "MODEL_CONVERGED" + ], + "description": "For successful job completions, this is the reason why the job has finished." + }, + "costMilliNodeHours": { + "format": "int64", + "type": "string", + "description": "The actual training cost of creating this model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed inputs.budgetMilliNodeHours." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionMetadata" + }, + "GoogleCloudAiplatformV1beta1ExamplesExampleGcsSource": { + "description": "The Cloud Storage input instances.", + "id": "GoogleCloudAiplatformV1beta1ExamplesExampleGcsSource", + "properties": { + "dataFormat": { + "description": "The format in which instances are given, if not specified, assume it's JSONL format. Currently only JSONL format is supported.", + "enumDescriptions": [ + "Format unspecified, used when unset.", + "Examples are stored in JSONL files." + ], + "type": "string", + "enum": [ + "DATA_FORMAT_UNSPECIFIED", + "JSONL" + ] + }, + "gcsSource": { + "$ref": "GoogleCloudAiplatformV1beta1GcsSource", + "description": "The Cloud Storage location for the input instances." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs", + "properties": { + "uptrainBaseModelId": { + "description": "The ID of `base` model for upTraining. If it is specified, the new model will be upTrained based on the `base` model for upTraining. Otherwise, the new model will be trained from scratch. The `base` model for upTraining must be in the same Project and Location as the new Model to train, and have the same modelType.", + "type": "string" + }, + "modelType": { + "enum": [ + "MODEL_TYPE_UNSPECIFIED", + "CLOUD", + "CLOUD_1", + "MOBILE_TF_LOW_LATENCY_1", + "MOBILE_TF_VERSATILE_1", + "MOBILE_TF_HIGH_ACCURACY_1", + "EFFICIENTNET", + "MAXVIT", + "VIT", + "COCA" + ], + "enumDescriptions": [ + "Should not be set.", + "A Model best tailored to be used within Google Cloud, and which cannot be exported. Default.", + "A model type best tailored to be used within Google Cloud, which cannot be exported externally. Compared to the CLOUD model above, it is expected to have higher prediction accuracy.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow or Core ML model and used on a mobile or edge device afterwards. Expected to have low latency, but may have lower prediction quality than other mobile models.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow or Core ML model and used on a mobile or edge device with afterwards.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow or Core ML model and used on a mobile or edge device afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other mobile models.", + "EfficientNet model for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally.", + "MaxViT model for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally.", + "ViT model for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally.", + "CoCa model for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally." + ], + "type": "string" + }, + "disableEarlyStopping": { + "description": "Use the entire training budget. This disables the early stopping feature. When false the early stopping feature is enabled, which means that AutoML Image Classification might stop training before the entire training budget has been used.", + "type": "boolean" + }, + "budgetMilliNodeHours": { + "type": "string", + "description": "The training budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The actual metadata.costMilliNodeHours will be equal or less than this value. If further model training ceases to provide any improvements, it will stop without using the full budget and the metadata.successfulStopReason will be `model-converged`. Note, node_hour = actual_hour * number_of_nodes_involved. For modelType `cloud`(default), the budget must be between 8,000 and 800,000 milli node hours, inclusive. The default value is 192,000 which represents one day in wall time, considering 8 nodes are used. For model types `mobile-tf-low-latency-1`, `mobile-tf-versatile-1`, `mobile-tf-high-accuracy-1`, the training budget must be between 1,000 and 100,000 milli node hours, inclusive. The default value is 24,000 which represents one day in wall time on a single node that is used.", + "format": "int64" + }, + "baseModelId": { + "type": "string", + "description": "The ID of the `base` model. If it is specified, the new model will be trained based on the `base` model. Otherwise, the new model will be trained from scratch. The `base` model must be in the same Project and Location as the new Model to train, and have the same modelType." + }, + "tunableParameter": { + "description": "Trainer type for Vision TrainRequest.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter" + }, + "multiLabel": { + "type": "boolean", + "description": "If false, a single-label (multi-class) Model will be trained (i.e. assuming that for each image just up to one annotation may be applicable). If true, a multi-label Model will be trained (i.e. assuming that for each image multiple annotations may be applicable)." + } + } + }, + "GoogleCloudAiplatformV1beta1SafetySetting": { + "type": "object", + "description": "Safety settings.", + "properties": { + "threshold": { + "description": "Required. The harm block threshold.", + "type": "string", + "enum": [ + "HARM_BLOCK_THRESHOLD_UNSPECIFIED", + "BLOCK_LOW_AND_ABOVE", + "BLOCK_MEDIUM_AND_ABOVE", + "BLOCK_ONLY_HIGH", + "BLOCK_NONE" + ], + "enumDescriptions": [ + "Unspecified harm block threshold.", + "Block low threshold and above (i.e. block more).", + "Block medium threshold and above.", + "Block only high threshold (i.e. block less).", + "Block none." + ] + }, + "category": { + "enum": [ + "HARM_CATEGORY_UNSPECIFIED", + "HARM_CATEGORY_HATE_SPEECH", + "HARM_CATEGORY_DANGEROUS_CONTENT", + "HARM_CATEGORY_HARASSMENT", + "HARM_CATEGORY_SEXUALLY_EXPLICIT" + ], + "enumDescriptions": [ + "The harm category is unspecified.", + "The harm category is hate speech.", + "The harm category is dangerous content.", + "The harm category is harassment.", + "The harm category is sexually explicit content." + ], + "description": "Required. Harm category.", + "type": "string" + }, + "method": { + "type": "string", + "description": "Optional. Specify if the threshold is used for probability or severity score. If not specified, the threshold is used for probability score.", + "enumDescriptions": [ + "The harm block method is unspecified.", + "The harm block method uses both probability and severity scores.", + "The harm block method uses the probability score." + ], + "enum": [ + "HARM_BLOCK_METHOD_UNSPECIFIED", + "SEVERITY", + "PROBABILITY" + ] + } + }, + "id": "GoogleCloudAiplatformV1beta1SafetySetting" + }, + "GoogleCloudAiplatformV1beta1UpdateFeaturestoreOperationMetadata": { + "description": "Details of operations that perform update Featurestore.", + "properties": { + "genericMetadata": { + "description": "Operation metadata for Featurestore.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1UpdateFeaturestoreOperationMetadata" + }, + "GoogleCloudAiplatformV1beta1RagFile": { + "description": "A RagFile contains user data for chunking, embedding and indexing.", + "type": "object", + "properties": { + "createTime": { + "type": "string", + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Timestamp when this RagFile was created." + }, + "sizeBytes": { + "readOnly": true, + "format": "int64", + "type": "string", + "description": "Output only. The size of the RagFile in bytes." + }, + "googleDriveSource": { + "$ref": "GoogleCloudAiplatformV1beta1GoogleDriveSource", + "readOnly": true, + "description": "Output only. Google Drive location. Supports importing individual files as well as Google Drive folders." + }, + "description": { + "type": "string", + "description": "Optional. The description of the RagFile." + }, + "jiraSource": { + "description": "The RagFile is imported from a Jira query.", + "$ref": "GoogleCloudAiplatformV1beta1JiraSource" + }, + "name": { + "description": "Output only. The resource name of the RagFile.", + "readOnly": true, + "type": "string" + }, + "displayName": { + "description": "Required. The display name of the RagFile. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + }, + "slackSource": { + "$ref": "GoogleCloudAiplatformV1beta1SlackSource", + "description": "The RagFile is imported from a Slack channel." + }, + "updateTime": { + "format": "google-datetime", + "description": "Output only. Timestamp when this RagFile was last updated.", + "type": "string", + "readOnly": true + }, + "gcsSource": { + "description": "Output only. Google Cloud Storage location of the RagFile. It does not support wildcards in the Cloud Storage uri for now.", + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1GcsSource" + }, + "directUploadSource": { + "readOnly": true, + "description": "Output only. The RagFile is encapsulated and uploaded in the UploadRagFile request.", + "$ref": "GoogleCloudAiplatformV1beta1DirectUploadSource" + }, + "ragFileType": { + "enumDescriptions": [ + "RagFile type is unspecified.", + "RagFile type is TXT.", + "RagFile type is PDF." + ], + "type": "string", + "readOnly": true, + "description": "Output only. The type of the RagFile.", + "enum": [ + "RAG_FILE_TYPE_UNSPECIFIED", + "RAG_FILE_TYPE_TXT", + "RAG_FILE_TYPE_PDF" + ] + } + }, + "id": "GoogleCloudAiplatformV1beta1RagFile" + }, + "GoogleCloudAiplatformV1beta1FeatureGroupBigQuery": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1FeatureGroupBigQuery", + "properties": { + "entityIdColumns": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Optional. Columns to construct entity_id / row keys. If not provided defaults to `entity_id`." + }, + "bigQuerySource": { + "$ref": "GoogleCloudAiplatformV1beta1BigQuerySource", + "description": "Required. Immutable. The BigQuery source URI that points to either a BigQuery Table or View." + } + }, + "description": "Input source type for BigQuery Tables and Views." + }, + "GoogleCloudAiplatformV1beta1FeatureViewIndexConfig": { + "type": "object", + "description": "Configuration for vector indexing.", + "properties": { + "embeddingDimension": { + "description": "Optional. The number of dimensions of the input embedding.", + "type": "integer", + "format": "int32" + }, + "distanceMeasureType": { + "type": "string", + "enumDescriptions": [ + "Should not be set.", + "Euclidean (L_2) Distance.", + "Cosine Distance. Defined as 1 - cosine similarity. We strongly suggest using DOT_PRODUCT_DISTANCE + UNIT_L2_NORM instead of COSINE distance. Our algorithms have been more optimized for DOT_PRODUCT distance which, when combined with UNIT_L2_NORM, is mathematically equivalent to COSINE distance and results in the same ranking.", + "Dot Product Distance. Defined as a negative of the dot product." + ], + "enum": [ + "DISTANCE_MEASURE_TYPE_UNSPECIFIED", + "SQUARED_L2_DISTANCE", + "COSINE_DISTANCE", + "DOT_PRODUCT_DISTANCE" + ], + "description": "Optional. The distance measure used in nearest neighbor search." + }, + "bruteForceConfig": { + "description": "Optional. Configuration options for using brute force search, which simply implements the standard linear search in the database for each query. It is primarily meant for benchmarking and to generate the ground truth for approximate search.", + "$ref": "GoogleCloudAiplatformV1beta1FeatureViewIndexConfigBruteForceConfig" + }, + "crowdingColumn": { + "type": "string", + "description": "Optional. Column of crowding. This column contains crowding attribute which is a constraint on a neighbor list produced by FeatureOnlineStoreService.SearchNearestEntities to diversify search results. If NearestNeighborQuery.per_crowding_attribute_neighbor_count is set to K in SearchNearestEntitiesRequest, it's guaranteed that no more than K entities of the same crowding attribute are returned in the response." + }, + "filterColumns": { + "type": "array", + "description": "Optional. Columns of features that're used to filter vector search results.", + "items": { + "type": "string" + } + }, + "embeddingColumn": { + "description": "Optional. Column of embedding. This column contains the source data to create index for vector search. embedding_column must be set when using vector search.", + "type": "string" + }, + "treeAhConfig": { + "description": "Optional. Configuration options for the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396", + "$ref": "GoogleCloudAiplatformV1beta1FeatureViewIndexConfigTreeAHConfig" + } + }, + "id": "GoogleCloudAiplatformV1beta1FeatureViewIndexConfig" + }, + "GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponsePerUserUsageData": { + "description": "Per user usage data.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponsePerUserUsageData", + "properties": { + "username": { + "type": "string", + "description": "User's username" + }, + "viewCount": { + "format": "int64", + "description": "Number of times the user has read data within the Tensorboard.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1ImportRagFilesConfig": { + "description": "Config for importing RagFiles.", + "id": "GoogleCloudAiplatformV1beta1ImportRagFilesConfig", + "type": "object", + "properties": { + "googleDriveSource": { + "$ref": "GoogleCloudAiplatformV1beta1GoogleDriveSource", + "description": "Google Drive location. Supports importing individual files as well as Google Drive folders." + }, + "slackSource": { + "description": "Slack channels with their corresponding access tokens.", + "$ref": "GoogleCloudAiplatformV1beta1SlackSource" + }, + "ragFileChunkingConfig": { + "$ref": "GoogleCloudAiplatformV1beta1RagFileChunkingConfig", + "description": "Specifies the size and overlap of chunks after importing RagFiles." + }, + "gcsSource": { + "$ref": "GoogleCloudAiplatformV1beta1GcsSource", + "description": "Google Cloud Storage location. Supports importing individual files as well as entire Google Cloud Storage directories. Sample formats: - `gs://bucket_name/my_directory/object_name/my_file.txt` - `gs://bucket_name/my_directory`" + }, + "jiraSource": { + "description": "Jira queries with their corresponding authentication.", + "$ref": "GoogleCloudAiplatformV1beta1JiraSource" + }, + "maxEmbeddingRequestsPerMin": { + "format": "int32", + "description": "Optional. The max number of queries per minute that this job is allowed to make to the embedding model specified on the corpus. This value is specific to this job and not shared across other import jobs. Consult the Quotas page on the project to set an appropriate value here. If unspecified, a default value of 1,000 QPM would be used.", + "type": "integer" + } + } + }, + "GoogleCloudAiplatformV1beta1ExtensionManifestApiSpec": { + "description": "The API specification shown to the LLM.", + "id": "GoogleCloudAiplatformV1beta1ExtensionManifestApiSpec", + "type": "object", + "properties": { + "openApiYaml": { + "description": "The API spec in Open API standard and YAML format.", + "type": "string" + }, + "openApiGcsUri": { + "type": "string", + "description": "Cloud Storage URI pointing to the OpenAPI spec." + } + } + }, + "GoogleCloudAiplatformV1beta1UpdateFeatureOnlineStoreOperationMetadata": { + "properties": { + "genericMetadata": { + "description": "Operation metadata for FeatureOnlineStore.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1UpdateFeatureOnlineStoreOperationMetadata", + "description": "Details of operations that perform update FeatureOnlineStore." + }, + "GoogleCloudAiplatformV1beta1FeatureOnlineStoreOptimized": { + "description": "Optimized storage type", + "id": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreOptimized", + "type": "object", + "properties": {} + }, + "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsResponse": { + "properties": { + "nextPageToken": { + "description": "The page token that can be used by the next ModelMonitoringService.SearchModelMonitoringStats call.", + "type": "string" + }, + "monitoringStats": { + "description": "Stats retrieved for requested objectives.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringStats" + } + } + }, + "description": "Response message for ModelMonitoringService.SearchModelMonitoringStats.", + "id": "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ListNasTrialDetailsResponse": { + "type": "object", + "description": "Response message for JobService.ListNasTrialDetails", + "properties": { + "nasTrialDetails": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1NasTrialDetail" + }, + "description": "List of top NasTrials in the requested page.", + "type": "array" + }, + "nextPageToken": { + "description": "A token to retrieve the next page of results. Pass to ListNasTrialDetailsRequest.page_token to obtain that page.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1ListNasTrialDetailsResponse" + }, + "GoogleProtobufEmpty": { + "id": "GoogleProtobufEmpty", + "description": "A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }", + "type": "object", + "properties": {} + }, + "GoogleCloudAiplatformV1beta1CreateFeatureOnlineStoreOperationMetadata": { + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "Operation metadata for FeatureOnlineStore." + } + }, + "id": "GoogleCloudAiplatformV1beta1CreateFeatureOnlineStoreOperationMetadata", + "type": "object", + "description": "Details of operations that perform create FeatureOnlineStore." + }, + "GoogleCloudAiplatformV1beta1AutoscalingMetricSpec": { + "properties": { + "metricName": { + "type": "string", + "description": "Required. The resource metric name. Supported metrics: * For Online Prediction: * `aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle` * `aiplatform.googleapis.com/prediction/online/cpu/utilization`" + }, + "target": { + "description": "The target resource utilization in percentage (1% - 100%) for the given metric; once the real usage deviates from the target by a certain percentage, the machine replicas change. The default value is 60 (representing 60%) if not provided.", + "format": "int32", + "type": "integer" + } + }, + "id": "GoogleCloudAiplatformV1beta1AutoscalingMetricSpec", + "type": "object", + "description": "The metric specification that defines the target resource utilization (CPU utilization, accelerator's duty cycle, and so on) for calculating the desired replica count." + }, + "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessSpec": { + "properties": { + "version": { + "format": "int32", + "description": "Optional. Which version to use for evaluation.", + "type": "integer" + }, + "useReference": { + "description": "Optional. Whether to use instance.reference to compute summarization helpfulness.", + "type": "boolean" + } + }, + "description": "Spec for summarization helpfulness score metric.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessSpec" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextExtractionEvaluationMetricsConfidenceMetrics": { + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextExtractionEvaluationMetricsConfidenceMetrics", + "properties": { + "confidenceThreshold": { + "type": "number", + "description": "Metrics are computed with an assumption that the Model never returns predictions with score lower than this value.", + "format": "float" + }, + "precision": { + "description": "Precision for the given confidence threshold.", + "type": "number", + "format": "float" + }, + "recall": { + "type": "number", + "format": "float", + "description": "Recall (True Positive Rate) for the given confidence threshold." + }, + "f1Score": { + "type": "number", + "format": "float", + "description": "The harmonic mean of recall and precision." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoObjectTrackingMetrics": { + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoObjectTrackingMetrics", + "properties": { + "evaluatedTrackCount": { + "description": "UNIMPLEMENTED. The total number of tracks (i.e. as seen across all frames) the ground truth used to create this evaluation had.", + "format": "int32", + "type": "integer" + }, + "evaluatedFrameCount": { + "type": "integer", + "description": "UNIMPLEMENTED. The number of video frames used to create this evaluation.", + "format": "int32" + }, + "evaluatedBoundingBoxCount": { + "description": "UNIMPLEMENTED. The total number of bounding boxes (i.e. summed over all frames) the ground truth used to create this evaluation had.", + "type": "integer", + "format": "int32" + }, + "trackMetrics": { + "type": "array", + "description": "UNIMPLEMENTED. The tracks match metrics for each intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTrackMetrics" + } + }, + "trackMeanMismatchRate": { + "format": "float", + "type": "number", + "description": "UNIMPLEMENTED. The single metric for tracking consistency evaluation: the `meanMismatchRate` averaged over all `trackMetrics`." + }, + "boundingBoxMetrics": { + "description": "The bounding boxes match metrics for each intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetrics" + }, + "type": "array" + }, + "boundingBoxMeanAveragePrecision": { + "type": "number", + "description": "The single metric for bounding boxes evaluation: the `meanAveragePrecision` averaged over all `boundingBoxMetrics`.", + "format": "float" + }, + "trackMeanBoundingBoxIou": { + "type": "number", + "description": "UNIMPLEMENTED. The single metric for tracks bounding box iou evaluation: the `meanBoundingBoxIou` averaged over all `trackMetrics`.", + "format": "float" + }, + "trackMeanAveragePrecision": { + "format": "float", + "description": "UNIMPLEMENTED. The single metric for tracks accuracy evaluation: the `meanAveragePrecision` averaged over all `trackMetrics`.", + "type": "number" + } + }, + "description": "Model evaluation metrics for video object tracking problems. Evaluates prediction quality of both labeled bounding boxes and labeled tracks (i.e. series of bounding boxes sharing same label and instance ID).", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1PipelineTaskDetailArtifactList": { + "id": "GoogleCloudAiplatformV1beta1PipelineTaskDetailArtifactList", + "type": "object", + "properties": { + "artifacts": { + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Artifact" + }, + "type": "array", + "description": "Output only. A list of artifact metadata." + } + }, + "description": "A list of artifact metadata." + }, + "GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetail": { + "properties": { + "customJobDetail": { + "description": "Output only. The detailed info for a custom job executor.", + "$ref": "GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetailCustomJobDetail", + "readOnly": true + }, + "containerDetail": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetailContainerDetail", + "description": "Output only. The detailed info for a container executor." + } + }, + "description": "The runtime detail of a pipeline executor.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetail" + }, + "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponse": { + "description": "Response message for FeaturestoreOnlineServingService.ReadFeatureValues.", + "properties": { + "entityView": { + "$ref": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseEntityView", + "description": "Entity view with Feature values. This may be the entity in the Featurestore if values for all Features were requested, or a projection of the entity in the Featurestore if values for only some Features were requested." + }, + "header": { + "$ref": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseHeader", + "description": "Response header." + } + }, + "id": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1CreateDatasetOperationMetadata": { + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "description": "Runtime operation information for DatasetService.CreateDataset.", + "id": "GoogleCloudAiplatformV1beta1CreateDatasetOperationMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpec": { + "properties": { + "parameterSpec": { + "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpec", + "description": "Required. The spec for a conditional parameter." + }, + "parentDiscreteValues": { + "description": "The spec for matching values from a parent parameter of `DISCRETE` type.", + "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecDiscreteValueCondition" + }, + "parentIntValues": { + "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecIntValueCondition", + "description": "The spec for matching values from a parent parameter of `INTEGER` type." + }, + "parentCategoricalValues": { + "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecCategoricalValueCondition", + "description": "The spec for matching values from a parent parameter of `CATEGORICAL` type." + } + }, + "id": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpec", + "type": "object", + "description": "Represents a parameter spec with condition from its parent parameter." + }, + "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateMlEngineModelVersionConfig": { + "description": "Config for migrating version in ml.googleapis.com to Vertex AI's Model.", + "properties": { + "endpoint": { + "description": "Required. The ml.googleapis.com endpoint that this model version should be migrated from. Example values: * ml.googleapis.com * us-centrall-ml.googleapis.com * europe-west4-ml.googleapis.com * asia-east1-ml.googleapis.com", + "type": "string" + }, + "modelDisplayName": { + "description": "Required. Display name of the model in Vertex AI. System will pick a display name if unspecified.", + "type": "string" + }, + "modelVersion": { + "type": "string", + "description": "Required. Full resource name of ml engine model version. Format: `projects/{project}/models/{model}/versions/{version}`." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateMlEngineModelVersionConfig" + }, + "GoogleCloudAiplatformV1beta1RetrieveContextsRequestVertexRagStore": { + "description": "The data source for Vertex RagStore.", + "properties": { + "ragCorpora": { + "items": { + "type": "string" + }, + "deprecated": true, + "description": "Optional. Deprecated. Please use rag_resources to specify the data source.", + "type": "array" + }, + "ragResources": { + "description": "Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1RetrieveContextsRequestVertexRagStoreRagResource" + } + }, + "vectorDistanceThreshold": { + "type": "number", + "description": "Optional. Only return contexts with vector distance smaller than the threshold.", + "format": "double" + } + }, + "id": "GoogleCloudAiplatformV1beta1RetrieveContextsRequestVertexRagStore", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1WriteFeatureValuesResponse": { + "description": "Response message for FeaturestoreOnlineServingService.WriteFeatureValues.", + "id": "GoogleCloudAiplatformV1beta1WriteFeatureValuesResponse", + "type": "object", + "properties": {} + }, + "GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfigBruteForceConfig": { + "id": "GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfigBruteForceConfig", + "type": "object", + "properties": {} + }, + "GoogleCloudAiplatformV1beta1Content": { + "properties": { + "role": { + "description": "Optional. The producer of the content. Must be either 'user' or 'model'. Useful to set for multi-turn conversations, otherwise can be left blank or unset.", + "type": "string" + }, + "parts": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Part" + }, + "description": "Required. Ordered `Parts` that constitute a single message. Parts may have different IANA MIME types." + } + }, + "description": "The base structured datatype containing multi-part content of a message. A `Content` includes a `role` field designating the producer of the `Content` and a `parts` field containing multi-part data that contains the content of the message turn.", + "id": "GoogleCloudAiplatformV1beta1Content", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1TrialParameter": { + "properties": { + "parameterId": { + "readOnly": true, + "type": "string", + "description": "Output only. The ID of the parameter. The parameter should be defined in StudySpec's Parameters." + }, + "value": { + "readOnly": true, + "description": "Output only. The value of the parameter. `number_value` will be set if a parameter defined in StudySpec is in type 'INTEGER', 'DOUBLE' or 'DISCRETE'. `string_value` will be set if a parameter defined in StudySpec is in type 'CATEGORICAL'.", + "type": "any" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1TrialParameter", + "description": "A message representing a parameter to be tuned." + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoClassificationInputs": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoClassificationInputs", + "type": "object", + "properties": { + "modelType": { + "type": "string", + "enum": [ + "MODEL_TYPE_UNSPECIFIED", + "CLOUD", + "MOBILE_VERSATILE_1", + "MOBILE_JETSON_VERSATILE_1" + ], + "enumDescriptions": [ + "Should not be set.", + "A model best tailored to be used within Google Cloud, and which cannot be exported. Default.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as a TensorFlow or TensorFlow Lite model and used on a mobile or edge device afterwards.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) to a Jetson device afterwards." + ] + } + } + }, + "GoogleCloudAiplatformV1beta1DeleteOperationMetadata": { + "type": "object", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "The common part of the operation metadata." + } + }, + "description": "Details of operations that perform deletes of any entities.", + "id": "GoogleCloudAiplatformV1beta1DeleteOperationMetadata" + }, + "GoogleIamV1TestIamPermissionsResponse": { + "properties": { + "permissions": { + "type": "array", + "items": { + "type": "string" + }, + "description": "A subset of `TestPermissionsRequest.permissions` that the caller is allowed." + } + }, + "description": "Response message for `TestIamPermissions` method.", + "id": "GoogleIamV1TestIamPermissionsResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponseSelectTimeRangeAndFeature": { + "id": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponseSelectTimeRangeAndFeature", + "properties": { + "impactedFeatureCount": { + "description": "The count of the features or columns impacted. This is the same as the feature count in the request.", + "format": "int64", + "type": "string" + }, + "offlineStorageModifiedEntityRowCount": { + "format": "int64", + "type": "string", + "description": "The count of modified entity rows in the offline storage. Each row corresponds to the combination of an entity ID and a timestamp. One entity ID can have multiple rows in the offline storage. Within each row, only the features specified in the request are deleted." + }, + "onlineStorageModifiedEntityCount": { + "format": "int64", + "type": "string", + "description": "The count of modified entities in the online storage. Each entity ID corresponds to one entity. Within each entity, only the features specified in the request are deleted." + } + }, + "type": "object", + "description": "Response message if the request uses the SelectTimeRangeAndFeature option." + }, + "GoogleTypeColor": { + "type": "object", + "id": "GoogleTypeColor", + "description": "Represents a color in the RGBA color space. This representation is designed for simplicity of conversion to and from color representations in various languages over compactness. For example, the fields of this representation can be trivially provided to the constructor of `java.awt.Color` in Java; it can also be trivially provided to UIColor's `+colorWithRed:green:blue:alpha` method in iOS; and, with just a little work, it can be easily formatted into a CSS `rgba()` string in JavaScript. This reference page doesn't have information about the absolute color space that should be used to interpret the RGB value—for example, sRGB, Adobe RGB, DCI-P3, and BT.2020. By default, applications should assume the sRGB color space. When color equality needs to be decided, implementations, unless documented otherwise, treat two colors as equal if all their red, green, blue, and alpha values each differ by at most `1e-5`. Example (Java): import com.google.type.Color; // ... public static java.awt.Color fromProto(Color protocolor) { float alpha = protocolor.hasAlpha() ? protocolor.getAlpha().getValue() : 1.0; return new java.awt.Color( protocolor.getRed(), protocolor.getGreen(), protocolor.getBlue(), alpha); } public static Color toProto(java.awt.Color color) { float red = (float) color.getRed(); float green = (float) color.getGreen(); float blue = (float) color.getBlue(); float denominator = 255.0; Color.Builder resultBuilder = Color .newBuilder() .setRed(red / denominator) .setGreen(green / denominator) .setBlue(blue / denominator); int alpha = color.getAlpha(); if (alpha != 255) { result.setAlpha( FloatValue .newBuilder() .setValue(((float) alpha) / denominator) .build()); } return resultBuilder.build(); } // ... Example (iOS / Obj-C): // ... static UIColor* fromProto(Color* protocolor) { float red = [protocolor red]; float green = [protocolor green]; float blue = [protocolor blue]; FloatValue* alpha_wrapper = [protocolor alpha]; float alpha = 1.0; if (alpha_wrapper != nil) { alpha = [alpha_wrapper value]; } return [UIColor colorWithRed:red green:green blue:blue alpha:alpha]; } static Color* toProto(UIColor* color) { CGFloat red, green, blue, alpha; if (![color getRed:&red green:&green blue:&blue alpha:&alpha]) { return nil; } Color* result = [[Color alloc] init]; [result setRed:red]; [result setGreen:green]; [result setBlue:blue]; if (alpha \u003c= 0.9999) { [result setAlpha:floatWrapperWithValue(alpha)]; } [result autorelease]; return result; } // ... Example (JavaScript): // ... var protoToCssColor = function(rgb_color) { var redFrac = rgb_color.red || 0.0; var greenFrac = rgb_color.green || 0.0; var blueFrac = rgb_color.blue || 0.0; var red = Math.floor(redFrac * 255); var green = Math.floor(greenFrac * 255); var blue = Math.floor(blueFrac * 255); if (!('alpha' in rgb_color)) { return rgbToCssColor(red, green, blue); } var alphaFrac = rgb_color.alpha.value || 0.0; var rgbParams = [red, green, blue].join(','); return ['rgba(', rgbParams, ',', alphaFrac, ')'].join(''); }; var rgbToCssColor = function(red, green, blue) { var rgbNumber = new Number((red \u003c\u003c 16) | (green \u003c\u003c 8) | blue); var hexString = rgbNumber.toString(16); var missingZeros = 6 - hexString.length; var resultBuilder = ['#']; for (var i = 0; i \u003c missingZeros; i++) { resultBuilder.push('0'); } resultBuilder.push(hexString); return resultBuilder.join(''); }; // ...", + "properties": { + "blue": { + "type": "number", + "format": "float", + "description": "The amount of blue in the color as a value in the interval [0, 1]." + }, + "alpha": { + "format": "float", + "description": "The fraction of this color that should be applied to the pixel. That is, the final pixel color is defined by the equation: `pixel color = alpha * (this color) + (1.0 - alpha) * (background color)` This means that a value of 1.0 corresponds to a solid color, whereas a value of 0.0 corresponds to a completely transparent color. This uses a wrapper message rather than a simple float scalar so that it is possible to distinguish between a default value and the value being unset. If omitted, this color object is rendered as a solid color (as if the alpha value had been explicitly given a value of 1.0).", + "type": "number" + }, + "red": { + "description": "The amount of red in the color as a value in the interval [0, 1].", + "type": "number", + "format": "float" + }, + "green": { + "type": "number", + "format": "float", + "description": "The amount of green in the color as a value in the interval [0, 1]." + } + } + }, + "GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadata": { + "description": "Metadata of the input of a feature. Fields other than InputMetadata.input_baselines are applicable only for Models that are using Vertex AI-provided images for Tensorflow.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadata", + "properties": { + "featureValueDomain": { + "description": "The domain details of the input feature value. Like min/max, original mean or standard deviation if normalized.", + "$ref": "GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadataFeatureValueDomain" + }, + "indexFeatureMapping": { + "description": "A list of feature names for each index in the input tensor. Required when the input InputMetadata.encoding is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.", + "type": "array", + "items": { + "type": "string" + } + }, + "inputBaselines": { + "items": { + "type": "any" + }, + "type": "array", + "description": "Baseline inputs for this feature. If no baseline is specified, Vertex AI chooses the baseline for this feature. If multiple baselines are specified, Vertex AI returns the average attributions across them in Attribution.feature_attributions. For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape of each baseline must match the shape of the input tensor. If a scalar is provided, we broadcast to the same shape as the input tensor. For custom images, the element of the baselines must be in the same format as the feature's input in the instance[]. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri." + }, + "groupName": { + "type": "string", + "description": "Name of the group that the input belongs to. Features with the same group name will be treated as one feature when computing attributions. Features grouped together can have different shapes in value. If provided, there will be one single attribution generated in Attribution.feature_attributions, keyed by the group name." + }, + "encoding": { + "description": "Defines how the feature is encoded into the input tensor. Defaults to IDENTITY.", + "enum": [ + "ENCODING_UNSPECIFIED", + "IDENTITY", + "BAG_OF_FEATURES", + "BAG_OF_FEATURES_SPARSE", + "INDICATOR", + "COMBINED_EMBEDDING", + "CONCAT_EMBEDDING" + ], + "enumDescriptions": [ + "Default value. This is the same as IDENTITY.", + "The tensor represents one feature.", + "The tensor represents a bag of features where each index maps to a feature. InputMetadata.index_feature_mapping must be provided for this encoding. For example: ``` input = [27, 6.0, 150] index_feature_mapping = [\"age\", \"height\", \"weight\"] ```", + "The tensor represents a bag of features where each index maps to a feature. Zero values in the tensor indicates feature being non-existent. InputMetadata.index_feature_mapping must be provided for this encoding. For example: ``` input = [2, 0, 5, 0, 1] index_feature_mapping = [\"a\", \"b\", \"c\", \"d\", \"e\"] ```", + "The tensor is a list of binaries representing whether a feature exists or not (1 indicates existence). InputMetadata.index_feature_mapping must be provided for this encoding. For example: ``` input = [1, 0, 1, 0, 1] index_feature_mapping = [\"a\", \"b\", \"c\", \"d\", \"e\"] ```", + "The tensor is encoded into a 1-dimensional array represented by an encoded tensor. InputMetadata.encoded_tensor_name must be provided for this encoding. For example: ``` input = [\"This\", \"is\", \"a\", \"test\", \".\"] encoded = [0.1, 0.2, 0.3, 0.4, 0.5] ```", + "Select this encoding when the input tensor is encoded into a 2-dimensional array represented by an encoded tensor. InputMetadata.encoded_tensor_name must be provided for this encoding. The first dimension of the encoded tensor's shape is the same as the input tensor's shape. For example: ``` input = [\"This\", \"is\", \"a\", \"test\", \".\"] encoded = [[0.1, 0.2, 0.3, 0.4, 0.5], [0.2, 0.1, 0.4, 0.3, 0.5], [0.5, 0.1, 0.3, 0.5, 0.4], [0.5, 0.3, 0.1, 0.2, 0.4], [0.4, 0.3, 0.2, 0.5, 0.1]] ```" + ], + "type": "string" + }, + "modality": { + "description": "Modality of the feature. Valid values are: numeric, image. Defaults to numeric.", + "type": "string" + }, + "encodedTensorName": { + "description": "Encoded tensor is a transformation of the input tensor. Must be provided if choosing Integrated Gradients attribution or XRAI attribution and the input tensor is not differentiable. An encoded tensor is generated if the input tensor is encoded by a lookup table.", + "type": "string" + }, + "indicesTensorName": { + "description": "Specifies the index of the values of the input tensor. Required when the input tensor is a sparse representation. Refer to Tensorflow documentation for more details: https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.", + "type": "string" + }, + "encodedBaselines": { + "items": { + "type": "any" + }, + "type": "array", + "description": "A list of baselines for the encoded tensor. The shape of each baseline should match the shape of the encoded tensor. If a scalar is provided, Vertex AI broadcasts to the same shape as the encoded tensor." + }, + "denseShapeTensorName": { + "description": "Specifies the shape of the values of the input if the input is a sparse representation. Refer to Tensorflow documentation for more details: https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.", + "type": "string" + }, + "visualization": { + "$ref": "GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadataVisualization", + "description": "Visualization configurations for image explanation." + }, + "inputTensorName": { + "type": "string", + "description": "Name of the input tensor for this feature. Required and is only applicable to Vertex AI-provided images for Tensorflow." + } + } + }, + "GoogleCloudAiplatformV1beta1AuthConfigApiKeyConfig": { + "properties": { + "apiKeySecret": { + "description": "Required. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.", + "type": "string" + }, + "name": { + "description": "Required. The parameter name of the API key. E.g. If the API request is \"https://example.com/act?api_key=\", \"api_key\" would be the parameter name.", + "type": "string" + }, + "httpElementLocation": { + "enumDescriptions": [ + "", + "Element is in the HTTP request query.", + "Element is in the HTTP request header.", + "Element is in the HTTP request path.", + "Element is in the HTTP request body.", + "Element is in the HTTP request cookie." + ], + "enum": [ + "HTTP_IN_UNSPECIFIED", + "HTTP_IN_QUERY", + "HTTP_IN_HEADER", + "HTTP_IN_PATH", + "HTTP_IN_BODY", + "HTTP_IN_COOKIE" + ], + "type": "string", + "description": "Required. The location of the API key." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1AuthConfigApiKeyConfig", + "description": "Config for authentication with API key." + }, + "GoogleCloudAiplatformV1beta1ListModelMonitorsResponse": { + "description": "Response message for ModelMonitoringService.ListModelMonitors", + "id": "GoogleCloudAiplatformV1beta1ListModelMonitorsResponse", + "properties": { + "nextPageToken": { + "description": "A token to retrieve the next page of results. Pass to ListModelMonitorsRequest.page_token to obtain that page.", + "type": "string" + }, + "modelMonitors": { + "description": "List of ModelMonitor in the requested page.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitor" + }, + "type": "array" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionCustomTask": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionCustomTask", + "properties": { + "metadata": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionCustomJobMetadata", + "description": "The metadata information." + }, + "inputs": { + "$ref": "GoogleCloudAiplatformV1beta1CustomJobSpec", + "description": "The input parameters of this CustomTask." + } + }, + "type": "object", + "description": "A TrainingJob that trains a custom code Model." + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetail": { + "properties": { + "baselineDatasets": { + "description": "Processed baseline datasets.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetailProcessedDataset" + } + }, + "objectiveStatus": { + "type": "object", + "description": "Status of data processing for each monitoring objective. Key is the objective.", + "additionalProperties": { + "$ref": "GoogleRpcStatus" + } + }, + "error": { + "description": "Additional job error status.", + "$ref": "GoogleRpcStatus" + }, + "targetDatasets": { + "type": "array", + "description": "Processed target datasets.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetailProcessedDataset" + } + } + }, + "type": "object", + "description": "Represent the execution details of the job.", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetail" + }, + "GoogleCloudAiplatformV1beta1ExactMatchMetricValue": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ExactMatchMetricValue", + "properties": { + "score": { + "type": "number", + "format": "float", + "readOnly": true, + "description": "Output only. Exact match score." + } + }, + "description": "Exact match metric value for an instance." + }, + "GoogleCloudAiplatformV1beta1SchemaImageClassificationAnnotation": { + "id": "GoogleCloudAiplatformV1beta1SchemaImageClassificationAnnotation", + "properties": { + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that this Annotation pertains to." + }, + "annotationSpecId": { + "type": "string", + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." + } + }, + "type": "object", + "description": "Annotation details specific to image classification." + }, + "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadataContentValidationStats": { + "type": "object", + "properties": { + "sourceGcsUri": { + "type": "string", + "description": "Cloud Storage URI pointing to the original file in user's bucket." + }, + "invalidSparseRecordCount": { + "description": "Number of sparse records in this file we skipped due to validate errors.", + "format": "int64", + "type": "string" + }, + "invalidRecordCount": { + "description": "Number of records in this file we skipped due to validate errors.", + "format": "int64", + "type": "string" + }, + "validRecordCount": { + "format": "int64", + "type": "string", + "description": "Number of records in this file that were successfully processed." + }, + "partialErrors": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadataRecordError" + }, + "description": "The detail information of the partial failures encountered for those invalid records that couldn't be parsed. Up to 50 partial errors will be reported." + }, + "validSparseRecordCount": { + "description": "Number of sparse records in this file that were successfully processed.", + "type": "string", + "format": "int64" + } + }, + "id": "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadataContentValidationStats" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextSentiment": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextSentiment", + "properties": { + "inputs": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextSentimentInputs", + "description": "The input parameters of this TrainingJob." + } + }, + "description": "A TrainingJob that trains and uploads an AutoML Text Sentiment Model." + }, + "GoogleCloudAiplatformV1beta1SearchDataItemsResponse": { + "id": "GoogleCloudAiplatformV1beta1SearchDataItemsResponse", + "properties": { + "dataItemViews": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1DataItemView" + }, + "description": "The DataItemViews read.", + "type": "array" + }, + "nextPageToken": { + "type": "string", + "description": "A token to retrieve next page of results. Pass to SearchDataItemsRequest.page_token to obtain that page." + } + }, + "type": "object", + "description": "Response message for DatasetService.SearchDataItems." + }, + "GoogleCloudAiplatformV1beta1ModelMonitorModelMonitoringTarget": { + "id": "GoogleCloudAiplatformV1beta1ModelMonitorModelMonitoringTarget", + "type": "object", + "properties": { + "vertexModel": { + "description": "Model in Vertex AI Model Registry.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitorModelMonitoringTargetVertexModelSource" + } + }, + "description": "The monitoring target refers to the entity that is subject to analysis. e.g. Vertex AI Model version." + }, + "GoogleCloudAiplatformV1beta1ListTensorboardExperimentsResponse": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ListTensorboardExperimentsResponse", + "properties": { + "nextPageToken": { + "description": "A token, which can be sent as ListTensorboardExperimentsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + }, + "tensorboardExperiments": { + "description": "The TensorboardExperiments mathching the request.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardExperiment" + }, + "type": "array" + } + }, + "description": "Response message for TensorboardService.ListTensorboardExperiments." + }, + "GoogleCloudAiplatformV1beta1RebootPersistentResourceOperationMetadata": { + "type": "object", + "description": "Details of operations that perform reboot PersistentResource.", + "id": "GoogleCloudAiplatformV1beta1RebootPersistentResourceOperationMetadata", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "Operation metadata for PersistentResource." + }, + "progressMessage": { + "description": "Progress Message for Reboot LRO", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTftFeatureImportance": { + "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTftFeatureImportance", + "properties": { + "contextWeights": { + "description": "TFT feature importance values. Each pair for {context/horizon/attribute} should have the same shape since the weight corresponds to the column names.", + "items": { + "format": "float", + "type": "number" + }, + "type": "array" + }, + "attributeWeights": { + "items": { + "type": "number", + "format": "float" + }, + "type": "array" + }, + "horizonWeights": { + "type": "array", + "items": { + "type": "number", + "format": "float" + } + }, + "attributeColumns": { + "items": { + "type": "string" + }, + "type": "array" + }, + "horizonColumns": { + "items": { + "type": "string" + }, + "type": "array" + }, + "contextColumns": { + "type": "array", + "items": { + "type": "string" + } + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1UpdateFeatureViewOperationMetadata": { + "description": "Details of operations that perform update FeatureView.", + "id": "GoogleCloudAiplatformV1beta1UpdateFeatureViewOperationMetadata", + "properties": { + "genericMetadata": { + "description": "Operation metadata for FeatureView Update.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "type": "object" + }, + "GoogleApiHttpBody": { + "type": "object", + "id": "GoogleApiHttpBody", + "properties": { + "contentType": { + "type": "string", + "description": "The HTTP Content-Type header value specifying the content type of the body." + }, + "data": { + "format": "byte", + "description": "The HTTP request/response body as raw binary.", + "type": "string" + }, + "extensions": { + "items": { + "additionalProperties": { + "description": "Properties of the object. Contains field @type with type URL.", + "type": "any" + }, + "type": "object" + }, + "description": "Application specific response metadata. Must be set in the first response for streaming APIs.", + "type": "array" + } + }, + "description": "Message that represents an arbitrary HTTP body. It should only be used for payload formats that can't be represented as JSON, such as raw binary or an HTML page. This message can be used both in streaming and non-streaming API methods in the request as well as the response. It can be used as a top-level request field, which is convenient if one wants to extract parameters from either the URL or HTTP template into the request fields and also want access to the raw HTTP body. Example: message GetResourceRequest { // A unique request id. string request_id = 1; // The raw HTTP body is bound to this field. google.api.HttpBody http_body = 2; } service ResourceService { rpc GetResource(GetResourceRequest) returns (google.api.HttpBody); rpc UpdateResource(google.api.HttpBody) returns (google.protobuf.Empty); } Example with streaming methods: service CaldavService { rpc GetCalendar(stream google.api.HttpBody) returns (stream google.api.HttpBody); rpc UpdateCalendar(stream google.api.HttpBody) returns (stream google.api.HttpBody); } Use of this type only changes how the request and response bodies are handled, all other features will continue to work unchanged." + }, + "GoogleCloudAiplatformV1beta1WriteTensorboardRunDataRequest": { + "id": "GoogleCloudAiplatformV1beta1WriteTensorboardRunDataRequest", + "description": "Request message for TensorboardService.WriteTensorboardRunData.", + "type": "object", + "properties": { + "tensorboardRun": { + "description": "Required. The resource name of the TensorboardRun to write data to. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", + "type": "string" + }, + "timeSeriesData": { + "description": "Required. The TensorboardTimeSeries data to write. Values with in a time series are indexed by their step value. Repeated writes to the same step will overwrite the existing value for that step. The upper limit of data points per write request is 5000.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1TimeSeriesData" + }, + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1beta1Attribution": { + "type": "object", + "properties": { + "featureAttributions": { + "type": "any", + "description": "Output only. Attributions of each explained feature. Features are extracted from the prediction instances according to explanation metadata for inputs. The value is a struct, whose keys are the name of the feature. The values are how much the feature in the instance contributed to the predicted result. The format of the value is determined by the feature's input format: * If the feature is a scalar value, the attribution value is a floating number. * If the feature is an array of scalar values, the attribution value is an array. * If the feature is a struct, the attribution value is a struct. The keys in the attribution value struct are the same as the keys in the feature struct. The formats of the values in the attribution struct are determined by the formats of the values in the feature struct. The ExplanationMetadata.feature_attributions_schema_uri field, pointed to by the ExplanationSpec field of the Endpoint.deployed_models object, points to the schema file that describes the features and their attribution values (if it is populated).", + "readOnly": true + }, + "outputName": { + "type": "string", + "description": "Output only. Name of the explain output. Specified as the key in ExplanationMetadata.outputs.", + "readOnly": true + }, + "outputIndex": { + "type": "array", + "readOnly": true, + "items": { + "format": "int32", + "type": "integer" + }, + "description": "Output only. The index that locates the explained prediction output. If the prediction output is a scalar value, output_index is not populated. If the prediction output has multiple dimensions, the length of the output_index list is the same as the number of dimensions of the output. The i-th element in output_index is the element index of the i-th dimension of the output vector. Indices start from 0." + }, + "baselineOutputValue": { + "type": "number", + "readOnly": true, + "description": "Output only. Model predicted output if the input instance is constructed from the baselines of all the features defined in ExplanationMetadata.inputs. The field name of the output is determined by the key in ExplanationMetadata.outputs. If the Model's predicted output has multiple dimensions (rank \u003e 1), this is the value in the output located by output_index. If there are multiple baselines, their output values are averaged.", + "format": "double" + }, + "instanceOutputValue": { + "format": "double", + "description": "Output only. Model predicted output on the corresponding explanation instance. The field name of the output is determined by the key in ExplanationMetadata.outputs. If the Model predicted output has multiple dimensions, this is the value in the output located by output_index.", + "readOnly": true, + "type": "number" + }, + "outputDisplayName": { + "description": "Output only. The display name of the output identified by output_index. For example, the predicted class name by a multi-classification Model. This field is only populated iff the Model predicts display names as a separate field along with the explained output. The predicted display name must has the same shape of the explained output, and can be located using output_index.", + "readOnly": true, + "type": "string" + }, + "approximationError": { + "type": "number", + "format": "double", + "description": "Output only. Error of feature_attributions caused by approximation used in the explanation method. Lower value means more precise attributions. * For Sampled Shapley attribution, increasing path_count might reduce the error. * For Integrated Gradients attribution, increasing step_count might reduce the error. * For XRAI attribution, increasing step_count might reduce the error. See [this introduction](/vertex-ai/docs/explainable-ai/overview) for more information.", + "readOnly": true + } + }, + "description": "Attribution that explains a particular prediction output.", + "id": "GoogleCloudAiplatformV1beta1Attribution" + }, + "GoogleCloudAiplatformV1beta1CopyModelResponse": { + "description": "Response message of ModelService.CopyModel operation.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1CopyModelResponse", + "properties": { + "modelVersionId": { + "description": "Output only. The version ID of the model that is copied.", + "type": "string", + "readOnly": true + }, + "model": { + "description": "The name of the copied Model resource. Format: `projects/{project}/locations/{location}/models/{model}`", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1StudySpecConvexAutomatedStoppingSpec": { + "id": "GoogleCloudAiplatformV1beta1StudySpecConvexAutomatedStoppingSpec", + "type": "object", + "properties": { + "maxStepCount": { + "format": "int64", + "description": "Steps used in predicting the final objective for early stopped trials. In general, it's set to be the same as the defined steps in training / tuning. If not defined, it will learn it from the completed trials. When use_steps is false, this field is set to the maximum elapsed seconds.", + "type": "string" + }, + "updateAllStoppedTrials": { + "type": "boolean", + "description": "ConvexAutomatedStoppingSpec by default only updates the trials that needs to be early stopped using a newly trained auto-regressive model. When this flag is set to True, all stopped trials from the beginning are potentially updated in terms of their `final_measurement`. Also, note that the training logic of autoregressive models is different in this case. Enabling this option has shown better results and this may be the default option in the future." + }, + "minMeasurementCount": { + "description": "The minimal number of measurements in a Trial. Early-stopping checks will not trigger if less than min_measurement_count+1 completed trials or pending trials with less than min_measurement_count measurements. If not defined, the default value is 5.", + "format": "int64", + "type": "string" + }, + "useElapsedDuration": { + "type": "boolean", + "description": "This bool determines whether or not the rule is applied based on elapsed_secs or steps. If use_elapsed_duration==false, the early stopping decision is made according to the predicted objective values according to the target steps. If use_elapsed_duration==true, elapsed_secs is used instead of steps. Also, in this case, the parameters max_num_steps and min_num_steps are overloaded to contain max_elapsed_seconds and min_elapsed_seconds." + }, + "minStepCount": { + "type": "string", + "description": "Minimum number of steps for a trial to complete. Trials which do not have a measurement with step_count \u003e min_step_count won't be considered for early stopping. It's ok to set it to 0, and a trial can be early stopped at any stage. By default, min_step_count is set to be one-tenth of the max_step_count. When use_elapsed_duration is true, this field is set to the minimum elapsed seconds.", + "format": "int64" + }, + "learningRateParameterName": { + "type": "string", + "description": "The hyper-parameter name used in the tuning job that stands for learning rate. Leave it blank if learning rate is not in a parameter in tuning. The learning_rate is used to estimate the objective value of the ongoing trial." + } + }, + "description": "Configuration for ConvexAutomatedStoppingSpec. When there are enough completed trials (configured by min_measurement_count), for pending trials with enough measurements and steps, the policy first computes an overestimate of the objective value at max_num_steps according to the slope of the incomplete objective value curve. No prediction can be made if the curve is completely flat. If the overestimation is worse than the best objective value of the completed trials, this pending trial will be early-stopped, but a last measurement will be added to the pending trial with max_num_steps and predicted objective value from the autoregression model." + }, + "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchResults": { + "properties": { + "toolParameterKeyMatchMetricValues": { + "description": "Output only. Tool parameter key match metric values.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchMetricValue" + }, + "readOnly": true + } + }, + "description": "Results for tool parameter key match metric.", + "id": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchResults", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaPredictInstanceVideoObjectTrackingPredictionInstance": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaPredictInstanceVideoObjectTrackingPredictionInstance", + "properties": { + "timeSegmentStart": { + "type": "string", + "description": "The beginning, inclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with \"s\" appended at the end. Fractions are allowed, up to a microsecond precision." + }, + "content": { + "description": "The Google Cloud Storage location of the video on which to perform the prediction.", + "type": "string" + }, + "timeSegmentEnd": { + "description": "The end, exclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with \"s\" appended at the end. Fractions are allowed, up to a microsecond precision, and \"inf\" or \"Infinity\" is allowed, which means the end of the video.", + "type": "string" + }, + "mimeType": { + "type": "string", + "description": "The MIME type of the content of the video. Only the following are supported: video/mp4 video/avi video/quicktime" + } + }, + "description": "Prediction input format for Video Object Tracking." + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpec": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpec", + "properties": { + "baselineDataset": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringInput", + "description": "Baseline dataset. It could be the training dataset or production serving dataset from a previous period." + }, + "explanationSpec": { + "$ref": "GoogleCloudAiplatformV1beta1ExplanationSpec", + "description": "The explanation spec. This spec is required when the objectives spec includes feature attribution objectives." + }, + "tabularObjective": { + "description": "Tabular monitoring objective.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecTabularObjective" + }, + "targetDataset": { + "description": "Target dataset.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringInput" + } + }, + "description": "Monitoring objectives spec." + }, + "GoogleCloudAiplatformV1beta1BatchPredictionJob": { + "type": "object", + "properties": { + "manualBatchTuningParameters": { + "$ref": "GoogleCloudAiplatformV1beta1ManualBatchTuningParameters", + "description": "Immutable. Parameters configuring the batch behavior. Currently only applicable when dedicated_resources are used (in other cases Vertex AI does the tuning itself)." + }, + "name": { + "description": "Output only. Resource name of the BatchPredictionJob.", + "type": "string", + "readOnly": true + }, + "state": { + "description": "Output only. The detailed state of the job.", + "enumDescriptions": [ + "The job state is unspecified.", + "The job has been just created or resumed and processing has not yet begun.", + "The service is preparing to run the job.", + "The job is in progress.", + "The job completed successfully.", + "The job failed.", + "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "The job has been cancelled.", + "The job has been stopped, and can be resumed.", + "The job has expired.", + "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", + "The job is partially succeeded, some results may be missing due to errors." + ], + "readOnly": true, + "enum": [ + "JOB_STATE_UNSPECIFIED", + "JOB_STATE_QUEUED", + "JOB_STATE_PENDING", + "JOB_STATE_RUNNING", + "JOB_STATE_SUCCEEDED", + "JOB_STATE_FAILED", + "JOB_STATE_CANCELLING", + "JOB_STATE_CANCELLED", + "JOB_STATE_PAUSED", + "JOB_STATE_EXPIRED", + "JOB_STATE_UPDATING", + "JOB_STATE_PARTIALLY_SUCCEEDED" + ], + "type": "string" + }, + "model": { + "type": "string", + "description": "The name of the Model resource that produces the predictions via this job, must share the same ancestor Location. Starting this job has no impact on any existing deployments of the Model and their resources. Exactly one of model and unmanaged_container_model must be set. The model resource name may contain version id or version alias to specify the version. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` if no version is specified, the default version will be deployed. The model resource could also be a publisher model. Example: `publishers/{publisher}/models/{model}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`" + }, + "dedicatedResources": { + "description": "The config of resources used by the Model during the batch prediction. If the Model supports DEDICATED_RESOURCES this config may be provided (and the job will use these resources), if the Model doesn't support AUTOMATIC_RESOURCES, this config must be provided.", + "$ref": "GoogleCloudAiplatformV1beta1BatchDedicatedResources" + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "description": "The labels with user-defined metadata to organize BatchPredictionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", + "type": "object" + }, + "partialFailures": { + "readOnly": true, + "items": { + "$ref": "GoogleRpcStatus" + }, + "description": "Output only. Partial failures encountered. For example, single files that can't be read. This field never exceeds 20 entries. Status details fields contain standard Google Cloud error details.", + "type": "array" + }, + "modelMonitoringConfig": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringConfig", + "description": "Model monitoring config will be used for analysis model behaviors, based on the input and output to the batch prediction job, as well as the provided training dataset." + }, + "modelMonitoringStatus": { + "description": "Output only. The running status of the model monitoring pipeline.", + "$ref": "GoogleRpcStatus", + "readOnly": true + }, + "outputInfo": { + "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJobOutputInfo", + "readOnly": true, + "description": "Output only. Information further describing the output of this job." + }, + "instanceConfig": { + "description": "Configuration for how to convert batch prediction input instances to the prediction instances that are sent to the Model.", + "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJobInstanceConfig" + }, + "createTime": { + "type": "string", + "description": "Output only. Time when the BatchPredictionJob was created.", + "format": "google-datetime", + "readOnly": true + }, + "unmanagedContainerModel": { + "description": "Contains model information necessary to perform batch prediction without requiring uploading to model registry. Exactly one of model and unmanaged_container_model must be set.", + "$ref": "GoogleCloudAiplatformV1beta1UnmanagedContainerModel" + }, + "explanationSpec": { + "description": "Explanation configuration for this BatchPredictionJob. Can be specified only if generate_explanation is set to `true`. This value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of the explanation_spec object is not populated, the corresponding field of the Model.explanation_spec object is inherited.", + "$ref": "GoogleCloudAiplatformV1beta1ExplanationSpec" + }, + "generateExplanation": { + "type": "boolean", + "description": "Generate explanation with the batch prediction results. When set to `true`, the batch prediction output changes based on the `predictions_format` field of the BatchPredictionJob.output_config object: * `bigquery`: output includes a column named `explanation`. The value is a struct that conforms to the Explanation object. * `jsonl`: The JSON objects on each line include an additional entry keyed `explanation`. The value of the entry is a JSON object that conforms to the Explanation object. * `csv`: Generating explanations for CSV format is not supported. If this field is set to true, either the Model.explanation_spec or explanation_spec must be populated." + }, + "modelParameters": { + "type": "any", + "description": "The parameters that govern the predictions. The schema of the parameters may be specified via the Model's PredictSchemata's parameters_schema_uri." + }, + "outputConfig": { + "description": "Required. The Configuration specifying where output predictions should be written. The schema of any single prediction may be specified as a concatenation of Model's PredictSchemata's instance_schema_uri and prediction_schema_uri.", + "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJobOutputConfig" + }, + "modelMonitoringStatsAnomalies": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomalies" + }, + "description": "Get batch prediction job monitoring statistics." + }, + "error": { + "$ref": "GoogleRpcStatus", + "description": "Output only. Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.", + "readOnly": true + }, + "resourcesConsumed": { + "$ref": "GoogleCloudAiplatformV1beta1ResourcesConsumed", + "readOnly": true, + "description": "Output only. Information about resources that had been consumed by this job. Provided in real time at best effort basis, as well as a final value once the job completes. Note: This field currently may be not populated for batch predictions that use AutoML Models." + }, + "disableContainerLogging": { + "description": "For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.", + "type": "boolean" + }, + "modelVersionId": { + "description": "Output only. The version ID of the Model that produces the predictions via this job.", + "type": "string", + "readOnly": true + }, + "inputConfig": { + "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJobInputConfig", + "description": "Required. Input configuration of the instances on which predictions are performed. The schema of any single instance may be specified via the Model's PredictSchemata's instance_schema_uri." + }, + "serviceAccount": { + "type": "string", + "description": "The service account that the DeployedModel's container runs as. If not specified, a system generated one will be used, which has minimal permissions and the custom container, if used, may not have enough permission to access other Google Cloud resources. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account." + }, + "updateTime": { + "description": "Output only. Time when the BatchPredictionJob was most recently updated.", + "format": "google-datetime", + "readOnly": true, + "type": "string" + }, + "startTime": { + "format": "google-datetime", + "type": "string", + "description": "Output only. Time when the BatchPredictionJob for the first time entered the `JOB_STATE_RUNNING` state.", + "readOnly": true + }, + "encryptionSpec": { + "description": "Customer-managed encryption key options for a BatchPredictionJob. If this is set, then all resources created by the BatchPredictionJob will be encrypted with the provided encryption key.", + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" + }, + "displayName": { + "type": "string", + "description": "Required. The user-defined name of this BatchPredictionJob." + }, + "endTime": { + "description": "Output only. Time when the BatchPredictionJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.", + "format": "google-datetime", + "type": "string", + "readOnly": true + }, + "completionStats": { + "description": "Output only. Statistics on completed and failed prediction instances.", + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1CompletionStats" + } + }, + "id": "GoogleCloudAiplatformV1beta1BatchPredictionJob", + "description": "A job that uses a Model to produce predictions on multiple input instances. If predictions for significant portion of the instances fail, the job may finish without attempting predictions for all remaining instances." + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter": { + "description": "A wrapper class which contains the tunable parameters in an AutoML Image training job.", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter", + "type": "object", + "properties": { + "studySpec": { + "$ref": "GoogleCloudAiplatformV1beta1StudySpec", + "description": "Optioinal. StudySpec of hyperparameter tuning job. Required for `model_garden_trainer`." + }, + "checkpointName": { + "type": "string", + "description": "Optional. An unique name of pretrained model checkpoint provided in model garden, it will be mapped to a GCS location internally." + }, + "trainerType": { + "type": "string", + "enumDescriptions": [ + "Default value.", + "", + "" + ], + "enum": [ + "TRAINER_TYPE_UNSPECIFIED", + "AUTOML_TRAINER", + "MODEL_GARDEN_TRAINER" + ] + }, + "trainerConfig": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "Customizable trainer settings, used in the `model_garden_trainer`." + }, + "datasetConfig": { + "type": "object", + "description": "Customizable dataset settings, used in the `model_garden_trainer`.", + "additionalProperties": { + "type": "string" + } + } + } + }, + "GoogleCloudAiplatformV1beta1ListDatasetsResponse": { + "description": "Response message for DatasetService.ListDatasets.", + "properties": { + "nextPageToken": { + "type": "string", + "description": "The standard List next-page token." + }, + "datasets": { + "description": "A list of Datasets that matches the specified filter in the request.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Dataset" + } + } + }, + "id": "GoogleCloudAiplatformV1beta1ListDatasetsResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1LineageSubgraph": { + "properties": { + "artifacts": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Artifact" + }, + "type": "array", + "description": "The Artifact nodes in the subgraph." + }, + "executions": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Execution" + }, + "type": "array", + "description": "The Execution nodes in the subgraph." + }, + "events": { + "type": "array", + "description": "The Event edges between Artifacts and Executions in the subgraph.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Event" + } + } + }, + "description": "A subgraph of the overall lineage graph. Event edges connect Artifact and Execution nodes.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1LineageSubgraph" + }, + "GoogleCloudAiplatformV1beta1CreatePipelineJobRequest": { + "properties": { + "pipelineJob": { + "$ref": "GoogleCloudAiplatformV1beta1PipelineJob", + "description": "Required. The PipelineJob to create." + }, + "parent": { + "description": "Required. The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`", + "type": "string" + }, + "pipelineJobId": { + "type": "string", + "description": "The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`." + } + }, + "id": "GoogleCloudAiplatformV1beta1CreatePipelineJobRequest", + "description": "Request message for PipelineService.CreatePipelineJob.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTrackMetrics": { + "properties": { + "confidenceMetrics": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTrackMetricsConfidenceMetrics" + }, + "type": "array", + "description": "Metrics for each label-match `confidenceThreshold` from 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is derived from them." + }, + "iouThreshold": { + "description": "The intersection-over-union threshold value between bounding boxes across frames used to compute this metric entry.", + "type": "number", + "format": "float" + }, + "meanTrackingAveragePrecision": { + "description": "The mean average precision over all confidence thresholds.", + "type": "number", + "format": "float" + }, + "meanMismatchRate": { + "format": "float", + "description": "The mean mismatch rate over all confidence thresholds.", + "type": "number" + }, + "meanBoundingBoxIou": { + "description": "The mean bounding box iou over all confidence thresholds.", + "type": "number", + "format": "float" + } + }, + "type": "object", + "description": "UNIMPLEMENTED. Track matching model metrics for a single track match threshold and multiple label match confidence thresholds.", + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTrackMetrics" + }, + "GoogleCloudAiplatformV1beta1FluencyInput": { + "description": "Input for fluency metric.", + "properties": { + "instance": { + "$ref": "GoogleCloudAiplatformV1beta1FluencyInstance", + "description": "Required. Fluency instance." + }, + "metricSpec": { + "description": "Required. Spec for fluency score metric.", + "$ref": "GoogleCloudAiplatformV1beta1FluencySpec" + } + }, + "id": "GoogleCloudAiplatformV1beta1FluencyInput", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1RougeResults": { + "description": "Results for rouge metric.", + "properties": { + "rougeMetricValues": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1RougeMetricValue" + }, + "readOnly": true, + "description": "Output only. Rouge metric values.", + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1beta1RougeResults", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1CreateNotebookExecutionJobRequest": { + "type": "object", + "description": "Request message for [NotebookService.CreateNotebookExecutionJob]", + "properties": { + "notebookExecutionJob": { + "$ref": "GoogleCloudAiplatformV1beta1NotebookExecutionJob", + "description": "Required. The NotebookExecutionJob to create." + }, + "parent": { + "description": "Required. The resource name of the Location to create the NotebookExecutionJob. Format: `projects/{project}/locations/{location}`", + "type": "string" + }, + "notebookExecutionJobId": { + "type": "string", + "description": "Optional. User specified ID for the NotebookExecutionJob." + } + }, + "id": "GoogleCloudAiplatformV1beta1CreateNotebookExecutionJobRequest" + }, + "GoogleCloudAiplatformV1beta1Schema": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1Schema", + "properties": { + "minimum": { + "description": "Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER Minimum value of the Type.INTEGER and Type.NUMBER", + "format": "double", + "type": "number" + }, + "maxProperties": { + "format": "int64", + "type": "string", + "description": "Optional. Maximum number of the properties for Type.OBJECT." + }, + "description": { + "type": "string", + "description": "Optional. The description of the data." + }, + "properties": { + "description": "Optional. SCHEMA FIELDS FOR TYPE OBJECT Properties of Type.OBJECT.", + "type": "object", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1Schema" + } + }, + "minProperties": { + "type": "string", + "format": "int64", + "description": "Optional. Minimum number of the properties for Type.OBJECT." + }, + "default": { + "description": "Optional. Default value of the data.", + "type": "any" + }, + "title": { + "type": "string", + "description": "Optional. The title of the Schema." + }, + "pattern": { + "description": "Optional. Pattern of the Type.STRING to restrict a string to a regular expression.", + "type": "string" + }, + "minLength": { + "format": "int64", + "description": "Optional. SCHEMA FIELDS FOR TYPE STRING Minimum length of the Type.STRING", + "type": "string" + }, + "nullable": { + "description": "Optional. Indicates if the value may be null.", + "type": "boolean" + }, + "required": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Optional. Required properties of Type.OBJECT." + }, + "maximum": { + "type": "number", + "description": "Optional. Maximum value of the Type.INTEGER and Type.NUMBER", + "format": "double" + }, + "example": { + "description": "Optional. Example of the object. Will only populated when the object is the root.", + "type": "any" + }, + "maxLength": { + "description": "Optional. Maximum length of the Type.STRING", + "format": "int64", + "type": "string" + }, + "type": { + "enum": [ + "TYPE_UNSPECIFIED", + "STRING", + "NUMBER", + "INTEGER", + "BOOLEAN", + "ARRAY", + "OBJECT" + ], + "enumDescriptions": [ + "Not specified, should not be used.", + "OpenAPI string type", + "OpenAPI number type", + "OpenAPI integer type", + "OpenAPI boolean type", + "OpenAPI array type", + "OpenAPI object type" + ], + "type": "string", + "description": "Optional. The type of the data." + }, + "items": { + "description": "Optional. SCHEMA FIELDS FOR TYPE ARRAY Schema of the elements of Type.ARRAY.", + "$ref": "GoogleCloudAiplatformV1beta1Schema" + }, + "minItems": { + "type": "string", + "description": "Optional. Minimum number of the elements for Type.ARRAY.", + "format": "int64" + }, + "enum": { + "description": "Optional. Possible values of the element of Type.STRING with enum format. For example we can define an Enum Direction as : {type:STRING, format:enum, enum:[\"EAST\", NORTH\", \"SOUTH\", \"WEST\"]}", + "items": { + "type": "string" + }, + "type": "array" + }, + "maxItems": { + "format": "int64", + "description": "Optional. Maximum number of the elements for Type.ARRAY.", + "type": "string" + }, + "format": { + "type": "string", + "description": "Optional. The format of the data. Supported formats: for NUMBER type: \"float\", \"double\" for INTEGER type: \"int32\", \"int64\" for STRING type: \"email\", \"byte\", etc" + } + }, + "description": "Schema is used to define the format of input/output data. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema). More fields may be added in the future as needed." + }, + "GoogleTypeInterval": { + "description": "Represents a time interval, encoded as a Timestamp start (inclusive) and a Timestamp end (exclusive). The start must be less than or equal to the end. When the start equals the end, the interval is empty (matches no time). When both start and end are unspecified, the interval matches any time.", + "id": "GoogleTypeInterval", + "type": "object", + "properties": { + "startTime": { + "description": "Optional. Inclusive start of the interval. If specified, a Timestamp matching this interval will have to be the same or after the start.", + "type": "string", + "format": "google-datetime" + }, + "endTime": { + "type": "string", + "format": "google-datetime", + "description": "Optional. Exclusive end of the interval. If specified, a Timestamp matching this interval will have to be before the end." + } + } + }, + "GoogleCloudAiplatformV1beta1UpdateFeatureGroupOperationMetadata": { + "properties": { + "genericMetadata": { + "description": "Operation metadata for FeatureGroup.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "type": "object", + "description": "Details of operations that perform update FeatureGroup.", + "id": "GoogleCloudAiplatformV1beta1UpdateFeatureGroupOperationMetadata" + }, + "GoogleCloudAiplatformV1beta1BatchDeletePipelineJobsRequest": { + "properties": { + "names": { + "description": "Required. The names of the PipelineJobs to delete. A maximum of 32 PipelineJobs can be deleted in a batch. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipelineJob}`", + "items": { + "type": "string" + }, + "type": "array" + } + }, + "description": "Request message for PipelineService.BatchDeletePipelineJobs.", + "id": "GoogleCloudAiplatformV1beta1BatchDeletePipelineJobsRequest", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics": { + "type": "object", + "properties": { + "truePositiveCount": { + "format": "int64", + "description": "The number of Model created labels that match a ground truth label.", + "type": "string" + }, + "confidenceThreshold": { + "type": "number", + "format": "float", + "description": "Metrics are computed with an assumption that the Model never returns predictions with score lower than this value." + }, + "f1ScoreMicro": { + "description": "Micro-averaged F1 Score.", + "format": "float", + "type": "number" + }, + "falsePositiveCount": { + "type": "string", + "description": "The number of Model created labels that do not match a ground truth label.", + "format": "int64" + }, + "falsePositiveRateAt1": { + "format": "float", + "description": "The False Positive Rate when only considering the label that has the highest prediction score and not below the confidence threshold for each DataItem.", + "type": "number" + }, + "f1ScoreMacro": { + "type": "number", + "format": "float", + "description": "Macro-averaged F1 Score." + }, + "f1ScoreAt1": { + "format": "float", + "type": "number", + "description": "The harmonic mean of recallAt1 and precisionAt1." + }, + "falsePositiveRate": { + "description": "False Positive Rate for the given confidence threshold.", + "format": "float", + "type": "number" + }, + "recallAt1": { + "description": "The Recall (True Positive Rate) when only considering the label that has the highest prediction score and not below the confidence threshold for each DataItem.", + "format": "float", + "type": "number" + }, + "precision": { + "format": "float", + "description": "Precision for the given confidence threshold.", + "type": "number" + }, + "f1Score": { + "format": "float", + "type": "number", + "description": "The harmonic mean of recall and precision. For summary metrics, it computes the micro-averaged F1 score." + }, + "precisionAt1": { + "description": "The precision when only considering the label that has the highest prediction score and not below the confidence threshold for each DataItem.", + "format": "float", + "type": "number" + }, + "maxPredictions": { + "type": "integer", + "description": "Metrics are computed with an assumption that the Model always returns at most this many predictions (ordered by their score, descendingly), but they all still need to meet the `confidenceThreshold`.", + "format": "int32" + }, + "confusionMatrix": { + "description": "Confusion matrix of the evaluation for this confidence_threshold.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix" + }, + "falseNegativeCount": { + "format": "int64", + "description": "The number of ground truth labels that are not matched by a Model created label.", + "type": "string" + }, + "recall": { + "type": "number", + "format": "float", + "description": "Recall (True Positive Rate) for the given confidence threshold." + }, + "trueNegativeCount": { + "type": "string", + "description": "The number of labels that were not created by the Model, but if they would, they would not match a ground truth label.", + "format": "int64" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics" + }, + "GoogleCloudAiplatformV1beta1TokensInfo": { + "type": "object", + "description": "Tokens info with a list of tokens and the corresponding list of token ids.", + "id": "GoogleCloudAiplatformV1beta1TokensInfo", + "properties": { + "tokens": { + "items": { + "format": "byte", + "type": "string" + }, + "type": "array", + "description": "A list of tokens from the input." + }, + "role": { + "type": "string", + "description": "Optional. Optional fields for the role from the corresponding Content." + }, + "tokenIds": { + "items": { + "format": "int64", + "type": "string" + }, + "type": "array", + "description": "A list of token ids from the input." + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsGranularity": { + "properties": { + "quantity": { + "type": "string", + "format": "int64", + "description": "The number of granularity_units between data points in the training data. If `granularity_unit` is `minute`, can be 1, 5, 10, 15, or 30. For all other values of `granularity_unit`, must be 1." + }, + "unit": { + "type": "string", + "description": "The time granularity unit of this time period. The supported units are: * \"minute\" * \"hour\" * \"day\" * \"week\" * \"month\" * \"year\"" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsGranularity", + "description": "A duration of time expressed in time granularity units." + }, + "GoogleCloudAiplatformV1beta1ListFeatureGroupsResponse": { + "type": "object", + "properties": { + "featureGroups": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureGroup" + }, + "description": "The FeatureGroups matching the request.", + "type": "array" + }, + "nextPageToken": { + "description": "A token, which can be sent as ListFeatureGroupsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + } + }, + "description": "Response message for FeatureRegistryService.ListFeatureGroups.", + "id": "GoogleCloudAiplatformV1beta1ListFeatureGroupsResponse" + }, + "GoogleCloudAiplatformV1beta1PublisherModelDocumentation": { + "description": "A named piece of documentation.", + "id": "GoogleCloudAiplatformV1beta1PublisherModelDocumentation", + "type": "object", + "properties": { + "title": { + "description": "Required. E.g., OVERVIEW, USE CASES, DOCUMENTATION, SDK & SAMPLES, JAVA, NODE.JS, etc..", + "type": "string" + }, + "content": { + "type": "string", + "description": "Required. Content of this piece of document (in Markdown format)." + } + } + }, + "GoogleCloudAiplatformV1beta1IndexDatapointSparseEmbedding": { + "type": "object", + "properties": { + "dimensions": { + "type": "array", + "items": { + "format": "int64", + "type": "string" + }, + "description": "Required. The list of indexes for the embedding values of the sparse vector." + }, + "values": { + "items": { + "format": "float", + "type": "number" + }, + "type": "array", + "description": "Required. The list of embedding values of the sparse vector." + } + }, + "description": "Feature embedding vector for sparse index. An array of numbers whose values are located in the specified dimensions.", + "id": "GoogleCloudAiplatformV1beta1IndexDatapointSparseEmbedding" + }, + "GoogleCloudAiplatformV1beta1UploadModelOperationMetadata": { + "description": "Details of ModelService.UploadModel operation.", + "id": "GoogleCloudAiplatformV1beta1UploadModelOperationMetadata", + "type": "object", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "The common part of the operation metadata." + } + } + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringStats": { + "properties": { + "tabularStats": { + "description": "Generated tabular statistics.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringTabularStats" + } + }, + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringStats", + "description": "Represents the collection of statistics for a metric.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec": { + "type": "object", + "properties": { + "maxParallelTrialCount": { + "description": "Required. The maximum number of trials to run in parallel.", + "type": "integer", + "format": "int32" + }, + "trainTrialJobSpec": { + "$ref": "GoogleCloudAiplatformV1beta1CustomJobSpec", + "description": "Required. The spec of a train trial job. The same spec applies to all train trials." + }, + "frequency": { + "description": "Required. Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.", + "format": "int32", + "type": "integer" + } + }, + "id": "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec", + "description": "Represent spec for train trials." + }, + "GoogleLongrunningListOperationsResponse": { + "type": "object", + "id": "GoogleLongrunningListOperationsResponse", + "description": "The response message for Operations.ListOperations.", + "properties": { + "operations": { + "description": "A list of operations that matches the specified filter in the request.", + "type": "array", + "items": { + "$ref": "GoogleLongrunningOperation" + } + }, + "nextPageToken": { + "description": "The standard List next-page token.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1UndeployModelResponse": { + "type": "object", + "properties": {}, + "id": "GoogleCloudAiplatformV1beta1UndeployModelResponse", + "description": "Response message for EndpointService.UndeployModel." + }, + "GoogleCloudAiplatformV1beta1BatchCreateTensorboardRunsRequest": { + "description": "Request message for TensorboardService.BatchCreateTensorboardRuns.", + "id": "GoogleCloudAiplatformV1beta1BatchCreateTensorboardRunsRequest", + "properties": { + "requests": { + "description": "Required. The request message specifying the TensorboardRuns to create. A maximum of 1000 TensorboardRuns can be created in a batch.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1CreateTensorboardRunRequest" + } + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ModelEvaluationSlice": { + "properties": { + "modelExplanation": { + "$ref": "GoogleCloudAiplatformV1beta1ModelExplanation", + "readOnly": true, + "description": "Output only. Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for tabular Models." + }, + "createTime": { + "type": "string", + "readOnly": true, + "description": "Output only. Timestamp when this ModelEvaluationSlice was created.", + "format": "google-datetime" + }, + "slice": { + "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSlice", + "readOnly": true, + "description": "Output only. The slice of the test data that is used to evaluate the Model." + }, + "name": { + "type": "string", + "description": "Output only. The resource name of the ModelEvaluationSlice.", + "readOnly": true + }, + "metricsSchemaUri": { + "readOnly": true, + "type": "string", + "description": "Output only. Points to a YAML file stored on Google Cloud Storage describing the metrics of this ModelEvaluationSlice. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject)." + }, + "metrics": { + "description": "Output only. Sliced evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri", + "type": "any", + "readOnly": true + } + }, + "id": "GoogleCloudAiplatformV1beta1ModelEvaluationSlice", + "description": "A collection of metrics calculated by comparing Model's predictions on a slice of the test data against ground truth annotations.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1HyperparameterTuningJob": { + "description": "Represents a HyperparameterTuningJob. A HyperparameterTuningJob has a Study specification and multiple CustomJobs with identical CustomJob specification.", + "id": "GoogleCloudAiplatformV1beta1HyperparameterTuningJob", + "properties": { + "endTime": { + "type": "string", + "readOnly": true, + "description": "Output only. Time when the HyperparameterTuningJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.", + "format": "google-datetime" + }, + "trials": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Trial" + }, + "description": "Output only. Trials of the HyperparameterTuningJob.", + "readOnly": true + }, + "maxFailedTrialCount": { + "format": "int32", + "type": "integer", + "description": "The number of failed Trials that need to be seen before failing the HyperparameterTuningJob. If set to 0, Vertex AI decides how many Trials must fail before the whole job fails." + }, + "maxTrialCount": { + "type": "integer", + "format": "int32", + "description": "Required. The desired total number of Trials." + }, + "startTime": { + "description": "Output only. Time when the HyperparameterTuningJob for the first time entered the `JOB_STATE_RUNNING` state.", + "readOnly": true, + "format": "google-datetime", + "type": "string" + }, + "studySpec": { + "description": "Required. Study configuration of the HyperparameterTuningJob.", + "$ref": "GoogleCloudAiplatformV1beta1StudySpec" + }, + "name": { + "description": "Output only. Resource name of the HyperparameterTuningJob.", + "type": "string", + "readOnly": true + }, + "encryptionSpec": { + "description": "Customer-managed encryption key options for a HyperparameterTuningJob. If this is set, then all resources created by the HyperparameterTuningJob will be encrypted with the provided encryption key.", + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" + }, + "displayName": { + "type": "string", + "description": "Required. The display name of the HyperparameterTuningJob. The name can be up to 128 characters long and can consist of any UTF-8 characters." + }, + "error": { + "$ref": "GoogleRpcStatus", + "description": "Output only. Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.", + "readOnly": true + }, + "parallelTrialCount": { + "description": "Required. The desired number of Trials to run in parallel.", + "type": "integer", + "format": "int32" + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "The labels with user-defined metadata to organize HyperparameterTuningJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels." + }, + "state": { + "type": "string", + "readOnly": true, + "description": "Output only. The detailed state of the job.", + "enum": [ + "JOB_STATE_UNSPECIFIED", + "JOB_STATE_QUEUED", + "JOB_STATE_PENDING", + "JOB_STATE_RUNNING", + "JOB_STATE_SUCCEEDED", + "JOB_STATE_FAILED", + "JOB_STATE_CANCELLING", + "JOB_STATE_CANCELLED", + "JOB_STATE_PAUSED", + "JOB_STATE_EXPIRED", + "JOB_STATE_UPDATING", + "JOB_STATE_PARTIALLY_SUCCEEDED" + ], + "enumDescriptions": [ + "The job state is unspecified.", + "The job has been just created or resumed and processing has not yet begun.", + "The service is preparing to run the job.", + "The job is in progress.", + "The job completed successfully.", + "The job failed.", + "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "The job has been cancelled.", + "The job has been stopped, and can be resumed.", + "The job has expired.", + "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", + "The job is partially succeeded, some results may be missing due to errors." + ] + }, + "createTime": { + "type": "string", + "description": "Output only. Time when the HyperparameterTuningJob was created.", + "format": "google-datetime", + "readOnly": true + }, + "updateTime": { + "description": "Output only. Time when the HyperparameterTuningJob was most recently updated.", + "format": "google-datetime", + "readOnly": true, + "type": "string" + }, + "trialJobSpec": { + "$ref": "GoogleCloudAiplatformV1beta1CustomJobSpec", + "description": "Required. The spec of a trial job. The same spec applies to the CustomJobs created in all the trials." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTimestampTransformation": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTimestampTransformation", + "properties": { + "columnName": { + "type": "string" + }, + "timeFormat": { + "type": "string", + "description": "The format in which that time field is expressed. The time_format must either be one of: * `unix-seconds` * `unix-milliseconds` * `unix-microseconds` * `unix-nanoseconds` (for respectively number of seconds, milliseconds, microseconds and nanoseconds since start of the Unix epoch); or be written in `strftime` syntax. If time_format is not set, then the default format is RFC 3339 `date-time` format, where `time-offset` = `\"Z\"` (e.g. 1985-04-12T23:20:50.52Z)" + } + }, + "type": "object", + "description": "Training pipeline will perform following transformation functions. * Apply the transformation functions for Numerical columns. * Determine the year, month, day,and weekday. Treat each value from the timestamp as a Categorical column. * Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed." + }, + "GoogleCloudAiplatformV1beta1CacheConfig": { + "type": "object", + "description": "Config of GenAI caching features. This is a singleton resource.", + "id": "GoogleCloudAiplatformV1beta1CacheConfig", + "properties": { + "name": { + "description": "Identifier. Name of the cache config. Format: - `projects/{project}/cacheConfig`.", + "type": "string" + }, + "disableCache": { + "type": "boolean", + "description": "If set to true, disables GenAI caching. Otherwise caching is enabled." + } + } + }, + "GoogleCloudAiplatformV1beta1StartNotebookRuntimeOperationMetadata": { + "id": "GoogleCloudAiplatformV1beta1StartNotebookRuntimeOperationMetadata", + "description": "Metadata information for NotebookService.StartNotebookRuntime.", + "type": "object", + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + }, + "progressMessage": { + "type": "string", + "description": "A human-readable message that shows the intermediate progress details of NotebookRuntime." + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadata", + "properties": { + "inputConfig": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataInputConfig" + } + }, + "description": "The metadata of Datasets that contain tables data." + }, + "GoogleCloudAiplatformV1beta1PublisherModelCallToActionOpenFineTuningPipelines": { + "type": "object", + "description": "Open fine tuning pipelines.", + "id": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionOpenFineTuningPipelines", + "properties": { + "fineTuningPipelines": { + "description": "Required. Regional resource references to fine tuning pipelines.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences" + } + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationMetadata": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationMetadata", + "type": "object", + "properties": { + "costMilliNodeHours": { + "type": "string", + "description": "The actual training cost of creating this model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed inputs.budgetMilliNodeHours.", + "format": "int64" + }, + "successfulStopReason": { + "enumDescriptions": [ + "Should not be set.", + "The inputs.budgetMilliNodeHours had been reached.", + "Further training of the Model ceased to increase its quality, since it already has converged." + ], + "description": "For successful job completions, this is the reason why the job has finished.", + "enum": [ + "SUCCESSFUL_STOP_REASON_UNSPECIFIED", + "BUDGET_REACHED", + "MODEL_CONVERGED" + ], + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1DirectPredictRequest": { + "type": "object", + "properties": { + "parameters": { + "$ref": "GoogleCloudAiplatformV1beta1Tensor", + "description": "The parameters that govern the prediction." + }, + "inputs": { + "description": "The prediction input.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Tensor" + }, + "type": "array" + } + }, + "description": "Request message for PredictionService.DirectPredict.", + "id": "GoogleCloudAiplatformV1beta1DirectPredictRequest" + }, + "GoogleCloudAiplatformV1beta1RuntimeConfig": { + "type": "object", + "description": "Runtime configuration to run the extension.", + "id": "GoogleCloudAiplatformV1beta1RuntimeConfig", + "properties": { + "codeInterpreterRuntimeConfig": { + "$ref": "GoogleCloudAiplatformV1beta1RuntimeConfigCodeInterpreterRuntimeConfig", + "description": "Code execution runtime configurations for code interpreter extension." + }, + "defaultParams": { + "additionalProperties": { + "description": "Properties of the object.", + "type": "any" + }, + "type": "object", + "description": "Optional. Default parameters that will be set for all the execution of this extension. If specified, the parameter values can be overridden by values in [[ExecuteExtensionRequest.operation_params]] at request time. The struct should be in a form of map with param name as the key and actual param value as the value. E.g. If this operation requires a param \"name\" to be set to \"abc\". you can set this to something like {\"name\": \"abc\"}." + }, + "vertexAiSearchRuntimeConfig": { + "$ref": "GoogleCloudAiplatformV1beta1RuntimeConfigVertexAISearchRuntimeConfig", + "description": "Runtime configuration for Vertex AI Search extension." + } + } + }, + "GoogleCloudAiplatformV1beta1BatchCreateFeaturesRequest": { + "properties": { + "requests": { + "description": "Required. The request message specifying the Features to create. All Features must be created under the same parent EntityType. The `parent` field in each child request message can be omitted. If `parent` is set in a child request, then the value must match the `parent` value in this request message.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1CreateFeatureRequest" + }, + "type": "array" + } + }, + "description": "Request message for FeaturestoreService.BatchCreateFeatures.", + "id": "GoogleCloudAiplatformV1beta1BatchCreateFeaturesRequest", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1GoogleSearchRetrieval": { + "properties": {}, + "description": "Tool to retrieve public web data for grounding, powered by Google.", + "id": "GoogleCloudAiplatformV1beta1GoogleSearchRetrieval", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1TrialContext": { + "description": "Next ID: 3", + "type": "object", + "properties": { + "parameters": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1TrialParameter" + }, + "type": "array", + "description": "If/when a Trial is generated or selected from this Context, its Parameters will match any parameters specified here. (I.e. if this context specifies parameter name:'a' int_value:3, then a resulting Trial will have int_value:3 for its parameter named 'a'.) Note that we first attempt to match existing REQUESTED Trials with contexts, and if there are no matches, we generate suggestions in the subspace defined by the parameters specified here. NOTE: a Context without any Parameters matches the entire feasible search space." + }, + "description": { + "type": "string", + "description": "A human-readable field which can store a description of this context. This will become part of the resulting Trial's description field." + } + }, + "id": "GoogleCloudAiplatformV1beta1TrialContext" + }, + "GoogleCloudAiplatformV1beta1ImportDataResponse": { + "description": "Response message for DatasetService.ImportData.", + "type": "object", + "properties": {}, + "id": "GoogleCloudAiplatformV1beta1ImportDataResponse" + }, + "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualitySpec": { + "properties": { + "version": { + "format": "int32", + "description": "Optional. Which version to use for evaluation.", + "type": "integer" + }, + "useReference": { + "type": "boolean", + "description": "Optional. Whether to use instance.reference to compute question answering quality." + } + }, + "description": "Spec for pairwise question answering quality score metric.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualitySpec" + }, + "GoogleCloudAiplatformV1beta1PurgeExecutionsMetadata": { + "id": "GoogleCloudAiplatformV1beta1PurgeExecutionsMetadata", + "type": "object", + "properties": { + "genericMetadata": { + "description": "Operation metadata for purging Executions.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "description": "Details of operations that perform MetadataService.PurgeExecutions." + }, + "GoogleCloudAiplatformV1beta1QueryExtensionResponse": { + "id": "GoogleCloudAiplatformV1beta1QueryExtensionResponse", + "properties": { + "failureMessage": { + "type": "string", + "description": "Failure message if any." + }, + "steps": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Content" + }, + "type": "array", + "description": "Steps of extension or LLM interaction, can contain function call, function response, or text response. The last step contains the final response to the query." + } + }, + "type": "object", + "description": "Response message for ExtensionExecutionService.QueryExtension." + }, + "GoogleCloudAiplatformV1beta1CreateFeatureRequest": { + "id": "GoogleCloudAiplatformV1beta1CreateFeatureRequest", + "description": "Request message for FeaturestoreService.CreateFeature. Request message for FeatureRegistryService.CreateFeature.", + "properties": { + "parent": { + "type": "string", + "description": "Required. The resource name of the EntityType or FeatureGroup to create a Feature. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`" + }, + "feature": { + "$ref": "GoogleCloudAiplatformV1beta1Feature", + "description": "Required. The Feature to create." + }, + "featureId": { + "type": "string", + "description": "Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1StartNotebookRuntimeRequest": { + "id": "GoogleCloudAiplatformV1beta1StartNotebookRuntimeRequest", + "description": "Request message for NotebookService.StartNotebookRuntime.", + "type": "object", + "properties": {} + }, + "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceInstance": { + "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceInstance", + "properties": { + "instruction": { + "description": "Required. The question asked and other instruction in the inference prompt.", + "type": "string" + }, + "reference": { + "description": "Optional. Ground truth used to compare against the prediction.", + "type": "string" + }, + "context": { + "type": "string", + "description": "Optional. Text provided as context to answer the question." + }, + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + } + }, + "type": "object", + "description": "Spec for question answering relevance instance." + }, + "GoogleCloudAiplatformV1beta1CreateSpecialistPoolOperationMetadata": { + "description": "Runtime operation information for SpecialistPoolService.CreateSpecialistPool.", + "type": "object", + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "id": "GoogleCloudAiplatformV1beta1CreateSpecialistPoolOperationMetadata" + }, + "GoogleCloudAiplatformV1beta1PythonPackageSpec": { + "id": "GoogleCloudAiplatformV1beta1PythonPackageSpec", + "type": "object", + "properties": { + "args": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Command line arguments to be passed to the Python task." + }, + "packageUris": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Required. The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100." + }, + "executorImageUri": { + "description": "Required. The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of [pre-built containers for training](https://cloud.google.com/vertex-ai/docs/training/pre-built-containers). You must use an image from this list.", + "type": "string" + }, + "env": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1EnvVar" + }, + "type": "array", + "description": "Environment variables to be passed to the python module. Maximum limit is 100." + }, + "pythonModule": { + "type": "string", + "description": "Required. The Python module name to run after installing the packages." + } + }, + "description": "The spec of a Python packaged code." + }, + "GoogleCloudAiplatformV1beta1ReportExecutionEventResponse": { + "id": "GoogleCloudAiplatformV1beta1ReportExecutionEventResponse", + "properties": {}, + "description": "Response message for NotebookInternalService.ReportExecutionEvent.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ListIndexesResponse": { + "id": "GoogleCloudAiplatformV1beta1ListIndexesResponse", + "description": "Response message for IndexService.ListIndexes.", + "type": "object", + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token to retrieve next page of results. Pass to ListIndexesRequest.page_token to obtain that page." + }, + "indexes": { + "type": "array", + "description": "List of indexes in the requested page.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Index" + } + } + } + }, + "GoogleCloudAiplatformV1beta1StreamingPredictResponse": { + "type": "object", + "properties": { + "parameters": { + "$ref": "GoogleCloudAiplatformV1beta1Tensor", + "description": "The parameters that govern the prediction." + }, + "outputs": { + "type": "array", + "description": "The prediction output.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Tensor" + } + } + }, + "id": "GoogleCloudAiplatformV1beta1StreamingPredictResponse", + "description": "Response message for PredictionService.StreamingPredict." + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextClassificationInputs": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextClassificationInputs", + "type": "object", + "properties": { + "multiLabel": { + "type": "boolean" + } + } + }, + "GoogleCloudAiplatformV1beta1ListNotebookRuntimeTemplatesResponse": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ListNotebookRuntimeTemplatesResponse", + "description": "Response message for NotebookService.ListNotebookRuntimeTemplates.", + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token to retrieve next page of results. Pass to ListNotebookRuntimeTemplatesRequest.page_token to obtain that page." + }, + "notebookRuntimeTemplates": { + "type": "array", + "description": "List of NotebookRuntimeTemplates in the requested page.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate" + } + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoActionRecognitionPredictionResult": { + "properties": { + "displayName": { + "description": "The display name of the AnnotationSpec that had been identified.", + "type": "string" + }, + "confidence": { + "description": "The Model's confidence in correction of this prediction, higher value means higher confidence.", + "type": "number", + "format": "float" + }, + "id": { + "description": "The resource ID of the AnnotationSpec that had been identified.", + "type": "string" + }, + "timeSegmentEnd": { + "format": "google-duration", + "type": "string", + "description": "The end, exclusive, of the video's time segment in which the AnnotationSpec has been identified. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end." + }, + "timeSegmentStart": { + "format": "google-duration", + "description": "The beginning, inclusive, of the video's time segment in which the AnnotationSpec has been identified. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoActionRecognitionPredictionResult", + "description": "Prediction output format for Video Action Recognition." + }, + "GoogleCloudAiplatformV1beta1BatchPredictionJobInputConfig": { + "type": "object", + "properties": { + "bigquerySource": { + "$ref": "GoogleCloudAiplatformV1beta1BigQuerySource", + "description": "The BigQuery location of the input table. The schema of the table should be in the format described by the given context OpenAPI Schema, if one is provided. The table may contain additional columns that are not described by the schema, and they will be ignored." + }, + "instancesFormat": { + "description": "Required. The format in which instances are given, must be one of the Model's supported_input_storage_formats.", + "type": "string" + }, + "gcsSource": { + "description": "The Cloud Storage location for the input instances.", + "$ref": "GoogleCloudAiplatformV1beta1GcsSource" + } + }, + "description": "Configures the input to BatchPredictionJob. See Model.supported_input_storage_formats for Model's supported input formats, and how instances should be expressed via any of them.", + "id": "GoogleCloudAiplatformV1beta1BatchPredictionJobInputConfig" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputs": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputs", + "properties": { + "hierarchyConfig": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHierarchyConfig", + "description": "Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies." + }, + "contextWindow": { + "format": "int64", + "type": "string", + "description": "The amount of time into the past training and prediction data is used for model training and prediction respectively. Expressed in number of units defined by the `data_granularity` field." + }, + "dataGranularity": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsGranularity", + "description": "Expected difference in time granularity between rows in the data." + }, + "exportEvaluatedDataItemsConfig": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig", + "description": "Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed." + }, + "windowConfig": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionWindowConfig", + "description": "Config containing strategy for generating sliding windows." + }, + "quantiles": { + "type": "array", + "items": { + "format": "double", + "type": "number" + }, + "description": "Quantiles to use for minimize-quantile-loss `optimization_objective`. Up to 5 quantiles are allowed of values between 0 and 1, exclusive. Required if the value of optimization_objective is minimize-quantile-loss. Represents the percent quantiles to use for that objective. Quantiles must be unique." + }, + "optimizationObjective": { + "description": "Objective function the model is optimizing towards. The training process creates a model that optimizes the value of the objective function over the validation set. The supported optimization objectives: * \"minimize-rmse\" (default) - Minimize root-mean-squared error (RMSE). * \"minimize-mae\" - Minimize mean-absolute error (MAE). * \"minimize-rmsle\" - Minimize root-mean-squared log error (RMSLE). * \"minimize-rmspe\" - Minimize root-mean-squared percentage error (RMSPE). * \"minimize-wape-mae\" - Minimize the combination of weighted absolute percentage error (WAPE) and mean-absolute-error (MAE). * \"minimize-quantile-loss\" - Minimize the quantile loss at the quantiles defined in `quantiles`. * \"minimize-mape\" - Minimize the mean absolute percentage error.", + "type": "string" + }, + "timeSeriesAttributeColumns": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Column names that should be used as attribute columns. The value of these columns does not vary as a function of time. For example, store ID or item color." + }, + "trainBudgetMilliNodeHours": { + "description": "Required. The train budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The training cost of the model will not exceed this budget. The final cost will be attempted to be close to the budget, though may end up being (even) noticeably smaller - at the backend's discretion. This especially may happen when further model training ceases to provide any improvements. If the budget is set to a value known to be insufficient to train a model for the given dataset, the training won't be attempted and will error. The train budget must be between 1,000 and 72,000 milli node hours, inclusive.", + "type": "string", + "format": "int64" + }, + "unavailableAtForecastColumns": { + "description": "Names of columns that are unavailable when a forecast is requested. This column contains information for the given entity (identified by the time_series_identifier_column) that is unknown before the forecast For example, actual weather on a given day.", + "items": { + "type": "string" + }, + "type": "array" + }, + "forecastHorizon": { + "format": "int64", + "type": "string", + "description": "The amount of time into the future for which forecasted values for the target are returned. Expressed in number of units defined by the `data_granularity` field." + }, + "validationOptions": { + "description": "Validation options for the data validation component. The available options are: * \"fail-pipeline\" - default, will validate against the validation and fail the pipeline if it fails. * \"ignore-validation\" - ignore the results of the validation and continue", + "type": "string" + }, + "timeSeriesIdentifierColumn": { + "type": "string", + "description": "The name of the column that identifies the time series." + }, + "weightColumn": { + "description": "Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1. This column must be available at forecast.", + "type": "string" + }, + "timeColumn": { + "type": "string", + "description": "The name of the column that identifies time order in the time series. This column must be available at forecast." + }, + "transformations": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformation" + }, + "type": "array", + "description": "Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using \".\" as the delimiter." + }, + "holidayRegions": { + "description": "The geographical region based on which the holiday effect is applied in modeling by adding holiday categorical array feature that include all holidays matching the date. This option only allowed when data_granularity is day. By default, holiday effect modeling is disabled. To turn it on, specify the holiday region using this option.", + "items": { + "type": "string" + }, + "type": "array" + }, + "targetColumn": { + "type": "string", + "description": "The name of the column that the Model is to predict values for. This column must be unavailable at forecast." + }, + "additionalExperiments": { + "description": "Additional experiment flags for the time series forcasting training.", + "type": "array", + "items": { + "type": "string" + } + }, + "availableAtForecastColumns": { + "description": "Names of columns that are available and provided when a forecast is requested. These columns contain information for the given entity (identified by the time_series_identifier_column column) that is known at forecast. For example, predicted weather for a specific day.", + "items": { + "type": "string" + }, + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1beta1SupervisedTuningDataStats": { + "properties": { + "userMessagePerExampleDistribution": { + "$ref": "GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistribution", + "readOnly": true, + "description": "Output only. Dataset distributions for the messages per example." + }, + "tuningStepCount": { + "format": "int64", + "description": "Output only. Number of tuning steps for this Tuning Job.", + "type": "string", + "readOnly": true + }, + "userOutputTokenDistribution": { + "$ref": "GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistribution", + "readOnly": true, + "description": "Output only. Dataset distributions for the user output tokens." + }, + "totalBillableTokenCount": { + "type": "string", + "readOnly": true, + "format": "int64", + "description": "Output only. Number of billable tokens in the tuning dataset." + }, + "totalTuningCharacterCount": { + "description": "Output only. Number of tuning characters in the tuning dataset.", + "format": "int64", + "type": "string", + "readOnly": true + }, + "totalBillableCharacterCount": { + "description": "Output only. Number of billable characters in the tuning dataset.", + "format": "int64", + "readOnly": true, + "deprecated": true, + "type": "string" + }, + "tuningDatasetExampleCount": { + "readOnly": true, + "description": "Output only. Number of examples in the tuning dataset.", + "format": "int64", + "type": "string" + }, + "userInputTokenDistribution": { + "description": "Output only. Dataset distributions for the user input tokens.", + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistribution" + }, + "userDatasetExamples": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Content" + }, + "readOnly": true, + "type": "array", + "description": "Output only. Sample user messages in the training dataset uri." + } + }, + "id": "GoogleCloudAiplatformV1beta1SupervisedTuningDataStats", + "type": "object", + "description": "Tuning data statistics for Supervised Tuning." + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesMetadata", + "description": "Model metadata specific to AutoML Tables.", + "properties": { + "evaluatedDataItemsBigqueryUri": { + "type": "string", + "description": "BigQuery destination uri for exported evaluated examples." + }, + "trainCostMilliNodeHours": { + "type": "string", + "format": "int64", + "description": "Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget." + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaPredictParamsImageSegmentationPredictionParams": { + "properties": { + "confidenceThreshold": { + "type": "number", + "format": "float", + "description": "When the model predicts category of pixels of the image, it will only provide predictions for pixels that it is at least this much confident about. All other pixels will be classified as background. Default value is 0.5." + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaPredictParamsImageSegmentationPredictionParams", + "description": "Prediction model parameters for Image Segmentation.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1PurgeArtifactsRequest": { + "description": "Request message for MetadataService.PurgeArtifacts.", + "properties": { + "filter": { + "description": "Required. A required filter matching the Artifacts to be purged. E.g., `update_time \u003c= 2020-11-19T11:30:00-04:00`.", + "type": "string" + }, + "force": { + "type": "boolean", + "description": "Optional. Flag to indicate to actually perform the purge. If `force` is set to false, the method will return a sample of Artifact names that would be deleted." + } + }, + "id": "GoogleCloudAiplatformV1beta1PurgeArtifactsRequest", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1DoubleArray": { + "id": "GoogleCloudAiplatformV1beta1DoubleArray", + "description": "A list of double values.", + "type": "object", + "properties": { + "values": { + "type": "array", + "description": "A list of double values.", + "items": { + "type": "number", + "format": "double" + } + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaPredictInstanceVideoActionRecognitionPredictionInstance": { + "type": "object", + "description": "Prediction input format for Video Action Recognition.", + "properties": { + "content": { + "type": "string", + "description": "The Google Cloud Storage location of the video on which to perform the prediction." + }, + "timeSegmentEnd": { + "type": "string", + "description": "The end, exclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with \"s\" appended at the end. Fractions are allowed, up to a microsecond precision, and \"inf\" or \"Infinity\" is allowed, which means the end of the video." + }, + "mimeType": { + "type": "string", + "description": "The MIME type of the content of the video. Only the following are supported: video/mp4 video/avi video/quicktime" + }, + "timeSegmentStart": { + "type": "string", + "description": "The beginning, inclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with \"s\" appended at the end. Fractions are allowed, up to a microsecond precision." + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaPredictInstanceVideoActionRecognitionPredictionInstance" + }, + "GoogleCloudAiplatformV1beta1RayLogsSpec": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1RayLogsSpec", + "description": "Configuration for the Ray OSS Logs.", + "properties": { + "disabled": { + "description": "Optional. Flag to disable the export of Ray OSS logs to Cloud Logging.", + "type": "boolean" + } + } + }, + "GoogleCloudAiplatformV1beta1SearchModelMonitoringAlertsRequest": { + "id": "GoogleCloudAiplatformV1beta1SearchModelMonitoringAlertsRequest", + "properties": { + "statsName": { + "type": "string", + "description": "If non-empty, returns the alerts of this stats_name." + }, + "objectiveType": { + "type": "string", + "description": "If non-empty, returns the alerts of this objective type. Supported monitoring objectives: `raw-feature-drift` `prediction-output-drift` `feature-attribution`" + }, + "modelMonitoringJob": { + "description": "If non-empty, returns the alerts of this model monitoring job.", + "type": "string" + }, + "pageSize": { + "type": "integer", + "format": "int32", + "description": "The standard list page size." + }, + "alertTimeInterval": { + "description": "If non-empty, returns the alerts in this time interval.", + "$ref": "GoogleTypeInterval" + }, + "pageToken": { + "type": "string", + "description": "A page token received from a previous ModelMonitoringService.SearchModelMonitoringAlerts call." + } + }, + "description": "Request message for ModelMonitoringService.SearchModelMonitoringAlerts.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomaliesFeatureHistoricStatsAnomalies": { + "description": "Historical Stats (and Anomalies) for a specific Feature.", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomaliesFeatureHistoricStatsAnomalies", + "type": "object", + "properties": { + "featureDisplayName": { + "type": "string", + "description": "Display Name of the Feature." + }, + "predictionStats": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureStatsAnomaly" + }, + "type": "array", + "description": "A list of historical stats generated by different time window's Prediction Dataset." + }, + "trainingStats": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureStatsAnomaly", + "description": "Stats calculated for the Training Dataset." + }, + "threshold": { + "$ref": "GoogleCloudAiplatformV1beta1ThresholdConfig", + "description": "Threshold for anomaly detection." + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTabularRegressionPredictionResult": { + "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTabularRegressionPredictionResult", + "description": "Prediction output format for Tabular Regression.", + "properties": { + "value": { + "format": "float", + "type": "number", + "description": "The regression value." + }, + "upperBound": { + "format": "float", + "description": "The upper bound of the prediction interval.", + "type": "number" + }, + "quantilePredictions": { + "items": { + "format": "float", + "type": "number" + }, + "type": "array", + "description": "Quantile predictions, in 1-1 correspondence with quantile_values." + }, + "lowerBound": { + "type": "number", + "format": "float", + "description": "The lower bound of the prediction interval." + }, + "quantileValues": { + "type": "array", + "items": { + "format": "float", + "type": "number" + }, + "description": "Quantile values." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1PurgeArtifactsResponse": { + "description": "Response message for MetadataService.PurgeArtifacts.", + "properties": { + "purgeSample": { + "description": "A sample of the Artifact names that will be deleted. Only populated if `force` is set to false. The maximum number of samples is 100 (it is possible to return fewer).", + "items": { + "type": "string" + }, + "type": "array" + }, + "purgeCount": { + "description": "The number of Artifacts that this request deleted (or, if `force` is false, the number of Artifacts that will be deleted). This can be an estimate.", + "format": "int64", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1PurgeArtifactsResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1IndexDatapointCrowdingTag": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1IndexDatapointCrowdingTag", + "description": "Crowding tag is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than some value k' of the k neighbors returned have the same value of crowding_attribute.", + "properties": { + "crowdingAttribute": { + "type": "string", + "description": "The attribute value used for crowding. The maximum number of neighbors to return per crowding attribute value (per_crowding_attribute_num_neighbors) is configured per-query. This field is ignored if per_crowding_attribute_num_neighbors is larger than the total number of neighbors to return for a given query." + } + } + }, + "GoogleCloudAiplatformV1beta1DeployedIndex": { + "properties": { + "privateEndpoints": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1IndexPrivateEndpoints", + "description": "Output only. Provides paths for users to send requests directly to the deployed index services running on Cloud via private services access. This field is populated if network is configured." + }, + "index": { + "type": "string", + "description": "Required. The name of the Index this is the deployment of. We may refer to this Index as the DeployedIndex's \"original\" Index." + }, + "reservedIpRanges": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Optional. A list of reserved ip ranges under the VPC network that can be used for this DeployedIndex. If set, we will deploy the index within the provided ip ranges. Otherwise, the index might be deployed to any ip ranges under the provided VPC network. The value should be the name of the address (https://cloud.google.com/compute/docs/reference/rest/v1/addresses) Example: ['vertex-ai-ip-range']. For more information about subnets and network IP ranges, please see https://cloud.google.com/vpc/docs/subnets#manually_created_subnet_ip_ranges." + }, + "deploymentGroup": { + "description": "Optional. The deployment group can be no longer than 64 characters (eg: 'test', 'prod'). If not set, we will use the 'default' deployment group. Creating `deployment_groups` with `reserved_ip_ranges` is a recommended practice when the peered network has multiple peering ranges. This creates your deployments from predictable IP spaces for easier traffic administration. Also, one deployment_group (except 'default') can only be used with the same reserved_ip_ranges which means if the deployment_group has been used with reserved_ip_ranges: [a, b, c], using it with [a, b] or [d, e] is disallowed. Note: we only support up to 5 deployment groups(not including 'default').", + "type": "string" + }, + "deployedIndexAuthConfig": { + "description": "Optional. If set, the authentication is enabled for the private endpoint.", + "$ref": "GoogleCloudAiplatformV1beta1DeployedIndexAuthConfig" + }, + "automaticResources": { + "$ref": "GoogleCloudAiplatformV1beta1AutomaticResources", + "description": "Optional. A description of resources that the DeployedIndex uses, which to large degree are decided by Vertex AI, and optionally allows only a modest additional configuration. If min_replica_count is not set, the default value is 2 (we don't provide SLA when min_replica_count=1). If max_replica_count is not set, the default value is min_replica_count. The max allowed replica count is 1000." + }, + "displayName": { + "description": "The display name of the DeployedIndex. If not provided upon creation, the Index's display_name is used.", + "type": "string" + }, + "id": { + "description": "Required. The user specified ID of the DeployedIndex. The ID can be up to 128 characters long and must start with a letter and only contain letters, numbers, and underscores. The ID must be unique within the project it is created in.", + "type": "string" + }, + "createTime": { + "format": "google-datetime", + "description": "Output only. Timestamp when the DeployedIndex was created.", + "type": "string", + "readOnly": true + }, + "indexSyncTime": { + "readOnly": true, + "type": "string", + "description": "Output only. The DeployedIndex may depend on various data on its original Index. Additionally when certain changes to the original Index are being done (e.g. when what the Index contains is being changed) the DeployedIndex may be asynchronously updated in the background to reflect these changes. If this timestamp's value is at least the Index.update_time of the original Index, it means that this DeployedIndex and the original Index are in sync. If this timestamp is older, then to see which updates this DeployedIndex already contains (and which it does not), one must list the operations that are running on the original Index. Only the successfully completed Operations with update_time equal or before this sync time are contained in this DeployedIndex.", + "format": "google-datetime" + }, + "enableAccessLogging": { + "type": "boolean", + "description": "Optional. If true, private endpoint's access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each MatchRequest. Note that logs may incur a cost, especially if the deployed index receives a high queries per second rate (QPS). Estimate your costs before enabling this option." + }, + "dedicatedResources": { + "description": "Optional. A description of resources that are dedicated to the DeployedIndex, and that need a higher degree of manual configuration. The field min_replica_count must be set to a value strictly greater than 0, or else validation will fail. We don't provide SLA when min_replica_count=1. If max_replica_count is not set, the default value is min_replica_count. The max allowed replica count is 1000. Available machine types for SMALL shard: e2-standard-2 and all machine types available for MEDIUM and LARGE shard. Available machine types for MEDIUM shard: e2-standard-16 and all machine types available for LARGE shard. Available machine types for LARGE shard: e2-highmem-16, n2d-standard-32. n1-standard-16 and n1-standard-32 are still available, but we recommend e2-standard-16 and e2-highmem-16 for cost efficiency.", + "$ref": "GoogleCloudAiplatformV1beta1DedicatedResources" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1DeployedIndex", + "description": "A deployment of an Index. IndexEndpoints contain one or more DeployedIndexes." + }, + "GoogleCloudAiplatformV1beta1StudySpecStudyStoppingConfig": { + "description": "The configuration (stopping conditions) for automated stopping of a Study. Conditions include trial budgets, time budgets, and convergence detection.", + "id": "GoogleCloudAiplatformV1beta1StudySpecStudyStoppingConfig", + "properties": { + "maximumRuntimeConstraint": { + "description": "If the specified time or duration has passed, stop the study.", + "$ref": "GoogleCloudAiplatformV1beta1StudyTimeConstraint" + }, + "maxNumTrialsNoProgress": { + "description": "If the objective value has not improved for this many consecutive trials, stop the study. WARNING: Effective only for single-objective studies.", + "format": "int32", + "type": "integer" + }, + "minNumTrials": { + "type": "integer", + "format": "int32", + "description": "If there are fewer than this many COMPLETED trials, do not stop the study." + }, + "minimumRuntimeConstraint": { + "$ref": "GoogleCloudAiplatformV1beta1StudyTimeConstraint", + "description": "Each \"stopping rule\" in this proto specifies an \"if\" condition. Before Vizier would generate a new suggestion, it first checks each specified stopping rule, from top to bottom in this list. Note that the first few rules (e.g. minimum_runtime_constraint, min_num_trials) will prevent other stopping rules from being evaluated until they are met. For example, setting `min_num_trials=5` and `always_stop_after= 1 hour` means that the Study will ONLY stop after it has 5 COMPLETED trials, even if more than an hour has passed since its creation. It follows the first applicable rule (whose \"if\" condition is satisfied) to make a stopping decision. If none of the specified rules are applicable, then Vizier decides that the study should not stop. If Vizier decides that the study should stop, the study enters STOPPING state (or STOPPING_ASAP if should_stop_asap = true). IMPORTANT: The automatic study state transition happens precisely as described above; that is, deleting trials or updating StudyConfig NEVER automatically moves the study state back to ACTIVE. If you want to _resume_ a Study that was stopped, 1) change the stopping conditions if necessary, 2) activate the study, and then 3) ask for suggestions. If the specified time or duration has not passed, do not stop the study." + }, + "maxDurationNoProgress": { + "description": "If the objective value has not improved for this much time, stop the study. WARNING: Effective only for single-objective studies.", + "type": "string", + "format": "google-duration" + }, + "shouldStopAsap": { + "type": "boolean", + "description": "If true, a Study enters STOPPING_ASAP whenever it would normally enters STOPPING state. The bottom line is: set to true if you want to interrupt on-going evaluations of Trials as soon as the study stopping condition is met. (Please see Study.State documentation for the source of truth)." + }, + "maxNumTrials": { + "type": "integer", + "description": "If there are more than this many trials, stop the study.", + "format": "int32" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ImportExtensionOperationMetadata": { + "description": "Details of ExtensionRegistryService.ImportExtension operation.", + "properties": { + "genericMetadata": { + "description": "The common part of the operation metadata.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "id": "GoogleCloudAiplatformV1beta1ImportExtensionOperationMetadata", + "type": "object" + }, + "CloudAiLargeModelsVisionVideo": { + "properties": { + "uri": { + "type": "string", + "description": "Path to another storage (typically Google Cloud Storage)." + }, + "video": { + "format": "byte", + "type": "string", + "description": "Raw bytes." + } + }, + "description": "Video", + "id": "CloudAiLargeModelsVisionVideo", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSlice": { + "id": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSlice", + "properties": { + "sliceSpec": { + "description": "Output only. Specification for how the data was sliced.", + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpec" + }, + "dimension": { + "readOnly": true, + "description": "Output only. The dimension of the slice. Well-known dimensions are: * `annotationSpec`: This slice is on the test data that has either ground truth or prediction with AnnotationSpec.display_name equals to value. * `slice`: This slice is a user customized slice defined by its SliceSpec.", + "type": "string" + }, + "value": { + "type": "string", + "readOnly": true, + "description": "Output only. The value of the dimension in this slice." + } + }, + "description": "Definition of a slice.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringSchemaFieldSchema": { + "type": "object", + "description": "Schema field definition.", + "properties": { + "repeated": { + "type": "boolean", + "description": "Describes if the schema field is an array of given data type." + }, + "name": { + "description": "Field name.", + "type": "string" + }, + "dataType": { + "description": "Supported data types are: `float` `integer` `boolean` `string` `categorical`", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringSchemaFieldSchema" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrixAnnotationSpecRef": { + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrixAnnotationSpecRef", + "properties": { + "displayName": { + "description": "Display name of the AnnotationSpec.", + "type": "string" + }, + "id": { + "type": "string", + "description": "ID of the AnnotationSpec." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1Neighbor": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1Neighbor", + "description": "Neighbors for example-based explanations.", + "properties": { + "neighborId": { + "type": "string", + "description": "Output only. The neighbor id.", + "readOnly": true + }, + "neighborDistance": { + "type": "number", + "format": "double", + "readOnly": true, + "description": "Output only. The neighbor distance." + } + } + }, + "GoogleCloudAiplatformV1beta1TensorboardRun": { + "id": "GoogleCloudAiplatformV1beta1TensorboardRun", + "description": "TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc", + "properties": { + "displayName": { + "description": "Required. User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.", + "type": "string" + }, + "labels": { + "description": "The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", + "additionalProperties": { + "type": "string" + }, + "type": "object" + }, + "createTime": { + "format": "google-datetime", + "type": "string", + "readOnly": true, + "description": "Output only. Timestamp when this TensorboardRun was created." + }, + "name": { + "type": "string", + "readOnly": true, + "description": "Output only. Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`" + }, + "description": { + "description": "Description of this TensorboardRun.", + "type": "string" + }, + "etag": { + "type": "string", + "description": "Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + }, + "updateTime": { + "format": "google-datetime", + "readOnly": true, + "type": "string", + "description": "Output only. Timestamp when this TensorboardRun was last updated." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1NfsMount": { + "type": "object", + "properties": { + "mountPoint": { + "type": "string", + "description": "Required. Destination mount path. The NFS will be mounted for the user under /mnt/nfs/" + }, + "path": { + "type": "string", + "description": "Required. Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of `server:path`" + }, + "server": { + "type": "string", + "description": "Required. IP address of the NFS server." + } + }, + "description": "Represents a mount configuration for Network File System (NFS) to mount.", + "id": "GoogleCloudAiplatformV1beta1NfsMount" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionMetricsConfidenceMetrics": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionMetricsConfidenceMetrics", + "properties": { + "f1Score": { + "format": "float", + "type": "number", + "description": "Output only. The harmonic mean of recall and precision." + }, + "precision": { + "type": "number", + "format": "float", + "description": "Output only. Precision for the given confidence threshold." + }, + "recall": { + "type": "number", + "description": "Output only. Recall for the given confidence threshold.", + "format": "float" + }, + "confidenceThreshold": { + "format": "float", + "description": "Output only. The confidence threshold value used to compute the metrics.", + "type": "number" + } + }, + "description": "Metrics for a single confidence threshold." + }, + "GoogleCloudAiplatformV1beta1FunctionResponse": { + "type": "object", + "description": "The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction.", + "properties": { + "name": { + "type": "string", + "description": "Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name]." + }, + "response": { + "description": "Required. The function response in JSON object format.", + "additionalProperties": { + "type": "any", + "description": "Properties of the object." + }, + "type": "object" + } + }, + "id": "GoogleCloudAiplatformV1beta1FunctionResponse" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsForecastingEvaluationMetrics": { + "type": "object", + "description": "Metrics for forecasting evaluation results.", + "properties": { + "rSquared": { + "format": "float", + "description": "Coefficient of determination as Pearson correlation coefficient. Undefined when ground truth or predictions are constant or near constant.", + "type": "number" + }, + "rootMeanSquaredError": { + "description": "Root Mean Squared Error (RMSE).", + "format": "float", + "type": "number" + }, + "rootMeanSquaredLogError": { + "type": "number", + "description": "Root mean squared log error. Undefined when there are negative ground truth values or predictions.", + "format": "float" + }, + "quantileMetrics": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsForecastingEvaluationMetricsQuantileMetricsEntry" + }, + "description": "The quantile metrics entries for each quantile." + }, + "meanAbsoluteError": { + "format": "float", + "description": "Mean Absolute Error (MAE).", + "type": "number" + }, + "meanAbsolutePercentageError": { + "description": "Mean absolute percentage error. Infinity when there are zeros in the ground truth.", + "format": "float", + "type": "number" + }, + "rootMeanSquaredPercentageError": { + "format": "float", + "type": "number", + "description": "Root Mean Square Percentage Error. Square root of MSPE. Undefined/imaginary when MSPE is negative." + }, + "weightedAbsolutePercentageError": { + "type": "number", + "format": "float", + "description": "Weighted Absolute Percentage Error. Does not use weights, this is just what the metric is called. Undefined if actual values sum to zero. Will be very large if actual values sum to a very small number." + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsForecastingEvaluationMetrics" + }, + "GoogleCloudAiplatformV1beta1MigrateResourceRequest": { + "description": "Config of migrating one resource from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI.", + "properties": { + "migrateDataLabelingDatasetConfig": { + "$ref": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateDataLabelingDatasetConfig", + "description": "Config for migrating Dataset in datalabeling.googleapis.com to Vertex AI's Dataset." + }, + "migrateMlEngineModelVersionConfig": { + "description": "Config for migrating Version in ml.googleapis.com to Vertex AI's Model.", + "$ref": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateMlEngineModelVersionConfig" + }, + "migrateAutomlModelConfig": { + "description": "Config for migrating Model in automl.googleapis.com to Vertex AI's Model.", + "$ref": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateAutomlModelConfig" + }, + "migrateAutomlDatasetConfig": { + "description": "Config for migrating Dataset in automl.googleapis.com to Vertex AI's Dataset.", + "$ref": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateAutomlDatasetConfig" + } + }, + "id": "GoogleCloudAiplatformV1beta1MigrateResourceRequest", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ExtensionManifest": { + "id": "GoogleCloudAiplatformV1beta1ExtensionManifest", + "properties": { + "authConfig": { + "description": "Required. Immutable. Type of auth supported by this extension.", + "$ref": "GoogleCloudAiplatformV1beta1AuthConfig" + }, + "apiSpec": { + "$ref": "GoogleCloudAiplatformV1beta1ExtensionManifestApiSpec", + "description": "Required. Immutable. The API specification shown to the LLM." + }, + "description": { + "type": "string", + "description": "Required. The natural language description shown to the LLM. It should describe the usage of the extension, and is essential for the LLM to perform reasoning. e.g., if the extension is a data store, you can let the LLM know what data it contains." + }, + "name": { + "type": "string", + "description": "Required. Extension name shown to the LLM. The name can be up to 128 characters long." + } + }, + "description": "Manifest spec of an Extension needed for runtime execution.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1NotebookExecutionJobDataformRepositorySource": { + "id": "GoogleCloudAiplatformV1beta1NotebookExecutionJobDataformRepositorySource", + "type": "object", + "properties": { + "dataformRepositoryResourceName": { + "description": "The resource name of the Dataform Repository. Format: `projects/{project_id}/locations/{location}/repositories/{repository_id}`", + "type": "string" + }, + "commitSha": { + "description": "The commit SHA to read repository with. If unset, the file will be read at HEAD.", + "type": "string" + } + }, + "description": "The Dataform Repository containing the input notebook." + }, + "GoogleCloudAiplatformV1beta1UploadRagFileRequest": { + "properties": { + "ragFile": { + "description": "Required. The RagFile to upload.", + "$ref": "GoogleCloudAiplatformV1beta1RagFile" + }, + "uploadRagFileConfig": { + "$ref": "GoogleCloudAiplatformV1beta1UploadRagFileConfig", + "description": "Required. The config for the RagFiles to be uploaded into the RagCorpus. VertexRagDataService.UploadRagFile." + } + }, + "description": "Request message for VertexRagDataService.UploadRagFile.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1UploadRagFileRequest" + }, + "GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesRequestStatsAnomaliesObjective": { + "description": "Stats requested for specific objective.", + "id": "GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesRequestStatsAnomaliesObjective", + "type": "object", + "properties": { + "topFeatureCount": { + "type": "integer", + "description": "If set, all attribution scores between SearchModelDeploymentMonitoringStatsAnomaliesRequest.start_time and SearchModelDeploymentMonitoringStatsAnomaliesRequest.end_time are fetched, and page token doesn't take effect in this case. Only used to retrieve attribution score for the top Features which has the highest attribution score in the latest monitoring run.", + "format": "int32" + }, + "type": { + "enum": [ + "MODEL_DEPLOYMENT_MONITORING_OBJECTIVE_TYPE_UNSPECIFIED", + "RAW_FEATURE_SKEW", + "RAW_FEATURE_DRIFT", + "FEATURE_ATTRIBUTION_SKEW", + "FEATURE_ATTRIBUTION_DRIFT" + ], + "type": "string", + "enumDescriptions": [ + "Default value, should not be set.", + "Raw feature values' stats to detect skew between Training-Prediction datasets.", + "Raw feature values' stats to detect drift between Serving-Prediction datasets.", + "Feature attribution scores to detect skew between Training-Prediction datasets.", + "Feature attribution scores to detect skew between Prediction datasets collected within different time windows." + ] + } + } + }, + "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeploy": { + "id": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeploy", + "type": "object", + "description": "Model metadata that is needed for UploadModel or DeployModel/CreateEndpoint requests.", + "properties": { + "publicArtifactUri": { + "description": "Optional. The signed URI for ephemeral Cloud Storage access to model artifact.", + "type": "string" + }, + "deployMetadata": { + "description": "Optional. Metadata information about this deployment config.", + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployDeployMetadata" + }, + "containerSpec": { + "$ref": "GoogleCloudAiplatformV1beta1ModelContainerSpec", + "description": "Optional. The specification of the container that is to be used when deploying this Model in Vertex AI. Not present for Large Models." + }, + "deployTaskName": { + "type": "string", + "description": "Optional. The name of the deploy task (e.g., \"text to image generation\")." + }, + "artifactUri": { + "type": "string", + "description": "Optional. The path to the directory containing the Model artifact and any of its supporting files." + }, + "dedicatedResources": { + "description": "A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.", + "$ref": "GoogleCloudAiplatformV1beta1DedicatedResources" + }, + "title": { + "description": "Required. The title of the regional resource reference.", + "type": "string" + }, + "modelDisplayName": { + "type": "string", + "description": "Optional. Default model display name." + }, + "largeModelReference": { + "$ref": "GoogleCloudAiplatformV1beta1LargeModelReference", + "description": "Optional. Large model reference. When this is set, model_artifact_spec is not needed." + }, + "sharedResources": { + "type": "string", + "description": "The resource name of the shared DeploymentResourcePool to deploy on. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`" + }, + "automaticResources": { + "$ref": "GoogleCloudAiplatformV1beta1AutomaticResources", + "description": "A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration." + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationNumericTransformation": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationNumericTransformation", + "type": "object", + "properties": { + "columnName": { + "type": "string" + } + }, + "description": "Training pipeline will perform following transformation functions. * The value converted to float32. * The z_score of the value. * log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value." + }, + "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityInstance": { + "description": "Spec for pairwise summarization quality instance.", + "properties": { + "prediction": { + "type": "string", + "description": "Required. Output of the candidate model." + }, + "context": { + "description": "Required. Text to be summarized.", + "type": "string" + }, + "instruction": { + "description": "Required. Summarization prompt for LLM.", + "type": "string" + }, + "reference": { + "description": "Optional. Ground truth used to compare against the prediction.", + "type": "string" + }, + "baselinePrediction": { + "description": "Required. Output of the baseline model.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityInstance" + }, + "GoogleCloudAiplatformV1beta1ReportRuntimeEventRequest": { + "id": "GoogleCloudAiplatformV1beta1ReportRuntimeEventRequest", + "type": "object", + "properties": { + "eventType": { + "enum": [ + "EVENT_TYPE_UNSPECIFIED", + "HEARTBEAT", + "IDLE" + ], + "enumDescriptions": [ + "Unspecified.", + "Used for readiness reporting.", + "Used for idle reporting." + ], + "type": "string", + "description": "Required. The type of the event." + }, + "eventDetails": { + "description": "Optional. The details of the request for debug.", + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "internalOsServiceStateInstance": { + "type": "array", + "description": "The details of the internal os service states.", + "deprecated": true, + "items": { + "$ref": "GoogleCloudAiplatformV1beta1InternalOsServiceStateInstance" + } + }, + "internalOsServiceStateInstances": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1InternalOsServiceStateInstance" + }, + "description": "Optional. The details of the internal os service states.", + "type": "array" + }, + "vmToken": { + "description": "Required. The VM identity token (a JWT) for authenticating the VM. https://cloud.google.com/compute/docs/instances/verifying-instance-identity", + "type": "string" + } + }, + "description": "Request message for NotebookInternalService.ReportRuntimeEvent." + }, + "GoogleCloudAiplatformV1beta1ReportRuntimeEventResponse": { + "description": "Response message for NotebookInternalService.ReportRuntimeEvent.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ReportRuntimeEventResponse", + "properties": { + "idleShutdownMessage": { + "description": "If the idle shutdown is blocked by CP, CP will send the block message. Otherwise, this field is not set.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1ListPersistentResourcesResponse": { + "id": "GoogleCloudAiplatformV1beta1ListPersistentResourcesResponse", + "description": "Response message for PersistentResourceService.ListPersistentResources", + "type": "object", + "properties": { + "nextPageToken": { + "description": "A token to retrieve next page of results. Pass to ListPersistentResourcesRequest.page_token to obtain that page.", + "type": "string" + }, + "persistentResources": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1PersistentResource" + } + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaPredictInstanceTextClassificationPredictionInstance": { + "description": "Prediction input format for Text Classification.", + "properties": { + "mimeType": { + "description": "The MIME type of the text snippet. The supported MIME types are listed below. - text/plain", + "type": "string" + }, + "content": { + "description": "The text snippet to make the predictions on.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaPredictInstanceTextClassificationPredictionInstance", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ListFeatureViewSyncsResponse": { + "id": "GoogleCloudAiplatformV1beta1ListFeatureViewSyncsResponse", + "description": "Response message for FeatureOnlineStoreAdminService.ListFeatureViewSyncs.", + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token, which can be sent as ListFeatureViewSyncsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages." + }, + "featureViewSyncs": { + "description": "The FeatureViewSyncs matching the request.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureViewSync" + }, + "type": "array" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FindNeighborsResponseNeighbor": { + "id": "GoogleCloudAiplatformV1beta1FindNeighborsResponseNeighbor", + "properties": { + "datapoint": { + "description": "The datapoint of the neighbor. Note that full datapoints are returned only when \"return_full_datapoint\" is set to true. Otherwise, only the \"datapoint_id\" and \"crowding_tag\" fields are populated.", + "$ref": "GoogleCloudAiplatformV1beta1IndexDatapoint" + }, + "sparseDistance": { + "format": "double", + "description": "The distance between the neighbor and the query sparse_embedding.", + "type": "number" + }, + "distance": { + "description": "The distance between the neighbor and the dense embedding query.", + "format": "double", + "type": "number" + } + }, + "description": "A neighbor of the query vector.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1PredictSchemata": { + "id": "GoogleCloudAiplatformV1beta1PredictSchemata", + "description": "Contains the schemata used in Model's predictions and explanations via PredictionService.Predict, PredictionService.Explain and BatchPredictionJob.", + "type": "object", + "properties": { + "instanceSchemaUri": { + "type": "string", + "description": "Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single instance, which are used in PredictRequest.instances, ExplainRequest.instances and BatchPredictionJob.input_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access." + }, + "parametersSchemaUri": { + "type": "string", + "description": "Immutable. Points to a YAML file stored on Google Cloud Storage describing the parameters of prediction and explanation via PredictRequest.parameters, ExplainRequest.parameters and BatchPredictionJob.model_parameters. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no parameters are supported, then it is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access." + }, + "predictionSchemaUri": { + "description": "Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single prediction produced by this Model, which are returned via PredictResponse.predictions, ExplainResponse.explanations, and BatchPredictionJob.output_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1StopTrialRequest": { + "description": "Request message for VizierService.StopTrial.", + "id": "GoogleCloudAiplatformV1beta1StopTrialRequest", + "type": "object", + "properties": {} + }, + "GoogleCloudAiplatformV1beta1ListTensorboardRunsResponse": { + "properties": { + "tensorboardRuns": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardRun" + }, + "description": "The TensorboardRuns mathching the request." + }, + "nextPageToken": { + "description": "A token, which can be sent as ListTensorboardRunsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1ListTensorboardRunsResponse", + "description": "Response message for TensorboardService.ListTensorboardRuns.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ToolUseExample": { + "properties": { + "responseParams": { + "additionalProperties": { + "description": "Properties of the object.", + "type": "any" + }, + "description": "Response parameters generated by this tool.", + "type": "object" + }, + "requestParams": { + "additionalProperties": { + "type": "any", + "description": "Properties of the object." + }, + "description": "Request parameters used for executing this tool.", + "type": "object" + }, + "functionName": { + "type": "string", + "description": "Function name to call." + }, + "extensionOperation": { + "$ref": "GoogleCloudAiplatformV1beta1ToolUseExampleExtensionOperation", + "description": "Extension operation to call." + }, + "displayName": { + "description": "Required. The display name for example.", + "type": "string" + }, + "responseSummary": { + "type": "string", + "description": "Summary of the tool response to the user query." + }, + "query": { + "description": "Required. Query that should be routed to this tool.", + "type": "string" + } + }, + "type": "object", + "description": "A single example of the tool usage.", + "id": "GoogleCloudAiplatformV1beta1ToolUseExample" + }, + "CloudAiLargeModelsVisionRaiInfo": { + "properties": { + "detectedLabels": { + "items": { + "$ref": "CloudAiLargeModelsVisionRaiInfoDetectedLabels" + }, + "type": "array", + "description": "The list of detected labels for different rai categories." + }, + "raiCategories": { + "type": "array", + "description": "List of rai categories' information to return", + "items": { + "type": "string" + } + }, + "modelName": { + "type": "string", + "description": "The model name used to indexing into the RaiFilterConfig map. Would either be one of imagegeneration@002-006, imagen-3.0-... api endpoint names, or internal names used for mapping to different filter configs (genselfie, ai_watermark) than its api endpoint." + }, + "scores": { + "items": { + "format": "float", + "type": "number" + }, + "description": "List of rai scores mapping to the rai categories. Rounded to 1 decimal place.", + "type": "array" + } + }, + "type": "object", + "id": "CloudAiLargeModelsVisionRaiInfo" + }, + "GoogleCloudAiplatformV1beta1PublisherModelCallToActionViewRestApi": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionViewRestApi", + "description": "Rest API docs.", + "properties": { + "title": { + "type": "string", + "description": "Required. The title of the view rest API." + }, + "documentations": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelDocumentation" + }, + "description": "Required." + } + } + }, + "GoogleCloudAiplatformV1beta1AddExecutionEventsRequest": { + "id": "GoogleCloudAiplatformV1beta1AddExecutionEventsRequest", + "description": "Request message for MetadataService.AddExecutionEvents.", + "properties": { + "events": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Event" + }, + "description": "The Events to create and add." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaPredictInstanceTextExtractionPredictionInstance": { + "description": "Prediction input format for Text Extraction.", + "id": "GoogleCloudAiplatformV1beta1SchemaPredictInstanceTextExtractionPredictionInstance", + "type": "object", + "properties": { + "key": { + "description": "This field is only used for batch prediction. If a key is provided, the batch prediction result will by mapped to this key. If omitted, then the batch prediction result will contain the entire input instance. Vertex AI will not check if keys in the request are duplicates, so it is up to the caller to ensure the keys are unique.", + "type": "string" + }, + "content": { + "type": "string", + "description": "The text snippet to make the predictions on." + }, + "mimeType": { + "type": "string", + "description": "The MIME type of the text snippet. The supported MIME types are listed below. - text/plain" + } + } + }, + "GoogleCloudAiplatformV1beta1AssignNotebookRuntimeRequest": { + "properties": { + "notebookRuntime": { + "$ref": "GoogleCloudAiplatformV1beta1NotebookRuntime", + "description": "Required. Provide runtime specific information (e.g. runtime owner, notebook id) used for NotebookRuntime assignment." + }, + "notebookRuntimeTemplate": { + "description": "Required. The resource name of the NotebookRuntimeTemplate based on which a NotebookRuntime will be assigned (reuse or create a new one).", + "type": "string" + }, + "notebookRuntimeId": { + "type": "string", + "description": "Optional. User specified ID for the notebook runtime." + } + }, + "description": "Request message for NotebookService.AssignNotebookRuntime.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1AssignNotebookRuntimeRequest" + }, + "GoogleCloudAiplatformV1beta1ExportTensorboardTimeSeriesDataRequest": { + "type": "object", + "description": "Request message for TensorboardService.ExportTensorboardTimeSeriesData.", + "id": "GoogleCloudAiplatformV1beta1ExportTensorboardTimeSeriesDataRequest", + "properties": { + "orderBy": { + "description": "Field to use to sort the TensorboardTimeSeries' data. By default, TensorboardTimeSeries' data is returned in a pseudo random order.", + "type": "string" + }, + "pageToken": { + "description": "A page token, received from a previous ExportTensorboardTimeSeriesData call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to ExportTensorboardTimeSeriesData must match the call that provided the page token.", + "type": "string" + }, + "pageSize": { + "description": "The maximum number of data points to return per page. The default page_size is 1000. Values must be between 1 and 10000. Values above 10000 are coerced to 10000.", + "type": "integer", + "format": "int32" + }, + "filter": { + "description": "Exports the TensorboardTimeSeries' data that match the filter expression.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1CreatePersistentResourceOperationMetadata": { + "type": "object", + "description": "Details of operations that perform create PersistentResource.", + "id": "GoogleCloudAiplatformV1beta1CreatePersistentResourceOperationMetadata", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "Operation metadata for PersistentResource." + }, + "progressMessage": { + "type": "string", + "description": "Progress Message for Create LRO" + } + } + }, + "GoogleCloudAiplatformV1beta1CancelBatchPredictionJobRequest": { + "description": "Request message for JobService.CancelBatchPredictionJob.", + "id": "GoogleCloudAiplatformV1beta1CancelBatchPredictionJobRequest", + "properties": {}, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomalies": { + "properties": { + "objective": { + "description": "Model Monitoring Objective those stats and anomalies belonging to.", + "enumDescriptions": [ + "Default value, should not be set.", + "Raw feature values' stats to detect skew between Training-Prediction datasets.", + "Raw feature values' stats to detect drift between Serving-Prediction datasets.", + "Feature attribution scores to detect skew between Training-Prediction datasets.", + "Feature attribution scores to detect skew between Prediction datasets collected within different time windows." + ], + "type": "string", + "enum": [ + "MODEL_DEPLOYMENT_MONITORING_OBJECTIVE_TYPE_UNSPECIFIED", + "RAW_FEATURE_SKEW", + "RAW_FEATURE_DRIFT", + "FEATURE_ATTRIBUTION_SKEW", + "FEATURE_ATTRIBUTION_DRIFT" + ] + }, + "deployedModelId": { + "description": "Deployed Model ID.", + "type": "string" + }, + "featureStats": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomaliesFeatureHistoricStatsAnomalies" + }, + "description": "A list of historical Stats and Anomalies generated for all Features.", + "type": "array" + }, + "anomalyCount": { + "type": "integer", + "description": "Number of anomalies within all stats.", + "format": "int32" + } + }, + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomalies", + "type": "object", + "description": "Statistics and anomalies generated by Model Monitoring." + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextArrayTransformation": { + "type": "object", + "description": "Treats the column as text array and performs following transformation functions. * Concatenate all text values in the array into a single text value using a space (\" \") as a delimiter, and then treat the result as a single text value. Apply the transformations for Text columns. * Empty arrays treated as an empty text.", + "properties": { + "columnName": { + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextArrayTransformation" + }, + "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponse": { + "id": "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponse", + "properties": { + "protoStruct": { + "type": "object", + "additionalProperties": { + "description": "Properties of the object.", + "type": "any" + }, + "description": "Feature values in proto Struct format." + }, + "keyValues": { + "$ref": "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponseFeatureNameValuePairList", + "description": "Feature values in KeyValue format." + }, + "dataKey": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDataKey", + "description": "The data key associated with this response. Will only be populated for FeatureOnlineStoreService.StreamingFetchFeatureValues RPCs." + } + }, + "type": "object", + "description": "Response message for FeatureOnlineStoreService.FetchFeatureValues" + }, + "GoogleCloudAiplatformV1beta1Probe": { + "id": "GoogleCloudAiplatformV1beta1Probe", + "type": "object", + "description": "Probe describes a health check to be performed against a container to determine whether it is alive or ready to receive traffic.", + "properties": { + "exec": { + "description": "ExecAction probes the health of a container by executing a command.", + "$ref": "GoogleCloudAiplatformV1beta1ProbeExecAction" + }, + "periodSeconds": { + "format": "int32", + "description": "How often (in seconds) to perform the probe. Default to 10 seconds. Minimum value is 1. Must be less than timeout_seconds. Maps to Kubernetes probe argument 'periodSeconds'.", + "type": "integer" + }, + "timeoutSeconds": { + "description": "Number of seconds after which the probe times out. Defaults to 1 second. Minimum value is 1. Must be greater or equal to period_seconds. Maps to Kubernetes probe argument 'timeoutSeconds'.", + "type": "integer", + "format": "int32" + } + } + }, + "GoogleCloudAiplatformV1beta1UpdateFeatureOperationMetadata": { + "description": "Details of operations that perform update Feature.", + "id": "GoogleCloudAiplatformV1beta1UpdateFeatureOperationMetadata", + "type": "object", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "Operation metadata for Feature Update." + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalTransformation": { + "properties": { + "columnName": { + "type": "string" + } + }, + "description": "Training pipeline will perform following transformation functions. * The categorical string as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. * Categories that appear less than 5 times in the training dataset are treated as the \"unknown\" category. The \"unknown\" category gets its own special lookup index and resulting embedding.", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalTransformation", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1Int64Array": { + "id": "GoogleCloudAiplatformV1beta1Int64Array", + "properties": { + "values": { + "description": "A list of int64 values.", + "items": { + "format": "int64", + "type": "string" + }, + "type": "array" + } + }, + "type": "object", + "description": "A list of int64 values." + }, + "GoogleCloudAiplatformV1beta1RagContexts": { + "properties": { + "contexts": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1RagContextsContext" + }, + "type": "array", + "description": "All its contexts." + } + }, + "description": "Relevant contexts for one query.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1RagContexts" + }, + "GoogleCloudAiplatformV1beta1CreateFeatureOperationMetadata": { + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "Operation metadata for Feature." + } + }, + "id": "GoogleCloudAiplatformV1beta1CreateFeatureOperationMetadata", + "description": "Details of operations that perform create Feature.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1InputDataConfig": { + "description": "Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model.", + "properties": { + "fractionSplit": { + "description": "Split based on fractions defining the size of each set.", + "$ref": "GoogleCloudAiplatformV1beta1FractionSplit" + }, + "gcsDestination": { + "$ref": "GoogleCloudAiplatformV1beta1GcsDestination", + "description": "The Cloud Storage location where the training data is to be written to. In the given directory a new directory is created with name: `dataset---` where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All training input data is written into that directory. The Vertex AI environment variables representing Cloud Storage data URIs are represented in the Cloud Storage wildcard format to support sharded data. e.g.: \"gs://.../training-*.jsonl\" * AIP_DATA_FORMAT = \"jsonl\" for non-tabular data, \"csv\" for tabular data * AIP_TRAINING_DATA_URI = \"gcs_destination/dataset---/training-*.${AIP_DATA_FORMAT}\" * AIP_VALIDATION_DATA_URI = \"gcs_destination/dataset---/validation-*.${AIP_DATA_FORMAT}\" * AIP_TEST_DATA_URI = \"gcs_destination/dataset---/test-*.${AIP_DATA_FORMAT}\"" + }, + "filterSplit": { + "description": "Split based on the provided filters for each set.", + "$ref": "GoogleCloudAiplatformV1beta1FilterSplit" + }, + "stratifiedSplit": { + "description": "Supported only for tabular Datasets. Split based on the distribution of the specified column.", + "$ref": "GoogleCloudAiplatformV1beta1StratifiedSplit" + }, + "bigqueryDestination": { + "$ref": "GoogleCloudAiplatformV1beta1BigQueryDestination", + "description": "Only applicable to custom training with tabular Dataset with BigQuery source. The BigQuery project location where the training data is to be written to. In the given project a new dataset is created with name `dataset___` where timestamp is in YYYY_MM_DDThh_mm_ss_sssZ format. All training input data is written into that dataset. In the dataset three tables are created, `training`, `validation` and `test`. * AIP_DATA_FORMAT = \"bigquery\". * AIP_TRAINING_DATA_URI = \"bigquery_destination.dataset___.training\" * AIP_VALIDATION_DATA_URI = \"bigquery_destination.dataset___.validation\" * AIP_TEST_DATA_URI = \"bigquery_destination.dataset___.test\"" + }, + "savedQueryId": { + "description": "Only applicable to Datasets that have SavedQueries. The ID of a SavedQuery (annotation set) under the Dataset specified by dataset_id used for filtering Annotations for training. Only Annotations that are associated with this SavedQuery are used in respectively training. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both saved_query_id and annotations_filter. Only one of saved_query_id and annotation_schema_uri should be specified as both of them represent the same thing: problem type.", + "type": "string" + }, + "annotationsFilter": { + "description": "Applicable only to Datasets that have DataItems and Annotations. A filter on Annotations of the Dataset. Only Annotations that both match this filter and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on (for the auto-assigned that role is decided by Vertex AI). A filter with same syntax as the one used in ListAnnotations may be used, but note here it filters across all Annotations of the Dataset, and not just within a single DataItem.", + "type": "string" + }, + "datasetId": { + "type": "string", + "description": "Required. The ID of the Dataset in the same Project and Location which data will be used to train the Model. The Dataset must use schema compatible with Model being trained, and what is compatible should be described in the used TrainingPipeline's training_task_definition. For tabular Datasets, all their data is exported to training, to pick and choose from." + }, + "timestampSplit": { + "$ref": "GoogleCloudAiplatformV1beta1TimestampSplit", + "description": "Supported only for tabular Datasets. Split based on the timestamp of the input data pieces." + }, + "annotationSchemaUri": { + "description": "Applicable only to custom training with Datasets that have DataItems and Annotations. Cloud Storage URI that points to a YAML file describing the annotation schema. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/annotation/ , note that the chosen schema must be consistent with metadata of the Dataset specified by dataset_id. Only Annotations that both match this schema and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both annotations_filter and annotation_schema_uri.", + "type": "string" + }, + "persistMlUseAssignment": { + "type": "boolean", + "description": "Whether to persist the ML use assignment to data item system labels." + }, + "predefinedSplit": { + "$ref": "GoogleCloudAiplatformV1beta1PredefinedSplit", + "description": "Supported only for tabular Datasets. Split based on a predefined key." + } + }, + "id": "GoogleCloudAiplatformV1beta1InputDataConfig", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateResponse": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateResponse", + "properties": { + "shouldStop": { + "description": "True if the Trial should stop.", + "type": "boolean" + } + }, + "description": "Response message for VizierService.CheckTrialEarlyStoppingState." + }, + "GoogleCloudAiplatformV1beta1ExplanationSpec": { + "description": "Specification of Model explanation.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ExplanationSpec", + "properties": { + "parameters": { + "$ref": "GoogleCloudAiplatformV1beta1ExplanationParameters", + "description": "Required. Parameters that configure explaining of the Model's predictions." + }, + "metadata": { + "$ref": "GoogleCloudAiplatformV1beta1ExplanationMetadata", + "description": "Optional. Metadata describing the Model's input and output for explanation." + } + } + }, + "GoogleCloudAiplatformV1beta1SuggestTrialsResponse": { + "id": "GoogleCloudAiplatformV1beta1SuggestTrialsResponse", + "description": "Response message for VizierService.SuggestTrials.", + "type": "object", + "properties": { + "startTime": { + "format": "google-datetime", + "description": "The time at which the operation was started.", + "type": "string" + }, + "studyState": { + "enumDescriptions": [ + "The study state is unspecified.", + "The study is active.", + "The study is stopped due to an internal error.", + "The study is done when the service exhausts the parameter search space or max_trial_count is reached." + ], + "enum": [ + "STATE_UNSPECIFIED", + "ACTIVE", + "INACTIVE", + "COMPLETED" + ], + "type": "string", + "description": "The state of the Study." + }, + "trials": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Trial" + }, + "type": "array", + "description": "A list of Trials." + }, + "endTime": { + "type": "string", + "format": "google-datetime", + "description": "The time at which operation processing completed." + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputs": { + "type": "object", + "properties": { + "weightColumn": { + "type": "string", + "description": "Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1." + }, + "unavailableAtForecastColumns": { + "description": "Names of columns that are unavailable when a forecast is requested. This column contains information for the given entity (identified by the time_series_identifier_column) that is unknown before the forecast For example, actual weather on a given day.", + "type": "array", + "items": { + "type": "string" + } + }, + "forecastHorizon": { + "format": "int64", + "description": "The amount of time into the future for which forecasted values for the target are returned. Expressed in number of units defined by the `data_granularity` field.", + "type": "string" + }, + "trainBudgetMilliNodeHours": { + "type": "string", + "description": "Required. The train budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The training cost of the model will not exceed this budget. The final cost will be attempted to be close to the budget, though may end up being (even) noticeably smaller - at the backend's discretion. This especially may happen when further model training ceases to provide any improvements. If the budget is set to a value known to be insufficient to train a model for the given dataset, the training won't be attempted and will error. The train budget must be between 1,000 and 72,000 milli node hours, inclusive.", + "format": "int64" + }, + "contextWindow": { + "format": "int64", + "type": "string", + "description": "The amount of time into the past training and prediction data is used for model training and prediction respectively. Expressed in number of units defined by the `data_granularity` field." + }, + "holidayRegions": { + "items": { + "type": "string" + }, + "type": "array", + "description": "The geographical region based on which the holiday effect is applied in modeling by adding holiday categorical array feature that include all holidays matching the date. This option only allowed when data_granularity is day. By default, holiday effect modeling is disabled. To turn it on, specify the holiday region using this option." + }, + "exportEvaluatedDataItemsConfig": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig", + "description": "Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed." + }, + "enableProbabilisticInference": { + "type": "boolean", + "description": "If probabilistic inference is enabled, the model will fit a distribution that captures the uncertainty of a prediction. At inference time, the predictive distribution is used to make a point prediction that minimizes the optimization objective. For example, the mean of a predictive distribution is the point prediction that minimizes RMSE loss. If quantiles are specified, then the quantiles of the distribution are also returned. The optimization objective cannot be minimize-quantile-loss." + }, + "windowConfig": { + "description": "Config containing strategy for generating sliding windows.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionWindowConfig" + }, + "quantiles": { + "type": "array", + "items": { + "format": "double", + "type": "number" + }, + "description": "Quantiles to use for minimize-quantile-loss `optimization_objective`, or for probabilistic inference. Up to 5 quantiles are allowed of values between 0 and 1, exclusive. Required if the value of optimization_objective is minimize-quantile-loss. Represents the percent quantiles to use for that objective. Quantiles must be unique." + }, + "validationOptions": { + "description": "Validation options for the data validation component. The available options are: * \"fail-pipeline\" - default, will validate against the validation and fail the pipeline if it fails. * \"ignore-validation\" - ignore the results of the validation and continue", + "type": "string" + }, + "timeColumn": { + "type": "string", + "description": "The name of the column that identifies time order in the time series. This column must be available at forecast." + }, + "transformations": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation" + }, + "description": "Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using \".\" as the delimiter." + }, + "targetColumn": { + "description": "The name of the column that the Model is to predict values for. This column must be unavailable at forecast.", + "type": "string" + }, + "timeSeriesAttributeColumns": { + "type": "array", + "description": "Column names that should be used as attribute columns. The value of these columns does not vary as a function of time. For example, store ID or item color.", + "items": { + "type": "string" + } + }, + "availableAtForecastColumns": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Names of columns that are available and provided when a forecast is requested. These columns contain information for the given entity (identified by the time_series_identifier_column column) that is known at forecast. For example, predicted weather for a specific day." + }, + "additionalExperiments": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Additional experiment flags for the time series forcasting training." + }, + "optimizationObjective": { + "type": "string", + "description": "Objective function the model is optimizing towards. The training process creates a model that optimizes the value of the objective function over the validation set. The supported optimization objectives: * \"minimize-rmse\" (default) - Minimize root-mean-squared error (RMSE). * \"minimize-mae\" - Minimize mean-absolute error (MAE). * \"minimize-rmsle\" - Minimize root-mean-squared log error (RMSLE). * \"minimize-rmspe\" - Minimize root-mean-squared percentage error (RMSPE). * \"minimize-wape-mae\" - Minimize the combination of weighted absolute percentage error (WAPE) and mean-absolute-error (MAE). * \"minimize-quantile-loss\" - Minimize the quantile loss at the quantiles defined in `quantiles`. * \"minimize-mape\" - Minimize the mean absolute percentage error." + }, + "dataGranularity": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsGranularity", + "description": "Expected difference in time granularity between rows in the data." + }, + "timeSeriesIdentifierColumn": { + "type": "string", + "description": "The name of the column that identifies the time series." + }, + "hierarchyConfig": { + "description": "Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHierarchyConfig" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputs" + }, + "GoogleCloudAiplatformV1beta1ListHyperparameterTuningJobsResponse": { + "type": "object", + "description": "Response message for JobService.ListHyperparameterTuningJobs", + "properties": { + "hyperparameterTuningJobs": { + "description": "List of HyperparameterTuningJobs in the requested page. HyperparameterTuningJob.trials of the jobs will be not be returned.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1HyperparameterTuningJob" + } + }, + "nextPageToken": { + "description": "A token to retrieve the next page of results. Pass to ListHyperparameterTuningJobsRequest.page_token to obtain that page.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1ListHyperparameterTuningJobsResponse" + }, + "GoogleCloudAiplatformV1beta1ProbeExecAction": { + "type": "object", + "properties": { + "command": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Command is the command line to execute inside the container, the working directory for the command is root ('/') in the container's filesystem. The command is simply exec'd, it is not run inside a shell, so traditional shell instructions ('|', etc) won't work. To use a shell, you need to explicitly call out to that shell. Exit status of 0 is treated as live/healthy and non-zero is unhealthy." + } + }, + "description": "ExecAction specifies a command to execute.", + "id": "GoogleCloudAiplatformV1beta1ProbeExecAction" + }, + "GoogleCloudAiplatformV1beta1ListMetadataStoresResponse": { + "properties": { + "metadataStores": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1MetadataStore" + }, + "description": "The MetadataStores found for the Location.", + "type": "array" + }, + "nextPageToken": { + "type": "string", + "description": "A token, which can be sent as ListMetadataStoresRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ListMetadataStoresResponse", + "description": "Response message for MetadataService.ListMetadataStores." + }, + "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecCategoricalValueCondition": { + "properties": { + "values": { + "items": { + "type": "string" + }, + "description": "Required. Matches values of the parent parameter of 'CATEGORICAL' type. All values must exist in `categorical_value_spec` of parent parameter.", + "type": "array" + } + }, + "description": "Represents the spec to match categorical values from parent parameter.", + "id": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecCategoricalValueCondition", + "type": "object" + }, + "GoogleTypeExpr": { + "description": "Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: \"Summary size limit\" description: \"Determines if a summary is less than 100 chars\" expression: \"document.summary.size() \u003c 100\" Example (Equality): title: \"Requestor is owner\" description: \"Determines if requestor is the document owner\" expression: \"document.owner == request.auth.claims.email\" Example (Logic): title: \"Public documents\" description: \"Determine whether the document should be publicly visible\" expression: \"document.type != 'private' && document.type != 'internal'\" Example (Data Manipulation): title: \"Notification string\" description: \"Create a notification string with a timestamp.\" expression: \"'New message received at ' + string(document.create_time)\" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.", + "properties": { + "location": { + "description": "Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.", + "type": "string" + }, + "expression": { + "type": "string", + "description": "Textual representation of an expression in Common Expression Language syntax." + }, + "title": { + "type": "string", + "description": "Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression." + }, + "description": { + "type": "string", + "description": "Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI." + } + }, + "type": "object", + "id": "GoogleTypeExpr" + }, + "GoogleCloudAiplatformV1beta1ExportModelOperationMetadata": { + "description": "Details of ModelService.ExportModel operation.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ExportModelOperationMetadata", + "properties": { + "outputInfo": { + "$ref": "GoogleCloudAiplatformV1beta1ExportModelOperationMetadataOutputInfo", + "readOnly": true, + "description": "Output only. Information further describing the output of this Model export." + }, + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "The common part of the operation metadata." + } + } + }, + "GoogleCloudAiplatformV1beta1StudySpecConvexStopConfig": { + "properties": { + "minNumSteps": { + "description": "Minimum number of steps for a trial to complete. Trials which do not have a measurement with num_steps \u003e min_num_steps won't be considered for early stopping. It's ok to set it to 0, and a trial can be early stopped at any stage. By default, min_num_steps is set to be one-tenth of the max_num_steps. When use_steps is false, this field is set to the minimum elapsed seconds.", + "type": "string", + "format": "int64" + }, + "autoregressiveOrder": { + "format": "int64", + "description": "The number of Trial measurements used in autoregressive model for value prediction. A trial won't be considered early stopping if has fewer measurement points.", + "type": "string" + }, + "maxNumSteps": { + "type": "string", + "format": "int64", + "description": "Steps used in predicting the final objective for early stopped trials. In general, it's set to be the same as the defined steps in training / tuning. When use_steps is false, this field is set to the maximum elapsed seconds." + }, + "useSeconds": { + "description": "This bool determines whether or not the rule is applied based on elapsed_secs or steps. If use_seconds==false, the early stopping decision is made according to the predicted objective values according to the target steps. If use_seconds==true, elapsed_secs is used instead of steps. Also, in this case, the parameters max_num_steps and min_num_steps are overloaded to contain max_elapsed_seconds and min_elapsed_seconds.", + "type": "boolean" + }, + "learningRateParameterName": { + "description": "The hyper-parameter name used in the tuning job that stands for learning rate. Leave it blank if learning rate is not in a parameter in tuning. The learning_rate is used to estimate the objective value of the ongoing trial.", + "type": "string" + } + }, + "deprecated": true, + "description": "Configuration for ConvexStopPolicy.", + "id": "GoogleCloudAiplatformV1beta1StudySpecConvexStopConfig", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix": { + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix", + "properties": { + "annotationSpecs": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrixAnnotationSpecRef" + }, + "description": "AnnotationSpecs used in the confusion matrix. For AutoML Text Extraction, a special negative AnnotationSpec with empty `id` and `displayName` of \"NULL\" will be added as the last element." + }, + "rows": { + "type": "array", + "items": { + "items": { + "type": "any" + }, + "type": "array" + }, + "description": "Rows in the confusion matrix. The number of rows is equal to the size of `annotationSpecs`. `rowsi` is the number of DataItems that have ground truth of the `annotationSpecs[i]` and are predicted as `annotationSpecs[j]` by the Model being evaluated. For Text Extraction, when `annotationSpecs[i]` is the last element in `annotationSpecs`, i.e. the special negative AnnotationSpec, `rowsi` is the number of predicted entities of `annoatationSpec[j]` that are not labeled as any of the ground truth AnnotationSpec. When annotationSpecs[j] is the special negative AnnotationSpec, `rowsi` is the number of entities have ground truth of `annotationSpec[i]` that are not predicted as an entity by the Model. The value of the last cell, i.e. `rowi` where i == j and `annotationSpec[i]` is the special negative AnnotationSpec, is always 0." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1Extension": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1Extension", + "description": "Extensions are tools for large language models to access external data, run computations, etc.", + "properties": { + "createTime": { + "type": "string", + "description": "Output only. Timestamp when this Extension was created.", + "readOnly": true, + "format": "google-datetime" + }, + "description": { + "description": "Optional. The description of the Extension.", + "type": "string" + }, + "extensionOperations": { + "description": "Output only. Supported operations.", + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ExtensionOperation" + }, + "type": "array" + }, + "displayName": { + "type": "string", + "description": "Required. The display name of the Extension. The name can be up to 128 characters long and can consist of any UTF-8 characters." + }, + "runtimeConfig": { + "description": "Optional. Runtime config controlling the runtime behavior of this Extension.", + "$ref": "GoogleCloudAiplatformV1beta1RuntimeConfig" + }, + "name": { + "description": "Identifier. The resource name of the Extension.", + "type": "string" + }, + "privateServiceConnectConfig": { + "description": "Optional. The PrivateServiceConnect config for the extension. If specified, the service endpoints associated with the Extension should be registered with private network access in the provided Service Directory (https://cloud.google.com/service-directory/docs/configuring-private-network-access). If the service contains more than one endpoint with a network, the service will arbitrarilty choose one of the endpoints to use for extension execution.", + "$ref": "GoogleCloudAiplatformV1beta1ExtensionPrivateServiceConnectConfig" + }, + "toolUseExamples": { + "description": "Optional. Examples to illustrate the usage of the extension as a tool.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ToolUseExample" + }, + "type": "array" + }, + "manifest": { + "$ref": "GoogleCloudAiplatformV1beta1ExtensionManifest", + "description": "Required. Manifest of the Extension." + }, + "etag": { + "type": "string", + "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + }, + "updateTime": { + "description": "Output only. Timestamp when this Extension was most recently updated.", + "type": "string", + "format": "google-datetime", + "readOnly": true + } + } + }, + "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigImportFeaturesAnalysis": { + "properties": { + "state": { + "type": "string", + "enum": [ + "STATE_UNSPECIFIED", + "DEFAULT", + "ENABLED", + "DISABLED" + ], + "enumDescriptions": [ + "Should not be used.", + "The default behavior of whether to enable the monitoring. EntityType-level config: disabled. Feature-level config: inherited from the configuration of EntityType this Feature belongs to.", + "Explicitly enables import features analysis. EntityType-level config: by default enables import features analysis for all Features under it. Feature-level config: enables import features analysis regardless of the EntityType-level config.", + "Explicitly disables import features analysis. EntityType-level config: by default disables import features analysis for all Features under it. Feature-level config: disables import features analysis regardless of the EntityType-level config." + ], + "description": "Whether to enable / disable / inherite default hebavior for import features analysis." + }, + "anomalyDetectionBaseline": { + "enum": [ + "BASELINE_UNSPECIFIED", + "LATEST_STATS", + "MOST_RECENT_SNAPSHOT_STATS", + "PREVIOUS_IMPORT_FEATURES_STATS" + ], + "type": "string", + "description": "The baseline used to do anomaly detection for the statistics generated by import features analysis.", + "enumDescriptions": [ + "Should not be used.", + "Choose the later one statistics generated by either most recent snapshot analysis or previous import features analysis. If non of them exists, skip anomaly detection and only generate a statistics.", + "Use the statistics generated by the most recent snapshot analysis if exists.", + "Use the statistics generated by the previous import features analysis if exists." + ] + } + }, + "description": "Configuration of the Featurestore's ImportFeature Analysis Based Monitoring. This type of analysis generates statistics for values of each Feature imported by every ImportFeatureValues operation.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigImportFeaturesAnalysis" + }, + "GoogleCloudAiplatformV1beta1RemoveContextChildrenResponse": { + "id": "GoogleCloudAiplatformV1beta1RemoveContextChildrenResponse", + "description": "Response message for MetadataService.RemoveContextChildren.", + "type": "object", + "properties": {} + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTables": { + "properties": { + "metadata": { + "description": "The metadata information.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesMetadata" + }, + "inputs": { + "description": "The input parameters of this TrainingJob.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputs" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTables", + "type": "object", + "description": "A TrainingJob that trains and uploads an AutoML Tables Model." + }, + "GoogleCloudAiplatformV1beta1ReadIndexDatapointsRequest": { + "properties": { + "deployedIndexId": { + "type": "string", + "description": "The ID of the DeployedIndex that will serve the request." + }, + "ids": { + "type": "array", + "items": { + "type": "string" + }, + "description": "IDs of the datapoints to be searched for." + } + }, + "description": "The request message for MatchService.ReadIndexDatapoints.", + "id": "GoogleCloudAiplatformV1beta1ReadIndexDatapointsRequest", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ListRagCorporaResponse": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ListRagCorporaResponse", + "properties": { + "nextPageToken": { + "description": "A token to retrieve the next page of results. Pass to ListRagCorporaRequest.page_token to obtain that page.", + "type": "string" + }, + "ragCorpora": { + "description": "List of RagCorpora in the requested page.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1RagCorpus" + }, + "type": "array" + } + }, + "description": "Response message for VertexRagDataService.ListRagCorpora." + }, + "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTabularClassificationPredictionResult": { + "description": "Prediction output format for Tabular Classification.", + "type": "object", + "properties": { + "scores": { + "type": "array", + "description": "The model's confidence in each class being correct, higher value means higher confidence. The N-th score corresponds to the N-th class in classes.", + "items": { + "format": "float", + "type": "number" + } + }, + "classes": { + "items": { + "type": "string" + }, + "type": "array", + "description": "The name of the classes being classified, contains all possible values of the target column." + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTabularClassificationPredictionResult" + }, + "GoogleCloudLocationLocation": { + "type": "object", + "description": "A resource that represents a Google Cloud location.", + "id": "GoogleCloudLocationLocation", + "properties": { + "name": { + "description": "Resource name for the location, which may vary between implementations. For example: `\"projects/example-project/locations/us-east1\"`", + "type": "string" + }, + "metadata": { + "type": "object", + "additionalProperties": { + "description": "Properties of the object. Contains field @type with type URL.", + "type": "any" + }, + "description": "Service-specific metadata. For example the available capacity at the given location." + }, + "displayName": { + "description": "The friendly name for this location, typically a nearby city name. For example, \"Tokyo\".", + "type": "string" + }, + "locationId": { + "description": "The canonical id for this location. For example: `\"us-east1\"`.", + "type": "string" + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "description": "Cross-service attributes for the location. For example {\"cloud.googleapis.com/region\": \"us-east1\"}", + "type": "object" + } + } + }, + "GoogleRpcStatus": { + "id": "GoogleRpcStatus", + "description": "The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors).", + "type": "object", + "properties": { + "details": { + "items": { + "additionalProperties": { + "description": "Properties of the object. Contains field @type with type URL.", + "type": "any" + }, + "type": "object" + }, + "type": "array", + "description": "A list of messages that carry the error details. There is a common set of message types for APIs to use." + }, + "message": { + "description": "A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.", + "type": "string" + }, + "code": { + "type": "integer", + "format": "int32", + "description": "The status code, which should be an enum value of google.rpc.Code." + } + } + }, + "GoogleCloudAiplatformV1beta1DeployModelOperationMetadata": { + "description": "Runtime operation information for EndpointService.DeployModel.", + "type": "object", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "The operation generic information." + } + }, + "id": "GoogleCloudAiplatformV1beta1DeployModelOperationMetadata" + }, + "GoogleIamV1Policy": { + "properties": { + "etag": { + "description": "`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.", + "type": "string", + "format": "byte" + }, + "version": { + "type": "integer", + "description": "Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", + "format": "int32" + }, + "bindings": { + "items": { + "$ref": "GoogleIamV1Binding" + }, + "description": "Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.", + "type": "array" + } + }, + "type": "object", + "description": "An Identity and Access Management (IAM) policy, which specifies access controls for Google Cloud resources. A `Policy` is a collection of `bindings`. A `binding` binds one or more `members`, or principals, to a single `role`. Principals can be user accounts, service accounts, Google groups, and domains (such as G Suite). A `role` is a named list of permissions; each `role` can be an IAM predefined role or a user-created custom role. For some types of Google Cloud resources, a `binding` can also specify a `condition`, which is a logical expression that allows access to a resource only if the expression evaluates to `true`. A condition can add constraints based on attributes of the request, the resource, or both. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies). **JSON example:** ``` { \"bindings\": [ { \"role\": \"roles/resourcemanager.organizationAdmin\", \"members\": [ \"user:mike@example.com\", \"group:admins@example.com\", \"domain:google.com\", \"serviceAccount:my-project-id@appspot.gserviceaccount.com\" ] }, { \"role\": \"roles/resourcemanager.organizationViewer\", \"members\": [ \"user:eve@example.com\" ], \"condition\": { \"title\": \"expirable access\", \"description\": \"Does not grant access after Sep 2020\", \"expression\": \"request.time \u003c timestamp('2020-10-01T00:00:00.000Z')\", } } ], \"etag\": \"BwWWja0YfJA=\", \"version\": 3 } ``` **YAML example:** ``` bindings: - members: - user:mike@example.com - group:admins@example.com - domain:google.com - serviceAccount:my-project-id@appspot.gserviceaccount.com role: roles/resourcemanager.organizationAdmin - members: - user:eve@example.com role: roles/resourcemanager.organizationViewer condition: title: expirable access description: Does not grant access after Sep 2020 expression: request.time \u003c timestamp('2020-10-01T00:00:00.000Z') etag: BwWWja0YfJA= version: 3 ``` For a description of IAM and its features, see the [IAM documentation](https://cloud.google.com/iam/docs/).", + "id": "GoogleIamV1Policy" + }, + "GoogleCloudAiplatformV1beta1PrivateServiceConnectConfig": { + "id": "GoogleCloudAiplatformV1beta1PrivateServiceConnectConfig", + "properties": { + "projectAllowlist": { + "items": { + "type": "string" + }, + "type": "array", + "description": "A list of Projects from which the forwarding rule will target the service attachment." + }, + "enablePrivateServiceConnect": { + "type": "boolean", + "description": "Required. If true, expose the IndexEndpoint via private service connect." + } + }, + "description": "Represents configuration for private service connect.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsRequest": { + "type": "object", + "description": "Request message for ModelService.BatchImportEvaluatedAnnotations", + "id": "GoogleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsRequest", + "properties": { + "evaluatedAnnotations": { + "description": "Required. Evaluated annotations resource to be imported.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1EvaluatedAnnotation" + }, + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1beta1ListContextsResponse": { + "description": "Response message for MetadataService.ListContexts.", + "properties": { + "nextPageToken": { + "description": "A token, which can be sent as ListContextsRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages.", + "type": "string" + }, + "contexts": { + "type": "array", + "description": "The Contexts retrieved from the MetadataStore.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Context" + } + } + }, + "id": "GoogleCloudAiplatformV1beta1ListContextsResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringAnomaly": { + "description": "Represents a single model monitoring anomaly.", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringAnomaly", + "type": "object", + "properties": { + "algorithm": { + "description": "Algorithm used to calculated the metrics, eg: jensen_shannon_divergence, l_infinity.", + "type": "string" + }, + "tabularAnomaly": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAnomalyTabularAnomaly", + "description": "Tabular anomaly." + }, + "modelMonitoringJob": { + "description": "Model monitoring job resource name.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1ListNotebookRuntimesResponse": { + "id": "GoogleCloudAiplatformV1beta1ListNotebookRuntimesResponse", + "type": "object", + "properties": { + "notebookRuntimes": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1NotebookRuntime" + }, + "type": "array", + "description": "List of NotebookRuntimes in the requested page." + }, + "nextPageToken": { + "description": "A token to retrieve next page of results. Pass to ListNotebookRuntimesRequest.page_token to obtain that page.", + "type": "string" + } + }, + "description": "Response message for NotebookService.ListNotebookRuntimes." + }, + "GoogleCloudAiplatformV1beta1ListModelEvaluationSlicesResponse": { + "id": "GoogleCloudAiplatformV1beta1ListModelEvaluationSlicesResponse", + "properties": { + "modelEvaluationSlices": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationSlice" + }, + "description": "List of ModelEvaluations in the requested page.", + "type": "array" + }, + "nextPageToken": { + "type": "string", + "description": "A token to retrieve next page of results. Pass to ListModelEvaluationSlicesRequest.page_token to obtain that page." + } + }, + "type": "object", + "description": "Response message for ModelService.ListModelEvaluationSlices." + }, + "GoogleCloudAiplatformV1beta1StratifiedSplit": { + "properties": { + "trainingFraction": { + "type": "number", + "description": "The fraction of the input data that is to be used to train the Model.", + "format": "double" + }, + "key": { + "type": "string", + "description": "Required. The key is a name of one of the Dataset's data columns. The key provided must be for a categorical column." + }, + "testFraction": { + "format": "double", + "type": "number", + "description": "The fraction of the input data that is to be used to evaluate the Model." + }, + "validationFraction": { + "format": "double", + "type": "number", + "description": "The fraction of the input data that is to be used to validate the Model." + } + }, + "type": "object", + "description": "Assigns input data to the training, validation, and test sets so that the distribution of values found in the categorical column (as specified by the `key` field) is mirrored within each split. The fraction values determine the relative sizes of the splits. For example, if the specified column has three values, with 50% of the rows having value \"A\", 25% value \"B\", and 25% value \"C\", and the split fractions are specified as 80/10/10, then the training set will constitute 80% of the training data, with about 50% of the training set rows having the value \"A\" for the specified column, about 25% having the value \"B\", and about 25% having the value \"C\". Only the top 500 occurring values are used; any values not in the top 500 values are randomly assigned to a split. If less than three rows contain a specific value, those rows are randomly assigned. Supported only for tabular Datasets.", + "id": "GoogleCloudAiplatformV1beta1StratifiedSplit" + }, + "GoogleCloudAiplatformV1beta1SyncFeatureViewResponse": { + "description": "Respose message for FeatureOnlineStoreAdminService.SyncFeatureView.", + "id": "GoogleCloudAiplatformV1beta1SyncFeatureViewResponse", + "type": "object", + "properties": { + "featureViewSync": { + "type": "string", + "description": "Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}/featureViewSyncs/{feature_view_sync}`" + } + } + }, + "GoogleCloudAiplatformV1beta1ListNotebookExecutionJobsResponse": { + "properties": { + "notebookExecutionJobs": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1NotebookExecutionJob" + }, + "type": "array", + "description": "List of NotebookExecutionJobs in the requested page." + }, + "nextPageToken": { + "description": "A token to retrieve next page of results. Pass to ListNotebookExecutionJobs.page_token to obtain that page.", + "type": "string" + } + }, + "type": "object", + "description": "Response message for [NotebookService.CreateNotebookExecutionJob]", + "id": "GoogleCloudAiplatformV1beta1ListNotebookExecutionJobsResponse" + }, + "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataGcsSource": { + "id": "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataGcsSource", + "properties": { + "uri": { + "type": "array", + "description": "Cloud Storage URI of one or more files. Only CSV files are supported. The first line of the CSV file is used as the header. If there are multiple files, the header is the first line of the lexicographically first file, the other files must either contain the exact same header or omit the header.", + "items": { + "type": "string" + } + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FindNeighborsResponseNearestNeighbors": { + "description": "Nearest neighbors for one query.", + "properties": { + "id": { + "type": "string", + "description": "The ID of the query datapoint." + }, + "neighbors": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1FindNeighborsResponseNeighbor" + }, + "description": "All its neighbors." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1FindNeighborsResponseNearestNeighbors" + }, + "GoogleCloudAiplatformV1beta1ListOptimalTrialsResponse": { + "id": "GoogleCloudAiplatformV1beta1ListOptimalTrialsResponse", + "properties": { + "optimalTrials": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Trial" + }, + "description": "The pareto-optimal Trials for multiple objective Study or the optimal trial for single objective Study. The definition of pareto-optimal can be checked in wiki page. https://en.wikipedia.org/wiki/Pareto_efficiency" + } + }, + "description": "Response message for VizierService.ListOptimalTrials.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1WriteFeatureValuesRequest": { + "properties": { + "payloads": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1WriteFeatureValuesPayload" + }, + "description": "Required. The entities to be written. Up to 100,000 feature values can be written across all `payloads`.", + "type": "array" + } + }, + "description": "Request message for FeaturestoreOnlineServingService.WriteFeatureValues.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1WriteFeatureValuesRequest" + }, + "GoogleCloudAiplatformV1beta1SchemaImageDataItem": { + "type": "object", + "properties": { + "mimeType": { + "readOnly": true, + "type": "string", + "description": "Output only. The mime type of the content of the image. Only the images in below listed mime types are supported. - image/jpeg - image/gif - image/png - image/webp - image/bmp - image/tiff - image/vnd.microsoft.icon" + }, + "gcsUri": { + "type": "string", + "description": "Required. Google Cloud Storage URI points to the original image in user's bucket. The image is up to 30MB in size." + } + }, + "description": "Payload of Image DataItem.", + "id": "GoogleCloudAiplatformV1beta1SchemaImageDataItem" + }, + "GoogleCloudAiplatformV1beta1NasJobOutputMultiTrialJobOutput": { + "properties": { + "searchTrials": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1NasTrial" + }, + "type": "array", + "readOnly": true, + "description": "Output only. List of NasTrials that were started as part of search stage." + }, + "trainTrials": { + "readOnly": true, + "description": "Output only. List of NasTrials that were started as part of train stage.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1NasTrial" + } + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1NasJobOutputMultiTrialJobOutput", + "description": "The output of a multi-trial Neural Architecture Search (NAS) jobs." + }, + "GoogleCloudAiplatformV1beta1CreateFeatureViewOperationMetadata": { + "type": "object", + "properties": { + "genericMetadata": { + "description": "Operation metadata for FeatureView Create.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "id": "GoogleCloudAiplatformV1beta1CreateFeatureViewOperationMetadata", + "description": "Details of operations that perform create FeatureView." + }, + "GoogleCloudAiplatformV1beta1GenieSource": { + "description": "Contains information about the source of the models generated from Generative AI Studio.", + "id": "GoogleCloudAiplatformV1beta1GenieSource", + "type": "object", + "properties": { + "baseModelUri": { + "type": "string", + "description": "Required. The public base model URI." + } + } + }, + "GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtableAutoScaling": { + "type": "object", + "properties": { + "minNodeCount": { + "type": "integer", + "format": "int32", + "description": "Required. The minimum number of nodes to scale down to. Must be greater than or equal to 1." + }, + "cpuUtilizationTarget": { + "format": "int32", + "description": "Optional. A percentage of the cluster's CPU capacity. Can be from 10% to 80%. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set will default to 50%.", + "type": "integer" + }, + "maxNodeCount": { + "description": "Required. The maximum number of nodes to scale up to. Must be greater than or equal to min_node_count, and less than or equal to 10 times of 'min_node_count'.", + "format": "int32", + "type": "integer" + } + }, + "id": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtableAutoScaling" + }, + "GoogleCloudAiplatformV1beta1ReadIndexDatapointsResponse": { + "description": "The response message for MatchService.ReadIndexDatapoints.", + "properties": { + "datapoints": { + "type": "array", + "description": "The result list of datapoints.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1IndexDatapoint" + } + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ReadIndexDatapointsResponse" + }, + "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseEntityViewData": { + "id": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseEntityViewData", + "description": "Container to hold value(s), successive in time, for one Feature from the request.", + "properties": { + "value": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureValue", + "description": "Feature value if a single value is requested." + }, + "values": { + "description": "Feature values list if values, successive in time, are requested. If the requested number of values is greater than the number of existing Feature values, nonexistent values are omitted instead of being returned as empty.", + "$ref": "GoogleCloudAiplatformV1beta1FeatureValueList" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ExportFeatureValuesRequest": { + "description": "Request message for FeaturestoreService.ExportFeatureValues.", + "id": "GoogleCloudAiplatformV1beta1ExportFeatureValuesRequest", + "properties": { + "snapshotExport": { + "$ref": "GoogleCloudAiplatformV1beta1ExportFeatureValuesRequestSnapshotExport", + "description": "Exports the latest Feature values of all entities of the EntityType within a time range." + }, + "featureSelector": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureSelector", + "description": "Required. Selects Features to export values of." + }, + "fullExport": { + "description": "Exports all historical values of all entities of the EntityType within a time range", + "$ref": "GoogleCloudAiplatformV1beta1ExportFeatureValuesRequestFullExport" + }, + "settings": { + "type": "array", + "description": "Per-Feature export settings.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1DestinationFeatureSetting" + } + }, + "destination": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureValueDestination", + "description": "Required. Specifies destination location and format." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTextExtractionPredictionResult": { + "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTextExtractionPredictionResult", + "properties": { + "displayNames": { + "description": "The display names of the AnnotationSpecs that had been identified, order matches the IDs.", + "items": { + "type": "string" + }, + "type": "array" + }, + "textSegmentStartOffsets": { + "type": "array", + "description": "The start offsets, inclusive, of the text segment in which the AnnotationSpec has been identified. Expressed as a zero-based number of characters as measured from the start of the text snippet.", + "items": { + "type": "string", + "format": "int64" + } + }, + "ids": { + "description": "The resource IDs of the AnnotationSpecs that had been identified, ordered by the confidence score descendingly.", + "type": "array", + "items": { + "format": "int64", + "type": "string" + } + }, + "confidences": { + "description": "The Model's confidences in correctness of the predicted IDs, higher value means higher confidence. Order matches the Ids.", + "type": "array", + "items": { + "format": "float", + "type": "number" + } + }, + "textSegmentEndOffsets": { + "description": "The end offsets, inclusive, of the text segment in which the AnnotationSpec has been identified. Expressed as a zero-based number of characters as measured from the start of the text snippet.", + "type": "array", + "items": { + "format": "int64", + "type": "string" + } + } + }, + "type": "object", + "description": "Prediction output format for Text Extraction." + }, + "GoogleCloudAiplatformV1beta1UndeployModelRequest": { + "type": "object", + "description": "Request message for EndpointService.UndeployModel.", + "properties": { + "trafficSplit": { + "description": "If this field is provided, then the Endpoint's traffic_split will be overwritten with it. If last DeployedModel is being undeployed from the Endpoint, the [Endpoint.traffic_split] will always end up empty when this call returns. A DeployedModel will be successfully undeployed only if it doesn't have any traffic assigned to it when this method executes, or if this field unassigns any traffic to it.", + "type": "object", + "additionalProperties": { + "type": "integer", + "format": "int32" + } + }, + "deployedModelId": { + "description": "Required. The ID of the DeployedModel to be undeployed from the Endpoint.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1UndeployModelRequest" + }, + "GoogleCloudAiplatformV1beta1ToolCallValidResults": { + "properties": { + "toolCallValidMetricValues": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ToolCallValidMetricValue" + }, + "description": "Output only. Tool call valid metric values.", + "type": "array", + "readOnly": true + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ToolCallValidResults", + "description": "Results for tool call valid metric." + }, + "GoogleCloudAiplatformV1beta1Dataset": { + "properties": { + "metadata": { + "type": "any", + "description": "Required. Additional information about the Dataset." + }, + "savedQueries": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SavedQuery" + }, + "description": "All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.", + "type": "array" + }, + "createTime": { + "type": "string", + "description": "Output only. Timestamp when this Dataset was created.", + "readOnly": true, + "format": "google-datetime" + }, + "metadataSchemaUri": { + "type": "string", + "description": "Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/." + }, + "name": { + "type": "string", + "description": "Output only. Identifier. The resource name of the Dataset.", + "readOnly": true + }, + "metadataArtifact": { + "type": "string", + "readOnly": true, + "description": "Output only. The resource name of the Artifact that was created in MetadataStore when creating the Dataset. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`." + }, + "description": { + "type": "string", + "description": "The description of the Dataset." + }, + "labels": { + "description": "The labels with user-defined metadata to organize your Datasets. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable. Following system labels exist for each Dataset: * \"aiplatform.googleapis.com/dataset_metadata_schema\": output only, its value is the metadata_schema's title.", + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "updateTime": { + "description": "Output only. Timestamp when this Dataset was last updated.", + "readOnly": true, + "format": "google-datetime", + "type": "string" + }, + "dataItemCount": { + "type": "string", + "description": "Output only. The number of DataItems in this Dataset. Only apply for non-structured Dataset.", + "format": "int64", + "readOnly": true + }, + "modelReference": { + "type": "string", + "description": "Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets." + }, + "etag": { + "type": "string", + "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", + "description": "Customer-managed encryption key spec for a Dataset. If set, this Dataset and all sub-resources of this Dataset will be secured by this key." + }, + "displayName": { + "description": "Required. The user-defined name of the Dataset. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + } + }, + "type": "object", + "description": "A collection of DataItems and Annotations on them.", + "id": "GoogleCloudAiplatformV1beta1Dataset" + }, + "GoogleCloudAiplatformV1beta1ReasoningEngine": { + "id": "GoogleCloudAiplatformV1beta1ReasoningEngine", + "description": "ReasoningEngine provides a customizable runtime for models to determine which actions to take and in which order.", + "type": "object", + "properties": { + "spec": { + "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpec", + "description": "Required. Configurations of the ReasoningEngine" + }, + "etag": { + "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "description": { + "type": "string", + "description": "Optional. The description of the ReasoningEngine." + }, + "updateTime": { + "format": "google-datetime", + "description": "Output only. Timestamp when this ReasoningEngine was most recently updated.", + "readOnly": true, + "type": "string" + }, + "createTime": { + "description": "Output only. Timestamp when this ReasoningEngine was created.", + "readOnly": true, + "format": "google-datetime", + "type": "string" + }, + "displayName": { + "description": "Required. The display name of the ReasoningEngine.", + "type": "string" + }, + "name": { + "description": "Identifier. The resource name of the ReasoningEngine.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaPredictParamsVideoClassificationPredictionParams": { + "id": "GoogleCloudAiplatformV1beta1SchemaPredictParamsVideoClassificationPredictionParams", + "description": "Prediction model parameters for Video Classification.", + "properties": { + "shotClassification": { + "type": "boolean", + "description": "Set to true to request shot-level classification. Vertex AI determines the boundaries for each camera shot in the entire time segment of the video that user specified in the input instance. Vertex AI then returns labels and their confidence scores for each detected shot, along with the start and end time of the shot. WARNING: Model evaluation is not done for this classification type, the quality of it depends on the training data, but there are no metrics provided to describe that quality. Default value is false" + }, + "confidenceThreshold": { + "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0", + "format": "float", + "type": "number" + }, + "maxPredictions": { + "format": "int32", + "type": "integer", + "description": "The Model only returns up to that many top, by confidence score, predictions per instance. If this number is very high, the Model may return fewer predictions. Default value is 10,000." + }, + "oneSecIntervalClassification": { + "description": "Set to true to request classification for a video at one-second intervals. Vertex AI returns labels and their confidence scores for each second of the entire time segment of the video that user specified in the input WARNING: Model evaluation is not done for this classification type, the quality of it depends on the training data, but there are no metrics provided to describe that quality. Default value is false", + "type": "boolean" + }, + "segmentClassification": { + "type": "boolean", + "description": "Set to true to request segment-level classification. Vertex AI returns labels and their confidence scores for the entire time segment of the video that user specified in the input instance. Default value is true" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SummarizationQualitySpec": { + "type": "object", + "description": "Spec for summarization quality score metric.", + "properties": { + "version": { + "type": "integer", + "description": "Optional. Which version to use for evaluation.", + "format": "int32" + }, + "useReference": { + "type": "boolean", + "description": "Optional. Whether to use instance.reference to compute summarization quality." + } + }, + "id": "GoogleCloudAiplatformV1beta1SummarizationQualitySpec" + }, + "GoogleCloudAiplatformV1beta1Tool": { + "properties": { + "retrieval": { + "$ref": "GoogleCloudAiplatformV1beta1Retrieval", + "description": "Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation." + }, + "googleSearchRetrieval": { + "$ref": "GoogleCloudAiplatformV1beta1GoogleSearchRetrieval", + "description": "Optional. GoogleSearchRetrieval tool type. Specialized retrieval tool that is powered by Google search." + }, + "functionDeclarations": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1FunctionDeclaration" + }, + "type": "array", + "description": "Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 64 function declarations can be provided." + } + }, + "description": "Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1Tool" + }, + "GoogleCloudAiplatformV1beta1GenericOperationMetadata": { + "id": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "properties": { + "updateTime": { + "description": "Output only. Time when the operation was updated for the last time. If the operation has finished (successfully or not), this is the finish time.", + "type": "string", + "readOnly": true, + "format": "google-datetime" + }, + "createTime": { + "description": "Output only. Time when the operation was created.", + "readOnly": true, + "format": "google-datetime", + "type": "string" + }, + "partialFailures": { + "items": { + "$ref": "GoogleRpcStatus" + }, + "readOnly": true, + "type": "array", + "description": "Output only. Partial failures encountered. E.g. single files that couldn't be read. This field should never exceed 20 entries. Status details field will contain standard Google Cloud error details." + } + }, + "description": "Generic Metadata shared by all operations.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FindNeighborsRequestQueryRRF": { + "description": "Parameters for RRF algorithm that combines search results.", + "type": "object", + "properties": { + "alpha": { + "type": "number", + "format": "float", + "description": "Required. Users can provide an alpha value to give more weight to dense vs sparse results. For example, if the alpha is 0, we only return sparse and if the alpha is 1, we only return dense." + } + }, + "id": "GoogleCloudAiplatformV1beta1FindNeighborsRequestQueryRRF" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValueDistributionDataValue": { + "description": "Summary statistics for a population of values.", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValueDistributionDataValue", + "type": "object", + "properties": { + "distributionDeviation": { + "type": "number", + "format": "double", + "description": "Distribution distance deviation from the current dataset's statistics to baseline dataset's statistics. * For categorical feature, the distribution distance is calculated by L-inifinity norm or Jensen–Shannon divergence. * For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence." + }, + "distribution": { + "type": "any", + "description": "Predictive monitoring drift distribution in `tensorflow.metadata.v0.DatasetFeatureStatistics` format." + } + } + }, + "GoogleCloudAiplatformV1beta1MutateDeployedModelOperationMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1MutateDeployedModelOperationMetadata", + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "description": "Runtime operation information for EndpointService.MutateDeployedModel." + }, + "GoogleCloudAiplatformV1beta1SchemaVideoDatasetMetadata": { + "type": "object", + "description": "The metadata of Datasets that contain Video DataItems.", + "properties": { + "dataItemSchemaUri": { + "description": "Points to a YAML file stored on Google Cloud Storage describing payload of the Video DataItems that belong to this Dataset.", + "type": "string" + }, + "gcsBucket": { + "type": "string", + "description": "Google Cloud Storage Bucket name that contains the blob data of this Dataset." + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaVideoDatasetMetadata" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningJobMetadata": { + "properties": { + "bestTrialBackingCustomJob": { + "type": "string", + "description": "The resource name of the CustomJob that has been created to run the best Trial of this HyperparameterTuning task." + }, + "backingHyperparameterTuningJob": { + "type": "string", + "description": "The resource name of the HyperparameterTuningJob that has been created to carry out this HyperparameterTuning task." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningJobMetadata" + }, + "GoogleCloudAiplatformV1beta1ServiceAccountSpec": { + "description": "Configuration for the use of custom service account to run the workloads.", + "type": "object", + "properties": { + "enableCustomServiceAccount": { + "description": "Required. If true, custom user-managed service account is enforced to run any workloads (for example, Vertex Jobs) on the resource. Otherwise, uses the [Vertex AI Custom Code Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).", + "type": "boolean" + }, + "serviceAccount": { + "type": "string", + "description": "Optional. Required when all below conditions are met * `enable_custom_service_account` is true; * any runtime is specified via `ResourceRuntimeSpec` on creation time, for example, Ray The users must have `iam.serviceAccounts.actAs` permission on this service account and then the specified runtime containers will run as it. Do not set this field if you want to submit jobs using custom service account to this PersistentResource after creation, but only specify the `service_account` inside the job." + } + }, + "id": "GoogleCloudAiplatformV1beta1ServiceAccountSpec" + }, + "GoogleCloudAiplatformV1beta1MigratableResourceAutomlDataset": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1MigratableResourceAutomlDataset", + "description": "Represents one Dataset in automl.googleapis.com.", + "properties": { + "dataset": { + "type": "string", + "description": "Full resource name of automl Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`." + }, + "datasetDisplayName": { + "type": "string", + "description": "The Dataset's display name in automl.googleapis.com." + } + } + }, + "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseEntityView": { + "id": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseEntityView", + "properties": { + "data": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseEntityViewData" + }, + "description": "Each piece of data holds the k requested values for one requested Feature. If no values for the requested Feature exist, the corresponding cell will be empty. This has the same size and is in the same order as the features from the header ReadFeatureValuesResponse.header." + }, + "entityId": { + "description": "ID of the requested entity.", + "type": "string" + } + }, + "description": "Entity view with Feature values.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfigTreeAHConfig": { + "id": "GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfigTreeAHConfig", + "properties": { + "leafNodeEmbeddingCount": { + "format": "int64", + "type": "string", + "description": "Optional. Number of embeddings on each leaf node. The default value is 1000 if not set." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FeatureStatsAnomaly": { + "description": "Stats and Anomaly generated at specific timestamp for specific Feature. The start_time and end_time are used to define the time range of the dataset that current stats belongs to, e.g. prediction traffic is bucketed into prediction datasets by time window. If the Dataset is not defined by time window, start_time = end_time. Timestamp of the stats and anomalies always refers to end_time. Raw stats and anomalies are stored in stats_uri or anomaly_uri in the tensorflow defined protos. Field data_stats contains almost identical information with the raw stats in Vertex AI defined proto, for UI to display.", + "properties": { + "startTime": { + "description": "The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).", + "type": "string", + "format": "google-datetime" + }, + "anomalyDetectionThreshold": { + "type": "number", + "format": "double", + "description": "This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value." + }, + "endTime": { + "format": "google-datetime", + "type": "string", + "description": "The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values)." + }, + "distributionDeviation": { + "type": "number", + "format": "double", + "description": "Deviation from the current stats to baseline stats. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence." + }, + "anomalyUri": { + "type": "string", + "description": "Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message [tensorflow.metadata.v0.AnomalyInfo] (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto)." + }, + "score": { + "format": "double", + "description": "Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT.", + "type": "number" + }, + "statsUri": { + "type": "string", + "description": "Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:////stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message [tensorflow.metadata.v0.FeatureNameStatistics](https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/statistics.proto)." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1FeatureStatsAnomaly" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHierarchyConfig": { + "description": "Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies.", + "type": "object", + "properties": { + "temporalTotalWeight": { + "format": "double", + "description": "The weight of the loss for predictions aggregated over the horizon for a single time series.", + "type": "number" + }, + "groupColumns": { + "type": "array", + "description": "A list of time series attribute column names that define the time series hierarchy. Only one level of hierarchy is supported, ex. 'region' for a hierarchy of stores or 'department' for a hierarchy of products. If multiple columns are specified, time series will be grouped by their combined values, ex. ('blue', 'large') for 'color' and 'size', up to 5 columns are accepted. If no group columns are specified, all time series are considered to be part of the same group.", + "items": { + "type": "string" + } + }, + "groupTemporalTotalWeight": { + "format": "double", + "description": "The weight of the loss for predictions aggregated over both the horizon and time series in the same hierarchy group.", + "type": "number" + }, + "groupTotalWeight": { + "format": "double", + "type": "number", + "description": "The weight of the loss for predictions aggregated over time series in the same group." + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHierarchyConfig" + }, + "GoogleCloudAiplatformV1beta1CreateNotebookExecutionJobOperationMetadata": { + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + }, + "progressMessage": { + "description": "A human-readable message that shows the intermediate progress details of NotebookRuntime.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1CreateNotebookExecutionJobOperationMetadata", + "description": "Metadata information for NotebookService.CreateNotebookExecutionJob.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsForecastingEvaluationMetricsQuantileMetricsEntry": { + "properties": { + "scaledPinballLoss": { + "type": "number", + "format": "float", + "description": "The scaled pinball loss of this quantile." + }, + "quantile": { + "format": "double", + "type": "number", + "description": "The quantile for this entry." + }, + "observedQuantile": { + "type": "number", + "description": "This is a custom metric that calculates the percentage of true values that were less than the predicted value for that quantile. Only populated when optimization_objective is minimize-quantile-loss and each entry corresponds to an entry in quantiles The percent value can be used to compare with the quantile value, which is the target value.", + "format": "double" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsForecastingEvaluationMetricsQuantileMetricsEntry", + "description": "Entry for the Quantiles loss type optimization objective." + }, + "GoogleCloudAiplatformV1beta1ToolConfig": { + "description": "Tool config. This config is shared for all tools provided in the request.", + "id": "GoogleCloudAiplatformV1beta1ToolConfig", + "properties": { + "functionCallingConfig": { + "description": "Optional. Function calling config.", + "$ref": "GoogleCloudAiplatformV1beta1FunctionCallingConfig" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1PublisherModel": { + "description": "A Model Garden Publisher Model.", + "id": "GoogleCloudAiplatformV1beta1PublisherModel", + "type": "object", + "properties": { + "openSourceCategory": { + "type": "string", + "enumDescriptions": [ + "The open source category is unspecified, which should not be used.", + "Used to indicate the PublisherModel is not open sourced.", + "Used to indicate the PublisherModel is a Google-owned open source model w/ Google checkpoint.", + "Used to indicate the PublisherModel is a 3p-owned open source model w/ Google checkpoint.", + "Used to indicate the PublisherModel is a Google-owned pure open source model.", + "Used to indicate the PublisherModel is a 3p-owned pure open source model." + ], + "description": "Required. Indicates the open source category of the publisher model.", + "enum": [ + "OPEN_SOURCE_CATEGORY_UNSPECIFIED", + "PROPRIETARY", + "GOOGLE_OWNED_OSS_WITH_GOOGLE_CHECKPOINT", + "THIRD_PARTY_OWNED_OSS_WITH_GOOGLE_CHECKPOINT", + "GOOGLE_OWNED_OSS", + "THIRD_PARTY_OWNED_OSS" + ] + }, + "predictSchemata": { + "description": "Optional. The schemata that describes formats of the PublisherModel's predictions and explanations as given and returned via PredictionService.Predict.", + "$ref": "GoogleCloudAiplatformV1beta1PredictSchemata" + }, + "versionState": { + "description": "Optional. Indicates the state of the model version.", + "enumDescriptions": [ + "The version state is unspecified.", + "Used to indicate the version is stable.", + "Used to indicate the version is unstable." + ], + "type": "string", + "enum": [ + "VERSION_STATE_UNSPECIFIED", + "VERSION_STATE_STABLE", + "VERSION_STATE_UNSTABLE" + ] + }, + "name": { + "readOnly": true, + "description": "Output only. The resource name of the PublisherModel.", + "type": "string" + }, + "parent": { + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelParent", + "description": "Optional. The parent that this model was customized from. E.g., Vision API, Natural Language API, LaMDA, T5, etc. Foundation models don't have parents." + }, + "frameworks": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Optional. Additional information about the model's Frameworks." + }, + "versionId": { + "type": "string", + "description": "Output only. Immutable. The version ID of the PublisherModel. A new version is committed when a new model version is uploaded under an existing model id. It is an auto-incrementing decimal number in string representation.", + "readOnly": true + }, + "launchStage": { + "type": "string", + "enumDescriptions": [ + "The model launch stage is unspecified.", + "Used to indicate the PublisherModel is at Experimental launch stage, available to a small set of customers.", + "Used to indicate the PublisherModel is at Private Preview launch stage, only available to a small set of customers, although a larger set of customers than an Experimental launch. Previews are the first launch stage used to get feedback from customers.", + "Used to indicate the PublisherModel is at Public Preview launch stage, available to all customers, although not supported for production workloads.", + "Used to indicate the PublisherModel is at GA launch stage, available to all customers and ready for production workload." + ], + "enum": [ + "LAUNCH_STAGE_UNSPECIFIED", + "EXPERIMENTAL", + "PRIVATE_PREVIEW", + "PUBLIC_PREVIEW", + "GA" + ], + "description": "Optional. Indicates the launch stage of the model." + }, + "supportedActions": { + "description": "Optional. Supported call-to-action options.", + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToAction" + }, + "publisherModelTemplate": { + "readOnly": true, + "type": "string", + "description": "Optional. Output only. Immutable. Used to indicate this model has a publisher model and provide the template of the publisher model resource name." + } + } + }, + "GoogleCloudAiplatformV1beta1ExplanationMetadataOutputMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ExplanationMetadataOutputMetadata", + "description": "Metadata of the prediction output to be explained.", + "properties": { + "indexDisplayNameMapping": { + "type": "any", + "description": "Static mapping between the index and display name. Use this if the outputs are a deterministic n-dimensional array, e.g. a list of scores of all the classes in a pre-defined order for a multi-classification Model. It's not feasible if the outputs are non-deterministic, e.g. the Model produces top-k classes or sort the outputs by their values. The shape of the value must be an n-dimensional array of strings. The number of dimensions must match that of the outputs to be explained. The Attribution.output_display_name is populated by locating in the mapping with Attribution.output_index." + }, + "displayNameMappingKey": { + "type": "string", + "description": "Specify a field name in the prediction to look for the display name. Use this if the prediction contains the display names for the outputs. The display names in the prediction must have the same shape of the outputs, so that it can be located by Attribution.output_index for a specific output." + }, + "outputTensorName": { + "description": "Name of the output tensor. Required and is only applicable to Vertex AI provided images for Tensorflow.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1SyncFeatureViewRequest": { + "description": "Request message for FeatureOnlineStoreAdminService.SyncFeatureView.", + "properties": {}, + "id": "GoogleCloudAiplatformV1beta1SyncFeatureViewRequest", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1StudyTimeConstraint": { + "type": "object", + "description": "Time-based Constraint for Study", + "properties": { + "endTime": { + "type": "string", + "format": "google-datetime", + "description": "Compares the wallclock time to this time. Must use UTC timezone." + }, + "maxDuration": { + "format": "google-duration", + "type": "string", + "description": "Counts the wallclock time passed since the creation of this Study." + } + }, + "id": "GoogleCloudAiplatformV1beta1StudyTimeConstraint" + }, + "GoogleCloudAiplatformV1beta1SchemaAnnotationSpecColor": { + "properties": { + "id": { + "description": "The ID of the AnnotationSpec represented by the color in the segmentation mask.", + "type": "string" + }, + "color": { + "$ref": "GoogleTypeColor", + "description": "The color of the AnnotationSpec in a segmentation mask." + }, + "displayName": { + "description": "The display name of the AnnotationSpec represented by the color in the segmentation mask.", + "type": "string" + } + }, + "description": "An entry of mapping between color and AnnotationSpec. The mapping is used in segmentation mask.", + "id": "GoogleCloudAiplatformV1beta1SchemaAnnotationSpecColor", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaImageBoundingBoxAnnotation": { + "description": "Annotation details specific to image object detection.", + "id": "GoogleCloudAiplatformV1beta1SchemaImageBoundingBoxAnnotation", + "properties": { + "xMin": { + "format": "double", + "description": "The leftmost coordinate of the bounding box.", + "type": "number" + }, + "xMax": { + "description": "The rightmost coordinate of the bounding box.", + "type": "number", + "format": "double" + }, + "annotationSpecId": { + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", + "type": "string" + }, + "yMin": { + "type": "number", + "description": "The topmost coordinate of the bounding box.", + "format": "double" + }, + "yMax": { + "type": "number", + "format": "double", + "description": "The bottommost coordinate of the bounding box." + }, + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that this Annotation pertains to." + } + }, + "type": "object" + }, + "CloudAiLargeModelsVisionImage": { + "id": "CloudAiLargeModelsVisionImage", + "description": "Image.", + "type": "object", + "properties": { + "raiInfo": { + "description": "RAI info for image.", + "$ref": "CloudAiLargeModelsVisionRaiInfo" + }, + "uri": { + "description": "Path to another storage (typically Google Cloud Storage).", + "type": "string" + }, + "encoding": { + "description": "Image encoding, encoded as \"image/png\" or \"image/jpg\".", + "type": "string" + }, + "semanticFilterResponse": { + "description": "Semantic filter info for image.", + "$ref": "CloudAiLargeModelsVisionSemanticFilterResponse" + }, + "imageRaiScores": { + "$ref": "CloudAiLargeModelsVisionImageRAIScores", + "description": "RAI scores for generated image." + }, + "image": { + "description": "Raw bytes.", + "type": "string", + "format": "byte" + }, + "text": { + "type": "string", + "description": "Text/Expanded text input for imagen." + } + } + }, + "GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponse": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponse", + "description": "Response message for FeaturestoreService.DeleteFeatureValues.", + "properties": { + "selectTimeRangeAndFeature": { + "description": "Response for request specifying time range and feature", + "$ref": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponseSelectTimeRangeAndFeature" + }, + "selectEntity": { + "description": "Response for request specifying the entities to delete", + "$ref": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponseSelectEntity" + } + } + }, + "GoogleCloudAiplatformV1beta1CoherenceResult": { + "type": "object", + "properties": { + "explanation": { + "type": "string", + "description": "Output only. Explanation for coherence score.", + "readOnly": true + }, + "confidence": { + "type": "number", + "description": "Output only. Confidence for coherence score.", + "format": "float", + "readOnly": true + }, + "score": { + "type": "number", + "description": "Output only. Coherence score.", + "format": "float", + "readOnly": true + } + }, + "description": "Spec for coherence result.", + "id": "GoogleCloudAiplatformV1beta1CoherenceResult" + }, + "GoogleCloudAiplatformV1beta1BatchCancelPipelineJobsResponse": { + "id": "GoogleCloudAiplatformV1beta1BatchCancelPipelineJobsResponse", + "description": "Response message for PipelineService.BatchCancelPipelineJobs.", + "properties": { + "pipelineJobs": { + "description": "PipelineJobs cancelled.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1PipelineJob" + } + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ExplanationMetadataOverride": { + "description": "The ExplanationMetadata entries that can be overridden at online explanation time.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ExplanationMetadataOverride", + "properties": { + "inputs": { + "description": "Required. Overrides the input metadata of the features. The key is the name of the feature to be overridden. The keys specified here must exist in the input metadata to be overridden. If a feature is not specified here, the corresponding feature's input metadata is not overridden.", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1ExplanationMetadataOverrideInputMetadataOverride" + }, + "type": "object" + } + } + }, + "GoogleCloudAiplatformV1beta1ResourceRuntimeSpec": { + "id": "GoogleCloudAiplatformV1beta1ResourceRuntimeSpec", + "type": "object", + "properties": { + "serviceAccountSpec": { + "description": "Optional. Configure the use of workload identity on the PersistentResource", + "$ref": "GoogleCloudAiplatformV1beta1ServiceAccountSpec" + }, + "raySpec": { + "$ref": "GoogleCloudAiplatformV1beta1RaySpec", + "description": "Optional. Ray cluster configuration. Required when creating a dedicated RayCluster on the PersistentResource." + } + }, + "description": "Configuration for the runtime on a PersistentResource instance, including but not limited to: * Service accounts used to run the workloads. * Whether to make it a dedicated Ray Cluster." + }, + "GoogleTypeDate": { + "type": "object", + "description": "Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values. * A month and day, with a zero year (for example, an anniversary). * A year on its own, with a zero month and a zero day. * A year and month, with a zero day (for example, a credit card expiration date). Related types: * google.type.TimeOfDay * google.type.DateTime * google.protobuf.Timestamp", + "properties": { + "month": { + "description": "Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.", + "format": "int32", + "type": "integer" + }, + "day": { + "format": "int32", + "description": "Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn't significant.", + "type": "integer" + }, + "year": { + "format": "int32", + "description": "Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.", + "type": "integer" + } + }, + "id": "GoogleTypeDate" + }, + "CloudAiLargeModelsVisionRaiInfoDetectedLabelsEntity": { + "id": "CloudAiLargeModelsVisionRaiInfoDetectedLabelsEntity", + "properties": { + "iouScore": { + "format": "float", + "type": "number", + "description": "The intersection ratio between the detection bounding box and the mask." + }, + "boundingBox": { + "description": "Bounding box of the label", + "$ref": "CloudAiLargeModelsVisionRaiInfoDetectedLabelsBoundingBox" + }, + "mid": { + "type": "string", + "description": "MID of the label" + }, + "description": { + "type": "string", + "description": "Description of the label" + }, + "score": { + "description": "Confidence score of the label", + "format": "float", + "type": "number" + } + }, + "description": "The properties for a detected entity from the rai signal.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1BatchMigrateResourcesOperationMetadataPartialResult": { + "description": "Represents a partial result in batch migration operation for one MigrateResourceRequest.", + "type": "object", + "properties": { + "dataset": { + "type": "string", + "description": "Migrated dataset resource name." + }, + "model": { + "description": "Migrated model resource name.", + "type": "string" + }, + "error": { + "$ref": "GoogleRpcStatus", + "description": "The error result of the migration request in case of failure." + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1MigrateResourceRequest", + "description": "It's the same as the value in MigrateResourceRequest.migrate_resource_requests." + } + }, + "id": "GoogleCloudAiplatformV1beta1BatchMigrateResourcesOperationMetadataPartialResult" + }, + "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecValue": { + "properties": { + "stringValue": { + "type": "string", + "description": "String type." + }, + "floatValue": { + "description": "Float type.", + "format": "float", + "type": "number" + } + }, + "id": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecValue", + "type": "object", + "description": "Single value that supports strings and floats." + }, + "GoogleCloudAiplatformV1beta1CreateIndexOperationMetadata": { + "type": "object", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "The operation generic information." + }, + "nearestNeighborSearchOperationMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadata", + "description": "The operation metadata with regard to Matching Engine Index operation." + } + }, + "id": "GoogleCloudAiplatformV1beta1CreateIndexOperationMetadata", + "description": "Runtime operation information for IndexService.CreateIndex." + }, + "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityResult": { + "type": "object", + "properties": { + "explanation": { + "readOnly": true, + "type": "string", + "description": "Output only. Explanation for question answering quality score." + }, + "pairwiseChoice": { + "description": "Output only. Pairwise question answering prediction choice.", + "type": "string", + "enum": [ + "PAIRWISE_CHOICE_UNSPECIFIED", + "BASELINE", + "CANDIDATE", + "TIE" + ], + "enumDescriptions": [ + "Unspecified prediction choice.", + "Baseline prediction wins", + "Candidate prediction wins", + "Winner cannot be determined" + ], + "readOnly": true + }, + "confidence": { + "readOnly": true, + "description": "Output only. Confidence for question answering quality score.", + "type": "number", + "format": "float" + } + }, + "id": "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityResult", + "description": "Spec for pairwise question answering quality result." + }, + "GoogleCloudAiplatformV1beta1ListFeaturesResponse": { + "description": "Response message for FeaturestoreService.ListFeatures. Response message for FeatureRegistryService.ListFeatures.", + "type": "object", + "properties": { + "features": { + "description": "The Features matching the request.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Feature" + }, + "type": "array" + }, + "nextPageToken": { + "description": "A token, which can be sent as ListFeaturesRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1ListFeaturesResponse" + }, + "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployDeployMetadata": { + "type": "object", + "description": "Metadata information about the deployment for managing deployment config.", + "properties": { + "labels": { + "description": "Optional. Labels for the deployment. For managing deployment config like verifying, source of deployment config, etc.", + "additionalProperties": { + "type": "string" + }, + "type": "object" + } + }, + "id": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployDeployMetadata" + }, + "GoogleCloudAiplatformV1beta1QuestionAnsweringQualitySpec": { + "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringQualitySpec", + "description": "Spec for question answering quality score metric.", + "properties": { + "useReference": { + "type": "boolean", + "description": "Optional. Whether to use instance.reference to compute question answering quality." + }, + "version": { + "description": "Optional. Which version to use for evaluation.", + "format": "int32", + "type": "integer" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentation": { + "properties": { + "metadata": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentationMetadata", + "description": "The metadata information." + }, + "inputs": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentationInputs", + "description": "The input parameters of this TrainingJob." + } + }, + "type": "object", + "description": "A TrainingJob that trains and uploads an AutoML Image Segmentation Model.", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentation" + }, + "GoogleCloudAiplatformV1beta1SchemaPredictParamsImageObjectDetectionPredictionParams": { + "id": "GoogleCloudAiplatformV1beta1SchemaPredictParamsImageObjectDetectionPredictionParams", + "type": "object", + "description": "Prediction model parameters for Image Object Detection.", + "properties": { + "confidenceThreshold": { + "format": "float", + "type": "number", + "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0" + }, + "maxPredictions": { + "description": "The Model only returns up to that many top, by confidence score, predictions per instance. Note that number of returned predictions is also limited by metadata's predictionsLimit. Default value is 10.", + "format": "int32", + "type": "integer" + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaPredictInstanceTextSentimentPredictionInstance": { + "description": "Prediction input format for Text Sentiment.", + "id": "GoogleCloudAiplatformV1beta1SchemaPredictInstanceTextSentimentPredictionInstance", + "properties": { + "content": { + "type": "string", + "description": "The text snippet to make the predictions on." + }, + "mimeType": { + "description": "The MIME type of the text snippet. The supported MIME types are listed below. - text/plain", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1QueryReasoningEngineResponse": { + "properties": { + "output": { + "description": "Response provided by users in JSON object format.", + "type": "any" + } + }, + "description": "Response message for ReasoningEngineExecutionService.Query", + "id": "GoogleCloudAiplatformV1beta1QueryReasoningEngineResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition": { + "description": "Monitoring alert triggered condition.", + "type": "object", + "properties": { + "threshold": { + "description": "A condition that compares a stats value against a threshold. Alert will be triggered if value above the threshold.", + "format": "double", + "type": "number" + } + }, + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition" + }, + "GoogleCloudAiplatformV1beta1CsvDestination": { + "type": "object", + "description": "The storage details for CSV output content.", + "id": "GoogleCloudAiplatformV1beta1CsvDestination", + "properties": { + "gcsDestination": { + "$ref": "GoogleCloudAiplatformV1beta1GcsDestination", + "description": "Required. Google Cloud Storage location." + } + } + }, + "GoogleCloudAiplatformV1beta1SuggestTrialsMetadata": { + "description": "Details of operations that perform Trials suggestion.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SuggestTrialsMetadata", + "properties": { + "clientId": { + "type": "string", + "description": "The identifier of the client that is requesting the suggestion. If multiple SuggestTrialsRequests have the same `client_id`, the service will return the identical suggested Trial if the Trial is pending, and provide a new Trial if the last suggested Trial was completed." + }, + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "Operation metadata for suggesting Trials." + } + } + }, + "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate": { + "properties": { + "dataPersistentDiskSpec": { + "$ref": "GoogleCloudAiplatformV1beta1PersistentDiskSpec", + "description": "Optional. The specification of persistent disk attached to the runtime as data disk storage." + }, + "createTime": { + "description": "Output only. Timestamp when this NotebookRuntimeTemplate was created.", + "type": "string", + "readOnly": true, + "format": "google-datetime" + }, + "serviceAccount": { + "description": "The service account that the runtime workload runs as. You can use any service account within the same project, but you must have the service account user permission to use the instance. If not specified, the [Compute Engine default service account](https://cloud.google.com/compute/docs/access/service-accounts#default_service_account) is used.", + "type": "string" + }, + "labels": { + "description": "The labels with user-defined metadata to organize the NotebookRuntimeTemplates. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "updateTime": { + "readOnly": true, + "format": "google-datetime", + "type": "string", + "description": "Output only. Timestamp when this NotebookRuntimeTemplate was most recently updated." + }, + "etag": { + "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "shieldedVmConfig": { + "$ref": "GoogleCloudAiplatformV1beta1ShieldedVmConfig", + "description": "Optional. Immutable. Runtime Shielded VM spec." + }, + "machineSpec": { + "description": "Optional. Immutable. The specification of a single machine for the template.", + "$ref": "GoogleCloudAiplatformV1beta1MachineSpec" + }, + "name": { + "description": "The resource name of the NotebookRuntimeTemplate.", + "type": "string" + }, + "networkSpec": { + "$ref": "GoogleCloudAiplatformV1beta1NetworkSpec", + "description": "Optional. Network spec." + }, + "isDefault": { + "type": "boolean", + "description": "Output only. The default template to use if not specified.", + "readOnly": true + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", + "description": "Customer-managed encryption key spec for the notebook runtime." + }, + "idleShutdownConfig": { + "description": "The idle shutdown configuration of NotebookRuntimeTemplate. This config will only be set when idle shutdown is enabled.", + "$ref": "GoogleCloudAiplatformV1beta1NotebookIdleShutdownConfig" + }, + "displayName": { + "description": "Required. The display name of the NotebookRuntimeTemplate. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + }, + "description": { + "description": "The description of the NotebookRuntimeTemplate.", + "type": "string" + }, + "networkTags": { + "type": "array", + "description": "Optional. The Compute Engine tags to add to runtime (see [Tagging instances](https://cloud.google.com/vpc/docs/add-remove-network-tags)).", + "items": { + "type": "string" + } + }, + "eucConfig": { + "description": "EUC configuration of the NotebookRuntimeTemplate.", + "$ref": "GoogleCloudAiplatformV1beta1NotebookEucConfig" + }, + "notebookRuntimeType": { + "enum": [ + "NOTEBOOK_RUNTIME_TYPE_UNSPECIFIED", + "USER_DEFINED", + "ONE_CLICK" + ], + "type": "string", + "description": "Optional. Immutable. The type of the notebook runtime template.", + "enumDescriptions": [ + "Unspecified notebook runtime type, NotebookRuntimeType will default to USER_DEFINED.", + "runtime or template with coustomized configurations from user.", + "runtime or template with system defined configurations." + ] + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate", + "description": "A template that specifies runtime configurations such as machine type, runtime version, network configurations, etc. Multiple runtimes can be created from a runtime template." + }, + "GoogleCloudAiplatformV1beta1ListFeaturestoresResponse": { + "type": "object", + "properties": { + "featurestores": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Featurestore" + }, + "description": "The Featurestores matching the request." + }, + "nextPageToken": { + "description": "A token, which can be sent as ListFeaturestoresRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1ListFeaturestoresResponse", + "description": "Response message for FeaturestoreService.ListFeaturestores." + }, + "GoogleCloudAiplatformV1beta1Examples": { + "description": "Example-based explainability that returns the nearest neighbors from the provided dataset.", + "id": "GoogleCloudAiplatformV1beta1Examples", + "properties": { + "nearestNeighborSearchConfig": { + "description": "The full configuration for the generated index, the semantics are the same as metadata and should match [NearestNeighborSearchConfig](https://cloud.google.com/vertex-ai/docs/explainable-ai/configuring-explanations-example-based#nearest-neighbor-search-config).", + "type": "any" + }, + "gcsSource": { + "description": "The Cloud Storage locations that contain the instances to be indexed for approximate nearest neighbor search.", + "$ref": "GoogleCloudAiplatformV1beta1GcsSource" + }, + "exampleGcsSource": { + "$ref": "GoogleCloudAiplatformV1beta1ExamplesExampleGcsSource", + "description": "The Cloud Storage input instances." + }, + "presets": { + "$ref": "GoogleCloudAiplatformV1beta1Presets", + "description": "Simplified preset configuration, which automatically sets configuration values based on the desired query speed-precision trade-off and modality." + }, + "neighborCount": { + "format": "int32", + "type": "integer", + "description": "The number of neighbors to return when querying for examples." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ExportTensorboardTimeSeriesDataResponse": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ExportTensorboardTimeSeriesDataResponse", + "properties": { + "timeSeriesDataPoints": { + "type": "array", + "description": "The returned time series data points.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1TimeSeriesDataPoint" + } + }, + "nextPageToken": { + "description": "A token, which can be sent as page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + } + }, + "description": "Response message for TensorboardService.ExportTensorboardTimeSeriesData." + }, + "GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponsePerMonthUsageData": { + "type": "object", + "properties": { + "userUsageData": { + "description": "Usage data for each user in the given month.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponsePerUserUsageData" + } + } + }, + "id": "GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponsePerMonthUsageData", + "description": "Per month usage data" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDatasetModelMonitoringGcsSource": { + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDatasetModelMonitoringGcsSource", + "properties": { + "format": { + "type": "string", + "enumDescriptions": [ + "Data format unspecified, used when this field is unset.", + "CSV files.", + "TfRecord files", + "JsonL files." + ], + "description": "Data format of the dataset.", + "enum": [ + "DATA_FORMAT_UNSPECIFIED", + "CSV", + "TF_RECORD", + "JSONL" + ] + }, + "gcsUri": { + "type": "string", + "description": "Google Cloud Storage URI to the input file(s). May contain wildcards. For more information on wildcards, see https://cloud.google.com/storage/docs/gsutil/addlhelp/WildcardNames." + } + }, + "description": "Dataset spec for data stored in Google Cloud Storage.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1CreateEntityTypeOperationMetadata": { + "type": "object", + "description": "Details of operations that perform create EntityType.", + "properties": { + "genericMetadata": { + "description": "Operation metadata for EntityType.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "id": "GoogleCloudAiplatformV1beta1CreateEntityTypeOperationMetadata" + }, + "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecMetricSpec": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecMetricSpec", + "description": "Represents a metric to optimize.", + "properties": { + "metricId": { + "description": "Required. The ID of the metric. Must not contain whitespaces.", + "type": "string" + }, + "goal": { + "enum": [ + "GOAL_TYPE_UNSPECIFIED", + "MAXIMIZE", + "MINIMIZE" + ], + "description": "Required. The optimization goal of the metric.", + "type": "string", + "enumDescriptions": [ + "Goal Type will default to maximize.", + "Maximize the goal metric.", + "Minimize the goal metric." + ] + } + } + }, + "GoogleCloudAiplatformV1beta1RemoveDatapointsResponse": { + "id": "GoogleCloudAiplatformV1beta1RemoveDatapointsResponse", + "properties": {}, + "type": "object", + "description": "Response message for IndexService.RemoveDatapoints" + }, + "GoogleCloudAiplatformV1beta1Tensorboard": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1Tensorboard", + "description": "Tensorboard is a physical database that stores users' training metrics. A default Tensorboard is provided in each region of a Google Cloud project. If needed users can also create extra Tensorboards in their projects.", + "properties": { + "satisfiesPzs": { + "type": "boolean", + "description": "Output only. Reserved for future use.", + "readOnly": true + }, + "etag": { + "type": "string", + "description": "Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + }, + "description": { + "type": "string", + "description": "Description of this Tensorboard." + }, + "labels": { + "description": "The labels with user-defined metadata to organize your Tensorboards. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Tensorboard (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "satisfiesPzi": { + "type": "boolean", + "readOnly": true, + "description": "Output only. Reserved for future use." + }, + "updateTime": { + "format": "google-datetime", + "type": "string", + "readOnly": true, + "description": "Output only. Timestamp when this Tensorboard was last updated." + }, + "isDefault": { + "description": "Used to indicate if the TensorBoard instance is the default one. Each project & region can have at most one default TensorBoard instance. Creation of a default TensorBoard instance and updating an existing TensorBoard instance to be default will mark all other TensorBoard instances (if any) as non default.", + "type": "boolean" + }, + "createTime": { + "format": "google-datetime", + "description": "Output only. Timestamp when this Tensorboard was created.", + "type": "string", + "readOnly": true + }, + "runCount": { + "readOnly": true, + "type": "integer", + "description": "Output only. The number of Runs stored in this Tensorboard.", + "format": "int32" + }, + "encryptionSpec": { + "description": "Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key.", + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" + }, + "name": { + "type": "string", + "description": "Output only. Name of the Tensorboard. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", + "readOnly": true + }, + "displayName": { + "type": "string", + "description": "Required. User provided name of this Tensorboard." + }, + "blobStoragePathPrefix": { + "type": "string", + "readOnly": true, + "description": "Output only. Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'." + } + } + }, + "GoogleCloudAiplatformV1beta1BatchCreateFeaturesResponse": { + "type": "object", + "description": "Response message for FeaturestoreService.BatchCreateFeatures.", + "properties": { + "features": { + "description": "The Features created.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Feature" + } + } + }, + "id": "GoogleCloudAiplatformV1beta1BatchCreateFeaturesResponse" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationCategoricalTransformation": { + "properties": { + "columnName": { + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationCategoricalTransformation", + "type": "object", + "description": "Training pipeline will perform following transformation functions. * The categorical string as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. * Categories that appear less than 5 times in the training dataset are treated as the \"unknown\" category. The \"unknown\" category gets its own special lookup index and resulting embedding." + }, + "GoogleCloudAiplatformV1beta1Blob": { + "description": "Content blob. It's preferred to send as text directly rather than raw bytes.", + "type": "object", + "properties": { + "data": { + "format": "byte", + "description": "Required. Raw bytes.", + "type": "string" + }, + "mimeType": { + "description": "Required. The IANA standard MIME type of the source data.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1Blob" + }, + "GoogleCloudAiplatformV1beta1TFRecordDestination": { + "properties": { + "gcsDestination": { + "$ref": "GoogleCloudAiplatformV1beta1GcsDestination", + "description": "Required. Google Cloud Storage location." + } + }, + "type": "object", + "description": "The storage details for TFRecord output content.", + "id": "GoogleCloudAiplatformV1beta1TFRecordDestination" + }, + "GoogleCloudAiplatformV1beta1Index": { + "id": "GoogleCloudAiplatformV1beta1Index", + "properties": { + "metadataSchemaUri": { + "description": "Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Index, that is specific to it. Unset if the Index does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.", + "type": "string" + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "description": "The labels with user-defined metadata to organize your Indexes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", + "type": "object" + }, + "name": { + "readOnly": true, + "description": "Output only. The resource name of the Index.", + "type": "string" + }, + "description": { + "description": "The description of the Index.", + "type": "string" + }, + "displayName": { + "description": "Required. The display name of the Index. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + }, + "indexStats": { + "$ref": "GoogleCloudAiplatformV1beta1IndexStats", + "readOnly": true, + "description": "Output only. Stats of the index resource." + }, + "createTime": { + "readOnly": true, + "description": "Output only. Timestamp when this Index was created.", + "type": "string", + "format": "google-datetime" + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", + "description": "Immutable. Customer-managed encryption key spec for an Index. If set, this Index and all sub-resources of this Index will be secured by this key." + }, + "updateTime": { + "type": "string", + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Timestamp when this Index was most recently updated. This also includes any update to the contents of the Index. Note that Operations working on this Index may have their Operations.metadata.generic_metadata.update_time a little after the value of this timestamp, yet that does not mean their results are not already reflected in the Index. Result of any successfully completed Operation on the Index is reflected in it." + }, + "indexUpdateMethod": { + "description": "Immutable. The update method to use with this Index. If not set, BATCH_UPDATE will be used by default.", + "enumDescriptions": [ + "Should not be used.", + "BatchUpdate: user can call UpdateIndex with files on Cloud Storage of Datapoints to update.", + "StreamUpdate: user can call UpsertDatapoints/DeleteDatapoints to update the Index and the updates will be applied in corresponding DeployedIndexes in nearly real-time." + ], + "enum": [ + "INDEX_UPDATE_METHOD_UNSPECIFIED", + "BATCH_UPDATE", + "STREAM_UPDATE" + ], + "type": "string" + }, + "etag": { + "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "deployedIndexes": { + "description": "Output only. The pointers to DeployedIndexes created from this Index. An Index can be only deleted if all its DeployedIndexes had been undeployed first.", + "type": "array", + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1beta1DeployedIndexRef" + } + }, + "metadata": { + "description": "An additional information about the Index; the schema of the metadata can be found in metadata_schema.", + "type": "any" + } + }, + "description": "A representation of a collection of database items organized in a way that allows for approximate nearest neighbor (a.k.a ANN) algorithms search.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1CancelNasJobRequest": { + "properties": {}, + "type": "object", + "description": "Request message for JobService.CancelNasJob.", + "id": "GoogleCloudAiplatformV1beta1CancelNasJobRequest" + }, + "GoogleCloudAiplatformV1beta1CoherenceSpec": { + "id": "GoogleCloudAiplatformV1beta1CoherenceSpec", + "description": "Spec for coherence score metric.", + "properties": { + "version": { + "type": "integer", + "description": "Optional. Which version to use for evaluation.", + "format": "int32" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1QuestionAnsweringQualityResult": { + "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringQualityResult", + "properties": { + "explanation": { + "readOnly": true, + "type": "string", + "description": "Output only. Explanation for question answering quality score." + }, + "confidence": { + "format": "float", + "readOnly": true, + "type": "number", + "description": "Output only. Confidence for question answering quality score." + }, + "score": { + "format": "float", + "type": "number", + "description": "Output only. Question Answering Quality score.", + "readOnly": true + } + }, + "description": "Spec for question answering quality result.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationPolygonAnnotation": { + "properties": { + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that this Annotation pertains to." + }, + "vertexes": { + "type": "array", + "description": "The vertexes are connected one by one and the last vertex is connected to the first one to represent a polygon.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaVertex" + } + }, + "annotationSpecId": { + "type": "string", + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationPolygonAnnotation", + "type": "object", + "description": "Represents a polygon in image." + }, + "GoogleCloudAiplatformV1beta1DeployedIndexAuthConfig": { + "description": "Used to set up the auth on the DeployedIndex's private endpoint.", + "id": "GoogleCloudAiplatformV1beta1DeployedIndexAuthConfig", + "type": "object", + "properties": { + "authProvider": { + "$ref": "GoogleCloudAiplatformV1beta1DeployedIndexAuthConfigAuthProvider", + "description": "Defines the authentication provider that the DeployedIndex uses." + } + } + }, + "GoogleCloudAiplatformV1beta1VertexRagStoreRagResource": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1VertexRagStoreRagResource", + "description": "The definition of the Rag resource.", + "properties": { + "ragFileIds": { + "type": "array", + "description": "Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.", + "items": { + "type": "string" + } + }, + "ragCorpus": { + "description": "Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1CopyModelRequest": { + "description": "Request message for ModelService.CopyModel.", + "id": "GoogleCloudAiplatformV1beta1CopyModelRequest", + "properties": { + "parentModel": { + "description": "Optional. Specify this field to copy source_model into this existing Model as a new version. Format: `projects/{project}/locations/{location}/models/{model}`", + "type": "string" + }, + "modelId": { + "type": "string", + "description": "Optional. Copy source_model into a new Model with this ID. The ID will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen." + }, + "sourceModel": { + "type": "string", + "description": "Required. The resource name of the Model to copy. That Model must be in the same Project. Format: `projects/{project}/locations/{location}/models/{model}`" + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", + "description": "Customer-managed encryption key options. If this is set, then the Model copy will be encrypted with the provided encryption key." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ToolCallValidInput": { + "properties": { + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1beta1ToolCallValidSpec", + "description": "Required. Spec for tool call valid metric." + }, + "instances": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ToolCallValidInstance" + }, + "description": "Required. Repeated tool call valid instances." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ToolCallValidInput", + "description": "Input for tool call valid metric." + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecTabularObjective": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecTabularObjective", + "description": "Tabular monitoring objective.", + "properties": { + "featureDriftSpec": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecDataDriftSpec", + "description": "Input feature distribution drift monitoring spec." + }, + "predictionOutputDriftSpec": { + "description": "Prediction output distribution drift monitoring spec.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecDataDriftSpec" + }, + "featureAttributionSpec": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecFeatureAttributionSpec", + "description": "Feature attribution monitoring spec." + } + } + }, + "GoogleCloudAiplatformV1beta1JiraSource": { + "properties": { + "jiraQueries": { + "type": "array", + "description": "Required. The Jira queries.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1JiraSourceJiraQueries" + } + } + }, + "id": "GoogleCloudAiplatformV1beta1JiraSource", + "description": "The Jira source for the ImportRagFilesRequest.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1CountTokensRequest": { + "properties": { + "instances": { + "description": "Optional. The instances that are the input to token counting call. Schema is identical to the prediction schema of the underlying model.", + "items": { + "type": "any" + }, + "type": "array" + }, + "tools": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Tool" + }, + "description": "Optional. A list of `Tools` the model may use to generate the next response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model." + }, + "model": { + "description": "Optional. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`", + "type": "string" + }, + "systemInstruction": { + "$ref": "GoogleCloudAiplatformV1beta1Content", + "description": "Optional. The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph." + }, + "contents": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Content" + }, + "description": "Optional. Input content.", + "type": "array" + } + }, + "description": "Request message for PredictionService.CountTokens.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1CountTokensRequest" + }, + "GoogleCloudAiplatformV1beta1AddTrialMeasurementRequest": { + "id": "GoogleCloudAiplatformV1beta1AddTrialMeasurementRequest", + "description": "Request message for VizierService.AddTrialMeasurement.", + "properties": { + "measurement": { + "description": "Required. The measurement to be added to a Trial.", + "$ref": "GoogleCloudAiplatformV1beta1Measurement" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadataFeatureValueDomain": { + "id": "GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadataFeatureValueDomain", + "type": "object", + "properties": { + "minValue": { + "description": "The minimum permissible value for this feature.", + "format": "float", + "type": "number" + }, + "maxValue": { + "description": "The maximum permissible value for this feature.", + "format": "float", + "type": "number" + }, + "originalStddev": { + "type": "number", + "description": "If this input feature has been normalized to a standard deviation of 1.0, the original_stddev specifies the standard deviation of the domain prior to normalization.", + "format": "float" + }, + "originalMean": { + "format": "float", + "type": "number", + "description": "If this input feature has been normalized to a mean value of 0, the original_mean specifies the mean value of the domain prior to normalization." + } + }, + "description": "Domain details of the input feature value. Provides numeric information about the feature, such as its range (min, max). If the feature has been pre-processed, for example with z-scoring, then it provides information about how to recover the original feature. For example, if the input feature is an image and it has been pre-processed to obtain 0-mean and stddev = 1 values, then original_mean, and original_stddev refer to the mean and stddev of the original feature (e.g. image tensor) from which input feature (with mean = 0 and stddev = 1) was obtained." + }, + "GoogleCloudAiplatformV1beta1CreateModelMonitorOperationMetadata": { + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "The operation generic information." + } + }, + "id": "GoogleCloudAiplatformV1beta1CreateModelMonitorOperationMetadata", + "description": "Runtime operation information for ModelMonitoringService.CreateModelMonitor.", + "type": "object" + }, + "GoogleLongrunningOperation": { + "properties": { + "response": { + "description": "The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.", + "type": "object", + "additionalProperties": { + "description": "Properties of the object. Contains field @type with type URL.", + "type": "any" + } + }, + "metadata": { + "type": "object", + "additionalProperties": { + "description": "Properties of the object. Contains field @type with type URL.", + "type": "any" + }, + "description": "Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any." + }, + "name": { + "type": "string", + "description": "The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`." + }, + "error": { + "description": "The error result of the operation in case of failure or cancellation.", + "$ref": "GoogleRpcStatus" + }, + "done": { + "description": "If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.", + "type": "boolean" + } + }, + "type": "object", + "id": "GoogleLongrunningOperation", + "description": "This resource represents a long-running operation that is the result of a network API call." + }, + "GoogleCloudAiplatformV1beta1Scalar": { + "properties": { + "value": { + "type": "number", + "format": "double", + "description": "Value of the point at this step / timestamp." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1Scalar", + "description": "One point viewable on a scalar metric plot." + }, + "CloudAiLargeModelsVisionNamedBoundingBox": { + "type": "object", + "properties": { + "y2": { + "format": "float", + "type": "number" + }, + "y1": { + "format": "float", + "type": "number" + }, + "x2": { + "format": "float", + "type": "number" + }, + "scores": { + "items": { + "type": "number", + "format": "float" + }, + "type": "array" + }, + "entities": { + "items": { + "type": "string" + }, + "type": "array" + }, + "x1": { + "format": "float", + "type": "number" + }, + "classes": { + "type": "array", + "items": { + "type": "string" + } + } + }, + "id": "CloudAiLargeModelsVisionNamedBoundingBox" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsGeneralTextGenerationEvaluationMetrics": { + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsGeneralTextGenerationEvaluationMetrics", + "properties": { + "bleu": { + "format": "float", + "description": "BLEU (bilingual evaluation understudy) scores based on sacrebleu implementation.", + "type": "number" + }, + "rougeLSum": { + "description": "ROUGE-L (Longest Common Subsequence) scoring at summary level.", + "format": "float", + "type": "number" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ExplainResponseConcurrentExplanation": { + "type": "object", + "properties": { + "explanations": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Explanation" + }, + "description": "The explanations of the Model's PredictResponse.predictions. It has the same number of elements as instances to be explained." + } + }, + "description": "This message is a wrapper grouping Concurrent Explanations.", + "id": "GoogleCloudAiplatformV1beta1ExplainResponseConcurrentExplanation" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsSummarizationEvaluationMetrics": { + "type": "object", + "properties": { + "rougeLSum": { + "type": "number", + "description": "ROUGE-L (Longest Common Subsequence) scoring at summary level.", + "format": "float" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsSummarizationEvaluationMetrics" + }, + "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesResponse": { + "description": "Response message for FeaturestoreService.BatchReadFeatureValues.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesResponse", + "properties": {} + }, + "GoogleCloudAiplatformV1beta1NearestNeighborsNeighbor": { + "type": "object", + "description": "A neighbor of the query vector.", + "id": "GoogleCloudAiplatformV1beta1NearestNeighborsNeighbor", + "properties": { + "distance": { + "format": "double", + "description": "The distance between the neighbor and the query vector.", + "type": "number" + }, + "entityId": { + "type": "string", + "description": "The id of the similar entity." + }, + "entityKeyValues": { + "$ref": "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponse", + "description": "The attributes of the neighbor, e.g. filters, crowding and metadata Note that full entities are returned only when \"return_full_entity\" is set to true. Otherwise, only the \"entity_id\" and \"distance\" fields are populated." + } + } + }, + "GoogleCloudAiplatformV1beta1FeaturestoreOnlineServingConfigScaling": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1FeaturestoreOnlineServingConfigScaling", + "properties": { + "maxNodeCount": { + "format": "int32", + "description": "The maximum number of nodes to scale up to. Must be greater than min_node_count, and less than or equal to 10 times of 'min_node_count'.", + "type": "integer" + }, + "minNodeCount": { + "format": "int32", + "type": "integer", + "description": "Required. The minimum number of nodes to scale down to. Must be greater than or equal to 1." + }, + "cpuUtilizationTarget": { + "description": "Optional. The cpu utilization that the Autoscaler should be trying to achieve. This number is on a scale from 0 (no utilization) to 100 (total utilization), and is limited between 10 and 80. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set or set to 0, default to 50.", + "type": "integer", + "format": "int32" + } + }, + "description": "Online serving scaling configuration. If min_node_count and max_node_count are set to the same value, the cluster will be configured with the fixed number of node (no auto-scaling)." + }, + "GoogleCloudAiplatformV1beta1UndeployIndexResponse": { + "id": "GoogleCloudAiplatformV1beta1UndeployIndexResponse", + "properties": {}, + "description": "Response message for IndexEndpointService.UndeployIndex.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1AssignNotebookRuntimeOperationMetadata": { + "description": "Metadata information for NotebookService.AssignNotebookRuntime.", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "The operation generic information." + }, + "progressMessage": { + "description": "A human-readable message that shows the intermediate progress details of NotebookRuntime.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1AssignNotebookRuntimeOperationMetadata" + }, + "GoogleCloudAiplatformV1beta1PersistentDiskSpec": { + "id": "GoogleCloudAiplatformV1beta1PersistentDiskSpec", + "properties": { + "diskSizeGb": { + "format": "int64", + "type": "string", + "description": "Size in GB of the disk (default is 100GB)." + }, + "diskType": { + "description": "Type of the disk (default is \"pd-standard\"). Valid values: \"pd-ssd\" (Persistent Disk Solid State Drive) \"pd-standard\" (Persistent Disk Hard Disk Drive) \"pd-balanced\" (Balanced Persistent Disk) \"pd-extreme\" (Extreme Persistent Disk)", + "type": "string" + } + }, + "description": "Represents the spec of persistent disk options.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1MeasurementMetric": { + "description": "A message representing a metric in the measurement.", + "id": "GoogleCloudAiplatformV1beta1MeasurementMetric", + "properties": { + "value": { + "readOnly": true, + "format": "double", + "type": "number", + "description": "Output only. The value for this metric." + }, + "metricId": { + "readOnly": true, + "type": "string", + "description": "Output only. The ID of the Metric. The Metric should be defined in StudySpec's Metrics." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1DeployedIndexAuthConfigAuthProvider": { + "id": "GoogleCloudAiplatformV1beta1DeployedIndexAuthConfigAuthProvider", + "properties": { + "audiences": { + "items": { + "type": "string" + }, + "type": "array", + "description": "The list of JWT [audiences](https://tools.ietf.org/html/draft-ietf-oauth-json-web-token-32#section-4.1.3). that are allowed to access. A JWT containing any of these audiences will be accepted." + }, + "allowedIssuers": { + "type": "array", + "items": { + "type": "string" + }, + "description": "A list of allowed JWT issuers. Each entry must be a valid Google service account, in the following format: `service-account-name@project-id.iam.gserviceaccount.com`" + } + }, + "description": "Configuration for an authentication provider, including support for [JSON Web Token (JWT)](https://tools.ietf.org/html/draft-ietf-oauth-json-web-token-32).", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1VertexAISearch": { + "type": "object", + "description": "Retrieve from Vertex AI Search datastore for grounding. See https://cloud.google.com/vertex-ai-search-and-conversation", + "properties": { + "datastore": { + "description": "Required. Fully-qualified Vertex AI Search's datastore resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1VertexAISearch" + }, + "GoogleCloudAiplatformV1beta1PscInterfaceConfig": { + "description": "Configuration for PSC-I.", + "properties": { + "networkAttachment": { + "description": "Optional. The full name of the Compute Engine [network attachment](https://cloud.google.com/vpc/docs/about-network-attachments) to attach to the resource. For example, `projects/12345/regions/us-central1/networkAttachments/myNA`. is of the form `projects/{project}/regions/{region}/networkAttachments/{networkAttachment}`. Where {project} is a project number, as in `12345`, and {networkAttachment} is a network attachment name. To specify this field, you must have already [created a network attachment] (https://cloud.google.com/vpc/docs/create-manage-network-attachments#create-network-attachments). This field is only used for resources using PSC-I.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1PscInterfaceConfig" + }, + "GoogleCloudAiplatformV1beta1StringArray": { + "description": "A list of string values.", + "type": "object", + "properties": { + "values": { + "description": "A list of string values.", + "type": "array", + "items": { + "type": "string" + } + } + }, + "id": "GoogleCloudAiplatformV1beta1StringArray" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextExtractionInputs": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextExtractionInputs", + "properties": {}, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalArrayTransformation": { + "properties": { + "columnName": { + "type": "string" + } + }, + "description": "Treats the column as categorical array and performs following transformation functions. * For each element in the array, convert the category name to a dictionary lookup index and generate an embedding for each index. Combine the embedding of all elements into a single embedding using the mean. * Empty arrays treated as an embedding of zeroes.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalArrayTransformation" + }, + "GoogleCloudAiplatformV1beta1SchemaTextSentimentSavedQueryMetadata": { + "description": "The metadata of SavedQuery contains TextSentiment Annotations.", + "properties": { + "sentimentMax": { + "type": "integer", + "format": "int32", + "description": "The maximum sentiment of sentiment Anntoation in this SavedQuery." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTextSentimentSavedQueryMetadata" + }, + "GoogleCloudAiplatformV1beta1ToolCallValidMetricValue": { + "description": "Tool call valid metric value for an instance.", + "id": "GoogleCloudAiplatformV1beta1ToolCallValidMetricValue", + "type": "object", + "properties": { + "score": { + "description": "Output only. Tool call valid score.", + "readOnly": true, + "format": "float", + "type": "number" + } + } + }, + "GoogleCloudAiplatformV1beta1NotebookExecutionJobGcsNotebookSource": { + "properties": { + "generation": { + "description": "The version of the Cloud Storage object to read. If unset, the current version of the object is read. See https://cloud.google.com/storage/docs/metadata#generation-number.", + "type": "string" + }, + "uri": { + "type": "string", + "description": "The Cloud Storage uri pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`" + } + }, + "description": "The Cloud Storage uri for the input notebook.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1NotebookExecutionJobGcsNotebookSource" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfig": { + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfig", + "properties": { + "notificationChannels": { + "type": "array", + "description": "Resource names of the NotificationChannels to send alert. Must be of the format `projects//notificationChannels/`", + "items": { + "type": "string" + } + }, + "enableLogging": { + "description": "Dump the anomalies to Cloud Logging. The anomalies will be put to json payload encoded from proto google.cloud.aiplatform.logging.ModelMonitoringAnomaliesLogEntry. This can be further sinked to Pub/Sub or any other services supported by Cloud Logging.", + "type": "boolean" + }, + "emailAlertConfig": { + "description": "Email alert config.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfigEmailAlertConfig" + } + }, + "description": "The alert config for model monitoring.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ExecuteExtensionResponse": { + "properties": { + "content": { + "type": "string", + "description": "Response content from the extension. The content should be conformant to the response.content schema in the extension's manifest/OpenAPI spec." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ExecuteExtensionResponse", + "description": "Response message for ExtensionExecutionService.ExecuteExtension." + }, + "GoogleCloudAiplatformV1beta1DeploySolverOperationMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1DeploySolverOperationMetadata", + "description": "Runtime operation information for SolverService.DeploySolver.", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "The generic operation information." + } + } + }, + "CloudAiLargeModelsVisionGenerateVideoResponse": { + "type": "object", + "properties": { + "generatedSamples": { + "description": "The generates samples.", + "items": { + "$ref": "CloudAiLargeModelsVisionMedia" + }, + "type": "array" + }, + "raiMediaFilteredReasons": { + "description": "Returns rai failure reasons if any.", + "type": "array", + "items": { + "type": "string" + } + }, + "raiMediaFilteredCount": { + "description": "Returns if any videos were filtered due to RAI policies.", + "type": "integer", + "format": "int32" + } + }, + "description": "Generate video response.", + "id": "CloudAiLargeModelsVisionGenerateVideoResponse" + }, + "GoogleCloudAiplatformV1beta1SearchFeaturesResponse": { + "id": "GoogleCloudAiplatformV1beta1SearchFeaturesResponse", + "type": "object", + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token, which can be sent as SearchFeaturesRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages." + }, + "features": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Feature" + }, + "type": "array", + "description": "The Features matching the request. Fields returned: * `name` * `description` * `labels` * `create_time` * `update_time`" + } + }, + "description": "Response message for FeaturestoreService.SearchFeatures." + }, + "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringScheduleConfig": { + "description": "The config for scheduling monitoring job.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringScheduleConfig", + "properties": { + "monitorWindow": { + "type": "string", + "description": "The time window of the prediction data being included in each prediction dataset. This window specifies how long the data should be collected from historical model results for each run. If not set, ModelDeploymentMonitoringScheduleConfig.monitor_interval will be used. e.g. If currently the cutoff time is 2022-01-08 14:30:00 and the monitor_window is set to be 3600, then data from 2022-01-08 13:30:00 to 2022-01-08 14:30:00 will be retrieved and aggregated to calculate the monitoring statistics.", + "format": "google-duration" + }, + "monitorInterval": { + "type": "string", + "format": "google-duration", + "description": "Required. The model monitoring job scheduling interval. It will be rounded up to next full hour. This defines how often the monitoring jobs are triggered." + } + } + }, + "CloudAiLargeModelsVisionSemanticFilterResponse": { + "id": "CloudAiLargeModelsVisionSemanticFilterResponse", + "properties": { + "namedBoundingBoxes": { + "description": "Class labels of the bounding boxes that failed the semantic filtering. Bounding box coordinates.", + "items": { + "$ref": "CloudAiLargeModelsVisionNamedBoundingBox" + }, + "type": "array" + }, + "passedSemanticFilter": { + "type": "boolean", + "description": "This response is added when semantic filter config is turned on in EditConfig. It reports if this image is passed semantic filter response. If passed_semantic_filter is false, the bounding box information will be populated for user to check what caused the semantic filter to fail." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoActionRecognition": { + "type": "object", + "description": "A TrainingJob that trains and uploads an AutoML Video Action Recognition Model.", + "properties": { + "inputs": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoActionRecognitionInputs", + "description": "The input parameters of this TrainingJob." + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoActionRecognition" + }, + "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequestPassThroughField": { + "type": "object", + "description": "Describe pass-through fields in read_instance source.", + "properties": { + "fieldName": { + "type": "string", + "description": "Required. The name of the field in the CSV header or the name of the column in BigQuery table. The naming restriction is the same as Feature.name." + } + }, + "id": "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequestPassThroughField" + }, + "GoogleCloudAiplatformV1beta1ToolNameMatchMetricValue": { + "id": "GoogleCloudAiplatformV1beta1ToolNameMatchMetricValue", + "properties": { + "score": { + "format": "float", + "readOnly": true, + "type": "number", + "description": "Output only. Tool name match score." + } + }, + "type": "object", + "description": "Tool name match metric value for an instance." + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringInput": { + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringInput", + "type": "object", + "description": "Model monitoring data input spec.", + "properties": { + "batchPredictionOutput": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringInputBatchPredictionOutput", + "description": "Vertex AI Batch prediction Job." + }, + "timeOffset": { + "description": "The time offset setting for which results should be returned.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringInputTimeOffset" + }, + "timeInterval": { + "$ref": "GoogleTypeInterval", + "description": "The time interval (pair of start_time and end_time) for which results should be returned." + }, + "columnizedDataset": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDataset", + "description": "Columnized dataset." + }, + "vertexEndpointLogs": { + "description": "Vertex AI Endpoint request & response logging.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringInputVertexEndpointLogs" + } + } + }, + "GoogleCloudAiplatformV1beta1CancelDataLabelingJobRequest": { + "description": "Request message for JobService.CancelDataLabelingJob.", + "type": "object", + "properties": {}, + "id": "GoogleCloudAiplatformV1beta1CancelDataLabelingJobRequest" + }, + "GoogleCloudAiplatformV1beta1Retrieval": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1Retrieval", + "description": "Defines a retrieval tool that model can call to access external knowledge.", + "properties": { + "disableAttribution": { + "description": "Optional. Deprecated. This option is no longer supported.", + "type": "boolean", + "deprecated": true + }, + "vertexAiSearch": { + "$ref": "GoogleCloudAiplatformV1beta1VertexAISearch", + "description": "Set to use data source powered by Vertex AI Search." + }, + "vertexRagStore": { + "description": "Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.", + "$ref": "GoogleCloudAiplatformV1beta1VertexRagStore" + } + } + }, + "GoogleCloudAiplatformV1beta1ListReasoningEnginesResponse": { + "description": "Response message for ReasoningEngineService.ListReasoningEngines", + "type": "object", + "properties": { + "reasoningEngines": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngine" + }, + "description": "List of ReasoningEngines in the requested page.", + "type": "array" + }, + "nextPageToken": { + "description": "A token to retrieve the next page of results. Pass to ListReasoningEnginesRequest.page_token to obtain that page.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1ListReasoningEnginesResponse" + }, + "GoogleCloudAiplatformV1beta1QueryDeployedModelsResponse": { + "type": "object", + "description": "Response message for QueryDeployedModels method.", + "id": "GoogleCloudAiplatformV1beta1QueryDeployedModelsResponse", + "properties": { + "deployedModels": { + "type": "array", + "deprecated": true, + "description": "DEPRECATED Use deployed_model_refs instead.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1DeployedModel" + } + }, + "nextPageToken": { + "description": "A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + }, + "deployedModelRefs": { + "description": "References to the DeployedModels that share the specified deploymentResourcePool.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1DeployedModelRef" + } + }, + "totalEndpointCount": { + "format": "int32", + "type": "integer", + "description": "The total number of Endpoints that have DeployedModels on this DeploymentResourcePool." + }, + "totalDeployedModelCount": { + "format": "int32", + "description": "The total number of DeployedModels on this DeploymentResourcePool.", + "type": "integer" + } + } + }, + "GoogleCloudAiplatformV1beta1GoogleDriveSource": { + "description": "The Google Drive location for the input content.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1GoogleDriveSource", + "properties": { + "resourceIds": { + "type": "array", + "description": "Required. Google Drive resource IDs.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1GoogleDriveSourceResourceId" + } + } + } + }, + "GoogleCloudAiplatformV1beta1DedicatedResources": { + "type": "object", + "description": "A description of resources that are dedicated to a DeployedModel, and that need a higher degree of manual configuration.", + "properties": { + "minReplicaCount": { + "type": "integer", + "description": "Required. Immutable. The minimum number of machine replicas this DeployedModel will be always deployed on. This value must be greater than or equal to 1. If traffic against the DeployedModel increases, it may dynamically be deployed onto more replicas, and as traffic decreases, some of these extra replicas may be freed.", + "format": "int32" + }, + "autoscalingMetricSpecs": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1AutoscalingMetricSpec" + }, + "description": "Immutable. The metric specifications that overrides a resource utilization metric (CPU utilization, accelerator's duty cycle, and so on) target value (default to 60 if not set). At most one entry is allowed per metric. If machine_spec.accelerator_count is above 0, the autoscaling will be based on both CPU utilization and accelerator's duty cycle metrics and scale up when either metrics exceeds its target value while scale down if both metrics are under their target value. The default target value is 60 for both metrics. If machine_spec.accelerator_count is 0, the autoscaling will be based on CPU utilization metric only with default target value 60 if not explicitly set. For example, in the case of Online Prediction, if you want to override target CPU utilization to 80, you should set autoscaling_metric_specs.metric_name to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and autoscaling_metric_specs.target to `80`." + }, + "machineSpec": { + "$ref": "GoogleCloudAiplatformV1beta1MachineSpec", + "description": "Required. Immutable. The specification of a single machine used by the prediction." + }, + "maxReplicaCount": { + "format": "int32", + "type": "integer", + "description": "Immutable. The maximum number of replicas this DeployedModel may be deployed on when the traffic against it increases. If the requested value is too large, the deployment will error, but if deployment succeeds then the ability to scale the model to that many replicas is guaranteed (barring service outages). If traffic against the DeployedModel increases beyond what its replicas at maximum may handle, a portion of the traffic will be dropped. If this value is not provided, will use min_replica_count as the default value. The value of this field impacts the charge against Vertex CPU and GPU quotas. Specifically, you will be charged for (max_replica_count * number of cores in the selected machine type) and (max_replica_count * number of GPUs per replica in the selected machine type)." + } + }, + "id": "GoogleCloudAiplatformV1beta1DedicatedResources" + }, + "GoogleCloudAiplatformV1beta1ShieldedVmConfig": { + "description": "A set of Shielded Instance options. See [Images using supported Shielded VM features](https://cloud.google.com/compute/docs/instances/modifying-shielded-vm).", + "properties": { + "enableSecureBoot": { + "type": "boolean", + "description": "Defines whether the instance has [Secure Boot](https://cloud.google.com/compute/shielded-vm/docs/shielded-vm#secure-boot) enabled. Secure Boot helps ensure that the system only runs authentic software by verifying the digital signature of all boot components, and halting the boot process if signature verification fails." + } + }, + "id": "GoogleCloudAiplatformV1beta1ShieldedVmConfig", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTrackMetricsConfidenceMetrics": { + "description": "Metrics for a single confidence threshold.", + "properties": { + "confidenceThreshold": { + "format": "float", + "type": "number", + "description": "The confidence threshold value used to compute the metrics." + }, + "trackingRecall": { + "format": "float", + "type": "number", + "description": "Tracking recall." + }, + "trackingPrecision": { + "type": "number", + "description": "Tracking precision.", + "format": "float" + }, + "boundingBoxIou": { + "format": "float", + "description": "Bounding box intersection-over-union precision. Measures how well the bounding boxes overlap between each other (e.g. complete overlap or just barely above iou_threshold).", + "type": "number" + }, + "mismatchRate": { + "format": "float", + "type": "number", + "description": "Mismatch rate, which measures the tracking consistency, i.e. correctness of instance ID continuity." + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTrackMetricsConfidenceMetrics", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationAutoTransformation": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationAutoTransformation", + "properties": { + "columnName": { + "type": "string" + } + }, + "type": "object", + "description": "Training pipeline will infer the proper transformation based on the statistic of dataset." + }, + "GoogleCloudAiplatformV1beta1SafetyResult": { + "description": "Spec for safety result.", + "properties": { + "score": { + "readOnly": true, + "description": "Output only. Safety score.", + "format": "float", + "type": "number" + }, + "confidence": { + "readOnly": true, + "description": "Output only. Confidence for safety score.", + "format": "float", + "type": "number" + }, + "explanation": { + "readOnly": true, + "description": "Output only. Explanation for safety score.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1SafetyResult", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1StructValue": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1StructValue", + "properties": { + "values": { + "type": "array", + "description": "A list of field values.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1StructFieldValue" + } + } + }, + "description": "Struct (or object) type feature value." + }, + "GoogleCloudAiplatformV1beta1SchemaPredictParamsVideoActionRecognitionPredictionParams": { + "type": "object", + "properties": { + "confidenceThreshold": { + "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0", + "format": "float", + "type": "number" + }, + "maxPredictions": { + "format": "int32", + "description": "The model only returns up to that many top, by confidence score, predictions per frame of the video. If this number is very high, the Model may return fewer predictions per frame. Default value is 50.", + "type": "integer" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaPredictParamsVideoActionRecognitionPredictionParams", + "description": "Prediction model parameters for Video Action Recognition." + }, + "GoogleCloudAiplatformV1beta1ListCustomJobsResponse": { + "description": "Response message for JobService.ListCustomJobs", + "type": "object", + "properties": { + "customJobs": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1CustomJob" + }, + "type": "array", + "description": "List of CustomJobs in the requested page." + }, + "nextPageToken": { + "type": "string", + "description": "A token to retrieve the next page of results. Pass to ListCustomJobsRequest.page_token to obtain that page." + } + }, + "id": "GoogleCloudAiplatformV1beta1ListCustomJobsResponse" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingMetadata": { + "description": "Model metadata specific to AutoML Forecasting.", + "properties": { + "evaluatedDataItemsBigqueryUri": { + "description": "BigQuery destination uri for exported evaluated examples.", + "type": "string" + }, + "trainCostMilliNodeHours": { + "description": "Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget.", + "format": "int64", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingMetadata" + }, + "GoogleCloudAiplatformV1beta1BoolArray": { + "properties": { + "values": { + "type": "array", + "description": "A list of bool values.", + "items": { + "type": "boolean" + } + } + }, + "description": "A list of boolean values.", + "id": "GoogleCloudAiplatformV1beta1BoolArray", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetailProcessedDataset": { + "properties": { + "timeRange": { + "$ref": "GoogleTypeInterval", + "description": "Dataset time range information if any." + }, + "location": { + "type": "string", + "description": "Actual data location of the processed dataset." + } + }, + "description": "Processed dataset information.", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetailProcessedDataset", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1AuthConfig": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1AuthConfig", + "properties": { + "authType": { + "enum": [ + "AUTH_TYPE_UNSPECIFIED", + "NO_AUTH", + "API_KEY_AUTH", + "HTTP_BASIC_AUTH", + "GOOGLE_SERVICE_ACCOUNT_AUTH", + "OAUTH", + "OIDC_AUTH" + ], + "description": "Type of auth scheme.", + "type": "string", + "enumDescriptions": [ + "", + "No Auth.", + "API Key Auth.", + "HTTP Basic Auth.", + "Google Service Account Auth.", + "OAuth auth.", + "OpenID Connect (OIDC) Auth." + ] + }, + "apiKeyConfig": { + "description": "Config for API key auth.", + "$ref": "GoogleCloudAiplatformV1beta1AuthConfigApiKeyConfig" + }, + "httpBasicAuthConfig": { + "description": "Config for HTTP Basic auth.", + "$ref": "GoogleCloudAiplatformV1beta1AuthConfigHttpBasicAuthConfig" + }, + "oidcConfig": { + "description": "Config for user OIDC auth.", + "$ref": "GoogleCloudAiplatformV1beta1AuthConfigOidcConfig" + }, + "googleServiceAccountConfig": { + "$ref": "GoogleCloudAiplatformV1beta1AuthConfigGoogleServiceAccountConfig", + "description": "Config for Google Service Account auth." + }, + "oauthConfig": { + "$ref": "GoogleCloudAiplatformV1beta1AuthConfigOauthConfig", + "description": "Config for user oauth." + } + }, + "description": "Auth configuration to run the extension." + }, + "GoogleCloudAiplatformV1beta1NotebookIdleShutdownConfig": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1NotebookIdleShutdownConfig", + "description": "The idle shutdown configuration of NotebookRuntimeTemplate, which contains the idle_timeout as required field.", + "properties": { + "idleTimeout": { + "type": "string", + "description": "Required. Duration is accurate to the second. In Notebook, Idle Timeout is accurate to minute so the range of idle_timeout (second) is: 10 * 60 ~ 1440 * 60.", + "format": "google-duration" + }, + "idleShutdownDisabled": { + "type": "boolean", + "description": "Whether Idle Shutdown is disabled in this NotebookRuntimeTemplate." + } + } + }, + "GoogleCloudAiplatformV1beta1IndexDatapointNumericRestriction": { + "properties": { + "valueDouble": { + "format": "double", + "description": "Represents 64 bit float.", + "type": "number" + }, + "namespace": { + "description": "The namespace of this restriction. e.g.: cost.", + "type": "string" + }, + "valueFloat": { + "type": "number", + "format": "float", + "description": "Represents 32 bit float." + }, + "op": { + "enum": [ + "OPERATOR_UNSPECIFIED", + "LESS", + "LESS_EQUAL", + "EQUAL", + "GREATER_EQUAL", + "GREATER", + "NOT_EQUAL" + ], + "type": "string", + "enumDescriptions": [ + "Default value of the enum.", + "Datapoints are eligible iff their value is \u003c the query's.", + "Datapoints are eligible iff their value is \u003c= the query's.", + "Datapoints are eligible iff their value is == the query's.", + "Datapoints are eligible iff their value is \u003e= the query's.", + "Datapoints are eligible iff their value is \u003e the query's.", + "Datapoints are eligible iff their value is != the query's." + ], + "description": "This MUST be specified for queries and must NOT be specified for datapoints." + }, + "valueInt": { + "type": "string", + "format": "int64", + "description": "Represents 64 bit integer." + } + }, + "id": "GoogleCloudAiplatformV1beta1IndexDatapointNumericRestriction", + "type": "object", + "description": "This field allows restricts to be based on numeric comparisons rather than categorical tokens." + }, + "CloudAiLargeModelsVisionImageRAIScores": { + "id": "CloudAiLargeModelsVisionImageRAIScores", + "properties": { + "agileWatermarkDetectionScore": { + "description": "Agile watermark score for image.", + "format": "double", + "type": "number" + } + }, + "description": "RAI scores for generated image returned.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1IdMatcher": { + "type": "object", + "description": "Matcher for Features of an EntityType by Feature ID.", + "id": "GoogleCloudAiplatformV1beta1IdMatcher", + "properties": { + "ids": { + "description": "Required. The following are accepted as `ids`: * A single-element list containing only `*`, which selects all Features in the target EntityType, or * A list containing only Feature IDs, which selects only Features with those IDs in the target EntityType.", + "items": { + "type": "string" + }, + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1beta1ListDeploymentResourcePoolsResponse": { + "id": "GoogleCloudAiplatformV1beta1ListDeploymentResourcePoolsResponse", + "description": "Response message for ListDeploymentResourcePools method.", + "properties": { + "nextPageToken": { + "description": "A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + }, + "deploymentResourcePools": { + "description": "The DeploymentResourcePools from the specified location.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1DeploymentResourcePool" + }, + "type": "array" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpecNotificationChannelConfig": { + "properties": { + "notificationChannel": { + "type": "string", + "description": "Resource names of the NotificationChannels. Must be of the format `projects//notificationChannels/`" + } + }, + "description": "Google Cloud Notification Channel config.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpecNotificationChannelConfig" + }, + "GoogleCloudAiplatformV1beta1Value": { + "properties": { + "stringValue": { + "type": "string", + "description": "A string value." + }, + "intValue": { + "description": "An integer value.", + "format": "int64", + "type": "string" + }, + "doubleValue": { + "type": "number", + "description": "A double value.", + "format": "double" + } + }, + "id": "GoogleCloudAiplatformV1beta1Value", + "type": "object", + "description": "Value is the value of the field." + }, + "GoogleCloudAiplatformV1beta1NearestNeighborQuery": { + "id": "GoogleCloudAiplatformV1beta1NearestNeighborQuery", + "description": "A query to find a number of similar entities.", + "properties": { + "entityId": { + "type": "string", + "description": "Optional. The entity id whose similar entities should be searched for. If embedding is set, search will use embedding instead of entity_id." + }, + "neighborCount": { + "type": "integer", + "description": "Optional. The number of similar entities to be retrieved from feature view for each query.", + "format": "int32" + }, + "stringFilters": { + "description": "Optional. The list of string filters.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborQueryStringFilter" + } + }, + "parameters": { + "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborQueryParameters", + "description": "Optional. Parameters that can be set to tune query on the fly." + }, + "numericFilters": { + "description": "Optional. The list of numeric filters.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborQueryNumericFilter" + } + }, + "embedding": { + "description": "Optional. The embedding vector that be used for similar search.", + "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborQueryEmbedding" + }, + "perCrowdingAttributeNeighborCount": { + "format": "int32", + "description": "Optional. Crowding is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than sper_crowding_attribute_neighbor_count of the k neighbors returned have the same value of crowding_attribute. It's used for improving result diversity.", + "type": "integer" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1DeployIndexRequest": { + "properties": { + "deployedIndex": { + "description": "Required. The DeployedIndex to be created within the IndexEndpoint.", + "$ref": "GoogleCloudAiplatformV1beta1DeployedIndex" + } + }, + "id": "GoogleCloudAiplatformV1beta1DeployIndexRequest", + "type": "object", + "description": "Request message for IndexEndpointService.DeployIndex." + }, + "GoogleCloudAiplatformV1beta1GroundednessResult": { + "description": "Spec for groundedness result.", + "properties": { + "explanation": { + "readOnly": true, + "description": "Output only. Explanation for groundedness score.", + "type": "string" + }, + "score": { + "format": "float", + "description": "Output only. Groundedness score.", + "readOnly": true, + "type": "number" + }, + "confidence": { + "description": "Output only. Confidence for groundedness score.", + "type": "number", + "readOnly": true, + "format": "float" + } + }, + "id": "GoogleCloudAiplatformV1beta1GroundednessResult", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsGranularity": { + "description": "A duration of time expressed in time granularity units.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsGranularity", + "properties": { + "quantity": { + "description": "The number of granularity_units between data points in the training data. If `granularity_unit` is `minute`, can be 1, 5, 10, 15, or 30. For all other values of `granularity_unit`, must be 1.", + "type": "string", + "format": "int64" + }, + "unit": { + "type": "string", + "description": "The time granularity unit of this time period. The supported units are: * \"minute\" * \"hour\" * \"day\" * \"week\" * \"month\" * \"year\"" + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataGcsSource": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataGcsSource", + "properties": { + "uri": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Cloud Storage URI of one or more files. Only CSV files are supported. The first line of the CSV file is used as the header. If there are multiple files, the header is the first line of the lexicographically first file, the other files must either contain the exact same header or omit the header." + } + } + }, + "GoogleCloudAiplatformV1beta1SlackSourceSlackChannelsSlackChannel": { + "id": "GoogleCloudAiplatformV1beta1SlackSourceSlackChannelsSlackChannel", + "properties": { + "startTime": { + "format": "google-datetime", + "description": "Optional. The starting timestamp for messages to import.", + "type": "string" + }, + "channelId": { + "description": "Required. The Slack channel ID.", + "type": "string" + }, + "endTime": { + "format": "google-datetime", + "type": "string", + "description": "Optional. The ending timestamp for messages to import." + } + }, + "type": "object", + "description": "SlackChannel contains the Slack channel ID and the time range to import." + }, + "GoogleCloudAiplatformV1beta1BatchMigrateResourcesRequest": { + "properties": { + "migrateResourceRequests": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1MigrateResourceRequest" + }, + "type": "array", + "description": "Required. The request messages specifying the resources to migrate. They must be in the same location as the destination. Up to 50 resources can be migrated in one batch." + } + }, + "id": "GoogleCloudAiplatformV1beta1BatchMigrateResourcesRequest", + "description": "Request message for MigrationService.BatchMigrateResources.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1NearestNeighbors": { + "description": "Nearest neighbors for one query.", + "type": "object", + "properties": { + "neighbors": { + "description": "All its neighbors.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborsNeighbor" + } + } + }, + "id": "GoogleCloudAiplatformV1beta1NearestNeighbors" + }, + "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponseFeatureNameValuePairListFeatureNameValuePair": { + "type": "object", + "description": "Feature name & value pair.", + "properties": { + "name": { + "type": "string", + "description": "Feature short name." + }, + "value": { + "description": "Feature value.", + "$ref": "GoogleCloudAiplatformV1beta1FeatureValue" + } + }, + "id": "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponseFeatureNameValuePairListFeatureNameValuePair" + }, + "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessInstance": { + "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessInstance", + "type": "object", + "properties": { + "reference": { + "description": "Optional. Ground truth used to compare against the prediction.", + "type": "string" + }, + "instruction": { + "description": "Required. The question asked and other instruction in the inference prompt.", + "type": "string" + }, + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + }, + "context": { + "type": "string", + "description": "Optional. Text provided as context to answer the question." + } + }, + "description": "Spec for question answering helpfulness instance." + }, + "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplateRef": { + "description": "Points to a NotebookRuntimeTemplateRef.", + "type": "object", + "properties": { + "notebookRuntimeTemplate": { + "description": "Immutable. A resource name of the NotebookRuntimeTemplate.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplateRef" + }, + "GoogleCloudAiplatformV1beta1ContainerRegistryDestination": { + "type": "object", + "description": "The Container Registry location for the container image.", + "id": "GoogleCloudAiplatformV1beta1ContainerRegistryDestination", + "properties": { + "outputUri": { + "type": "string", + "description": "Required. Container Registry URI of a container image. Only Google Container Registry and Artifact Registry are supported now. Accepted forms: * Google Container Registry path. For example: `gcr.io/projectId/imageName:tag`. * Artifact Registry path. For example: `us-central1-docker.pkg.dev/projectId/repoName/imageName:tag`. If a tag is not specified, \"latest\" will be used as the default tag." + } + } + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig": { + "description": "The config for Prediction data drift detection.", + "properties": { + "driftThresholds": { + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1ThresholdConfig" + }, + "description": "Key is the feature name and value is the threshold. If a feature needs to be monitored for drift, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between different time windws.", + "type": "object" + }, + "attributionScoreDriftThresholds": { + "type": "object", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1ThresholdConfig" + }, + "description": "Key is the feature name and value is the threshold. The threshold here is against attribution score distance between different time windows." + }, + "defaultDriftThreshold": { + "description": "Drift anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.", + "$ref": "GoogleCloudAiplatformV1beta1ThresholdConfig" + } + }, + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ImportFeatureValuesResponse": { + "type": "object", + "description": "Response message for FeaturestoreService.ImportFeatureValues.", + "properties": { + "invalidRowCount": { + "type": "string", + "format": "int64", + "description": "The number of rows in input source that weren't imported due to either * Not having any featureValues. * Having a null entityId. * Having a null timestamp. * Not being parsable (applicable for CSV sources)." + }, + "timestampOutsideRetentionRowsCount": { + "description": "The number rows that weren't ingested due to having feature timestamps outside the retention boundary.", + "format": "int64", + "type": "string" + }, + "importedEntityCount": { + "type": "string", + "description": "Number of entities that have been imported by the operation.", + "format": "int64" + }, + "importedFeatureValueCount": { + "description": "Number of Feature values that have been imported by the operation.", + "format": "int64", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1ImportFeatureValuesResponse" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageObjectDetectionEvaluationMetrics": { + "description": "Metrics for image object detection evaluation results.", + "properties": { + "boundingBoxMetrics": { + "description": "The bounding boxes match metrics for each intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetrics" + }, + "type": "array" + }, + "evaluatedBoundingBoxCount": { + "type": "integer", + "format": "int32", + "description": "The total number of bounding boxes (i.e. summed over all images) the ground truth used to create this evaluation had." + }, + "boundingBoxMeanAveragePrecision": { + "type": "number", + "description": "The single metric for bounding boxes evaluation: the `meanAveragePrecision` averaged over all `boundingBoxMetricsEntries`.", + "format": "float" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageObjectDetectionEvaluationMetrics" + }, + "GoogleCloudAiplatformV1beta1RagFileChunkingConfig": { + "id": "GoogleCloudAiplatformV1beta1RagFileChunkingConfig", + "properties": { + "chunkOverlap": { + "description": "The overlap between chunks.", + "format": "int32", + "type": "integer" + }, + "chunkSize": { + "description": "The size of the chunks.", + "format": "int32", + "type": "integer" + } + }, + "description": "Specifies the size and overlap of chunks for RagFiles.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FeatureViewDataKeyCompositeKey": { + "description": "ID that is comprised from several parts (columns).", + "properties": { + "parts": { + "description": "Parts to construct Entity ID. Should match with the same ID columns as defined in FeatureView in the same order.", + "items": { + "type": "string" + }, + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1beta1FeatureViewDataKeyCompositeKey", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1TensorboardBlob": { + "type": "object", + "properties": { + "id": { + "type": "string", + "description": "Output only. A URI safe key uniquely identifying a blob. Can be used to locate the blob stored in the Cloud Storage bucket of the consumer project.", + "readOnly": true + }, + "data": { + "description": "Optional. The bytes of the blob is not present unless it's returned by the ReadTensorboardBlobData endpoint.", + "format": "byte", + "type": "string" + } + }, + "description": "One blob (e.g, image, graph) viewable on a blob metric plot.", + "id": "GoogleCloudAiplatformV1beta1TensorboardBlob" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationNumericTransformation": { + "type": "object", + "properties": { + "columnName": { + "type": "string" + } + }, + "description": "Training pipeline will perform following transformation functions. * The value converted to float32. * The z_score of the value. * log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationNumericTransformation" + }, + "GoogleCloudAiplatformV1beta1Context": { + "properties": { + "name": { + "type": "string", + "description": "Immutable. The resource name of the Context." + }, + "description": { + "type": "string", + "description": "Description of the Context" + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "description": "The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).", + "type": "object" + }, + "updateTime": { + "readOnly": true, + "type": "string", + "format": "google-datetime", + "description": "Output only. Timestamp when this Context was last updated." + }, + "metadata": { + "type": "object", + "additionalProperties": { + "type": "any", + "description": "Properties of the object." + }, + "description": "Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB." + }, + "parentContexts": { + "type": "array", + "items": { + "type": "string" + }, + "readOnly": true, + "description": "Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts." + }, + "displayName": { + "description": "User provided display name of the Context. May be up to 128 Unicode characters.", + "type": "string" + }, + "etag": { + "type": "string", + "description": "An eTag used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + }, + "schemaVersion": { + "type": "string", + "description": "The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store." + }, + "createTime": { + "description": "Output only. Timestamp when this Context was created.", + "readOnly": true, + "format": "google-datetime", + "type": "string" + }, + "schemaTitle": { + "description": "The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1Context", + "type": "object", + "description": "Instance of a general context." + }, + "GoogleCloudAiplatformV1beta1SlackSourceSlackChannels": { + "properties": { + "apiKeyConfig": { + "$ref": "GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig", + "description": "Required. The SecretManager secret version resource name (e.g. projects/{project}/secrets/{secret}/versions/{version}) storing the Slack channel access token that has access to the slack channel IDs. See: https://api.slack.com/tutorials/tracks/getting-a-token." + }, + "channels": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SlackSourceSlackChannelsSlackChannel" + }, + "type": "array", + "description": "Required. The Slack channel IDs." + } + }, + "id": "GoogleCloudAiplatformV1beta1SlackSourceSlackChannels", + "type": "object", + "description": "SlackChannels contains the Slack channels and corresponding access token." + }, + "GoogleCloudAiplatformV1beta1RemoveDatapointsRequest": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1RemoveDatapointsRequest", + "description": "Request message for IndexService.RemoveDatapoints", + "properties": { + "datapointIds": { + "items": { + "type": "string" + }, + "type": "array", + "description": "A list of datapoint ids to be deleted." + } + } + }, + "GoogleCloudAiplatformV1beta1ExplanationSpecOverride": { + "id": "GoogleCloudAiplatformV1beta1ExplanationSpecOverride", + "description": "The ExplanationSpec entries that can be overridden at online explanation time.", + "type": "object", + "properties": { + "parameters": { + "$ref": "GoogleCloudAiplatformV1beta1ExplanationParameters", + "description": "The parameters to be overridden. Note that the attribution method cannot be changed. If not specified, no parameter is overridden." + }, + "examplesOverride": { + "description": "The example-based explanations parameter overrides.", + "$ref": "GoogleCloudAiplatformV1beta1ExamplesOverride" + }, + "metadata": { + "description": "The metadata to be overridden. If not specified, no metadata is overridden.", + "$ref": "GoogleCloudAiplatformV1beta1ExplanationMetadataOverride" + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaTextExtractionAnnotation": { + "description": "Annotation details specific to text extraction.", + "id": "GoogleCloudAiplatformV1beta1SchemaTextExtractionAnnotation", + "type": "object", + "properties": { + "annotationSpecId": { + "type": "string", + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." + }, + "textSegment": { + "description": "The segment of the text content.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaTextSegment" + }, + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that this Annotation pertains to." + } + } + }, + "GoogleCloudAiplatformV1beta1ExtensionPrivateServiceConnectConfig": { + "description": "PrivateExtensionConfig configuration for the extension.", + "properties": { + "serviceDirectory": { + "type": "string", + "description": "Required. The Service Directory resource name in which the service endpoints associated to the extension are registered. Format: `projects/{project_id}/locations/{location_id}/namespaces/{namespace_id}/services/{service_id}` - The Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) should be granted `servicedirectory.viewer` and `servicedirectory.pscAuthorizedService` roles on the resource." + } + }, + "id": "GoogleCloudAiplatformV1beta1ExtensionPrivateServiceConnectConfig", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1CitationMetadata": { + "properties": { + "citations": { + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Citation" + }, + "description": "Output only. List of citations.", + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1beta1CitationMetadata", + "type": "object", + "description": "A collection of source attributions for a piece of content." + }, + "GoogleCloudAiplatformV1beta1SchemaTextDatasetMetadata": { + "description": "The metadata of Datasets that contain Text DataItems.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTextDatasetMetadata", + "properties": { + "gcsBucket": { + "type": "string", + "description": "Google Cloud Storage Bucket name that contains the blob data of this Dataset." + }, + "dataItemSchemaUri": { + "type": "string", + "description": "Points to a YAML file stored on Google Cloud Storage describing payload of the Text DataItems that belong to this Dataset." + } + } + }, + "GoogleCloudAiplatformV1beta1UpdateDeploymentResourcePoolOperationMetadata": { + "type": "object", + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "description": "Runtime operation information for UpdateDeploymentResourcePool method.", + "id": "GoogleCloudAiplatformV1beta1UpdateDeploymentResourcePoolOperationMetadata" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigTrainingDataset": { + "properties": { + "dataset": { + "description": "The resource name of the Dataset used to train this Model.", + "type": "string" + }, + "loggingSamplingStrategy": { + "$ref": "GoogleCloudAiplatformV1beta1SamplingStrategy", + "description": "Strategy to sample data from Training Dataset. If not set, we process the whole dataset." + }, + "targetField": { + "description": "The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.", + "type": "string" + }, + "bigquerySource": { + "$ref": "GoogleCloudAiplatformV1beta1BigQuerySource", + "description": "The BigQuery table of the unmanaged Dataset used to train this Model." + }, + "gcsSource": { + "$ref": "GoogleCloudAiplatformV1beta1GcsSource", + "description": "The Google Cloud Storage uri of the unmanaged Dataset used to train this Model." + }, + "dataFormat": { + "description": "Data format of the dataset, only applicable if the input is from Google Cloud Storage. The possible formats are: \"tf-record\" The source file is a TFRecord file. \"csv\" The source file is a CSV file. \"jsonl\" The source file is a JSONL file.", + "type": "string" + } + }, + "description": "Training Dataset information.", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigTrainingDataset", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ExportFeatureValuesRequestSnapshotExport": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ExportFeatureValuesRequestSnapshotExport", + "properties": { + "startTime": { + "description": "Excludes Feature values with feature generation timestamp before this timestamp. If not set, retrieve oldest values kept in Feature Store. Timestamp, if present, must not have higher than millisecond precision.", + "format": "google-datetime", + "type": "string" + }, + "snapshotTime": { + "format": "google-datetime", + "description": "Exports Feature values as of this timestamp. If not set, retrieve values as of now. Timestamp, if present, must not have higher than millisecond precision.", + "type": "string" + } + }, + "description": "Describes exporting the latest Feature values of all entities of the EntityType between [start_time, snapshot_time]." + }, + "GoogleCloudAiplatformV1beta1PurgeContextsRequest": { + "id": "GoogleCloudAiplatformV1beta1PurgeContextsRequest", + "properties": { + "filter": { + "description": "Required. A required filter matching the Contexts to be purged. E.g., `update_time \u003c= 2020-11-19T11:30:00-04:00`.", + "type": "string" + }, + "force": { + "description": "Optional. Flag to indicate to actually perform the purge. If `force` is set to false, the method will return a sample of Context names that would be deleted.", + "type": "boolean" + } + }, + "type": "object", + "description": "Request message for MetadataService.PurgeContexts." + }, + "GoogleCloudAiplatformV1beta1CancelTuningJobRequest": { + "description": "Request message for GenAiTuningService.CancelTuningJob.", + "id": "GoogleCloudAiplatformV1beta1CancelTuningJobRequest", + "properties": {}, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ModelMonitorModelMonitoringTargetVertexModelSource": { + "id": "GoogleCloudAiplatformV1beta1ModelMonitorModelMonitoringTargetVertexModelSource", + "type": "object", + "properties": { + "model": { + "type": "string", + "description": "Model resource name. Format: projects/{project}/locations/{location}/models/{model}." + }, + "modelVersionId": { + "description": "Model version id.", + "type": "string" + } + }, + "description": "Model in Vertex AI Model Registry." + }, + "GoogleCloudAiplatformV1beta1ThresholdConfig": { + "description": "The config for feature monitoring threshold.", + "id": "GoogleCloudAiplatformV1beta1ThresholdConfig", + "type": "object", + "properties": { + "value": { + "format": "double", + "type": "number", + "description": "Specify a threshold value that can trigger the alert. If this threshold config is for feature distribution distance: 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature." + } + } + }, + "GoogleCloudAiplatformV1beta1DirectRawPredictResponse": { + "id": "GoogleCloudAiplatformV1beta1DirectRawPredictResponse", + "type": "object", + "description": "Response message for PredictionService.DirectRawPredict.", + "properties": { + "output": { + "type": "string", + "format": "byte", + "description": "The prediction output." + } + } + }, + "GoogleCloudAiplatformV1beta1SummarizationVerbosityInstance": { + "properties": { + "instruction": { + "description": "Optional. Summarization prompt for LLM.", + "type": "string" + }, + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + }, + "reference": { + "description": "Optional. Ground truth used to compare against the prediction.", + "type": "string" + }, + "context": { + "type": "string", + "description": "Required. Text to be summarized." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SummarizationVerbosityInstance", + "description": "Spec for summarization verbosity instance." + }, + "GoogleCloudAiplatformV1beta1SchemaVideoActionRecognitionAnnotation": { + "properties": { + "timeSegment": { + "description": "This Annotation applies to the time period represented by the TimeSegment. If it's not set, the Annotation applies to the whole video.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaTimeSegment" + }, + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that this Annotation pertains to." + }, + "annotationSpecId": { + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaVideoActionRecognitionAnnotation", + "description": "Annotation details specific to video action recognition.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformation": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformation", + "properties": { + "numeric": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationNumericTransformation" + }, + "text": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTextTransformation" + }, + "categorical": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationCategoricalTransformation" + }, + "auto": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationAutoTransformation" + }, + "timestamp": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTimestampTransformation" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1MigratableResourceDataLabelingDatasetDataLabelingAnnotatedDataset": { + "type": "object", + "properties": { + "annotatedDataset": { + "description": "Full resource name of data labeling AnnotatedDataset. Format: `projects/{project}/datasets/{dataset}/annotatedDatasets/{annotated_dataset}`.", + "type": "string" + }, + "annotatedDatasetDisplayName": { + "type": "string", + "description": "The AnnotatedDataset's display name in datalabeling.googleapis.com." + } + }, + "id": "GoogleCloudAiplatformV1beta1MigratableResourceDataLabelingDatasetDataLabelingAnnotatedDataset", + "description": "Represents one AnnotatedDataset in datalabeling.googleapis.com." + }, + "GoogleCloudAiplatformV1beta1TuningJob": { + "properties": { + "endTime": { + "description": "Output only. Time when the TuningJob entered any of the following JobStates: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`, `JOB_STATE_EXPIRED`.", + "readOnly": true, + "format": "google-datetime", + "type": "string" + }, + "baseModel": { + "type": "string", + "description": "The base model that is being tuned, e.g., \"gemini-1.0-pro-002\"." + }, + "supervisedTuningSpec": { + "$ref": "GoogleCloudAiplatformV1beta1SupervisedTuningSpec", + "description": "Tuning Spec for Supervised Fine Tuning." + }, + "labels": { + "description": "Optional. The labels with user-defined metadata to organize TuningJob and generated resources such as Model and Endpoint. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", + "additionalProperties": { + "type": "string" + }, + "type": "object" + }, + "state": { + "readOnly": true, + "type": "string", + "enum": [ + "JOB_STATE_UNSPECIFIED", + "JOB_STATE_QUEUED", + "JOB_STATE_PENDING", + "JOB_STATE_RUNNING", + "JOB_STATE_SUCCEEDED", + "JOB_STATE_FAILED", + "JOB_STATE_CANCELLING", + "JOB_STATE_CANCELLED", + "JOB_STATE_PAUSED", + "JOB_STATE_EXPIRED", + "JOB_STATE_UPDATING", + "JOB_STATE_PARTIALLY_SUCCEEDED" + ], + "description": "Output only. The detailed state of the job.", + "enumDescriptions": [ + "The job state is unspecified.", + "The job has been just created or resumed and processing has not yet begun.", + "The service is preparing to run the job.", + "The job is in progress.", + "The job completed successfully.", + "The job failed.", + "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "The job has been cancelled.", + "The job has been stopped, and can be resumed.", + "The job has expired.", + "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", + "The job is partially succeeded, some results may be missing due to errors." + ] + }, + "createTime": { + "format": "google-datetime", + "type": "string", + "readOnly": true, + "description": "Output only. Time when the TuningJob was created." + }, + "error": { + "description": "Output only. Only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "readOnly": true, + "$ref": "GoogleRpcStatus" + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", + "description": "Customer-managed encryption key options for a TuningJob. If this is set, then all resources created by the TuningJob will be encrypted with the provided encryption key." + }, + "updateTime": { + "type": "string", + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Time when the TuningJob was most recently updated." + }, + "name": { + "readOnly": true, + "type": "string", + "description": "Output only. Identifier. Resource name of a TuningJob. Format: `projects/{project}/locations/{location}/tuningJobs/{tuning_job}`" + }, + "tunedModelDisplayName": { + "type": "string", + "description": "Optional. The display name of the TunedModel. The name can be up to 128 characters long and can consist of any UTF-8 characters." + }, + "description": { + "type": "string", + "description": "Optional. The description of the TuningJob." + }, + "startTime": { + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Time when the TuningJob for the first time entered the `JOB_STATE_RUNNING` state.", + "type": "string" + }, + "experiment": { + "description": "Output only. The Experiment associated with this TuningJob.", + "type": "string", + "readOnly": true + }, + "tuningDataStats": { + "$ref": "GoogleCloudAiplatformV1beta1TuningDataStats", + "readOnly": true, + "description": "Output only. The tuning data statistics associated with this TuningJob." + }, + "tunedModel": { + "readOnly": true, + "description": "Output only. The tuned model resources assiociated with this TuningJob.", + "$ref": "GoogleCloudAiplatformV1beta1TunedModel" + } + }, + "id": "GoogleCloudAiplatformV1beta1TuningJob", + "type": "object", + "description": "Represents a TuningJob that runs with Google owned models." + }, + "GoogleCloudAiplatformV1beta1ImportFeatureValuesOperationMetadata": { + "properties": { + "importedEntityCount": { + "description": "Number of entities that have been imported by the operation.", + "format": "int64", + "type": "string" + }, + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "Operation metadata for Featurestore import Feature values." + }, + "invalidRowCount": { + "description": "The number of rows in input source that weren't imported due to either * Not having any featureValues. * Having a null entityId. * Having a null timestamp. * Not being parsable (applicable for CSV sources).", + "format": "int64", + "type": "string" + }, + "blockingOperationIds": { + "type": "array", + "items": { + "type": "string", + "format": "int64" + }, + "description": "List of ImportFeatureValues operations running under a single EntityType that are blocking this operation." + }, + "importedFeatureValueCount": { + "type": "string", + "description": "Number of Feature values that have been imported by the operation.", + "format": "int64" + }, + "timestampOutsideRetentionRowsCount": { + "description": "The number rows that weren't ingested due to having timestamps outside the retention boundary.", + "type": "string", + "format": "int64" + }, + "sourceUris": { + "items": { + "type": "string" + }, + "description": "The source URI from where Feature values are imported.", + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1beta1ImportFeatureValuesOperationMetadata", + "description": "Details of operations that perform import Feature values.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1StudySpecParameterSpecDiscreteValueSpec": { + "properties": { + "values": { + "type": "array", + "description": "Required. A list of possible values. The list should be in increasing order and at least 1e-10 apart. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.", + "items": { + "format": "double", + "type": "number" + } + }, + "defaultValue": { + "type": "number", + "description": "A default value for a `DISCRETE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. It automatically rounds to the nearest feasible discrete point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.", + "format": "double" + } + }, + "id": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecDiscreteValueSpec", + "type": "object", + "description": "Value specification for a parameter in `DISCRETE` type." + }, + "GoogleCloudAiplatformV1beta1UndeploySolverOperationMetadata": { + "id": "GoogleCloudAiplatformV1beta1UndeploySolverOperationMetadata", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "The generic operation information." + } + }, + "description": "Runtime operation information for SolverService.UndeploySolver.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ListOptimalTrialsRequest": { + "properties": {}, + "description": "Request message for VizierService.ListOptimalTrials.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ListOptimalTrialsRequest" + }, + "GoogleCloudAiplatformV1beta1ImportFeatureValuesRequest": { + "id": "GoogleCloudAiplatformV1beta1ImportFeatureValuesRequest", + "properties": { + "featureTimeField": { + "description": "Source column that holds the Feature timestamp for all Feature values in each entity.", + "type": "string" + }, + "featureTime": { + "format": "google-datetime", + "type": "string", + "description": "Single Feature timestamp for all entities being imported. The timestamp must not have higher than millisecond precision." + }, + "featureSpecs": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ImportFeatureValuesRequestFeatureSpec" + }, + "description": "Required. Specifications defining which Feature values to import from the entity. The request fails if no feature_specs are provided, and having multiple feature_specs for one Feature is not allowed.", + "type": "array" + }, + "bigquerySource": { + "$ref": "GoogleCloudAiplatformV1beta1BigQuerySource" + }, + "entityIdField": { + "description": "Source column that holds entity IDs. If not provided, entity IDs are extracted from the column named entity_id.", + "type": "string" + }, + "disableIngestionAnalysis": { + "type": "boolean", + "description": "If true, API doesn't start ingestion analysis pipeline." + }, + "disableOnlineServing": { + "type": "boolean", + "description": "If set, data will not be imported for online serving. This is typically used for backfilling, where Feature generation timestamps are not in the timestamp range needed for online serving." + }, + "csvSource": { + "$ref": "GoogleCloudAiplatformV1beta1CsvSource" + }, + "workerCount": { + "type": "integer", + "format": "int32", + "description": "Specifies the number of workers that are used to write data to the Featurestore. Consider the online serving capacity that you require to achieve the desired import throughput without interfering with online serving. The value must be positive, and less than or equal to 100. If not set, defaults to using 1 worker. The low count ensures minimal impact on online serving performance." + }, + "avroSource": { + "$ref": "GoogleCloudAiplatformV1beta1AvroSource" + } + }, + "description": "Request message for FeaturestoreService.ImportFeatureValues.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1PrivateEndpoints": { + "properties": { + "explainHttpUri": { + "description": "Output only. Http(s) path to send explain requests.", + "type": "string", + "readOnly": true + }, + "serviceAttachment": { + "type": "string", + "readOnly": true, + "description": "Output only. The name of the service attachment resource. Populated if private service connect is enabled." + }, + "predictHttpUri": { + "type": "string", + "readOnly": true, + "description": "Output only. Http(s) path to send prediction requests." + }, + "healthHttpUri": { + "description": "Output only. Http(s) path to send health check requests.", + "readOnly": true, + "type": "string" + } + }, + "description": "PrivateEndpoints proto is used to provide paths for users to send requests privately. To send request via private service access, use predict_http_uri, explain_http_uri or health_http_uri. To send request via private service connect, use service_attachment.", + "id": "GoogleCloudAiplatformV1beta1PrivateEndpoints", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FulfillmentSpec": { + "id": "GoogleCloudAiplatformV1beta1FulfillmentSpec", + "type": "object", + "properties": { + "version": { + "description": "Optional. Which version to use for evaluation.", + "format": "int32", + "type": "integer" + } + }, + "description": "Spec for fulfillment metric." + }, + "GoogleCloudAiplatformV1beta1UpdateIndexOperationMetadata": { + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "The operation generic information." + }, + "nearestNeighborSearchOperationMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadata", + "description": "The operation metadata with regard to Matching Engine Index operation." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1UpdateIndexOperationMetadata", + "description": "Runtime operation information for IndexService.UpdateIndex." + }, + "GoogleCloudAiplatformV1beta1LookupStudyRequest": { + "id": "GoogleCloudAiplatformV1beta1LookupStudyRequest", + "description": "Request message for VizierService.LookupStudy.", + "type": "object", + "properties": { + "displayName": { + "type": "string", + "description": "Required. The user-defined display name of the Study" + } + } + }, + "GoogleCloudAiplatformV1beta1DataLabelingJob": { + "id": "GoogleCloudAiplatformV1beta1DataLabelingJob", + "type": "object", + "description": "DataLabelingJob is used to trigger a human labeling job on unlabeled data from the following Dataset:", + "properties": { + "name": { + "description": "Output only. Resource name of the DataLabelingJob.", + "type": "string", + "readOnly": true + }, + "state": { + "enumDescriptions": [ + "The job state is unspecified.", + "The job has been just created or resumed and processing has not yet begun.", + "The service is preparing to run the job.", + "The job is in progress.", + "The job completed successfully.", + "The job failed.", + "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "The job has been cancelled.", + "The job has been stopped, and can be resumed.", + "The job has expired.", + "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", + "The job is partially succeeded, some results may be missing due to errors." + ], + "type": "string", + "description": "Output only. The detailed state of the job.", + "enum": [ + "JOB_STATE_UNSPECIFIED", + "JOB_STATE_QUEUED", + "JOB_STATE_PENDING", + "JOB_STATE_RUNNING", + "JOB_STATE_SUCCEEDED", + "JOB_STATE_FAILED", + "JOB_STATE_CANCELLING", + "JOB_STATE_CANCELLED", + "JOB_STATE_PAUSED", + "JOB_STATE_EXPIRED", + "JOB_STATE_UPDATING", + "JOB_STATE_PARTIALLY_SUCCEEDED" + ], + "readOnly": true + }, + "specialistPools": { + "type": "array", + "items": { + "type": "string" + }, + "description": "The SpecialistPools' resource names associated with this job." + }, + "error": { + "$ref": "GoogleRpcStatus", + "description": "Output only. DataLabelingJob errors. It is only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "readOnly": true + }, + "activeLearningConfig": { + "$ref": "GoogleCloudAiplatformV1beta1ActiveLearningConfig", + "description": "Parameters that configure the active learning pipeline. Active learning will label the data incrementally via several iterations. For every iteration, it will select a batch of data based on the sampling strategy." + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "The labels with user-defined metadata to organize your DataLabelingJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable. Following system labels exist for each DataLabelingJob: * \"aiplatform.googleapis.com/schema\": output only, its value is the inputs_schema's title." + }, + "datasets": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Required. Dataset resource names. Right now we only support labeling from a single Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`" + }, + "labelerCount": { + "description": "Required. Number of labelers to work on each DataItem.", + "format": "int32", + "type": "integer" + }, + "updateTime": { + "type": "string", + "readOnly": true, + "description": "Output only. Timestamp when this DataLabelingJob was updated most recently.", + "format": "google-datetime" + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", + "description": "Customer-managed encryption key spec for a DataLabelingJob. If set, this DataLabelingJob will be secured by this key. Note: Annotations created in the DataLabelingJob are associated with the EncryptionSpec of the Dataset they are exported to." + }, + "createTime": { + "type": "string", + "format": "google-datetime", + "description": "Output only. Timestamp when this DataLabelingJob was created.", + "readOnly": true + }, + "labelingProgress": { + "readOnly": true, + "description": "Output only. Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished.", + "type": "integer", + "format": "int32" + }, + "displayName": { + "type": "string", + "description": "Required. The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a DataLabelingJob." + }, + "annotationLabels": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "Labels to assign to annotations generated by this DataLabelingJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." + }, + "currentSpend": { + "readOnly": true, + "$ref": "GoogleTypeMoney", + "description": "Output only. Estimated cost(in US dollars) that the DataLabelingJob has incurred to date." + }, + "inputs": { + "description": "Required. Input config parameters for the DataLabelingJob.", + "type": "any" + }, + "inputsSchemaUri": { + "description": "Required. Points to a YAML file stored on Google Cloud Storage describing the config for a specific type of DataLabelingJob. The schema files that can be used here are found in the https://storage.googleapis.com/google-cloud-aiplatform bucket in the /schema/datalabelingjob/inputs/ folder.", + "type": "string" + }, + "instructionUri": { + "type": "string", + "description": "Required. The Google Cloud Storage location of the instruction pdf. This pdf is shared with labelers, and provides detailed description on how to label DataItems in Datasets." + } + } + }, + "GoogleCloudAiplatformV1beta1BleuInstance": { + "id": "GoogleCloudAiplatformV1beta1BleuInstance", + "type": "object", + "properties": { + "prediction": { + "description": "Required. Output of the evaluated model.", + "type": "string" + }, + "reference": { + "description": "Required. Ground truth used to compare against the prediction.", + "type": "string" + } + }, + "description": "Spec for bleu instance." + }, + "GoogleCloudAiplatformV1beta1SearchMigratableResourcesResponse": { + "id": "GoogleCloudAiplatformV1beta1SearchMigratableResourcesResponse", + "type": "object", + "description": "Response message for MigrationService.SearchMigratableResources.", + "properties": { + "nextPageToken": { + "type": "string", + "description": "The standard next-page token. The migratable_resources may not fill page_size in SearchMigratableResourcesRequest even when there are subsequent pages." + }, + "migratableResources": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1MigratableResource" + }, + "description": "All migratable resources that can be migrated to the location specified in the request." + } + } + }, + "GoogleCloudAiplatformV1beta1UpsertDatapointsRequest": { + "description": "Request message for IndexService.UpsertDatapoints", + "type": "object", + "properties": { + "datapoints": { + "description": "A list of datapoints to be created/updated.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1IndexDatapoint" + } + }, + "updateMask": { + "format": "google-fieldmask", + "description": "Optional. Update mask is used to specify the fields to be overwritten in the datapoints by the update. The fields specified in the update_mask are relative to each IndexDatapoint inside datapoints, not the full request. Updatable fields: * Use `all_restricts` to update both restricts and numeric_restricts.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1UpsertDatapointsRequest" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoObjectTracking": { + "description": "A TrainingJob that trains and uploads an AutoML Video ObjectTracking Model.", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoObjectTracking", + "type": "object", + "properties": { + "inputs": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoObjectTrackingInputs", + "description": "The input parameters of this TrainingJob." + } + } + }, + "GoogleCloudAiplatformV1beta1UpdateTensorboardOperationMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1UpdateTensorboardOperationMetadata", + "properties": { + "genericMetadata": { + "description": "Operation metadata for Tensorboard.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "description": "Details of operations that perform update Tensorboard." + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformation": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformation", + "type": "object", + "properties": { + "repeatedText": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextArrayTransformation" + }, + "timestamp": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTimestampTransformation" + }, + "auto": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationAutoTransformation" + }, + "numeric": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericTransformation" + }, + "categorical": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalTransformation" + }, + "repeatedNumeric": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericArrayTransformation" + }, + "text": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextTransformation" + }, + "repeatedCategorical": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalArrayTransformation" + } + } + }, + "GoogleCloudAiplatformV1beta1FeatureNoiseSigma": { + "properties": { + "noiseSigma": { + "description": "Noise sigma per feature. No noise is added to features that are not set.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureNoiseSigmaNoiseSigmaForFeature" + }, + "type": "array" + } + }, + "type": "object", + "description": "Noise sigma by features. Noise sigma represents the standard deviation of the gaussian kernel that will be used to add noise to interpolated inputs prior to computing gradients.", + "id": "GoogleCloudAiplatformV1beta1FeatureNoiseSigma" + }, + "GoogleCloudAiplatformV1beta1StudySpec": { + "description": "Represents specification of a Study.", + "properties": { + "decayCurveStoppingSpec": { + "$ref": "GoogleCloudAiplatformV1beta1StudySpecDecayCurveAutomatedStoppingSpec", + "description": "The automated early stopping spec using decay curve rule." + }, + "convexAutomatedStoppingSpec": { + "$ref": "GoogleCloudAiplatformV1beta1StudySpecConvexAutomatedStoppingSpec", + "description": "The automated early stopping spec using convex stopping rule." + }, + "observationNoise": { + "description": "The observation noise level of the study. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.", + "enumDescriptions": [ + "The default noise level chosen by Vertex AI.", + "Vertex AI assumes that the objective function is (nearly) perfectly reproducible, and will never repeat the same Trial parameters.", + "Vertex AI will estimate the amount of noise in metric evaluations, it may repeat the same Trial parameters more than once." + ], + "enum": [ + "OBSERVATION_NOISE_UNSPECIFIED", + "LOW", + "HIGH" + ], + "type": "string" + }, + "algorithm": { + "enum": [ + "ALGORITHM_UNSPECIFIED", + "GRID_SEARCH", + "RANDOM_SEARCH" + ], + "enumDescriptions": [ + "The default algorithm used by Vertex AI for [hyperparameter tuning](https://cloud.google.com/vertex-ai/docs/training/hyperparameter-tuning-overview) and [Vertex AI Vizier](https://cloud.google.com/vertex-ai/docs/vizier).", + "Simple grid search within the feasible space. To use grid search, all parameters must be `INTEGER`, `CATEGORICAL`, or `DISCRETE`.", + "Simple random search within the feasible space." + ], + "description": "The search algorithm specified for the Study.", + "type": "string" + }, + "measurementSelectionType": { + "enum": [ + "MEASUREMENT_SELECTION_TYPE_UNSPECIFIED", + "LAST_MEASUREMENT", + "BEST_MEASUREMENT" + ], + "description": "Describe which measurement selection type will be used", + "type": "string", + "enumDescriptions": [ + "Will be treated as LAST_MEASUREMENT.", + "Use the last measurement reported.", + "Use the best measurement reported." + ] + }, + "convexStopConfig": { + "deprecated": true, + "description": "Deprecated. The automated early stopping using convex stopping rule.", + "$ref": "GoogleCloudAiplatformV1beta1StudySpecConvexStopConfig" + }, + "medianAutomatedStoppingSpec": { + "$ref": "GoogleCloudAiplatformV1beta1StudySpecMedianAutomatedStoppingSpec", + "description": "The automated early stopping spec using median rule." + }, + "transferLearningConfig": { + "description": "The configuration info/options for transfer learning. Currently supported for Vertex AI Vizier service, not HyperParameterTuningJob", + "$ref": "GoogleCloudAiplatformV1beta1StudySpecTransferLearningConfig" + }, + "metrics": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1StudySpecMetricSpec" + }, + "description": "Required. Metric specs for the Study." + }, + "parameters": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpec" + }, + "type": "array", + "description": "Required. The set of parameters to tune." + }, + "studyStoppingConfig": { + "$ref": "GoogleCloudAiplatformV1beta1StudySpecStudyStoppingConfig", + "description": "Conditions for automated stopping of a Study. Enable automated stopping by configuring at least one condition." + } + }, + "id": "GoogleCloudAiplatformV1beta1StudySpec", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1TuningDataStats": { + "type": "object", + "description": "The tuning data statistic values for TuningJob.", + "id": "GoogleCloudAiplatformV1beta1TuningDataStats", + "properties": { + "supervisedTuningDataStats": { + "$ref": "GoogleCloudAiplatformV1beta1SupervisedTuningDataStats", + "description": "The SFT Tuning data stats." + } + } + }, + "GoogleCloudAiplatformV1beta1ListDataLabelingJobsResponse": { + "type": "object", + "description": "Response message for JobService.ListDataLabelingJobs.", + "properties": { + "dataLabelingJobs": { + "description": "A list of DataLabelingJobs that matches the specified filter in the request.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1DataLabelingJob" + } + }, + "nextPageToken": { + "description": "The standard List next-page token.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1ListDataLabelingJobsResponse" + }, + "GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig": { + "properties": { + "apiKeySecretVersion": { + "type": "string", + "description": "Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}" + } + }, + "type": "object", + "description": "The API secret.", + "id": "GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig" + }, + "GoogleCloudAiplatformV1beta1FeatureViewSyncConfig": { + "id": "GoogleCloudAiplatformV1beta1FeatureViewSyncConfig", + "properties": { + "cron": { + "description": "Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: \"CRON_TZ=${IANA_TIME_ZONE}\" or \"TZ=${IANA_TIME_ZONE}\". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, \"CRON_TZ=America/New_York 1 * * * *\", or \"TZ=America/New_York 1 * * * *\".", + "type": "string" + } + }, + "description": "Configuration for Sync. Only one option is set.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1PredictRequestResponseLoggingConfig": { + "id": "GoogleCloudAiplatformV1beta1PredictRequestResponseLoggingConfig", + "properties": { + "samplingRate": { + "type": "number", + "format": "double", + "description": "Percentage of requests to be logged, expressed as a fraction in range(0,1]." + }, + "enabled": { + "type": "boolean", + "description": "If logging is enabled or not." + }, + "bigqueryDestination": { + "description": "BigQuery table for logging. If only given a project, a new dataset will be created with name `logging__` where will be made BigQuery-dataset-name compatible (e.g. most special characters will become underscores). If no table name is given, a new table will be created with name `request_response_logging`", + "$ref": "GoogleCloudAiplatformV1beta1BigQueryDestination" + } + }, + "description": "Configuration for logging request-response to a BigQuery table.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FeatureValueMetadata": { + "properties": { + "generateTime": { + "format": "google-datetime", + "description": "Feature generation timestamp. Typically, it is provided by user at feature ingestion time. If not, feature store will use the system timestamp when the data is ingested into feature store. For streaming ingestion, the time, aligned by days, must be no older than five years (1825 days) and no later than one year (366 days) in the future.", + "type": "string" + } + }, + "description": "Metadata of feature value.", + "id": "GoogleCloudAiplatformV1beta1FeatureValueMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1GenerateContentResponse": { + "id": "GoogleCloudAiplatformV1beta1GenerateContentResponse", + "properties": { + "usageMetadata": { + "description": "Usage metadata about the response(s).", + "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponseUsageMetadata" + }, + "promptFeedback": { + "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponsePromptFeedback", + "readOnly": true, + "description": "Output only. Content filter results for a prompt sent in the request. Note: Sent only in the first stream chunk. Only happens when no candidates were generated due to content violations." + }, + "candidates": { + "description": "Output only. Generated candidates.", + "type": "array", + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Candidate" + } + } + }, + "description": "Response message for [PredictionService.GenerateContent].", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ListModelsResponse": { + "type": "object", + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token to retrieve next page of results. Pass to ListModelsRequest.page_token to obtain that page." + }, + "models": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Model" + }, + "type": "array", + "description": "List of Models in the requested page." + } + }, + "description": "Response message for ModelService.ListModels", + "id": "GoogleCloudAiplatformV1beta1ListModelsResponse" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringSpec": { + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringSpec", + "properties": { + "notificationSpec": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpec", + "description": "The model monitoring notification spec." + }, + "objectiveSpec": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpec", + "description": "The monitoring objective spec." + }, + "outputSpec": { + "description": "The Output destination spec for metrics, error logs, etc.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringOutputSpec" + } + }, + "description": "Monitoring monitoring job spec. It outlines the specifications for monitoring objectives, notifications, and result exports.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1GroundednessInstance": { + "id": "GoogleCloudAiplatformV1beta1GroundednessInstance", + "type": "object", + "properties": { + "prediction": { + "description": "Required. Output of the evaluated model.", + "type": "string" + }, + "context": { + "type": "string", + "description": "Required. Background information provided in context used to compare against the prediction." + } + }, + "description": "Spec for groundedness instance." + }, + "GoogleCloudAiplatformV1beta1SchemaPredictPredictionImageObjectDetectionPredictionResult": { + "properties": { + "displayNames": { + "type": "array", + "description": "The display names of the AnnotationSpecs that had been identified, order matches the IDs.", + "items": { + "type": "string" + } + }, + "bboxes": { + "type": "array", + "items": { + "type": "array", + "items": { + "type": "any" + } + }, + "description": "Bounding boxes, i.e. the rectangles over the image, that pinpoint the found AnnotationSpecs. Given in order that matches the IDs. Each bounding box is an array of 4 numbers `xMin`, `xMax`, `yMin`, and `yMax`, which represent the extremal coordinates of the box. They are relative to the image size, and the point 0,0 is in the top left of the image." + }, + "ids": { + "items": { + "format": "int64", + "type": "string" + }, + "description": "The resource IDs of the AnnotationSpecs that had been identified, ordered by the confidence score descendingly.", + "type": "array" + }, + "confidences": { + "description": "The Model's confidences in correctness of the predicted IDs, higher value means higher confidence. Order matches the Ids.", + "type": "array", + "items": { + "format": "float", + "type": "number" + } + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionImageObjectDetectionPredictionResult", + "description": "Prediction output format for Image Object Detection.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ToolUseExampleExtensionOperation": { + "properties": { + "operationId": { + "type": "string", + "description": "Required. Operation ID of the extension." + }, + "extension": { + "type": "string", + "description": "Resource name of the extension." + } + }, + "type": "object", + "description": "Identifies one operation of the extension.", + "id": "GoogleCloudAiplatformV1beta1ToolUseExampleExtensionOperation" + }, + "GoogleCloudAiplatformV1beta1StudySpecParameterSpecDoubleValueSpec": { + "properties": { + "minValue": { + "format": "double", + "description": "Required. Inclusive minimum value of the parameter.", + "type": "number" + }, + "defaultValue": { + "description": "A default value for a `DOUBLE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.", + "type": "number", + "format": "double" + }, + "maxValue": { + "type": "number", + "description": "Required. Inclusive maximum value of the parameter.", + "format": "double" + } + }, + "id": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecDoubleValueSpec", + "description": "Value specification for a parameter in `DOUBLE` type.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadata": { + "properties": { + "timeColumn": { + "type": "string", + "description": "The column name of the time column that identifies time order in the time series." + }, + "inputConfig": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataInputConfig" + }, + "timeSeriesIdentifierColumn": { + "type": "string", + "description": "The column name of the time series identifier column that identifies the time series." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadata", + "description": "The metadata of Datasets that contain time series data." + }, + "GoogleCloudAiplatformV1beta1SafetyInstance": { + "description": "Spec for safety instance.", + "id": "GoogleCloudAiplatformV1beta1SafetyInstance", + "type": "object", + "properties": { + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + } + } + }, + "GoogleCloudAiplatformV1beta1StudySpecMetricSpec": { + "properties": { + "metricId": { + "type": "string", + "description": "Required. The ID of the metric. Must not contain whitespaces and must be unique amongst all MetricSpecs." + }, + "goal": { + "description": "Required. The optimization goal of the metric.", + "enum": [ + "GOAL_TYPE_UNSPECIFIED", + "MAXIMIZE", + "MINIMIZE" + ], + "enumDescriptions": [ + "Goal Type will default to maximize.", + "Maximize the goal metric.", + "Minimize the goal metric." + ], + "type": "string" + }, + "safetyConfig": { + "description": "Used for safe search. In the case, the metric will be a safety metric. You must provide a separate metric for objective metric.", + "$ref": "GoogleCloudAiplatformV1beta1StudySpecMetricSpecSafetyMetricConfig" + } + }, + "id": "GoogleCloudAiplatformV1beta1StudySpecMetricSpec", + "type": "object", + "description": "Represents a metric to optimize." + }, + "GoogleCloudAiplatformV1beta1ToolParameterKVMatchResults": { + "description": "Results for tool parameter key value match metric.", + "type": "object", + "properties": { + "toolParameterKvMatchMetricValues": { + "type": "array", + "readOnly": true, + "description": "Output only. Tool parameter key value match metric values.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchMetricValue" + } + } + }, + "id": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchResults" + }, + "GoogleCloudAiplatformV1beta1SupervisedHyperParameters": { + "type": "object", + "description": "Hyperparameters for SFT.", + "id": "GoogleCloudAiplatformV1beta1SupervisedHyperParameters", + "properties": { + "epochCount": { + "format": "int64", + "description": "Optional. Number of complete passes the model makes over the entire training dataset during training.", + "type": "string" + }, + "learningRateMultiplier": { + "type": "number", + "description": "Optional. Multiplier for adjusting the default learning rate.", + "format": "double" + }, + "adapterSize": { + "description": "Optional. Adapter size for tuning.", + "enum": [ + "ADAPTER_SIZE_UNSPECIFIED", + "ADAPTER_SIZE_ONE", + "ADAPTER_SIZE_FOUR", + "ADAPTER_SIZE_EIGHT", + "ADAPTER_SIZE_SIXTEEN", + "ADAPTER_SIZE_THIRTY_TWO" + ], + "type": "string", + "enumDescriptions": [ + "Adapter size is unspecified.", + "Adapter size 1.", + "Adapter size 4.", + "Adapter size 8.", + "Adapter size 16.", + "Adapter size 32." + ] + } + } + }, + "GoogleCloudAiplatformV1beta1EvaluatedAnnotationExplanation": { + "type": "object", + "description": "Explanation result of the prediction produced by the Model.", + "properties": { + "explanation": { + "$ref": "GoogleCloudAiplatformV1beta1Explanation", + "description": "Explanation attribution response details." + }, + "explanationType": { + "type": "string", + "description": "Explanation type. For AutoML Image Classification models, possible values are: * `image-integrated-gradients` * `image-xrai`" + } + }, + "id": "GoogleCloudAiplatformV1beta1EvaluatedAnnotationExplanation" + }, + "GoogleCloudAiplatformV1beta1UpgradeNotebookRuntimeOperationMetadata": { + "description": "Metadata information for NotebookService.UpgradeNotebookRuntime.", + "id": "GoogleCloudAiplatformV1beta1UpgradeNotebookRuntimeOperationMetadata", + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + }, + "progressMessage": { + "description": "A human-readable message that shows the intermediate progress details of NotebookRuntime.", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1GcsSource": { + "description": "The Google Cloud Storage location for the input content.", + "id": "GoogleCloudAiplatformV1beta1GcsSource", + "properties": { + "uris": { + "items": { + "type": "string" + }, + "description": "Required. Google Cloud Storage URI(-s) to the input file(s). May contain wildcards. For more information on wildcards, see https://cloud.google.com/storage/docs/gsutil/addlhelp/WildcardNames.", + "type": "array" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1CreateIndexEndpointOperationMetadata": { + "description": "Runtime operation information for IndexEndpointService.CreateIndexEndpoint.", + "id": "GoogleCloudAiplatformV1beta1CreateIndexEndpointOperationMetadata", + "type": "object", + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsQuestionAnsweringEvaluationMetrics": { + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsQuestionAnsweringEvaluationMetrics", + "type": "object", + "properties": { + "exactMatch": { + "type": "number", + "description": "The rate at which the input predicted strings exactly match their references.", + "format": "float" + } + } + }, + "GoogleCloudAiplatformV1beta1SuggestTrialsRequest": { + "description": "Request message for VizierService.SuggestTrials.", + "type": "object", + "properties": { + "contexts": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1TrialContext" + }, + "description": "Optional. This allows you to specify the \"context\" for a Trial; a context is a slice (a subspace) of the search space. Typical uses for contexts: 1) You are using Vizier to tune a server for best performance, but there's a strong weekly cycle. The context specifies the day-of-week. This allows Tuesday to generalize from Wednesday without assuming that everything is identical. 2) Imagine you're optimizing some medical treatment for people. As they walk in the door, you know certain facts about them (e.g. sex, weight, height, blood-pressure). Put that information in the context, and Vizier will adapt its suggestions to the patient. 3) You want to do a fair A/B test efficiently. Specify the \"A\" and \"B\" conditions as contexts, and Vizier will generalize between \"A\" and \"B\" conditions. If they are similar, this will allow Vizier to converge to the optimum faster than if \"A\" and \"B\" were separate Studies. NOTE: You can also enter contexts as REQUESTED Trials, e.g. via the CreateTrial() RPC; that's the asynchronous option where you don't need a close association between contexts and suggestions. NOTE: All the Parameters you set in a context MUST be defined in the Study. NOTE: You must supply 0 or $suggestion_count contexts. If you don't supply any contexts, Vizier will make suggestions from the full search space specified in the StudySpec; if you supply a full set of context, each suggestion will match the corresponding context. NOTE: A Context with no features set matches anything, and allows suggestions from the full search space. NOTE: Contexts MUST lie within the search space specified in the StudySpec. It's an error if they don't. NOTE: Contexts preferentially match ACTIVE then REQUESTED trials before new suggestions are generated. NOTE: Generation of suggestions involves a match between a Context and (optionally) a REQUESTED trial; if that match is not fully specified, a suggestion will be geneated in the merged subspace." + }, + "clientId": { + "type": "string", + "description": "Required. The identifier of the client that is requesting the suggestion. If multiple SuggestTrialsRequests have the same `client_id`, the service will return the identical suggested Trial if the Trial is pending, and provide a new Trial if the last suggested Trial was completed." + }, + "suggestionCount": { + "type": "integer", + "description": "Required. The number of suggestions requested. It must be positive.", + "format": "int32" + } + }, + "id": "GoogleCloudAiplatformV1beta1SuggestTrialsRequest" + }, + "GoogleCloudAiplatformV1beta1Artifact": { + "properties": { + "description": { + "type": "string", + "description": "Description of the Artifact" + }, + "displayName": { + "type": "string", + "description": "User provided display name of the Artifact. May be up to 128 Unicode characters." + }, + "labels": { + "description": "The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).", + "additionalProperties": { + "type": "string" + }, + "type": "object" + }, + "schemaTitle": { + "type": "string", + "description": "The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store." + }, + "updateTime": { + "format": "google-datetime", + "description": "Output only. Timestamp when this Artifact was last updated.", + "readOnly": true, + "type": "string" + }, + "state": { + "enum": [ + "STATE_UNSPECIFIED", + "PENDING", + "LIVE" + ], + "type": "string", + "enumDescriptions": [ + "Unspecified state for the Artifact.", + "A state used by systems like Vertex AI Pipelines to indicate that the underlying data item represented by this Artifact is being created.", + "A state indicating that the Artifact should exist, unless something external to the system deletes it." + ], + "description": "The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions." + }, + "createTime": { + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Timestamp when this Artifact was created.", + "type": "string" + }, + "metadata": { + "description": "Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.", + "additionalProperties": { + "type": "any", + "description": "Properties of the object." + }, + "type": "object" + }, + "etag": { + "description": "An eTag used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "schemaVersion": { + "type": "string", + "description": "The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store." + }, + "name": { + "description": "Output only. The resource name of the Artifact.", + "readOnly": true, + "type": "string" + }, + "uri": { + "description": "The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1Artifact", + "description": "Instance of a general artifact.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1StudySpecMedianAutomatedStoppingSpec": { + "properties": { + "useElapsedDuration": { + "description": "True if median automated stopping rule applies on Measurement.elapsed_duration. It means that elapsed_duration field of latest measurement of current Trial is used to compute median objective value for each completed Trials.", + "type": "boolean" + } + }, + "description": "The median automated stopping rule stops a pending Trial if the Trial's best objective_value is strictly below the median 'performance' of all completed Trials reported up to the Trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the Trial in each measurement.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1StudySpecMedianAutomatedStoppingSpec" + }, + "GoogleCloudAiplatformV1beta1CsvSource": { + "id": "GoogleCloudAiplatformV1beta1CsvSource", + "properties": { + "gcsSource": { + "$ref": "GoogleCloudAiplatformV1beta1GcsSource", + "description": "Required. Google Cloud Storage location." + } + }, + "type": "object", + "description": "The storage details for CSV input content." + }, + "GoogleCloudAiplatformV1beta1ExportModelOperationMetadataOutputInfo": { + "description": "Further describes the output of the ExportModel. Supplements ExportModelRequest.OutputConfig.", + "id": "GoogleCloudAiplatformV1beta1ExportModelOperationMetadataOutputInfo", + "type": "object", + "properties": { + "imageOutputUri": { + "readOnly": true, + "description": "Output only. If the Model image is being exported to Google Container Registry or Artifact Registry this is the full path of the image created.", + "type": "string" + }, + "artifactOutputUri": { + "type": "string", + "description": "Output only. If the Model artifact is being exported to Google Cloud Storage this is the full path of the directory created, into which the Model files are being written to.", + "readOnly": true + } + } + }, + "GoogleCloudAiplatformV1beta1IndexDatapoint": { + "id": "GoogleCloudAiplatformV1beta1IndexDatapoint", + "description": "A datapoint of Index.", + "properties": { + "datapointId": { + "type": "string", + "description": "Required. Unique identifier of the datapoint." + }, + "restricts": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1IndexDatapointRestriction" + }, + "description": "Optional. List of Restrict of the datapoint, used to perform \"restricted searches\" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering", + "type": "array" + }, + "numericRestricts": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1IndexDatapointNumericRestriction" + }, + "description": "Optional. List of Restrict of the datapoint, used to perform \"restricted searches\" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons." + }, + "crowdingTag": { + "description": "Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query.", + "$ref": "GoogleCloudAiplatformV1beta1IndexDatapointCrowdingTag" + }, + "sparseEmbedding": { + "$ref": "GoogleCloudAiplatformV1beta1IndexDatapointSparseEmbedding", + "description": "Optional. Feature embedding vector for sparse index." + }, + "featureVector": { + "type": "array", + "items": { + "format": "float", + "type": "number" + }, + "description": "Required. Feature embedding vector for dense index. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions]." + } + }, + "type": "object" + }, + "CloudAiPlatformCommonCreatePipelineJobApiErrorDetail": { + "properties": { + "publicMessage": { + "description": "Public messages contains actionable items for the error cause.", + "type": "string" + }, + "errorCause": { + "enum": [ + "ERROR_CAUSE_UNSPECIFIED", + "INVALID_PIPELINE_SPEC_FORMAT", + "INVALID_PIPELINE_SPEC", + "INVALID_DEPLOYMENT_CONFIG", + "INVALID_DEPLOYMENT_SPEC", + "INVALID_INSTANCE_SCHEMA", + "INVALID_CUSTOM_JOB", + "INVALID_CONTAINER_SPEC", + "INVALID_NOTIFICATION_EMAIL_SETUP", + "INVALID_SERVICE_ACCOUNT_SETUP", + "INVALID_KMS_SETUP", + "INVALID_NETWORK_SETUP", + "INVALID_PIPELINE_TASK_SPEC", + "INVALID_PIPELINE_TASK_ARTIFACT", + "INVALID_IMPORTER_SPEC", + "INVALID_RESOLVER_SPEC", + "INVALID_RUNTIME_PARAMETERS", + "CLOUD_API_NOT_ENABLED", + "INVALID_GCS_INPUT_URI", + "INVALID_GCS_OUTPUT_URI", + "INVALID_COMPONENT_SPEC", + "INVALID_DAG_OUTPUTS_SPEC", + "INVALID_DAG_SPEC", + "INSUFFICIENT_QUOTA", + "INTERNAL" + ], + "enumDescriptions": [ + "Should never be used.", + "IR Pipeline Spec can not been parsed to yaml or json format.", + "A pipeline spec is invalid.", + "A deployment config is invalid.", + "A deployment spec is invalid.", + "An instance schema is invalid.", + "A custom job is invalid.", + "A container spec is invalid.", + "Notification email setup is invalid.", + "Service account setup is invalid.", + "KMS setup is invalid.", + "Network setup is invalid.", + "Task spec is invalid.", + "Task artifact is invalid.", + "Importer spec is invalid.", + "Resolver spec is invalid.", + "Runtime Parameters are invalid.", + "Cloud API not enabled.", + "Invalid GCS input uri", + "Invalid GCS output uri", + "Component spec of pipeline is invalid.", + "DagOutputsSpec is invalid.", + "DagSpec is invalid.", + "Project does not have enough quota.", + "An internal error with unknown cause." + ], + "type": "string", + "description": "The error root cause returned by CreatePipelineJob API." + } + }, + "description": "Create API error message for Vertex Pipeline. Next Id: 3.", + "type": "object", + "id": "CloudAiPlatformCommonCreatePipelineJobApiErrorDetail" + }, + "GoogleCloudAiplatformV1beta1FindNeighborsResponse": { + "id": "GoogleCloudAiplatformV1beta1FindNeighborsResponse", + "description": "The response message for MatchService.FindNeighbors.", + "properties": { + "nearestNeighbors": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1FindNeighborsResponseNearestNeighbors" + }, + "type": "array", + "description": "The nearest neighbors of the query datapoints." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1DeployIndexResponse": { + "description": "Response message for IndexEndpointService.DeployIndex.", + "id": "GoogleCloudAiplatformV1beta1DeployIndexResponse", + "properties": { + "deployedIndex": { + "$ref": "GoogleCloudAiplatformV1beta1DeployedIndex", + "description": "The DeployedIndex that had been deployed in the IndexEndpoint." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ExportDataOperationMetadata": { + "properties": { + "gcsOutputDirectory": { + "description": "A Google Cloud Storage directory which path ends with '/'. The exported data is stored in the directory.", + "type": "string" + }, + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "The common part of the operation metadata." + } + }, + "type": "object", + "description": "Runtime operation information for DatasetService.ExportData.", + "id": "GoogleCloudAiplatformV1beta1ExportDataOperationMetadata" + }, + "GoogleIamV1Binding": { + "type": "object", + "description": "Associates `members`, or principals, with a `role`.", + "properties": { + "members": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Specifies the principals requesting access for a Google Cloud resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. Does not include identities that come from external identity providers (IdPs) through identity federation. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a Google service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `serviceAccount:{projectid}.svc.id.goog[{namespace}/{kubernetes-sa}]`: An identifier for a [Kubernetes service account](https://cloud.google.com/kubernetes-engine/docs/how-to/kubernetes-service-accounts). For example, `my-project.svc.id.goog[my-namespace/my-kubernetes-sa]`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`. * `principal://iam.googleapis.com/locations/global/workforcePools/{pool_id}/subject/{subject_attribute_value}`: A single identity in a workforce identity pool. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/group/{group_id}`: All workforce identities in a group. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/attribute.{attribute_name}/{attribute_value}`: All workforce identities with a specific attribute value. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/*`: All identities in a workforce identity pool. * `principal://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/subject/{subject_attribute_value}`: A single identity in a workload identity pool. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/group/{group_id}`: A workload identity pool group. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/attribute.{attribute_name}/{attribute_value}`: All identities in a workload identity pool with a certain attribute. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/*`: All identities in a workload identity pool. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding. * `deleted:principal://iam.googleapis.com/locations/global/workforcePools/{pool_id}/subject/{subject_attribute_value}`: Deleted single identity in a workforce identity pool. For example, `deleted:principal://iam.googleapis.com/locations/global/workforcePools/my-pool-id/subject/my-subject-attribute-value`." + }, + "role": { + "description": "Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`. For an overview of the IAM roles and permissions, see the [IAM documentation](https://cloud.google.com/iam/docs/roles-overview). For a list of the available pre-defined roles, see [here](https://cloud.google.com/iam/docs/understanding-roles).", + "type": "string" + }, + "condition": { + "$ref": "GoogleTypeExpr", + "description": "The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies)." + } + }, + "id": "GoogleIamV1Binding" + }, + "GoogleCloudAiplatformV1beta1MetadataStoreDataplexConfig": { + "description": "Represents Dataplex integration settings.", + "id": "GoogleCloudAiplatformV1beta1MetadataStoreDataplexConfig", + "type": "object", + "properties": { + "enabledPipelinesLineage": { + "description": "Optional. Whether or not Data Lineage synchronization is enabled for Vertex Pipelines.", + "type": "boolean" + } + } + }, + "GoogleCloudAiplatformV1beta1PipelineTemplateMetadata": { + "properties": { + "version": { + "description": "The version_name in artifact registry. Will always be presented in output if the PipelineJob.template_uri is from supported template registry. Format is \"sha256:abcdef123456...\".", + "type": "string" + } + }, + "description": "Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry.", + "id": "GoogleCloudAiplatformV1beta1PipelineTemplateMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1RougeMetricValue": { + "type": "object", + "description": "Rouge metric value for an instance.", + "id": "GoogleCloudAiplatformV1beta1RougeMetricValue", + "properties": { + "score": { + "type": "number", + "description": "Output only. Rouge score.", + "format": "float", + "readOnly": true + } + } + }, + "GoogleCloudAiplatformV1beta1CreateRegistryFeatureOperationMetadata": { + "type": "object", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "Operation metadata for Feature." + } + }, + "id": "GoogleCloudAiplatformV1beta1CreateRegistryFeatureOperationMetadata", + "description": "Details of operations that perform create FeatureGroup." + }, + "GoogleCloudAiplatformV1beta1ExtensionOperation": { + "properties": { + "functionDeclaration": { + "$ref": "GoogleCloudAiplatformV1beta1FunctionDeclaration", + "readOnly": true, + "description": "Output only. Structured representation of a function declaration as defined by the OpenAPI Spec." + }, + "operationId": { + "description": "Operation ID that uniquely identifies the operations among the extension. See: \"Operation Object\" in https://swagger.io/specification/. This field is parsed from the OpenAPI spec. For HTTP extensions, if it does not exist in the spec, we will generate one from the HTTP method and path.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1ExtensionOperation", + "type": "object", + "description": "Operation of an extension." + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputs": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputs", + "type": "object", + "properties": { + "optimizationObjective": { + "description": "Objective function the model is optimizing towards. The training process creates a model that maximizes/minimizes the value of the objective function over the validation set. The supported optimization objectives depend on the prediction type. If the field is not set, a default objective function is used. classification (binary): \"maximize-au-roc\" (default) - Maximize the area under the receiver operating characteristic (ROC) curve. \"minimize-log-loss\" - Minimize log loss. \"maximize-au-prc\" - Maximize the area under the precision-recall curve. \"maximize-precision-at-recall\" - Maximize precision for a specified recall value. \"maximize-recall-at-precision\" - Maximize recall for a specified precision value. classification (multi-class): \"minimize-log-loss\" (default) - Minimize log loss. regression: \"minimize-rmse\" (default) - Minimize root-mean-squared error (RMSE). \"minimize-mae\" - Minimize mean-absolute error (MAE). \"minimize-rmsle\" - Minimize root-mean-squared log error (RMSLE).", + "type": "string" + }, + "targetColumn": { + "type": "string", + "description": "The column name of the target column that the model is to predict." + }, + "additionalExperiments": { + "description": "Additional experiment flags for the Tables training pipeline.", + "items": { + "type": "string" + }, + "type": "array" + }, + "optimizationObjectivePrecisionValue": { + "type": "number", + "description": "Required when optimization_objective is \"maximize-recall-at-precision\". Must be between 0 and 1, inclusive.", + "format": "float" + }, + "optimizationObjectiveRecallValue": { + "type": "number", + "description": "Required when optimization_objective is \"maximize-precision-at-recall\". Must be between 0 and 1, inclusive.", + "format": "float" + }, + "weightColumnName": { + "type": "string", + "description": "Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1." + }, + "trainBudgetMilliNodeHours": { + "format": "int64", + "description": "Required. The train budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The training cost of the model will not exceed this budget. The final cost will be attempted to be close to the budget, though may end up being (even) noticeably smaller - at the backend's discretion. This especially may happen when further model training ceases to provide any improvements. If the budget is set to a value known to be insufficient to train a model for the given dataset, the training won't be attempted and will error. The train budget must be between 1,000 and 72,000 milli node hours, inclusive.", + "type": "string" + }, + "transformations": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformation" + }, + "description": "Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using \".\" as the delimiter.", + "type": "array" + }, + "predictionType": { + "type": "string", + "description": "The type of prediction the Model is to produce. \"classification\" - Predict one out of multiple target values is picked for each row. \"regression\" - Predict a value based on its relation to other values. This type is available only to columns that contain semantically numeric values, i.e. integers or floating point number, even if stored as e.g. strings." + }, + "exportEvaluatedDataItemsConfig": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig", + "description": "Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed." + }, + "disableEarlyStopping": { + "description": "Use the entire training budget. This disables the early stopping feature. By default, the early stopping feature is enabled, which means that AutoML Tables might stop training before the entire training budget has been used.", + "type": "boolean" + } + } + }, + "GoogleCloudAiplatformV1beta1ListExecutionsResponse": { + "type": "object", + "description": "Response message for MetadataService.ListExecutions.", + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token, which can be sent as ListExecutionsRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages." + }, + "executions": { + "description": "The Executions retrieved from the MetadataStore.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Execution" + } + } + }, + "id": "GoogleCloudAiplatformV1beta1ListExecutionsResponse" + }, + "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualitySpec": { + "type": "object", + "description": "Spec for pairwise summarization quality score metric.", + "properties": { + "useReference": { + "type": "boolean", + "description": "Optional. Whether to use instance.reference to compute pairwise summarization quality." + }, + "version": { + "type": "integer", + "description": "Optional. Which version to use for evaluation.", + "format": "int32" + } + }, + "id": "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualitySpec" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageSegmentationEvaluationMetrics": { + "description": "Metrics for image segmentation evaluation results.", + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageSegmentationEvaluationMetrics", + "type": "object", + "properties": { + "confidenceMetricsEntries": { + "description": "Metrics for each confidenceThreshold in 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 Precision-recall curve can be derived from it.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageSegmentationEvaluationMetricsConfidenceMetricsEntry" + }, + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1beta1NearestNeighborQueryNumericFilter": { + "type": "object", + "description": "Numeric filter is used to search a subset of the entities by using boolean rules on numeric columns. For example: Database Point 0: {name: “a” value_int: 42} {name: “b” value_float: 1.0} Database Point 1: {name: “a” value_int: 10} {name: “b” value_float: 2.0} Database Point 2: {name: “a” value_int: -1} {name: “b” value_float: 3.0} Query: {name: “a” value_int: 12 operator: LESS} // Matches Point 1, 2 {name: “b” value_float: 2.0 operator: EQUAL} // Matches Point 1", + "properties": { + "valueInt": { + "format": "int64", + "type": "string", + "description": "int value type." + }, + "name": { + "type": "string", + "description": "Required. Column name in BigQuery that used as filters." + }, + "valueDouble": { + "type": "number", + "format": "double", + "description": "double value type." + }, + "valueFloat": { + "format": "float", + "type": "number", + "description": "float value type." + }, + "op": { + "type": "string", + "description": "Optional. This MUST be specified for queries and must NOT be specified for database points.", + "enum": [ + "OPERATOR_UNSPECIFIED", + "LESS", + "LESS_EQUAL", + "EQUAL", + "GREATER_EQUAL", + "GREATER", + "NOT_EQUAL" + ], + "enumDescriptions": [ + "Unspecified operator.", + "Entities are eligible if their value is \u003c the query's.", + "Entities are eligible if their value is \u003c= the query's.", + "Entities are eligible if their value is == the query's.", + "Entities are eligible if their value is \u003e= the query's.", + "Entities are eligible if their value is \u003e the query's.", + "Entities are eligible if their value is != the query's." + ] + } + }, + "id": "GoogleCloudAiplatformV1beta1NearestNeighborQueryNumericFilter" + }, + "GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequestSelectEntity": { + "id": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequestSelectEntity", + "properties": { + "entityIdSelector": { + "description": "Required. Selectors choosing feature values of which entity id to be deleted from the EntityType.", + "$ref": "GoogleCloudAiplatformV1beta1EntityIdSelector" + } + }, + "description": "Message to select entity. If an entity id is selected, all the feature values corresponding to the entity id will be deleted, including the entityId.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1BleuResults": { + "type": "object", + "properties": { + "bleuMetricValues": { + "description": "Output only. Bleu metric values.", + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1beta1BleuMetricValue" + }, + "type": "array" + } + }, + "description": "Results for bleu metric.", + "id": "GoogleCloudAiplatformV1beta1BleuResults" + }, + "GoogleCloudAiplatformV1beta1GoogleDriveSourceResourceId": { + "properties": { + "resourceId": { + "type": "string", + "description": "Required. The ID of the Google Drive resource." + }, + "resourceType": { + "type": "string", + "enumDescriptions": [ + "Unspecified resource type.", + "File resource type.", + "Folder resource type." + ], + "description": "Required. The type of the Google Drive resource.", + "enum": [ + "RESOURCE_TYPE_UNSPECIFIED", + "RESOURCE_TYPE_FILE", + "RESOURCE_TYPE_FOLDER" + ] + } + }, + "id": "GoogleCloudAiplatformV1beta1GoogleDriveSourceResourceId", + "description": "The type and ID of the Google Drive resource.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfig": { + "type": "object", + "description": "Deprecated. Use IndexConfig instead.", + "deprecated": true, + "properties": { + "embeddingDimension": { + "description": "Optional. The number of dimensions of the input embedding.", + "type": "integer", + "format": "int32" + }, + "crowdingColumn": { + "description": "Optional. Column of crowding. This column contains crowding attribute which is a constraint on a neighbor list produced by FeatureOnlineStoreService.SearchNearestEntities to diversify search results. If NearestNeighborQuery.per_crowding_attribute_neighbor_count is set to K in SearchNearestEntitiesRequest, it's guaranteed that no more than K entities of the same crowding attribute are returned in the response.", + "type": "string" + }, + "distanceMeasureType": { + "enumDescriptions": [ + "Should not be set.", + "Euclidean (L_2) Distance.", + "Cosine Distance. Defined as 1 - cosine similarity. We strongly suggest using DOT_PRODUCT_DISTANCE + UNIT_L2_NORM instead of COSINE distance. Our algorithms have been more optimized for DOT_PRODUCT distance which, when combined with UNIT_L2_NORM, is mathematically equivalent to COSINE distance and results in the same ranking.", + "Dot Product Distance. Defined as a negative of the dot product." + ], + "description": "Optional. The distance measure used in nearest neighbor search.", + "enum": [ + "DISTANCE_MEASURE_TYPE_UNSPECIFIED", + "SQUARED_L2_DISTANCE", + "COSINE_DISTANCE", + "DOT_PRODUCT_DISTANCE" + ], + "type": "string" + }, + "treeAhConfig": { + "description": "Optional. Configuration options for the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396", + "$ref": "GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfigTreeAHConfig" + }, + "filterColumns": { + "items": { + "type": "string" + }, + "description": "Optional. Columns of features that're used to filter vector search results.", + "type": "array" + }, + "bruteForceConfig": { + "description": "Optional. Configuration options for using brute force search, which simply implements the standard linear search in the database for each query. It is primarily meant for benchmarking and to generate the ground truth for approximate search.", + "$ref": "GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfigBruteForceConfig" + }, + "embeddingColumn": { + "description": "Optional. Column of embedding. This column contains the source data to create index for vector search. embedding_column must be set when using vector search.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfig" + }, + "GoogleCloudAiplatformV1beta1ListModelVersionsResponse": { + "description": "Response message for ModelService.ListModelVersions", + "properties": { + "models": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Model" + }, + "description": "List of Model versions in the requested page. In the returned Model name field, version ID instead of regvision tag will be included." + }, + "nextPageToken": { + "type": "string", + "description": "A token to retrieve the next page of results. Pass to ListModelVersionsRequest.page_token to obtain that page." + } + }, + "id": "GoogleCloudAiplatformV1beta1ListModelVersionsResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsRegressionEvaluationMetrics": { + "description": "Metrics for regression evaluation results.", + "properties": { + "rootMeanSquaredError": { + "type": "number", + "format": "float", + "description": "Root Mean Squared Error (RMSE)." + }, + "rSquared": { + "format": "float", + "description": "Coefficient of determination as Pearson correlation coefficient. Undefined when ground truth or predictions are constant or near constant.", + "type": "number" + }, + "rootMeanSquaredLogError": { + "format": "float", + "description": "Root mean squared log error. Undefined when there are negative ground truth values or predictions.", + "type": "number" + }, + "meanAbsolutePercentageError": { + "format": "float", + "type": "number", + "description": "Mean absolute percentage error. Infinity when there are zeros in the ground truth." + }, + "meanAbsoluteError": { + "format": "float", + "description": "Mean Absolute Error (MAE).", + "type": "number" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsRegressionEvaluationMetrics", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageSegmentationEvaluationMetricsConfidenceMetricsEntry": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageSegmentationEvaluationMetricsConfidenceMetricsEntry", + "properties": { + "iouScore": { + "format": "float", + "description": "The intersection-over-union score. The measure of overlap of the annotation's category mask with ground truth category mask on the DataItem.", + "type": "number" + }, + "confusionMatrix": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix", + "description": "Confusion matrix for the given confidence threshold." + }, + "diceScoreCoefficient": { + "type": "number", + "format": "float", + "description": "DSC or the F1 score, The harmonic mean of recall and precision." + }, + "precision": { + "format": "float", + "description": "Precision for the given confidence threshold.", + "type": "number" + }, + "recall": { + "type": "number", + "format": "float", + "description": "Recall (True Positive Rate) for the given confidence threshold." + }, + "confidenceThreshold": { + "format": "float", + "type": "number", + "description": "Metrics are computed with an assumption that the model never returns predictions with score lower than this value." + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationAutoTransformation": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationAutoTransformation", + "properties": { + "columnName": { + "type": "string" + } + }, + "description": "Training pipeline will infer the proper transformation based on the statistic of dataset." + }, + "GoogleCloudAiplatformV1beta1StudySpecParameterSpec": { + "properties": { + "categoricalValueSpec": { + "description": "The value spec for a 'CATEGORICAL' parameter.", + "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecCategoricalValueSpec" + }, + "conditionalParameterSpecs": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpec" + }, + "description": "A conditional parameter node is active if the parameter's value matches the conditional node's parent_value_condition. If two items in conditional_parameter_specs have the same name, they must have disjoint parent_value_condition." + }, + "integerValueSpec": { + "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecIntegerValueSpec", + "description": "The value spec for an 'INTEGER' parameter." + }, + "doubleValueSpec": { + "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecDoubleValueSpec", + "description": "The value spec for a 'DOUBLE' parameter." + }, + "scaleType": { + "description": "How the parameter should be scaled. Leave unset for `CATEGORICAL` parameters.", + "enum": [ + "SCALE_TYPE_UNSPECIFIED", + "UNIT_LINEAR_SCALE", + "UNIT_LOG_SCALE", + "UNIT_REVERSE_LOG_SCALE" + ], + "type": "string", + "enumDescriptions": [ + "By default, no scaling is applied.", + "Scales the feasible space to (0, 1) linearly.", + "Scales the feasible space logarithmically to (0, 1). The entire feasible space must be strictly positive.", + "Scales the feasible space \"reverse\" logarithmically to (0, 1). The result is that values close to the top of the feasible space are spread out more than points near the bottom. The entire feasible space must be strictly positive." + ] + }, + "discreteValueSpec": { + "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecDiscreteValueSpec", + "description": "The value spec for a 'DISCRETE' parameter." + }, + "parameterId": { + "type": "string", + "description": "Required. The ID of the parameter. Must not contain whitespaces and must be unique amongst all ParameterSpecs." + } + }, + "id": "GoogleCloudAiplatformV1beta1StudySpecParameterSpec", + "type": "object", + "description": "Represents a single parameter to optimize." + }, + "GoogleTypeMoney": { + "description": "Represents an amount of money with its currency type.", + "type": "object", + "properties": { + "units": { + "format": "int64", + "type": "string", + "description": "The whole units of the amount. For example if `currencyCode` is `\"USD\"`, then 1 unit is one US dollar." + }, + "currencyCode": { + "description": "The three-letter currency code defined in ISO 4217.", + "type": "string" + }, + "nanos": { + "format": "int32", + "description": "Number of nano (10^-9) units of the amount. The value must be between -999,999,999 and +999,999,999 inclusive. If `units` is positive, `nanos` must be positive or zero. If `units` is zero, `nanos` can be positive, zero, or negative. If `units` is negative, `nanos` must be negative or zero. For example $-1.75 is represented as `units`=-1 and `nanos`=-750,000,000.", + "type": "integer" + } + }, + "id": "GoogleTypeMoney" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsGranularity": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsGranularity", + "type": "object", + "properties": { + "quantity": { + "type": "string", + "description": "The number of granularity_units between data points in the training data. If `granularity_unit` is `minute`, can be 1, 5, 10, 15, or 30. For all other values of `granularity_unit`, must be 1.", + "format": "int64" + }, + "unit": { + "type": "string", + "description": "The time granularity unit of this time period. The supported units are: * \"minute\" * \"hour\" * \"day\" * \"week\" * \"month\" * \"year\"" + } + }, + "description": "A duration of time expressed in time granularity units." + }, + "GoogleCloudAiplatformV1beta1EvaluateInstancesRequest": { + "id": "GoogleCloudAiplatformV1beta1EvaluateInstancesRequest", + "description": "Request message for EvaluationService.EvaluateInstances.", + "type": "object", + "properties": { + "summarizationVerbosityInput": { + "description": "Input for summarization verbosity metric.", + "$ref": "GoogleCloudAiplatformV1beta1SummarizationVerbosityInput" + }, + "fluencyInput": { + "$ref": "GoogleCloudAiplatformV1beta1FluencyInput", + "description": "LLM-based metric instance. General text generation metrics, applicable to other categories. Input for fluency metric." + }, + "toolParameterKeyMatchInput": { + "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchInput", + "description": "Input for tool parameter key match metric." + }, + "safetyInput": { + "$ref": "GoogleCloudAiplatformV1beta1SafetyInput", + "description": "Input for safety metric." + }, + "coherenceInput": { + "description": "Input for coherence metric.", + "$ref": "GoogleCloudAiplatformV1beta1CoherenceInput" + }, + "toolParameterKvMatchInput": { + "description": "Input for tool parameter key value match metric.", + "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchInput" + }, + "groundednessInput": { + "$ref": "GoogleCloudAiplatformV1beta1GroundednessInput", + "description": "Input for groundedness metric." + }, + "pairwiseSummarizationQualityInput": { + "$ref": "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityInput", + "description": "Input for pairwise summarization quality metric." + }, + "pairwiseQuestionAnsweringQualityInput": { + "description": "Input for pairwise question answering quality metric.", + "$ref": "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityInput" + }, + "summarizationHelpfulnessInput": { + "$ref": "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessInput", + "description": "Input for summarization helpfulness metric." + }, + "fulfillmentInput": { + "$ref": "GoogleCloudAiplatformV1beta1FulfillmentInput", + "description": "Input for fulfillment metric." + }, + "toolNameMatchInput": { + "$ref": "GoogleCloudAiplatformV1beta1ToolNameMatchInput", + "description": "Input for tool name match metric." + }, + "summarizationQualityInput": { + "$ref": "GoogleCloudAiplatformV1beta1SummarizationQualityInput", + "description": "Input for summarization quality metric." + }, + "bleuInput": { + "$ref": "GoogleCloudAiplatformV1beta1BleuInput", + "description": "Instances and metric spec for bleu metric." + }, + "toolCallValidInput": { + "description": "Tool call metric instances. Input for tool call valid metric.", + "$ref": "GoogleCloudAiplatformV1beta1ToolCallValidInput" + }, + "questionAnsweringQualityInput": { + "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringQualityInput", + "description": "Input for question answering quality metric." + }, + "questionAnsweringHelpfulnessInput": { + "description": "Input for question answering helpfulness metric.", + "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessInput" + }, + "exactMatchInput": { + "description": "Auto metric instances. Instances and metric spec for exact match metric.", + "$ref": "GoogleCloudAiplatformV1beta1ExactMatchInput" + }, + "questionAnsweringCorrectnessInput": { + "description": "Input for question answering correctness metric.", + "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessInput" + }, + "questionAnsweringRelevanceInput": { + "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceInput", + "description": "Input for question answering relevance metric." + }, + "rougeInput": { + "$ref": "GoogleCloudAiplatformV1beta1RougeInput", + "description": "Instances and metric spec for rouge metric." + } + } + }, + "GoogleCloudAiplatformV1beta1FeatureViewIndexConfigBruteForceConfig": { + "type": "object", + "description": "Configuration options for using brute force search.", + "id": "GoogleCloudAiplatformV1beta1FeatureViewIndexConfigBruteForceConfig", + "properties": {} + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoObjectTrackingInputs": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoObjectTrackingInputs", + "properties": { + "modelType": { + "enumDescriptions": [ + "Should not be set.", + "A model best tailored to be used within Google Cloud, and which c annot be exported. Default.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as a TensorFlow or TensorFlow Lite model and used on a mobile or edge device afterwards.", + "A versatile model that is meant to be exported (see ModelService.ExportModel) and used on a Google Coral device.", + "A model that trades off quality for low latency, to be exported (see ModelService.ExportModel) and used on a Google Coral device.", + "A versatile model that is meant to be exported (see ModelService.ExportModel) and used on an NVIDIA Jetson device.", + "A model that trades off quality for low latency, to be exported (see ModelService.ExportModel) and used on an NVIDIA Jetson device." + ], + "enum": [ + "MODEL_TYPE_UNSPECIFIED", + "CLOUD", + "MOBILE_VERSATILE_1", + "MOBILE_CORAL_VERSATILE_1", + "MOBILE_CORAL_LOW_LATENCY_1", + "MOBILE_JETSON_VERSATILE_1", + "MOBILE_JETSON_LOW_LATENCY_1" + ], + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1DeploymentResourcePool": { + "description": "A description of resources that can be shared by multiple DeployedModels, whose underlying specification consists of a DedicatedResources.", + "type": "object", + "properties": { + "createTime": { + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Timestamp when this DeploymentResourcePool was created.", + "type": "string" + }, + "name": { + "description": "Immutable. The resource name of the DeploymentResourcePool. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", + "type": "string" + }, + "dedicatedResources": { + "$ref": "GoogleCloudAiplatformV1beta1DedicatedResources", + "description": "Required. The underlying DedicatedResources that the DeploymentResourcePool uses." + }, + "encryptionSpec": { + "description": "Customer-managed encryption key spec for a DeploymentResourcePool. If set, this DeploymentResourcePool will be secured by this key. Endpoints and the DeploymentResourcePool they deploy in need to have the same EncryptionSpec.", + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" + }, + "disableContainerLogging": { + "description": "If the DeploymentResourcePool is deployed with custom-trained Models or AutoML Tabular Models, the container(s) of the DeploymentResourcePool will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.", + "type": "boolean" + }, + "serviceAccount": { + "type": "string", + "description": "The service account that the DeploymentResourcePool's container(s) run as. Specify the email address of the service account. If this service account is not specified, the container(s) run as a service account that doesn't have access to the resource project. Users deploying the Models to this DeploymentResourcePool must have the `iam.serviceAccounts.actAs` permission on this service account." + } + }, + "id": "GoogleCloudAiplatformV1beta1DeploymentResourcePool" + }, + "GoogleCloudAiplatformV1beta1BatchMigrateResourcesResponse": { + "id": "GoogleCloudAiplatformV1beta1BatchMigrateResourcesResponse", + "description": "Response message for MigrationService.BatchMigrateResources.", + "properties": { + "migrateResourceResponses": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1MigrateResourceResponse" + }, + "type": "array", + "description": "Successfully migrated resources." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1StructFieldValue": { + "properties": { + "name": { + "description": "Name of the field in the struct feature.", + "type": "string" + }, + "value": { + "description": "The value for this field.", + "$ref": "GoogleCloudAiplatformV1beta1FeatureValue" + } + }, + "type": "object", + "description": "One field of a Struct (or object) type feature value.", + "id": "GoogleCloudAiplatformV1beta1StructFieldValue" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaseline": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaseline", + "description": "Output from BatchPredictionJob for Model Monitoring baseline dataset, which can be used to generate baseline attribution scores.", + "properties": { + "predictionFormat": { + "enumDescriptions": [ + "Should not be set.", + "Predictions are in JSONL files.", + "Predictions are in BigQuery." + ], + "type": "string", + "description": "The storage format of the predictions generated BatchPrediction job.", + "enum": [ + "PREDICTION_FORMAT_UNSPECIFIED", + "JSONL", + "BIGQUERY" + ] + }, + "gcs": { + "$ref": "GoogleCloudAiplatformV1beta1GcsDestination", + "description": "Cloud Storage location for BatchExplain output." + }, + "bigquery": { + "$ref": "GoogleCloudAiplatformV1beta1BigQueryDestination", + "description": "BigQuery location for BatchExplain output." + } + } + }, + "GoogleCloudAiplatformV1beta1FindNeighborsRequestQuery": { + "properties": { + "datapoint": { + "$ref": "GoogleCloudAiplatformV1beta1IndexDatapoint", + "description": "Required. The datapoint/vector whose nearest neighbors should be searched for." + }, + "approximateNeighborCount": { + "type": "integer", + "description": "The number of neighbors to find via approximate search before exact reordering is performed. If not set, the default value from scam config is used; if set, this value must be \u003e 0.", + "format": "int32" + }, + "perCrowdingAttributeNeighborCount": { + "format": "int32", + "description": "Crowding is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than some value k' of the k neighbors returned have the same value of crowding_attribute. It's used for improving result diversity. This field is the maximum number of matches with the same crowding tag.", + "type": "integer" + }, + "neighborCount": { + "description": "The number of nearest neighbors to be retrieved from database for each query. If not set, will use the default from the service configuration (https://cloud.google.com/vertex-ai/docs/matching-engine/configuring-indexes#nearest-neighbor-search-config).", + "format": "int32", + "type": "integer" + }, + "rrf": { + "description": "Optional. Represents RRF algorithm that combines search results.", + "$ref": "GoogleCloudAiplatformV1beta1FindNeighborsRequestQueryRRF" + }, + "fractionLeafNodesToSearchOverride": { + "description": "The fraction of the number of leaves to search, set at query time allows user to tune search performance. This value increase result in both search accuracy and latency increase. The value should be between 0.0 and 1.0. If not set or set to 0.0, query uses the default value specified in NearestNeighborSearchConfig.TreeAHConfig.fraction_leaf_nodes_to_search.", + "format": "double", + "type": "number" + } + }, + "type": "object", + "description": "A query to find a number of the nearest neighbors (most similar vectors) of a vector.", + "id": "GoogleCloudAiplatformV1beta1FindNeighborsRequestQuery" + }, + "GoogleCloudAiplatformV1beta1SearchEntryPoint": { + "type": "object", + "properties": { + "sdkBlob": { + "type": "string", + "description": "Optional. Base64 encoded JSON representing array of tuple.", + "format": "byte" + }, + "renderedContent": { + "type": "string", + "description": "Optional. Web content snippet that can be embedded in a web page or an app webview." + } + }, + "description": "Google search entry point.", + "id": "GoogleCloudAiplatformV1beta1SearchEntryPoint" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericArrayTransformation": { + "description": "Treats the column as numerical array and performs following transformation functions. * All transformations for Numerical types applied to the average of the all elements. * The average of empty arrays is treated as zero.", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericArrayTransformation", + "properties": { + "invalidValuesAllowed": { + "type": "boolean", + "description": "If invalid values is allowed, the training pipeline will create a boolean feature that indicated whether the value is valid. Otherwise, the training pipeline will discard the input row from trainining data." + }, + "columnName": { + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ListTensorboardTimeSeriesResponse": { + "id": "GoogleCloudAiplatformV1beta1ListTensorboardTimeSeriesResponse", + "properties": { + "tensorboardTimeSeries": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardTimeSeries" + }, + "description": "The TensorboardTimeSeries mathching the request.", + "type": "array" + }, + "nextPageToken": { + "type": "string", + "description": "A token, which can be sent as ListTensorboardTimeSeriesRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages." + } + }, + "description": "Response message for TensorboardService.ListTensorboardTimeSeries.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1BleuSpec": { + "id": "GoogleCloudAiplatformV1beta1BleuSpec", + "description": "Spec for bleu score metric - calculates the precision of n-grams in the prediction as compared to reference - returns a score ranging between 0 to 1.", + "properties": { + "useEffectiveOrder": { + "type": "boolean", + "description": "Optional. Whether to use_effective_order to compute bleu score." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1CoherenceInstance": { + "properties": { + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + } + }, + "id": "GoogleCloudAiplatformV1beta1CoherenceInstance", + "description": "Spec for coherence instance.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1MutateDeployedIndexResponse": { + "properties": { + "deployedIndex": { + "description": "The DeployedIndex that had been updated in the IndexEndpoint.", + "$ref": "GoogleCloudAiplatformV1beta1DeployedIndex" + } + }, + "description": "Response message for IndexEndpointService.MutateDeployedIndex.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1MutateDeployedIndexResponse" + }, + "GoogleCloudAiplatformV1beta1EnvVar": { + "type": "object", + "properties": { + "value": { + "description": "Required. Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.", + "type": "string" + }, + "name": { + "type": "string", + "description": "Required. Name of the environment variable. Must be a valid C identifier." + } + }, + "description": "Represents an environment variable present in a Container or Python Module.", + "id": "GoogleCloudAiplatformV1beta1EnvVar" + }, + "GoogleCloudAiplatformV1beta1ListSpecialistPoolsResponse": { + "id": "GoogleCloudAiplatformV1beta1ListSpecialistPoolsResponse", + "type": "object", + "properties": { + "nextPageToken": { + "description": "The standard List next-page token.", + "type": "string" + }, + "specialistPools": { + "type": "array", + "description": "A list of SpecialistPools that matches the specified filter in the request.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SpecialistPool" + } + } + }, + "description": "Response message for SpecialistPoolService.ListSpecialistPools." + }, + "GoogleCloudAiplatformV1beta1CreateDeploymentResourcePoolOperationMetadata": { + "type": "object", + "description": "Runtime operation information for CreateDeploymentResourcePool method.", + "id": "GoogleCloudAiplatformV1beta1CreateDeploymentResourcePoolOperationMetadata", + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + } + }, + "GoogleCloudAiplatformV1beta1EvaluateInstancesResponse": { + "id": "GoogleCloudAiplatformV1beta1EvaluateInstancesResponse", + "type": "object", + "description": "Response message for EvaluationService.EvaluateInstances.", + "properties": { + "questionAnsweringRelevanceResult": { + "description": "Result for question answering relevance metric.", + "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceResult" + }, + "summarizationQualityResult": { + "$ref": "GoogleCloudAiplatformV1beta1SummarizationQualityResult", + "description": "Summarization only metrics. Result for summarization quality metric." + }, + "questionAnsweringQualityResult": { + "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringQualityResult", + "description": "Question answering only metrics. Result for question answering quality metric." + }, + "groundednessResult": { + "$ref": "GoogleCloudAiplatformV1beta1GroundednessResult", + "description": "Result for groundedness metric." + }, + "questionAnsweringHelpfulnessResult": { + "description": "Result for question answering helpfulness metric.", + "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessResult" + }, + "pairwiseQuestionAnsweringQualityResult": { + "$ref": "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityResult", + "description": "Result for pairwise question answering quality metric." + }, + "rougeResults": { + "description": "Results for rouge metric.", + "$ref": "GoogleCloudAiplatformV1beta1RougeResults" + }, + "safetyResult": { + "$ref": "GoogleCloudAiplatformV1beta1SafetyResult", + "description": "Result for safety metric." + }, + "exactMatchResults": { + "description": "Auto metric evaluation results. Results for exact match metric.", + "$ref": "GoogleCloudAiplatformV1beta1ExactMatchResults" + }, + "summarizationVerbosityResult": { + "$ref": "GoogleCloudAiplatformV1beta1SummarizationVerbosityResult", + "description": "Result for summarization verbosity metric." + }, + "coherenceResult": { + "$ref": "GoogleCloudAiplatformV1beta1CoherenceResult", + "description": "Result for coherence metric." + }, + "toolParameterKeyMatchResults": { + "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchResults", + "description": "Results for tool parameter key match metric." + }, + "fulfillmentResult": { + "description": "Result for fulfillment metric.", + "$ref": "GoogleCloudAiplatformV1beta1FulfillmentResult" + }, + "toolParameterKvMatchResults": { + "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchResults", + "description": "Results for tool parameter key value match metric." + }, + "toolNameMatchResults": { + "$ref": "GoogleCloudAiplatformV1beta1ToolNameMatchResults", + "description": "Results for tool name match metric." + }, + "summarizationHelpfulnessResult": { + "$ref": "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessResult", + "description": "Result for summarization helpfulness metric." + }, + "pairwiseSummarizationQualityResult": { + "$ref": "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityResult", + "description": "Result for pairwise summarization quality metric." + }, + "questionAnsweringCorrectnessResult": { + "description": "Result for question answering correctness metric.", + "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessResult" + }, + "fluencyResult": { + "$ref": "GoogleCloudAiplatformV1beta1FluencyResult", + "description": "LLM-based metric evaluation result. General text generation metrics, applicable to other categories. Result for fluency metric." + }, + "bleuResults": { + "$ref": "GoogleCloudAiplatformV1beta1BleuResults", + "description": "Results for bleu metric." + }, + "toolCallValidResults": { + "description": "Tool call metrics. Results for tool call valid metric.", + "$ref": "GoogleCloudAiplatformV1beta1ToolCallValidResults" + } + } + }, + "GoogleCloudAiplatformV1beta1StreamRawPredictRequest": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1StreamRawPredictRequest", + "description": "Request message for PredictionService.StreamRawPredict.", + "properties": { + "httpBody": { + "description": "The prediction input. Supports HTTP headers and arbitrary data payload.", + "$ref": "GoogleApiHttpBody" + } + } + }, + "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceSpec": { + "properties": { + "version": { + "description": "Optional. Which version to use for evaluation.", + "type": "integer", + "format": "int32" + }, + "useReference": { + "type": "boolean", + "description": "Optional. Whether to use instance.reference to compute question answering relevance." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceSpec", + "description": "Spec for question answering relevance metric." + }, + "GoogleCloudAiplatformV1beta1BatchCreateFeaturesOperationMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1BatchCreateFeaturesOperationMetadata", + "description": "Details of operations that perform batch create Features.", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "Operation metadata for Feature." + } + } + }, + "GoogleCloudAiplatformV1beta1FeatureSelector": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1FeatureSelector", + "properties": { + "idMatcher": { + "description": "Required. Matches Features based on ID.", + "$ref": "GoogleCloudAiplatformV1beta1IdMatcher" + } + }, + "description": "Selector for Features of an EntityType." + }, + "GoogleCloudAiplatformV1beta1NasJob": { + "id": "GoogleCloudAiplatformV1beta1NasJob", + "description": "Represents a Neural Architecture Search (NAS) job.", + "properties": { + "error": { + "description": "Output only. Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.", + "readOnly": true, + "$ref": "GoogleRpcStatus" + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "The labels with user-defined metadata to organize NasJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels." + }, + "startTime": { + "type": "string", + "description": "Output only. Time when the NasJob for the first time entered the `JOB_STATE_RUNNING` state.", + "format": "google-datetime", + "readOnly": true + }, + "createTime": { + "type": "string", + "description": "Output only. Time when the NasJob was created.", + "format": "google-datetime", + "readOnly": true + }, + "displayName": { + "type": "string", + "description": "Required. The display name of the NasJob. The name can be up to 128 characters long and can consist of any UTF-8 characters." + }, + "state": { + "enumDescriptions": [ + "The job state is unspecified.", + "The job has been just created or resumed and processing has not yet begun.", + "The service is preparing to run the job.", + "The job is in progress.", + "The job completed successfully.", + "The job failed.", + "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "The job has been cancelled.", + "The job has been stopped, and can be resumed.", + "The job has expired.", + "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", + "The job is partially succeeded, some results may be missing due to errors." + ], + "type": "string", + "description": "Output only. The detailed state of the job.", + "enum": [ + "JOB_STATE_UNSPECIFIED", + "JOB_STATE_QUEUED", + "JOB_STATE_PENDING", + "JOB_STATE_RUNNING", + "JOB_STATE_SUCCEEDED", + "JOB_STATE_FAILED", + "JOB_STATE_CANCELLING", + "JOB_STATE_CANCELLED", + "JOB_STATE_PAUSED", + "JOB_STATE_EXPIRED", + "JOB_STATE_UPDATING", + "JOB_STATE_PARTIALLY_SUCCEEDED" + ], + "readOnly": true + }, + "updateTime": { + "readOnly": true, + "format": "google-datetime", + "type": "string", + "description": "Output only. Time when the NasJob was most recently updated." + }, + "name": { + "readOnly": true, + "type": "string", + "description": "Output only. Resource name of the NasJob." + }, + "nasJobOutput": { + "description": "Output only. Output of the NasJob.", + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1NasJobOutput" + }, + "nasJobSpec": { + "$ref": "GoogleCloudAiplatformV1beta1NasJobSpec", + "description": "Required. The specification of a NasJob." + }, + "endTime": { + "readOnly": true, + "type": "string", + "description": "Output only. Time when the NasJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.", + "format": "google-datetime" + }, + "encryptionSpec": { + "description": "Customer-managed encryption key options for a NasJob. If this is set, then all resources created by the NasJob will be encrypted with the provided encryption key.", + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" + }, + "enableRestrictedImageTraining": { + "description": "Optional. Enable a separation of Custom model training and restricted image training for tenant project.", + "type": "boolean", + "deprecated": true + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ImportModelEvaluationRequest": { + "id": "GoogleCloudAiplatformV1beta1ImportModelEvaluationRequest", + "type": "object", + "description": "Request message for ModelService.ImportModelEvaluation", + "properties": { + "modelEvaluation": { + "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluation", + "description": "Required. Model evaluation resource to be imported." + } + } + }, + "GoogleCloudAiplatformV1beta1PredefinedSplit": { + "id": "GoogleCloudAiplatformV1beta1PredefinedSplit", + "type": "object", + "description": "Assigns input data to training, validation, and test sets based on the value of a provided key. Supported only for tabular Datasets.", + "properties": { + "key": { + "description": "Required. The key is a name of one of the Dataset's data columns. The value of the key (either the label's value or value in the column) must be one of {`training`, `validation`, `test`}, and it defines to which set the given piece of data is assigned. If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadata": { + "type": "object", + "description": "Runtime operation metadata with regard to Matching Engine Index.", + "id": "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadata", + "properties": { + "dataBytesCount": { + "type": "string", + "description": "The ingested data size in bytes.", + "format": "int64" + }, + "contentValidationStats": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadataContentValidationStats" + }, + "description": "The validation stats of the content (per file) to be inserted or updated on the Matching Engine Index resource. Populated if contentsDeltaUri is provided as part of Index.metadata. Please note that, currently for those files that are broken or has unsupported file format, we will not have the stats for those files.", + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1beta1RebootPersistentResourceRequest": { + "description": "Request message for PersistentResourceService.RebootPersistentResource.", + "properties": {}, + "id": "GoogleCloudAiplatformV1beta1RebootPersistentResourceRequest", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ToolCallValidSpec": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ToolCallValidSpec", + "properties": {}, + "description": "Spec for tool call valid metric." + }, + "GoogleCloudAiplatformV1beta1DeleteFeatureValuesOperationMetadata": { + "id": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesOperationMetadata", + "type": "object", + "properties": { + "genericMetadata": { + "description": "Operation metadata for Featurestore delete Features values.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "description": "Details of operations that delete Feature values." + }, + "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationMaskAnnotation": { + "description": "The mask based segmentation annotation.", + "properties": { + "annotationSpecColors": { + "description": "The mapping between color and AnnotationSpec for this Annotation.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaAnnotationSpecColor" + } + }, + "maskGcsUri": { + "type": "string", + "description": "Google Cloud Storage URI that points to the mask image. The image must be in PNG format. It must have the same size as the DataItem's image. Each pixel in the image mask represents the AnnotationSpec which the pixel in the image DataItem belong to. Each color is mapped to one AnnotationSpec based on annotation_spec_colors." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationMaskAnnotation" + }, + "GoogleCloudAiplatformV1beta1ComputeTokensRequest": { + "id": "GoogleCloudAiplatformV1beta1ComputeTokensRequest", + "properties": { + "model": { + "type": "string", + "description": "Optional. The name of the publisher model requested to serve the prediction. Format: projects/{project}/locations/{location}/publishers/*/models/*" + }, + "instances": { + "type": "array", + "description": "Optional. The instances that are the input to token computing API call. Schema is identical to the prediction schema of the text model, even for the non-text models, like chat models, or Codey models.", + "items": { + "type": "any" + } + }, + "contents": { + "description": "Optional. Input content.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Content" + }, + "type": "array" + } + }, + "description": "Request message for ComputeTokens RPC call.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ListModelMonitoringJobsResponse": { + "id": "GoogleCloudAiplatformV1beta1ListModelMonitoringJobsResponse", + "type": "object", + "properties": { + "nextPageToken": { + "description": "The standard List next-page token.", + "type": "string" + }, + "modelMonitoringJobs": { + "type": "array", + "description": "A list of ModelMonitoringJobs that matches the specified filter in the request.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringJob" + } + } + }, + "description": "Response message for ModelMonitoringService.ListModelMonitoringJobs." + }, + "GoogleCloudAiplatformV1beta1FeatureOnlineStore": { + "id": "GoogleCloudAiplatformV1beta1FeatureOnlineStore", + "type": "object", + "properties": { + "etag": { + "type": "string", + "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + }, + "createTime": { + "description": "Output only. Timestamp when this FeatureOnlineStore was created.", + "format": "google-datetime", + "readOnly": true, + "type": "string" + }, + "bigtable": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtable", + "description": "Contains settings for the Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore." + }, + "labels": { + "description": "Optional. The labels with user-defined metadata to organize your FeatureOnlineStore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", + "additionalProperties": { + "type": "string" + }, + "type": "object" + }, + "updateTime": { + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Timestamp when this FeatureOnlineStore was last updated.", + "type": "string" + }, + "dedicatedServingEndpoint": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreDedicatedServingEndpoint", + "description": "Optional. The dedicated serving endpoint for this FeatureOnlineStore, which is different from common Vertex service endpoint." + }, + "embeddingManagement": { + "deprecated": true, + "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreEmbeddingManagement", + "description": "Optional. Deprecated: This field is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type." + }, + "optimized": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreOptimized", + "description": "Contains settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. When choose Optimized storage type, need to set PrivateServiceConnectConfig.enable_private_service_connect to use private endpoint. Otherwise will use public endpoint by default." + }, + "name": { + "description": "Identifier. Name of the FeatureOnlineStore. Format: `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}`", + "type": "string" + }, + "state": { + "enum": [ + "STATE_UNSPECIFIED", + "STABLE", + "UPDATING" + ], + "enumDescriptions": [ + "Default value. This value is unused.", + "State when the featureOnlineStore configuration is not being updated and the fields reflect the current configuration of the featureOnlineStore. The featureOnlineStore is usable in this state.", + "The state of the featureOnlineStore configuration when it is being updated. During an update, the fields reflect either the original configuration or the updated configuration of the featureOnlineStore. The featureOnlineStore is still usable in this state." + ], + "readOnly": true, + "type": "string", + "description": "Output only. State of the featureOnlineStore." + }, + "encryptionSpec": { + "description": "Optional. Customer-managed encryption key spec for data storage. If set, online store will be secured by this key.", + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" + } + }, + "description": "Vertex AI Feature Online Store provides a centralized repository for serving ML features and embedding indexes at low latency. The Feature Online Store is a top-level container." + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringJob": { + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringJob", + "properties": { + "scheduleTime": { + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Timestamp when this ModelMonitoringJob was scheduled. It will only appear when this job is triggered by a schedule.", + "type": "string" + }, + "updateTime": { + "readOnly": true, + "description": "Output only. Timestamp when this ModelMonitoringJob was updated most recently.", + "format": "google-datetime", + "type": "string" + }, + "createTime": { + "format": "google-datetime", + "type": "string", + "description": "Output only. Timestamp when this ModelMonitoringJob was created.", + "readOnly": true + }, + "schedule": { + "type": "string", + "description": "Output only. Schedule resource name. It will only appear when this job is triggered by a schedule.", + "readOnly": true + }, + "state": { + "type": "string", + "enum": [ + "JOB_STATE_UNSPECIFIED", + "JOB_STATE_QUEUED", + "JOB_STATE_PENDING", + "JOB_STATE_RUNNING", + "JOB_STATE_SUCCEEDED", + "JOB_STATE_FAILED", + "JOB_STATE_CANCELLING", + "JOB_STATE_CANCELLED", + "JOB_STATE_PAUSED", + "JOB_STATE_EXPIRED", + "JOB_STATE_UPDATING", + "JOB_STATE_PARTIALLY_SUCCEEDED" + ], + "description": "Output only. The state of the monitoring job. * When the job is still creating, the state will be 'JOB_STATE_PENDING'. * Once the job is successfully created, the state will be 'JOB_STATE_RUNNING'. * Once the job is finished, the state will be one of 'JOB_STATE_FAILED', 'JOB_STATE_SUCCEEDED', 'JOB_STATE_PARTIALLY_SUCCEEDED'.", + "readOnly": true, + "enumDescriptions": [ + "The job state is unspecified.", + "The job has been just created or resumed and processing has not yet begun.", + "The service is preparing to run the job.", + "The job is in progress.", + "The job completed successfully.", + "The job failed.", + "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "The job has been cancelled.", + "The job has been stopped, and can be resumed.", + "The job has expired.", + "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", + "The job is partially succeeded, some results may be missing due to errors." + ] + }, + "jobExecutionDetail": { + "description": "Output only. Execution results for all the monitoring objectives.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetail", + "readOnly": true + }, + "displayName": { + "type": "string", + "description": "The display name of the ModelMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8." + }, + "modelMonitoringSpec": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringSpec", + "description": "Monitoring monitoring job spec. It outlines the specifications for monitoring objectives, notifications, and result exports. If left blank, the default monitoring specifications from the top-level resource 'ModelMonitor' will be applied. If provided, we will use the specification defined here rather than the default one." + }, + "name": { + "description": "Output only. Resource name of a ModelMonitoringJob. Format: `projects/{project_id}/locations/{location_id}/modelMonitors/{model_monitor_id}/modelMonitoringJobs/{model_monitoring_job_id}`", + "readOnly": true, + "type": "string" + } + }, + "type": "object", + "description": "Represents a model monitoring job that analyze dataset using different monitoring algorithm." + }, + "GoogleCloudAiplatformV1beta1UpdateExplanationDatasetOperationMetadata": { + "type": "object", + "description": "Runtime operation information for ModelService.UpdateExplanationDataset.", + "properties": { + "genericMetadata": { + "description": "The common part of the operation metadata.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "id": "GoogleCloudAiplatformV1beta1UpdateExplanationDatasetOperationMetadata" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpecEmailConfig": { + "type": "object", + "description": "The config for email alerts.", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpecEmailConfig", + "properties": { + "userEmails": { + "description": "The email addresses to send the alerts.", + "items": { + "type": "string" + }, + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1beta1CreateSolverOperationMetadata": { + "type": "object", + "description": "Runtime operation information for SolverService.CreateSolver.", + "properties": { + "genericMetadata": { + "description": "The generic operation information.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "id": "GoogleCloudAiplatformV1beta1CreateSolverOperationMetadata" + }, + "GoogleCloudAiplatformV1beta1GroundingChunkWeb": { + "description": "Chunk from the web.", + "id": "GoogleCloudAiplatformV1beta1GroundingChunkWeb", + "type": "object", + "properties": { + "uri": { + "type": "string", + "description": "URI reference of the chunk." + }, + "title": { + "type": "string", + "description": "Title of the chunk." + } + } + }, + "GoogleCloudAiplatformV1beta1AddContextChildrenRequest": { + "type": "object", + "properties": { + "childContexts": { + "description": "The resource names of the child Contexts.", + "items": { + "type": "string" + }, + "type": "array" + } + }, + "description": "Request message for MetadataService.AddContextChildren.", + "id": "GoogleCloudAiplatformV1beta1AddContextChildrenRequest" + }, + "GoogleCloudAiplatformV1beta1IntegratedGradientsAttribution": { + "description": "An attribution method that computes the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365", + "id": "GoogleCloudAiplatformV1beta1IntegratedGradientsAttribution", + "properties": { + "stepCount": { + "type": "integer", + "description": "Required. The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is within the desired error range. Valid range of its value is [1, 100], inclusively.", + "format": "int32" + }, + "smoothGradConfig": { + "$ref": "GoogleCloudAiplatformV1beta1SmoothGradConfig", + "description": "Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf" + }, + "blurBaselineConfig": { + "$ref": "GoogleCloudAiplatformV1beta1BlurBaselineConfig", + "description": "Config for IG with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaPredictPredictionImageSegmentationPredictionResult": { + "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionImageSegmentationPredictionResult", + "type": "object", + "description": "Prediction output format for Image Segmentation.", + "properties": { + "confidenceMask": { + "description": "A one channel image which is encoded as an 8bit lossless PNG. The size of the image will be the same as the original image. For a specific pixel, darker color means less confidence in correctness of the cateogry in the categoryMask for the corresponding pixel. Black means no confidence and white means complete confidence.", + "type": "string" + }, + "categoryMask": { + "description": "A PNG image where each pixel in the mask represents the category in which the pixel in the original image was predicted to belong to. The size of this image will be the same as the original image. The mapping between the AnntoationSpec and the color can be found in model's metadata. The model will choose the most likely category and if none of the categories reach the confidence threshold, the pixel will be marked as background.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1SummarizationQualityResult": { + "description": "Spec for summarization quality result.", + "id": "GoogleCloudAiplatformV1beta1SummarizationQualityResult", + "properties": { + "confidence": { + "format": "float", + "readOnly": true, + "description": "Output only. Confidence for summarization quality score.", + "type": "number" + }, + "explanation": { + "readOnly": true, + "description": "Output only. Explanation for summarization quality score.", + "type": "string" + }, + "score": { + "readOnly": true, + "format": "float", + "description": "Output only. Summarization Quality score.", + "type": "number" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ListCachedContentsResponse": { + "description": "Response with a list of CachedContents.", + "type": "object", + "properties": { + "nextPageToken": { + "description": "A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + }, + "cachedContents": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1CachedContent" + }, + "type": "array", + "description": "List of cached contents." + } + }, + "id": "GoogleCloudAiplatformV1beta1ListCachedContentsResponse" + }, + "GoogleCloudAiplatformV1beta1VertexRagStore": { + "description": "Retrieve from Vertex RAG Store for grounding.", + "properties": { + "ragCorpora": { + "type": "array", + "deprecated": true, + "description": "Optional. Deprecated. Please use rag_resources instead.", + "items": { + "type": "string" + } + }, + "vectorDistanceThreshold": { + "type": "number", + "format": "double", + "description": "Optional. Only return results with vector distance smaller than the threshold." + }, + "similarityTopK": { + "format": "int32", + "description": "Optional. Number of top k results to return from the selected corpora.", + "type": "integer" + }, + "ragResources": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1VertexRagStoreRagResource" + }, + "description": "Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support." + } + }, + "id": "GoogleCloudAiplatformV1beta1VertexRagStore", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponseFeatureNameValuePairList": { + "properties": { + "features": { + "description": "List of feature names and values.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponseFeatureNameValuePairListFeatureNameValuePair" + }, + "type": "array" + } + }, + "description": "Response structure in the format of key (feature name) and (feature) value pair.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponseFeatureNameValuePairList" + }, + "GoogleCloudAiplatformV1beta1FileData": { + "id": "GoogleCloudAiplatformV1beta1FileData", + "description": "URI based data.", + "type": "object", + "properties": { + "fileUri": { + "type": "string", + "description": "Required. URI." + }, + "mimeType": { + "type": "string", + "description": "Required. The IANA standard MIME type of the source data." + } + } + }, + "GoogleCloudAiplatformV1beta1DeployModelRequest": { + "type": "object", + "description": "Request message for EndpointService.DeployModel.", + "properties": { + "deployedModel": { + "$ref": "GoogleCloudAiplatformV1beta1DeployedModel", + "description": "Required. The DeployedModel to be created within the Endpoint. Note that Endpoint.traffic_split must be updated for the DeployedModel to start receiving traffic, either as part of this call, or via EndpointService.UpdateEndpoint." + }, + "trafficSplit": { + "description": "A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If this field is non-empty, then the Endpoint's traffic_split will be overwritten with it. To refer to the ID of the just being deployed Model, a \"0\" should be used, and the actual ID of the new DeployedModel will be filled in its place by this method. The traffic percentage values must add up to 100. If this field is empty, then the Endpoint's traffic_split is not updated.", + "additionalProperties": { + "type": "integer", + "format": "int32" + }, + "type": "object" + } + }, + "id": "GoogleCloudAiplatformV1beta1DeployModelRequest" + }, + "GoogleCloudAiplatformV1beta1PauseScheduleRequest": { + "id": "GoogleCloudAiplatformV1beta1PauseScheduleRequest", + "properties": {}, + "type": "object", + "description": "Request message for ScheduleService.PauseSchedule." + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetrics": { + "description": "Metrics for classification evaluation results.", + "properties": { + "logLoss": { + "format": "float", + "description": "The Log Loss metric.", + "type": "number" + }, + "auRoc": { + "type": "number", + "description": "The Area Under Receiver Operating Characteristic curve metric. Micro-averaged for the overall evaluation.", + "format": "float" + }, + "confusionMatrix": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix", + "description": "Confusion matrix of the evaluation." + }, + "confidenceMetrics": { + "type": "array", + "description": "Metrics for each `confidenceThreshold` in 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and `positionThreshold` = INT32_MAX_VALUE. ROC and precision-recall curves, and other aggregated metrics are derived from them. The confidence metrics entries may also be supplied for additional values of `positionThreshold`, but from these no aggregated metrics are computed.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics" + } + }, + "auPrc": { + "format": "float", + "description": "The Area Under Precision-Recall Curve metric. Micro-averaged for the overall evaluation.", + "type": "number" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetrics" + }, + "GoogleCloudAiplatformV1beta1ContainerSpec": { + "properties": { + "imageUri": { + "description": "Required. The URI of a container image in the Container Registry that is to be run on each worker replica.", + "type": "string" + }, + "command": { + "type": "array", + "items": { + "type": "string" + }, + "description": "The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided." + }, + "env": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1EnvVar" + }, + "description": "Environment variables to be passed to the container. Maximum limit is 100." + }, + "args": { + "items": { + "type": "string" + }, + "type": "array", + "description": "The arguments to be passed when starting the container." + } + }, + "description": "The spec of a Container.", + "id": "GoogleCloudAiplatformV1beta1ContainerSpec", + "type": "object" + }, + "CloudAiLargeModelsVisionRaiInfoDetectedLabels": { + "id": "CloudAiLargeModelsVisionRaiInfoDetectedLabels", + "description": "Filters returning list of deteceted labels, scores, and bounding boxes.", + "type": "object", + "properties": { + "raiCategory": { + "description": "The RAI category for the deteceted labels.", + "type": "string" + }, + "entities": { + "items": { + "$ref": "CloudAiLargeModelsVisionRaiInfoDetectedLabelsEntity" + }, + "description": "The list of detected entities for the rai signal.", + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1beta1CancelTrainingPipelineRequest": { + "description": "Request message for PipelineService.CancelTrainingPipeline.", + "type": "object", + "properties": {}, + "id": "GoogleCloudAiplatformV1beta1CancelTrainingPipelineRequest" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringSchema": { + "description": "The Model Monitoring Schema definition.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringSchema", + "properties": { + "featureFields": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringSchemaFieldSchema" + }, + "description": "Feature names of the model. Vertex AI will try to match the features from your dataset as follows: * For 'csv' files, the header names are required, and we will extract the corresponding feature values when the header names align with the feature names. * For 'jsonl' files, we will extract the corresponding feature values if the key names match the feature names. Note: Nested features are not supported, so please ensure your features are flattened. Ensure the feature values are scalar or an array of scalars. * For 'bigquery' dataset, we will extract the corresponding feature values if the column names match the feature names. Note: The column type can be a scalar or an array of scalars. STRUCT or JSON types are not supported. You may use SQL queries to select or aggregate the relevant features from your original table. However, ensure that the 'schema' of the query results meets our requirements. * For the Vertex AI Endpoint Request Response Logging table or Vertex AI Batch Prediction Job results. If the instance_type is an array, ensure that the sequence in feature_fields matches the order of features in the prediction instance. We will match the feature with the array in the order specified in [feature_fields].", + "type": "array" + }, + "groundTruthFields": { + "description": "Target /ground truth names of the model.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringSchemaFieldSchema" + }, + "type": "array" + }, + "predictionFields": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringSchemaFieldSchema" + }, + "description": "Prediction output names of the model. The requirements are the same as the feature_fields. For AutoML Tables, the prediction output name presented in schema will be: `predicted_{target_column}`, the `target_column` is the one you specified when you train the model. For Prediction output drift analysis: * AutoML Classification, the distribution of the argmax label will be analyzed. * AutoML Regression, the distribution of the value will be analyzed." + } + } + }, + "GoogleCloudAiplatformV1beta1ListPublisherModelsResponse": { + "description": "Response message for ModelGardenService.ListPublisherModels.", + "properties": { + "publisherModels": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1PublisherModel" + }, + "description": "List of PublisherModels in the requested page." + }, + "nextPageToken": { + "type": "string", + "description": "A token to retrieve next page of results. Pass to ListPublisherModels.page_token to obtain that page." + } + }, + "id": "GoogleCloudAiplatformV1beta1ListPublisherModelsResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextTransformation": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextTransformation", + "type": "object", + "properties": { + "columnName": { + "type": "string" + } + }, + "description": "Training pipeline will perform following transformation functions. * The text as is--no change to case, punctuation, spelling, tense, and so on. * Tokenize text to words. Convert each words to a dictionary lookup index and generate an embedding for each index. Combine the embedding of all elements into a single embedding using the mean. * Tokenization is based on unicode script boundaries. * Missing values get their own lookup index and resulting embedding. * Stop-words receive no special treatment and are not removed." + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringOutputSpec": { + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringOutputSpec", + "type": "object", + "properties": { + "gcsBaseDirectory": { + "description": "Google Cloud Storage base folder path for metrics, error logs, etc.", + "$ref": "GoogleCloudAiplatformV1beta1GcsDestination" + } + }, + "description": "Specification for the export destination of monitoring results, including metrics, logs, etc." + }, + "GoogleCloudAiplatformV1beta1NotebookExecutionJob": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1NotebookExecutionJob", + "properties": { + "notebookRuntimeTemplateResourceName": { + "type": "string", + "description": "The NotebookRuntimeTemplate to source compute configuration from." + }, + "status": { + "readOnly": true, + "description": "Output only. Populated when the NotebookExecutionJob is completed. When there is an error during notebook execution, the error details are populated.", + "$ref": "GoogleRpcStatus" + }, + "directNotebookSource": { + "description": "The contents of an input notebook file.", + "$ref": "GoogleCloudAiplatformV1beta1NotebookExecutionJobDirectNotebookSource" + }, + "displayName": { + "type": "string", + "description": "The display name of the NotebookExecutionJob. The name can be up to 128 characters long and can consist of any UTF-8 characters." + }, + "gcsNotebookSource": { + "description": "The Cloud Storage url pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`", + "$ref": "GoogleCloudAiplatformV1beta1NotebookExecutionJobGcsNotebookSource" + }, + "scheduleResourceName": { + "readOnly": true, + "description": "Output only. The Schedule resource name if this job is triggered by one. Format: `projects/{project_id}/locations/{location}/schedules/{schedule_id}`", + "type": "string" + }, + "executionUser": { + "description": "The user email to run the execution as. Only supported by Colab runtimes.", + "type": "string" + }, + "updateTime": { + "format": "google-datetime", + "description": "Output only. Timestamp when this NotebookExecutionJob was most recently updated.", + "type": "string", + "readOnly": true + }, + "createTime": { + "type": "string", + "format": "google-datetime", + "description": "Output only. Timestamp when this NotebookExecutionJob was created.", + "readOnly": true + }, + "dataformRepositorySource": { + "description": "The Dataform Repository pointing to a single file notebook repository.", + "$ref": "GoogleCloudAiplatformV1beta1NotebookExecutionJobDataformRepositorySource" + }, + "jobState": { + "enum": [ + "JOB_STATE_UNSPECIFIED", + "JOB_STATE_QUEUED", + "JOB_STATE_PENDING", + "JOB_STATE_RUNNING", + "JOB_STATE_SUCCEEDED", + "JOB_STATE_FAILED", + "JOB_STATE_CANCELLING", + "JOB_STATE_CANCELLED", + "JOB_STATE_PAUSED", + "JOB_STATE_EXPIRED", + "JOB_STATE_UPDATING", + "JOB_STATE_PARTIALLY_SUCCEEDED" + ], + "description": "Output only. The state of the NotebookExecutionJob.", + "readOnly": true, + "type": "string", + "enumDescriptions": [ + "The job state is unspecified.", + "The job has been just created or resumed and processing has not yet begun.", + "The service is preparing to run the job.", + "The job is in progress.", + "The job completed successfully.", + "The job failed.", + "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "The job has been cancelled.", + "The job has been stopped, and can be resumed.", + "The job has expired.", + "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", + "The job is partially succeeded, some results may be missing due to errors." + ] + }, + "serviceAccount": { + "type": "string", + "description": "The service account to run the execution as." + }, + "gcsOutputUri": { + "type": "string", + "description": "The Cloud Storage location to upload the result to. Format: `gs://bucket-name`" + }, + "executionTimeout": { + "description": "Max running time of the execution job in seconds (default 86400s / 24 hrs).", + "type": "string", + "format": "google-duration" + }, + "name": { + "description": "Output only. The resource name of this NotebookExecutionJob. Format: `projects/{project_id}/locations/{location}/notebookExecutionJobs/{job_id}`", + "type": "string", + "readOnly": true + }, + "labels": { + "description": "The labels with user-defined metadata to organize NotebookExecutionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", + "type": "object", + "additionalProperties": { + "type": "string" + } + } + }, + "description": "NotebookExecutionJob represents an instance of a notebook execution." + }, + "GoogleCloudAiplatformV1beta1SpecialistPool": { + "description": "SpecialistPool represents customers' own workforce to work on their data labeling jobs. It includes a group of specialist managers and workers. Managers are responsible for managing the workers in this pool as well as customers' data labeling jobs associated with this pool. Customers create specialist pool as well as start data labeling jobs on Cloud, managers and workers handle the jobs using CrowdCompute console.", + "type": "object", + "properties": { + "pendingDataLabelingJobs": { + "readOnly": true, + "type": "array", + "description": "Output only. The resource name of the pending data labeling jobs.", + "items": { + "type": "string" + } + }, + "displayName": { + "type": "string", + "description": "Required. The user-defined name of the SpecialistPool. The name can be up to 128 characters long and can consist of any UTF-8 characters. This field should be unique on project-level." + }, + "name": { + "description": "Required. The resource name of the SpecialistPool.", + "type": "string" + }, + "specialistWorkerEmails": { + "description": "The email addresses of workers in the SpecialistPool.", + "type": "array", + "items": { + "type": "string" + } + }, + "specialistManagerEmails": { + "description": "The email addresses of the managers in the SpecialistPool.", + "type": "array", + "items": { + "type": "string" + } + }, + "specialistManagersCount": { + "description": "Output only. The number of managers in this SpecialistPool.", + "format": "int32", + "type": "integer", + "readOnly": true + } + }, + "id": "GoogleCloudAiplatformV1beta1SpecialistPool" + }, + "GoogleCloudAiplatformV1beta1RougeSpec": { + "properties": { + "rougeType": { + "description": "Optional. Supported rouge types are rougen[1-9], rougeL, and rougeLsum.", + "type": "string" + }, + "useStemmer": { + "type": "boolean", + "description": "Optional. Whether to use stemmer to compute rouge score." + }, + "splitSummaries": { + "type": "boolean", + "description": "Optional. Whether to split summaries while using rougeLsum." + } + }, + "description": "Spec for rouge score metric - calculates the recall of n-grams in prediction as compared to reference - returns a score ranging between 0 and 1.", + "id": "GoogleCloudAiplatformV1beta1RougeSpec", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ListStudiesResponse": { + "id": "GoogleCloudAiplatformV1beta1ListStudiesResponse", + "description": "Response message for VizierService.ListStudies.", + "properties": { + "nextPageToken": { + "type": "string", + "description": "Passes this token as the `page_token` field of the request for a subsequent call. If this field is omitted, there are no subsequent pages." + }, + "studies": { + "description": "The studies associated with the project.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Study" + }, + "type": "array" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationNumericTransformation": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationNumericTransformation", + "description": "Training pipeline will perform following transformation functions. * The value converted to float32. * The z_score of the value. * log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * A boolean value that indicates whether the value is valid.", + "properties": { + "columnName": { + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1RetrieveContextsResponse": { + "properties": { + "contexts": { + "$ref": "GoogleCloudAiplatformV1beta1RagContexts", + "description": "The contexts of the query." + } + }, + "description": "Response message for VertexRagService.RetrieveContexts.", + "id": "GoogleCloudAiplatformV1beta1RetrieveContextsResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetection": { + "type": "object", + "description": "A TrainingJob that trains and uploads an AutoML Image Object Detection Model.", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetection", + "properties": { + "metadata": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionMetadata", + "description": "The metadata information" + }, + "inputs": { + "description": "The input parameters of this TrainingJob.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionInputs" + } + } + }, + "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateDataLabelingDatasetConfigMigrateDataLabelingAnnotatedDatasetConfig": { + "type": "object", + "properties": { + "annotatedDataset": { + "type": "string", + "description": "Required. Full resource name of data labeling AnnotatedDataset. Format: `projects/{project}/datasets/{dataset}/annotatedDatasets/{annotated_dataset}`." + } + }, + "description": "Config for migrating AnnotatedDataset in datalabeling.googleapis.com to Vertex AI's SavedQuery.", + "id": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateDataLabelingDatasetConfigMigrateDataLabelingAnnotatedDatasetConfig" + }, + "GoogleCloudAiplatformV1beta1SchemaPredictInstanceImageObjectDetectionPredictionInstance": { + "properties": { + "mimeType": { + "type": "string", + "description": "The MIME type of the content of the image. Only the images in below listed MIME types are supported. - image/jpeg - image/gif - image/png - image/webp - image/bmp - image/tiff - image/vnd.microsoft.icon" + }, + "content": { + "description": "The image bytes or Cloud Storage URI to make the prediction on.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaPredictInstanceImageObjectDetectionPredictionInstance", + "type": "object", + "description": "Prediction input format for Image Object Detection." + }, + "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessInstance": { + "id": "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessInstance", + "type": "object", + "properties": { + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + }, + "reference": { + "description": "Optional. Ground truth used to compare against the prediction.", + "type": "string" + }, + "context": { + "description": "Required. Text to be summarized.", + "type": "string" + }, + "instruction": { + "description": "Optional. Summarization prompt for LLM.", + "type": "string" + } + }, + "description": "Spec for summarization helpfulness instance." + }, + "GoogleCloudAiplatformV1beta1Model": { + "properties": { + "satisfiesPzs": { + "readOnly": true, + "type": "boolean", + "description": "Output only. Reserved for future use." + }, + "artifactUri": { + "type": "string", + "description": "Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not required for AutoML Models." + }, + "versionDescription": { + "type": "string", + "description": "The description of this version." + }, + "createTime": { + "description": "Output only. Timestamp when this Model was uploaded into Vertex AI.", + "type": "string", + "readOnly": true, + "format": "google-datetime" + }, + "name": { + "description": "The resource name of the Model.", + "type": "string" + }, + "versionCreateTime": { + "description": "Output only. Timestamp when this version was created.", + "type": "string", + "format": "google-datetime", + "readOnly": true + }, + "encryptionSpec": { + "description": "Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key.", + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" + }, + "explanationSpec": { + "description": "The default explanation specification for this Model. The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated. All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob. If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob.", + "$ref": "GoogleCloudAiplatformV1beta1ExplanationSpec" + }, + "supportedOutputStorageFormats": { + "readOnly": true, + "description": "Output only. The formats this Model supports in BatchPredictionJob.output_config. If both PredictSchemata.instance_schema_uri and PredictSchemata.prediction_schema_uri exist, the predictions are returned together with their instances. In other words, the prediction has the original instance data first, followed by the actual prediction content (as per the schema). The possible formats are: * `jsonl` The JSON Lines format, where each prediction is a single line. Uses GcsDestination. * `csv` The CSV format, where each prediction is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses GcsDestination. * `bigquery` Each prediction is a single row in a BigQuery table, uses BigQueryDestination . If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.", + "type": "array", + "items": { + "type": "string" + } + }, + "updateTime": { + "readOnly": true, + "format": "google-datetime", + "type": "string", + "description": "Output only. Timestamp when this Model was most recently updated." + }, + "supportedInputStorageFormats": { + "readOnly": true, + "items": { + "type": "string" + }, + "description": "Output only. The formats this Model supports in BatchPredictionJob.input_config. If PredictSchemata.instance_schema_uri exists, the instances should be given as per that schema. The possible formats are: * `jsonl` The JSON Lines format, where each instance is a single line. Uses GcsSource. * `csv` The CSV format, where each instance is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses GcsSource. * `tf-record` The TFRecord format, where each instance is a single record in tfrecord syntax. Uses GcsSource. * `tf-record-gzip` Similar to `tf-record`, but the file is gzipped. Uses GcsSource. * `bigquery` Each instance is a single row in BigQuery. Uses BigQuerySource. * `file-list` Each line of the file is the location of an instance to process, uses `gcs_source` field of the InputConfig object. If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.", + "type": "array" + }, + "versionUpdateTime": { + "description": "Output only. Timestamp when this version was most recently updated.", + "type": "string", + "readOnly": true, + "format": "google-datetime" + }, + "displayName": { + "description": "Required. The display name of the Model. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + }, + "metadataArtifact": { + "description": "Output only. The resource name of the Artifact that was created in MetadataStore when creating the Model. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.", + "readOnly": true, + "type": "string" + }, + "predictSchemata": { + "$ref": "GoogleCloudAiplatformV1beta1PredictSchemata", + "description": "The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain." + }, + "modelSourceInfo": { + "$ref": "GoogleCloudAiplatformV1beta1ModelSourceInfo", + "description": "Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or saved and tuned from Genie or Model Garden.", + "readOnly": true + }, + "metadata": { + "description": "Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.", + "type": "any" + }, + "baseModelSource": { + "$ref": "GoogleCloudAiplatformV1beta1ModelBaseModelSource", + "description": "Optional. User input field to specify the base model source. Currently it only supports specifing the Model Garden models and Genie models." + }, + "containerSpec": { + "description": "Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not required for AutoML Models.", + "$ref": "GoogleCloudAiplatformV1beta1ModelContainerSpec" + }, + "supportedExportFormats": { + "description": "Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.", + "type": "array", + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelExportFormat" + } + }, + "etag": { + "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "description": { + "type": "string", + "description": "The description of the Model." + }, + "deployedModels": { + "description": "Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1DeployedModelRef" + }, + "readOnly": true, + "type": "array" + }, + "originalModelInfo": { + "description": "Output only. If this Model is a copy of another Model, this contains info about the original.", + "$ref": "GoogleCloudAiplatformV1beta1ModelOriginalModelInfo", + "readOnly": true + }, + "metadataSchemaUri": { + "description": "Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.", + "type": "string" + }, + "supportedDeploymentResourcesTypes": { + "readOnly": true, + "description": "Output only. When this Model is deployed, its prediction resources are described by the `prediction_resources` field of the Endpoint.deployed_models object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an Endpoint and does not support online predictions (PredictionService.Predict or PredictionService.Explain). Such a Model can serve predictions by using a BatchPredictionJob, if it has at least one entry each in supported_input_storage_formats and supported_output_storage_formats.", + "type": "array", + "items": { + "type": "string", + "enumDescriptions": [ + "Should not be used.", + "Resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.", + "Resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.", + "Resources that can be shared by multiple DeployedModels. A pre-configured DeploymentResourcePool is required." + ], + "enum": [ + "DEPLOYMENT_RESOURCES_TYPE_UNSPECIFIED", + "DEDICATED_RESOURCES", + "AUTOMATIC_RESOURCES", + "SHARED_RESOURCES" + ] + } + }, + "trainingPipeline": { + "description": "Output only. The resource name of the TrainingPipeline that uploaded this Model, if any.", + "readOnly": true, + "type": "string" + }, + "versionId": { + "description": "Output only. Immutable. The version ID of the model. A new version is committed when a new model version is uploaded or trained under an existing model id. It is an auto-incrementing decimal number in string representation.", + "type": "string", + "readOnly": true + }, + "satisfiesPzi": { + "type": "boolean", + "description": "Output only. Reserved for future use.", + "readOnly": true + }, + "labels": { + "description": "The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", + "additionalProperties": { + "type": "string" + }, + "type": "object" + }, + "versionAliases": { + "type": "array", + "items": { + "type": "string" + }, + "description": "User provided version aliases so that a model version can be referenced via alias (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_alias}` instead of auto-generated version id (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_id})`. The format is a-z{0,126}[a-z0-9] to distinguish from version_id. A default version alias will be created for the first version of the model, and there must be exactly one default version alias for a model." + } + }, + "description": "A trained machine learning Model.", + "id": "GoogleCloudAiplatformV1beta1Model", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SummarizationQualityInput": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SummarizationQualityInput", + "properties": { + "instance": { + "$ref": "GoogleCloudAiplatformV1beta1SummarizationQualityInstance", + "description": "Required. Summarization quality instance." + }, + "metricSpec": { + "description": "Required. Spec for summarization quality score metric.", + "$ref": "GoogleCloudAiplatformV1beta1SummarizationQualitySpec" + } + }, + "description": "Input for summarization quality metric." + }, + "GoogleCloudAiplatformV1beta1NasTrialDetail": { + "description": "Represents a NasTrial details along with its parameters. If there is a corresponding train NasTrial, the train NasTrial is also returned.", + "properties": { + "name": { + "type": "string", + "readOnly": true, + "description": "Output only. Resource name of the NasTrialDetail." + }, + "trainTrial": { + "$ref": "GoogleCloudAiplatformV1beta1NasTrial", + "description": "The train NasTrial corresponding to search_trial. Only populated if search_trial is used for training." + }, + "searchTrial": { + "description": "The requested search NasTrial.", + "$ref": "GoogleCloudAiplatformV1beta1NasTrial" + }, + "parameters": { + "type": "string", + "description": "The parameters for the NasJob NasTrial." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1NasTrialDetail" + }, + "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata": { + "description": "All metadata of most recent monitoring pipelines.", + "properties": { + "status": { + "description": "The status of the most recent monitoring pipeline.", + "$ref": "GoogleRpcStatus" + }, + "runTime": { + "format": "google-datetime", + "description": "The time that most recent monitoring pipelines that is related to this run.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata" + }, + "GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistributionDatasetBucket": { + "properties": { + "count": { + "description": "Output only. Number of values in the bucket.", + "type": "number", + "format": "double", + "readOnly": true + }, + "left": { + "readOnly": true, + "format": "double", + "type": "number", + "description": "Output only. Left bound of the bucket." + }, + "right": { + "format": "double", + "description": "Output only. Right bound of the bucket.", + "type": "number", + "readOnly": true + } + }, + "description": "Dataset bucket used to create a histogram for the distribution given a population of values.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistributionDatasetBucket" + }, + "GoogleCloudAiplatformV1beta1Presets": { + "type": "object", + "properties": { + "modality": { + "description": "The modality of the uploaded model, which automatically configures the distance measurement and feature normalization for the underlying example index and queries. If your model does not precisely fit one of these types, it is okay to choose the closest type.", + "enum": [ + "MODALITY_UNSPECIFIED", + "IMAGE", + "TEXT", + "TABULAR" + ], + "type": "string", + "enumDescriptions": [ + "Should not be set. Added as a recommended best practice for enums", + "IMAGE modality", + "TEXT modality", + "TABULAR modality" + ] + }, + "query": { + "description": "Preset option controlling parameters for speed-precision trade-off when querying for examples. If omitted, defaults to `PRECISE`.", + "enum": [ + "PRECISE", + "FAST" + ], + "enumDescriptions": [ + "More precise neighbors as a trade-off against slower response.", + "Faster response as a trade-off against less precise neighbors." + ], + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1Presets", + "description": "Preset configuration for example-based explanations" + }, + "GoogleCloudAiplatformV1beta1VideoMetadata": { + "type": "object", + "description": "Metadata describes the input video content.", + "properties": { + "endOffset": { + "format": "google-duration", + "type": "string", + "description": "Optional. The end offset of the video." + }, + "startOffset": { + "type": "string", + "format": "google-duration", + "description": "Optional. The start offset of the video." + } + }, + "id": "GoogleCloudAiplatformV1beta1VideoMetadata" + }, + "GoogleCloudAiplatformV1beta1SchemaTextSentimentAnnotation": { + "id": "GoogleCloudAiplatformV1beta1SchemaTextSentimentAnnotation", + "properties": { + "sentiment": { + "format": "int32", + "description": "The sentiment score for text.", + "type": "integer" + }, + "sentimentMax": { + "format": "int32", + "description": "The sentiment max score for text.", + "type": "integer" + }, + "annotationSpecId": { + "type": "string", + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." + }, + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that this Annotation pertains to." + } + }, + "type": "object", + "description": "Annotation details specific to text sentiment." + }, + "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfig": { + "type": "object", + "description": "Configuration of how features in Featurestore are monitored.", + "properties": { + "numericalThresholdConfig": { + "description": "Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).", + "$ref": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigThresholdConfig" + }, + "categoricalThresholdConfig": { + "$ref": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigThresholdConfig", + "description": "Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING)." + }, + "snapshotAnalysis": { + "description": "The config for Snapshot Analysis Based Feature Monitoring.", + "$ref": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigSnapshotAnalysis" + }, + "importFeaturesAnalysis": { + "$ref": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigImportFeaturesAnalysis", + "description": "The config for ImportFeatures Analysis Based Feature Monitoring." + } + }, + "id": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfig" + }, + "GoogleCloudAiplatformV1beta1DeployedIndexRef": { + "properties": { + "indexEndpoint": { + "description": "Immutable. A resource name of the IndexEndpoint.", + "type": "string" + }, + "displayName": { + "description": "Output only. The display name of the DeployedIndex.", + "readOnly": true, + "type": "string" + }, + "deployedIndexId": { + "description": "Immutable. The ID of the DeployedIndex in the above IndexEndpoint.", + "type": "string" + } + }, + "description": "Points to a DeployedIndex.", + "id": "GoogleCloudAiplatformV1beta1DeployedIndexRef", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1AvroSource": { + "properties": { + "gcsSource": { + "description": "Required. Google Cloud Storage location.", + "$ref": "GoogleCloudAiplatformV1beta1GcsSource" + } + }, + "id": "GoogleCloudAiplatformV1beta1AvroSource", + "description": "The storage details for Avro input content.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ListEndpointsResponse": { + "description": "Response message for EndpointService.ListEndpoints.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ListEndpointsResponse", + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token to retrieve the next page of results. Pass to ListEndpointsRequest.page_token to obtain that page." + }, + "endpoints": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Endpoint" + }, + "description": "List of Endpoints in the requested page." + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionRecognitionMetrics": { + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionRecognitionMetrics", + "description": "Model evaluation metrics for video action recognition.", + "properties": { + "evaluatedActionCount": { + "format": "int32", + "type": "integer", + "description": "The number of ground truth actions used to create this evaluation." + }, + "videoActionMetrics": { + "description": "The metric entries for precision window lengths: 1s,2s,3s.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionMetrics" + } + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SearchNearestEntitiesRequest": { + "properties": { + "query": { + "description": "Required. The query.", + "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborQuery" + }, + "returnFullEntity": { + "description": "Optional. If set to true, the full entities (including all vector values and metadata) of the nearest neighbors are returned; otherwise only entity id of the nearest neighbors will be returned. Note that returning full entities will significantly increase the latency and cost of the query.", + "type": "boolean" + } + }, + "id": "GoogleCloudAiplatformV1beta1SearchNearestEntitiesRequest", + "description": "The request message for FeatureOnlineStoreService.SearchNearestEntities.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FindNeighborsRequest": { + "type": "object", + "properties": { + "queries": { + "type": "array", + "description": "The list of queries.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1FindNeighborsRequestQuery" + } + }, + "returnFullDatapoint": { + "type": "boolean", + "description": "If set to true, the full datapoints (including all vector values and restricts) of the nearest neighbors are returned. Note that returning full datapoint will significantly increase the latency and cost of the query." + }, + "deployedIndexId": { + "type": "string", + "description": "The ID of the DeployedIndex that will serve the request. This request is sent to a specific IndexEndpoint, as per the IndexEndpoint.network. That IndexEndpoint also has IndexEndpoint.deployed_indexes, and each such index has a DeployedIndex.id field. The value of the field below must equal one of the DeployedIndex.id fields of the IndexEndpoint that is being called for this request." + } + }, + "description": "The request message for MatchService.FindNeighbors.", + "id": "GoogleCloudAiplatformV1beta1FindNeighborsRequest" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationAutoTransformation": { + "properties": { + "columnName": { + "type": "string" + } + }, + "description": "Training pipeline will infer the proper transformation based on the statistic of dataset.", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationAutoTransformation", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1AnnotationSpec": { + "properties": { + "createTime": { + "type": "string", + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Timestamp when this AnnotationSpec was created." + }, + "displayName": { + "description": "Required. The user-defined name of the AnnotationSpec. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + }, + "etag": { + "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "name": { + "readOnly": true, + "description": "Output only. Resource name of the AnnotationSpec.", + "type": "string" + }, + "updateTime": { + "type": "string", + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Timestamp when AnnotationSpec was last updated." + } + }, + "id": "GoogleCloudAiplatformV1beta1AnnotationSpec", + "type": "object", + "description": "Identifies a concept with which DataItems may be annotated with." + }, + "GoogleCloudAiplatformV1beta1CompletionStats": { + "type": "object", + "properties": { + "incompleteCount": { + "format": "int64", + "description": "Output only. In cases when enough errors are encountered a job, pipeline, or operation may be failed as a whole. Below is the number of entities for which the processing had not been finished (either in successful or failed state). Set to -1 if the number is unknown (for example, the operation failed before the total entity number could be collected).", + "readOnly": true, + "type": "string" + }, + "successfulForecastPointCount": { + "type": "string", + "readOnly": true, + "description": "Output only. The number of the successful forecast points that are generated by the forecasting model. This is ONLY used by the forecasting batch prediction.", + "format": "int64" + }, + "failedCount": { + "format": "int64", + "description": "Output only. The number of entities for which any error was encountered.", + "readOnly": true, + "type": "string" + }, + "successfulCount": { + "description": "Output only. The number of entities that had been processed successfully.", + "readOnly": true, + "type": "string", + "format": "int64" + } + }, + "description": "Success and error statistics of processing multiple entities (for example, DataItems or structured data rows) in batch.", + "id": "GoogleCloudAiplatformV1beta1CompletionStats" + }, + "GoogleCloudAiplatformV1beta1TimeSeriesData": { + "properties": { + "tensorboardTimeSeriesId": { + "description": "Required. The ID of the TensorboardTimeSeries, which will become the final component of the TensorboardTimeSeries' resource name", + "type": "string" + }, + "valueType": { + "description": "Required. Immutable. The value type of this time series. All the values in this time series data must match this value type.", + "enum": [ + "VALUE_TYPE_UNSPECIFIED", + "SCALAR", + "TENSOR", + "BLOB_SEQUENCE" + ], + "enumDescriptions": [ + "The value type is unspecified.", + "Used for TensorboardTimeSeries that is a list of scalars. E.g. accuracy of a model over epochs/time.", + "Used for TensorboardTimeSeries that is a list of tensors. E.g. histograms of weights of layer in a model over epoch/time.", + "Used for TensorboardTimeSeries that is a list of blob sequences. E.g. set of sample images with labels over epochs/time." + ], + "type": "string" + }, + "values": { + "description": "Required. Data points in this time series.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1TimeSeriesDataPoint" + } + } + }, + "id": "GoogleCloudAiplatformV1beta1TimeSeriesData", + "type": "object", + "description": "All the data stored in a TensorboardTimeSeries." + }, + "GoogleCloudAiplatformV1beta1SearchMigratableResourcesRequest": { + "properties": { + "filter": { + "type": "string", + "description": "A filter for your search. You can use the following types of filters: * Resource type filters. The following strings filter for a specific type of MigratableResource: * `ml_engine_model_version:*` * `automl_model:*` * `automl_dataset:*` * `data_labeling_dataset:*` * \"Migrated or not\" filters. The following strings filter for resources that either have or have not already been migrated: * `last_migrate_time:*` filters for migrated resources. * `NOT last_migrate_time:*` filters for not yet migrated resources." + }, + "pageSize": { + "type": "integer", + "format": "int32", + "description": "The standard page size. The default and maximum value is 100." + }, + "pageToken": { + "type": "string", + "description": "The standard page token." + } + }, + "id": "GoogleCloudAiplatformV1beta1SearchMigratableResourcesRequest", + "type": "object", + "description": "Request message for MigrationService.SearchMigratableResources." + }, + "GoogleCloudAiplatformV1beta1ExportDataConfig": { + "id": "GoogleCloudAiplatformV1beta1ExportDataConfig", + "description": "Describes what part of the Dataset is to be exported, the destination of the export and how to export.", + "properties": { + "fractionSplit": { + "$ref": "GoogleCloudAiplatformV1beta1ExportFractionSplit", + "description": "Split based on fractions defining the size of each set." + }, + "annotationsFilter": { + "type": "string", + "description": "An expression for filtering what part of the Dataset is to be exported. Only Annotations that match this filter will be exported. The filter syntax is the same as in ListAnnotations." + }, + "gcsDestination": { + "$ref": "GoogleCloudAiplatformV1beta1GcsDestination", + "description": "The Google Cloud Storage location where the output is to be written to. In the given directory a new directory will be created with name: `export-data--` where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All export output will be written into that directory. Inside that directory, annotations with the same schema will be grouped into sub directories which are named with the corresponding annotations' schema title. Inside these sub directories, a schema.yaml will be created to describe the output format." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1NearestNeighborQueryStringFilter": { + "type": "object", + "properties": { + "allowTokens": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Optional. The allowed tokens." + }, + "denyTokens": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Optional. The denied tokens." + }, + "name": { + "type": "string", + "description": "Required. Column names in BigQuery that used as filters." + } + }, + "description": "String filter is used to search a subset of the entities by using boolean rules on string columns. For example: if a query specifies string filter with 'name = color, allow_tokens = {red, blue}, deny_tokens = {purple}',' then that query will match entities that are red or blue, but if those points are also purple, then they will be excluded even if they are red/blue. Only string filter is supported for now, numeric filter will be supported in the near future.", + "id": "GoogleCloudAiplatformV1beta1NearestNeighborQueryStringFilter" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfigEmailAlertConfig": { + "properties": { + "userEmails": { + "description": "The email addresses to send the alert.", + "type": "array", + "items": { + "type": "string" + } + } + }, + "description": "The config for email alert.", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfigEmailAlertConfig", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaVisualInspectionClassificationLabelSavedQueryMetadata": { + "id": "GoogleCloudAiplatformV1beta1SchemaVisualInspectionClassificationLabelSavedQueryMetadata", + "properties": { + "multiLabel": { + "description": "Whether or not the classification label is multi_label.", + "type": "boolean" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1NearestNeighborQueryEmbedding": { + "type": "object", + "description": "The embedding vector.", + "properties": { + "value": { + "items": { + "type": "number", + "format": "float" + }, + "type": "array", + "description": "Optional. Individual value in the embedding." + } + }, + "id": "GoogleCloudAiplatformV1beta1NearestNeighborQueryEmbedding" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextExtractionEvaluationMetrics": { + "description": "Metrics for text extraction evaluation results.", + "properties": { + "confusionMatrix": { + "description": "Confusion matrix of the evaluation. Only set for Models where number of AnnotationSpecs is no more than 10. Only set for ModelEvaluations, not for ModelEvaluationSlices.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix" + }, + "confidenceMetrics": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextExtractionEvaluationMetricsConfidenceMetrics" + }, + "type": "array", + "description": "Metrics that have confidence thresholds. Precision-recall curve can be derived from them." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextExtractionEvaluationMetrics" + }, + "GoogleCloudAiplatformV1beta1SafetyRating": { + "id": "GoogleCloudAiplatformV1beta1SafetyRating", + "properties": { + "severityScore": { + "format": "float", + "type": "number", + "readOnly": true, + "description": "Output only. Harm severity score." + }, + "blocked": { + "description": "Output only. Indicates whether the content was filtered out because of this rating.", + "type": "boolean", + "readOnly": true + }, + "probability": { + "type": "string", + "enumDescriptions": [ + "Harm probability unspecified.", + "Negligible level of harm.", + "Low level of harm.", + "Medium level of harm.", + "High level of harm." + ], + "description": "Output only. Harm probability levels in the content.", + "readOnly": true, + "enum": [ + "HARM_PROBABILITY_UNSPECIFIED", + "NEGLIGIBLE", + "LOW", + "MEDIUM", + "HIGH" + ] + }, + "severity": { + "description": "Output only. Harm severity levels in the content.", + "enum": [ + "HARM_SEVERITY_UNSPECIFIED", + "HARM_SEVERITY_NEGLIGIBLE", + "HARM_SEVERITY_LOW", + "HARM_SEVERITY_MEDIUM", + "HARM_SEVERITY_HIGH" + ], + "enumDescriptions": [ + "Harm severity unspecified.", + "Negligible level of harm severity.", + "Low level of harm severity.", + "Medium level of harm severity.", + "High level of harm severity." + ], + "type": "string", + "readOnly": true + }, + "category": { + "enum": [ + "HARM_CATEGORY_UNSPECIFIED", + "HARM_CATEGORY_HATE_SPEECH", + "HARM_CATEGORY_DANGEROUS_CONTENT", + "HARM_CATEGORY_HARASSMENT", + "HARM_CATEGORY_SEXUALLY_EXPLICIT" + ], + "readOnly": true, + "description": "Output only. Harm category.", + "type": "string", + "enumDescriptions": [ + "The harm category is unspecified.", + "The harm category is hate speech.", + "The harm category is dangerous content.", + "The harm category is harassment.", + "The harm category is sexually explicit content." + ] + }, + "probabilityScore": { + "type": "number", + "format": "float", + "readOnly": true, + "description": "Output only. Harm probability score." + } + }, + "type": "object", + "description": "Safety rating corresponding to the generated content." + }, + "GoogleCloudAiplatformV1beta1ModelOriginalModelInfo": { + "properties": { + "model": { + "type": "string", + "readOnly": true, + "description": "Output only. The resource name of the Model this Model is a copy of, including the revision. Format: `projects/{project}/locations/{location}/models/{model_id}@{version_id}`" + } + }, + "type": "object", + "description": "Contains information about the original Model if this Model is a copy.", + "id": "GoogleCloudAiplatformV1beta1ModelOriginalModelInfo" + }, + "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessInstance": { + "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessInstance", + "type": "object", + "description": "Spec for question answering correctness instance.", + "properties": { + "instruction": { + "type": "string", + "description": "Required. The question asked and other instruction in the inference prompt." + }, + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + }, + "reference": { + "description": "Optional. Ground truth used to compare against the prediction.", + "type": "string" + }, + "context": { + "type": "string", + "description": "Optional. Text provided as context to answer the question." + } + } + }, + "GoogleCloudAiplatformV1beta1PublisherModelResourceReference": { + "id": "GoogleCloudAiplatformV1beta1PublisherModelResourceReference", + "description": "Reference to a resource.", + "properties": { + "description": { + "description": "Description of the resource.", + "deprecated": true, + "type": "string" + }, + "uri": { + "type": "string", + "description": "The URI of the resource." + }, + "resourceName": { + "type": "string", + "description": "The resource name of the Google Cloud resource." + }, + "useCase": { + "description": "Use case (CUJ) of the resource.", + "deprecated": true, + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaPredictParamsVideoObjectTrackingPredictionParams": { + "description": "Prediction model parameters for Video Object Tracking.", + "properties": { + "minBoundingBoxSize": { + "format": "float", + "description": "Only bounding boxes with shortest edge at least that long as a relative value of video frame size are returned. Default value is 0.0.", + "type": "number" + }, + "confidenceThreshold": { + "type": "number", + "format": "float", + "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0" + }, + "maxPredictions": { + "type": "integer", + "description": "The model only returns up to that many top, by confidence score, predictions per frame of the video. If this number is very high, the Model may return fewer predictions per frame. Default value is 50.", + "format": "int32" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaPredictParamsVideoObjectTrackingPredictionParams" + }, + "GoogleCloudAiplatformV1beta1ListNasJobsResponse": { + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token to retrieve the next page of results. Pass to ListNasJobsRequest.page_token to obtain that page." + }, + "nasJobs": { + "description": "List of NasJobs in the requested page. NasJob.nas_job_output of the jobs will not be returned.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1NasJob" + }, + "type": "array" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ListNasJobsResponse", + "description": "Response message for JobService.ListNasJobs" + }, + "GoogleCloudAiplatformV1beta1ToolParameterKVMatchInput": { + "type": "object", + "description": "Input for tool parameter key value match metric.", + "id": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchInput", + "properties": { + "metricSpec": { + "description": "Required. Spec for tool parameter key value match metric.", + "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchSpec" + }, + "instances": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchInstance" + }, + "description": "Required. Repeated tool parameter key value match instances." + } + } + }, + "GoogleCloudAiplatformV1beta1ImportDataRequest": { + "type": "object", + "properties": { + "importConfigs": { + "description": "Required. The desired input locations. The contents of all input locations will be imported in one batch.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ImportDataConfig" + }, + "type": "array" + } + }, + "description": "Request message for DatasetService.ImportData.", + "id": "GoogleCloudAiplatformV1beta1ImportDataRequest" + }, + "GoogleCloudAiplatformV1beta1ListModelEvaluationsResponse": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ListModelEvaluationsResponse", + "properties": { + "nextPageToken": { + "description": "A token to retrieve next page of results. Pass to ListModelEvaluationsRequest.page_token to obtain that page.", + "type": "string" + }, + "modelEvaluations": { + "description": "List of ModelEvaluations in the requested page.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluation" + } + } + }, + "description": "Response message for ModelService.ListModelEvaluations." + }, + "GoogleCloudAiplatformV1beta1FunctionCallingConfig": { + "description": "Function calling config.", + "properties": { + "mode": { + "enumDescriptions": [ + "Unspecified function calling mode. This value should not be used.", + "Default model behavior, model decides to predict either a function call or a natural language repspose.", + "Model is constrained to always predicting a function call only. If \"allowed_function_names\" are set, the predicted function call will be limited to any one of \"allowed_function_names\", else the predicted function call will be any one of the provided \"function_declarations\".", + "Model will not predict any function call. Model behavior is same as when not passing any function declarations." + ], + "description": "Optional. Function calling mode.", + "enum": [ + "MODE_UNSPECIFIED", + "AUTO", + "ANY", + "NONE" + ], + "type": "string" + }, + "allowedFunctionNames": { + "description": "Optional. Function names to call. Only set when the Mode is ANY. Function names should match [FunctionDeclaration.name]. With mode set to ANY, model will predict a function call from the set of function names provided.", + "items": { + "type": "string" + }, + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1beta1FunctionCallingConfig", + "type": "object" + }, + "GoogleIamV1GetPolicyOptions": { + "id": "GoogleIamV1GetPolicyOptions", + "description": "Encapsulates settings provided to GetIamPolicy.", + "type": "object", + "properties": { + "requestedPolicyVersion": { + "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", + "type": "integer", + "format": "int32" + } + } + }, + "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateDataLabelingDatasetConfig": { + "id": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateDataLabelingDatasetConfig", + "properties": { + "datasetDisplayName": { + "description": "Optional. Display name of the Dataset in Vertex AI. System will pick a display name if unspecified.", + "type": "string" + }, + "dataset": { + "description": "Required. Full resource name of data labeling Dataset. Format: `projects/{project}/datasets/{dataset}`.", + "type": "string" + }, + "migrateDataLabelingAnnotatedDatasetConfigs": { + "type": "array", + "description": "Optional. Configs for migrating AnnotatedDataset in datalabeling.googleapis.com to Vertex AI's SavedQuery. The specified AnnotatedDatasets have to belong to the datalabeling Dataset.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateDataLabelingDatasetConfigMigrateDataLabelingAnnotatedDatasetConfig" + } + } + }, + "description": "Config for migrating Dataset in datalabeling.googleapis.com to Vertex AI's Dataset.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1PipelineTaskDetailPipelineTaskStatus": { + "properties": { + "state": { + "enum": [ + "STATE_UNSPECIFIED", + "PENDING", + "RUNNING", + "SUCCEEDED", + "CANCEL_PENDING", + "CANCELLING", + "CANCELLED", + "FAILED", + "SKIPPED", + "NOT_TRIGGERED" + ], + "readOnly": true, + "type": "string", + "description": "Output only. The state of the task.", + "enumDescriptions": [ + "Unspecified.", + "Specifies pending state for the task.", + "Specifies task is being executed.", + "Specifies task completed successfully.", + "Specifies Task cancel is in pending state.", + "Specifies task is being cancelled.", + "Specifies task was cancelled.", + "Specifies task failed.", + "Specifies task was skipped due to cache hit.", + "Specifies that the task was not triggered because the task's trigger policy is not satisfied. The trigger policy is specified in the `condition` field of PipelineJob.pipeline_spec." + ] + }, + "error": { + "readOnly": true, + "description": "Output only. The error that occurred during the state. May be set when the state is any of the non-final state (PENDING/RUNNING/CANCELLING) or FAILED state. If the state is FAILED, the error here is final and not going to be retried. If the state is a non-final state, the error indicates a system-error being retried.", + "$ref": "GoogleRpcStatus" + }, + "updateTime": { + "readOnly": true, + "description": "Output only. Update time of this status.", + "type": "string", + "format": "google-datetime" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1PipelineTaskDetailPipelineTaskStatus", + "description": "A single record of the task status." + }, + "GoogleCloudAiplatformV1beta1Scheduling": { + "id": "GoogleCloudAiplatformV1beta1Scheduling", + "type": "object", + "properties": { + "disableRetries": { + "type": "boolean", + "description": "Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides `Scheduling.restart_job_on_worker_restart` to false." + }, + "restartJobOnWorkerRestart": { + "description": "Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.", + "type": "boolean" + }, + "strategy": { + "enum": [ + "STRATEGY_UNSPECIFIED", + "ON_DEMAND", + "LOW_COST" + ], + "enumDescriptions": [ + "Strategy will default to ON_DEMAND.", + "Regular on-demand provisioning strategy.", + "Low cost by making potential use of spot resources." + ], + "description": "Optional. This determines which type of scheduling strategy to use.", + "type": "string" + }, + "timeout": { + "type": "string", + "format": "google-duration", + "description": "The maximum job running time. The default is 7 days." + } + }, + "description": "All parameters related to queuing and scheduling of custom jobs." + }, + "GoogleCloudAiplatformV1beta1SchemaPredictParamsImageClassificationPredictionParams": { + "description": "Prediction model parameters for Image Classification.", + "id": "GoogleCloudAiplatformV1beta1SchemaPredictParamsImageClassificationPredictionParams", + "properties": { + "confidenceThreshold": { + "type": "number", + "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0", + "format": "float" + }, + "maxPredictions": { + "type": "integer", + "format": "int32", + "description": "The Model only returns up to that many top, by confidence score, predictions per instance. If this number is very high, the Model may return fewer predictions. Default value is 10." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataInputConfig": { + "description": "The time series Dataset's data source. The Dataset doesn't store the data directly, but only pointer(s) to its data.", + "id": "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataInputConfig", + "type": "object", + "properties": { + "gcsSource": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataGcsSource" + }, + "bigquerySource": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataBigQuerySource" + } + } + }, + "GoogleCloudAiplatformV1beta1FeatureViewFeatureRegistrySourceFeatureGroup": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1FeatureViewFeatureRegistrySourceFeatureGroup", + "properties": { + "featureGroupId": { + "type": "string", + "description": "Required. Identifier of the feature group." + }, + "featureIds": { + "type": "array", + "description": "Required. Identifiers of features under the feature group.", + "items": { + "type": "string" + } + } + }, + "description": "Features belonging to a single feature group that will be synced to Online Store." + }, + "GoogleCloudAiplatformV1beta1AddExecutionEventsResponse": { + "id": "GoogleCloudAiplatformV1beta1AddExecutionEventsResponse", + "type": "object", + "properties": {}, + "description": "Response message for MetadataService.AddExecutionEvents." + }, + "GoogleCloudAiplatformV1beta1GroundingChunkRetrievedContext": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1GroundingChunkRetrievedContext", + "description": "Chunk from context retrieved by the retrieval tools.", + "properties": { + "title": { + "type": "string", + "description": "Title of the attribution." + }, + "uri": { + "type": "string", + "description": "URI reference of the attribution." + } + } + }, + "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchInstance": { + "type": "object", + "properties": { + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + }, + "reference": { + "type": "string", + "description": "Required. Ground truth used to compare against the prediction." + } + }, + "description": "Spec for tool parameter key match instance.", + "id": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchInstance" + }, + "GoogleCloudAiplatformV1beta1ModelEvaluation": { + "id": "GoogleCloudAiplatformV1beta1ModelEvaluation", + "properties": { + "name": { + "readOnly": true, + "description": "Output only. The resource name of the ModelEvaluation.", + "type": "string" + }, + "metrics": { + "description": "Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri", + "type": "any" + }, + "createTime": { + "description": "Output only. Timestamp when this ModelEvaluation was created.", + "type": "string", + "format": "google-datetime", + "readOnly": true + }, + "metadata": { + "description": "The metadata of the ModelEvaluation. For the ModelEvaluation uploaded from Managed Pipeline, metadata contains a structured value with keys of \"pipeline_job_id\", \"evaluation_dataset_type\", \"evaluation_dataset_path\", \"row_based_metrics_path\".", + "type": "any" + }, + "explanationSpecs": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationModelEvaluationExplanationSpec" + }, + "description": "Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.", + "type": "array" + }, + "displayName": { + "description": "The display name of the ModelEvaluation.", + "type": "string" + }, + "biasConfigs": { + "description": "Specify the configuration for bias detection.", + "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationBiasConfig" + }, + "sliceDimensions": { + "items": { + "type": "string" + }, + "type": "array", + "description": "All possible dimensions of ModelEvaluationSlices. The dimensions can be used as the filter of the ModelService.ListModelEvaluationSlices request, in the form of `slice.dimension = `." + }, + "modelExplanation": { + "$ref": "GoogleCloudAiplatformV1beta1ModelExplanation", + "description": "Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for AutoML tabular Models. " + }, + "metricsSchemaUri": { + "description": "Points to a YAML file stored on Google Cloud Storage describing the metrics of this ModelEvaluation. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).", + "type": "string" + } + }, + "type": "object", + "description": "A collection of metrics calculated by comparing Model's predictions on all of the test data against annotations from the test data." + }, + "GoogleCloudAiplatformV1beta1WriteFeatureValuesPayload": { + "properties": { + "entityId": { + "type": "string", + "description": "Required. The ID of the entity." + }, + "featureValues": { + "type": "object", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureValue" + }, + "description": "Required. Feature values to be written, mapping from Feature ID to value. Up to 100,000 `feature_values` entries may be written across all payloads. The feature generation time, aligned by days, must be no older than five years (1825 days) and no later than one year (366 days) in the future." + } + }, + "type": "object", + "description": "Contains Feature values to be written for a specific entity.", + "id": "GoogleCloudAiplatformV1beta1WriteFeatureValuesPayload" + }, + "GoogleCloudAiplatformV1beta1ScheduleRunResponse": { + "properties": { + "runResponse": { + "type": "string", + "description": "The response of the scheduled run." + }, + "scheduledRunTime": { + "type": "string", + "format": "google-datetime", + "description": "The scheduled run time based on the user-specified schedule." + } + }, + "description": "Status of a scheduled run.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ScheduleRunResponse" + }, + "GoogleCloudAiplatformV1beta1ModelExportFormat": { + "properties": { + "id": { + "readOnly": true, + "description": "Output only. The ID of the export format. The possible format IDs are: * `tflite` Used for Android mobile devices. * `edgetpu-tflite` Used for [Edge TPU](https://cloud.google.com/edge-tpu/) devices. * `tf-saved-model` A tensorflow model in SavedModel format. * `tf-js` A [TensorFlow.js](https://www.tensorflow.org/js) model that can be used in the browser and in Node.js using JavaScript. * `core-ml` Used for iOS mobile devices. * `custom-trained` A Model that was uploaded or trained by custom code.", + "type": "string" + }, + "exportableContents": { + "items": { + "type": "string", + "enumDescriptions": [ + "Should not be used.", + "Model artifact and any of its supported files. Will be exported to the location specified by the `artifactDestination` field of the ExportModelRequest.output_config object.", + "The container image that is to be used when deploying this Model. Will be exported to the location specified by the `imageDestination` field of the ExportModelRequest.output_config object." + ], + "enum": [ + "EXPORTABLE_CONTENT_UNSPECIFIED", + "ARTIFACT", + "IMAGE" + ] + }, + "description": "Output only. The content of this Model that may be exported.", + "type": "array", + "readOnly": true + } + }, + "id": "GoogleCloudAiplatformV1beta1ModelExportFormat", + "description": "Represents export format supported by the Model. All formats export to Google Cloud Storage.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ResourcePoolAutoscalingSpec": { + "id": "GoogleCloudAiplatformV1beta1ResourcePoolAutoscalingSpec", + "type": "object", + "description": "The min/max number of replicas allowed if enabling autoscaling", + "properties": { + "maxReplicaCount": { + "description": "Optional. max replicas in the node pool, must be ≥ replica_count and \u003e min_replica_count or will throw error", + "type": "string", + "format": "int64" + }, + "minReplicaCount": { + "format": "int64", + "type": "string", + "description": "Optional. min replicas in the node pool, must be ≤ replica_count and \u003c max_replica_count or will throw error. For autoscaling enabled Ray-on-Vertex, we allow min_replica_count of a resource_pool to be 0 to match the OSS Ray behavior(https://docs.ray.io/en/latest/cluster/vms/user-guides/configuring-autoscaling.html#cluster-config-parameters). As for Persistent Resource, the min_replica_count must be \u003e 0, we added a corresponding validation inside CreatePersistentResourceRequestValidator.java." + } + } + }, + "GoogleCloudAiplatformV1beta1Trial": { + "properties": { + "clientId": { + "type": "string", + "readOnly": true, + "description": "Output only. The identifier of the client that originally requested this Trial. Each client is identified by a unique client_id. When a client asks for a suggestion, Vertex AI Vizier will assign it a Trial. The client should evaluate the Trial, complete it, and report back to Vertex AI Vizier. If suggestion is asked again by same client_id before the Trial is completed, the same Trial will be returned. Multiple clients with different client_ids can ask for suggestions simultaneously, each of them will get their own Trial." + }, + "parameters": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1TrialParameter" + }, + "readOnly": true, + "description": "Output only. The parameters of the Trial." + }, + "state": { + "type": "string", + "readOnly": true, + "description": "Output only. The detailed state of the Trial.", + "enum": [ + "STATE_UNSPECIFIED", + "REQUESTED", + "ACTIVE", + "STOPPING", + "SUCCEEDED", + "INFEASIBLE" + ], + "enumDescriptions": [ + "The Trial state is unspecified.", + "Indicates that a specific Trial has been requested, but it has not yet been suggested by the service.", + "Indicates that the Trial has been suggested.", + "Indicates that the Trial should stop according to the service.", + "Indicates that the Trial is completed successfully.", + "Indicates that the Trial should not be attempted again. The service will set a Trial to INFEASIBLE when it's done but missing the final_measurement." + ] + }, + "name": { + "description": "Output only. Resource name of the Trial assigned by the service.", + "readOnly": true, + "type": "string" + }, + "id": { + "type": "string", + "description": "Output only. The identifier of the Trial assigned by the service.", + "readOnly": true + }, + "endTime": { + "description": "Output only. Time when the Trial's status changed to `SUCCEEDED` or `INFEASIBLE`.", + "format": "google-datetime", + "readOnly": true, + "type": "string" + }, + "startTime": { + "type": "string", + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Time when the Trial was started." + }, + "infeasibleReason": { + "type": "string", + "readOnly": true, + "description": "Output only. A human readable string describing why the Trial is infeasible. This is set only if Trial state is `INFEASIBLE`." + }, + "customJob": { + "type": "string", + "description": "Output only. The CustomJob name linked to the Trial. It's set for a HyperparameterTuningJob's Trial.", + "readOnly": true + }, + "finalMeasurement": { + "description": "Output only. The final measurement containing the objective value.", + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1Measurement" + }, + "measurements": { + "type": "array", + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Measurement" + }, + "description": "Output only. A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_duration). These are used for early stopping computations." + }, + "webAccessUris": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "readOnly": true, + "description": "Output only. URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) (one URI for each training node). Only available if this trial is part of a HyperparameterTuningJob and the job's trial_job_spec.enable_web_access field is `true`. The keys are names of each node used for the trial; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell." + } + }, + "id": "GoogleCloudAiplatformV1beta1Trial", + "type": "object", + "description": "A message representing a Trial. A Trial contains a unique set of Parameters that has been or will be evaluated, along with the objective metrics got by running the Trial." + }, + "GoogleCloudAiplatformV1beta1FluencySpec": { + "description": "Spec for fluency score metric.", + "properties": { + "version": { + "type": "integer", + "description": "Optional. Which version to use for evaluation.", + "format": "int32" + } + }, + "id": "GoogleCloudAiplatformV1beta1FluencySpec", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1TimestampSplit": { + "properties": { + "testFraction": { + "type": "number", + "description": "The fraction of the input data that is to be used to evaluate the Model.", + "format": "double" + }, + "key": { + "description": "Required. The key is a name of one of the Dataset's data columns. The values of the key (the values in the column) must be in RFC 3339 `date-time` format, where `time-offset` = `\"Z\"` (e.g. 1985-04-12T23:20:50.52Z). If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline.", + "type": "string" + }, + "validationFraction": { + "format": "double", + "description": "The fraction of the input data that is to be used to validate the Model.", + "type": "number" + }, + "trainingFraction": { + "description": "The fraction of the input data that is to be used to train the Model.", + "type": "number", + "format": "double" + } + }, + "description": "Assigns input data to training, validation, and test sets based on a provided timestamps. The youngest data pieces are assigned to training set, next to validation set, and the oldest to the test set. Supported only for tabular Datasets.", + "id": "GoogleCloudAiplatformV1beta1TimestampSplit", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1CreateTensorboardOperationMetadata": { + "id": "GoogleCloudAiplatformV1beta1CreateTensorboardOperationMetadata", + "description": "Details of operations that perform create Tensorboard.", + "properties": { + "genericMetadata": { + "description": "Operation metadata for Tensorboard.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoClassification": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoClassification", + "properties": { + "inputs": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoClassificationInputs", + "description": "The input parameters of this TrainingJob." + } + }, + "description": "A TrainingJob that trains and uploads an AutoML Video Classification Model." + }, + "GoogleCloudAiplatformV1beta1ListSchedulesResponse": { + "description": "Response message for ScheduleService.ListSchedules", + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token to retrieve the next page of results. Pass to ListSchedulesRequest.page_token to obtain that page." + }, + "schedules": { + "type": "array", + "description": "List of Schedules in the requested page.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Schedule" + } + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ListSchedulesResponse" + }, + "GoogleCloudAiplatformV1beta1FunctionDeclaration": { + "description": "Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name and parameters. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.", + "properties": { + "parameters": { + "description": "Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1", + "$ref": "GoogleCloudAiplatformV1beta1Schema" + }, + "name": { + "description": "Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots and dashes, with a maximum length of 64.", + "type": "string" + }, + "description": { + "type": "string", + "description": "Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function." + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Schema", + "description": "Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1FunctionDeclaration" + }, + "GoogleCloudAiplatformV1beta1FeatureViewIndexConfigTreeAHConfig": { + "description": "Configuration options for the tree-AH algorithm.", + "properties": { + "leafNodeEmbeddingCount": { + "format": "int64", + "description": "Optional. Number of embeddings on each leaf node. The default value is 1000 if not set.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1FeatureViewIndexConfigTreeAHConfig" + }, + "GoogleCloudAiplatformV1beta1CustomJob": { + "id": "GoogleCloudAiplatformV1beta1CustomJob", + "type": "object", + "description": "Represents a job that runs custom workloads such as a Docker container or a Python package. A CustomJob can have multiple worker pools and each worker pool can have its own machine and input spec. A CustomJob will be cleaned up once the job enters terminal state (failed or succeeded).", + "properties": { + "encryptionSpec": { + "description": "Customer-managed encryption key options for a CustomJob. If this is set, then all resources created by the CustomJob will be encrypted with the provided encryption key.", + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" + }, + "startTime": { + "readOnly": true, + "description": "Output only. Time when the CustomJob for the first time entered the `JOB_STATE_RUNNING` state.", + "format": "google-datetime", + "type": "string" + }, + "name": { + "readOnly": true, + "type": "string", + "description": "Output only. Resource name of a CustomJob." + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "description": "The labels with user-defined metadata to organize CustomJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", + "type": "object" + }, + "displayName": { + "description": "Required. The display name of the CustomJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + }, + "error": { + "description": "Output only. Only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "readOnly": true, + "$ref": "GoogleRpcStatus" + }, + "endTime": { + "readOnly": true, + "description": "Output only. Time when the CustomJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.", + "type": "string", + "format": "google-datetime" + }, + "state": { + "readOnly": true, + "type": "string", + "enum": [ + "JOB_STATE_UNSPECIFIED", + "JOB_STATE_QUEUED", + "JOB_STATE_PENDING", + "JOB_STATE_RUNNING", + "JOB_STATE_SUCCEEDED", + "JOB_STATE_FAILED", + "JOB_STATE_CANCELLING", + "JOB_STATE_CANCELLED", + "JOB_STATE_PAUSED", + "JOB_STATE_EXPIRED", + "JOB_STATE_UPDATING", + "JOB_STATE_PARTIALLY_SUCCEEDED" + ], + "description": "Output only. The detailed state of the job.", + "enumDescriptions": [ + "The job state is unspecified.", + "The job has been just created or resumed and processing has not yet begun.", + "The service is preparing to run the job.", + "The job is in progress.", + "The job completed successfully.", + "The job failed.", + "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", + "The job has been cancelled.", + "The job has been stopped, and can be resumed.", + "The job has expired.", + "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", + "The job is partially succeeded, some results may be missing due to errors." + ] + }, + "createTime": { + "readOnly": true, + "description": "Output only. Time when the CustomJob was created.", + "type": "string", + "format": "google-datetime" + }, + "jobSpec": { + "description": "Required. Job spec.", + "$ref": "GoogleCloudAiplatformV1beta1CustomJobSpec" + }, + "updateTime": { + "readOnly": true, + "type": "string", + "format": "google-datetime", + "description": "Output only. Time when the CustomJob was most recently updated." + }, + "webAccessUris": { + "type": "object", + "readOnly": true, + "description": "Output only. URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) (one URI for each training node). Only available if job_spec.enable_web_access is `true`. The keys are names of each node in the training job; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell.", + "additionalProperties": { + "type": "string" + } + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoObjectTrackingPredictionResultFrame": { + "properties": { + "yMax": { + "description": "The bottommost coordinate of the bounding box.", + "format": "float", + "type": "number" + }, + "yMin": { + "format": "float", + "type": "number", + "description": "The topmost coordinate of the bounding box." + }, + "xMin": { + "type": "number", + "format": "float", + "description": "The leftmost coordinate of the bounding box." + }, + "xMax": { + "type": "number", + "format": "float", + "description": "The rightmost coordinate of the bounding box." + }, + "timeOffset": { + "description": "A time (frame) of a video in which the object has been detected. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end.", + "format": "google-duration", + "type": "string" + } + }, + "description": "The fields `xMin`, `xMax`, `yMin`, and `yMax` refer to a bounding box, i.e. the rectangle over the video frame pinpointing the found AnnotationSpec. The coordinates are relative to the frame size, and the point 0,0 is in the top left of the frame.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoObjectTrackingPredictionResultFrame" + }, + "GoogleCloudAiplatformV1beta1SchemaPredictInstanceImageSegmentationPredictionInstance": { + "description": "Prediction input format for Image Segmentation.", + "properties": { + "content": { + "description": "The image bytes to make the predictions on.", + "type": "string" + }, + "mimeType": { + "type": "string", + "description": "The MIME type of the content of the image. Only the images in below listed MIME types are supported. - image/jpeg - image/png" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaPredictInstanceImageSegmentationPredictionInstance", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ExplainResponse": { + "type": "object", + "properties": { + "explanations": { + "description": "The explanations of the Model's PredictResponse.predictions. It has the same number of elements as instances to be explained.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Explanation" + }, + "type": "array" + }, + "concurrentExplanations": { + "type": "object", + "description": "This field stores the results of the explanations run in parallel with The default explanation strategy/method.", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1ExplainResponseConcurrentExplanation" + } + }, + "predictions": { + "type": "array", + "description": "The predictions that are the output of the predictions call. Same as PredictResponse.predictions.", + "items": { + "type": "any" + } + }, + "deployedModelId": { + "type": "string", + "description": "ID of the Endpoint's DeployedModel that served this explanation." + } + }, + "id": "GoogleCloudAiplatformV1beta1ExplainResponse", + "description": "Response message for PredictionService.Explain." + }, + "GoogleCloudAiplatformV1beta1RestoreDatasetVersionOperationMetadata": { + "id": "GoogleCloudAiplatformV1beta1RestoreDatasetVersionOperationMetadata", + "properties": { + "genericMetadata": { + "description": "The common part of the operation metadata.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "type": "object", + "description": "Runtime operation information for DatasetService.RestoreDatasetVersion." + }, + "GoogleCloudAiplatformV1beta1ExportModelResponse": { + "id": "GoogleCloudAiplatformV1beta1ExportModelResponse", + "description": "Response message of ModelService.ExportModel operation.", + "type": "object", + "properties": {} + }, + "GoogleCloudAiplatformV1beta1StreamingFetchFeatureValuesResponse": { + "id": "GoogleCloudAiplatformV1beta1StreamingFetchFeatureValuesResponse", + "description": "Response message for FeatureOnlineStoreService.StreamingFetchFeatureValues.", + "properties": { + "data": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponse" + } + }, + "dataKeysWithError": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDataKey" + }, + "type": "array" + }, + "status": { + "description": "Response status. If OK, then StreamingFetchFeatureValuesResponse.data will be populated. Otherwise StreamingFetchFeatureValuesResponse.data_keys_with_error will be populated with the appropriate data keys. The error only applies to the listed data keys - the stream will remain open for further FeatureOnlineStoreService.StreamingFetchFeatureValuesRequest requests.", + "$ref": "GoogleRpcStatus" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaImageDatasetMetadata": { + "properties": { + "gcsBucket": { + "type": "string", + "description": "Google Cloud Storage Bucket name that contains the blob data of this Dataset." + }, + "dataItemSchemaUri": { + "type": "string", + "description": "Points to a YAML file stored on Google Cloud Storage describing payload of the Image DataItems that belong to this Dataset." + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaImageDatasetMetadata", + "type": "object", + "description": "The metadata of Datasets that contain Image DataItems." + }, + "GoogleCloudAiplatformV1beta1SchemaTextClassificationAnnotation": { + "type": "object", + "properties": { + "annotationSpecId": { + "type": "string", + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." + }, + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that this Annotation pertains to." + } + }, + "description": "Annotation details specific to text classification.", + "id": "GoogleCloudAiplatformV1beta1SchemaTextClassificationAnnotation" + }, + "GoogleCloudAiplatformV1beta1FluencyInstance": { + "description": "Spec for fluency instance.", + "properties": { + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1FluencyInstance" + }, + "GoogleCloudAiplatformV1beta1BleuMetricValue": { + "description": "Bleu metric value for an instance.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1BleuMetricValue", + "properties": { + "score": { + "type": "number", + "readOnly": true, + "description": "Output only. Bleu score.", + "format": "float" + } + } + }, + "GoogleCloudAiplatformV1beta1CompleteTrialRequest": { + "id": "GoogleCloudAiplatformV1beta1CompleteTrialRequest", + "properties": { + "finalMeasurement": { + "$ref": "GoogleCloudAiplatformV1beta1Measurement", + "description": "Optional. If provided, it will be used as the completed Trial's final_measurement; Otherwise, the service will auto-select a previously reported measurement as the final-measurement" + }, + "trialInfeasible": { + "type": "boolean", + "description": "Optional. True if the Trial cannot be run with the given Parameter, and final_measurement will be ignored." + }, + "infeasibleReason": { + "type": "string", + "description": "Optional. A human readable reason why the trial was infeasible. This should only be provided if `trial_infeasible` is true." + } + }, + "type": "object", + "description": "Request message for VizierService.CompleteTrial." + }, + "GoogleCloudAiplatformV1beta1ModelBaseModelSource": { + "description": "User input field to specify the base model source. Currently it only supports specifing the Model Garden models and Genie models.", + "properties": { + "genieSource": { + "$ref": "GoogleCloudAiplatformV1beta1GenieSource", + "description": "Information about the base model of Genie models." + }, + "modelGardenSource": { + "description": "Source information of Model Garden models.", + "$ref": "GoogleCloudAiplatformV1beta1ModelGardenSource" + } + }, + "id": "GoogleCloudAiplatformV1beta1ModelBaseModelSource", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ExecuteExtensionRequest": { + "type": "object", + "properties": { + "operationId": { + "type": "string", + "description": "Required. The desired ID of the operation to be executed in this extension as defined in ExtensionOperation.operation_id." + }, + "operationParams": { + "type": "object", + "additionalProperties": { + "type": "any", + "description": "Properties of the object." + }, + "description": "Optional. Request parameters that will be used for executing this operation. The struct should be in a form of map with param name as the key and actual param value as the value. E.g. If this operation requires a param \"name\" to be set to \"abc\". you can set this to something like {\"name\": \"abc\"}." + }, + "runtimeAuthConfig": { + "$ref": "GoogleCloudAiplatformV1beta1AuthConfig", + "description": "Optional. Auth config provided at runtime to override the default value in Extension.manifest.auth_config. The AuthConfig.auth_type should match the value in Extension.manifest.auth_config." + } + }, + "id": "GoogleCloudAiplatformV1beta1ExecuteExtensionRequest", + "description": "Request message for ExtensionExecutionService.ExecuteExtension." + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputs": { + "properties": { + "targetColumn": { + "description": "The name of the column that the Model is to predict values for. This column must be unavailable at forecast.", + "type": "string" + }, + "additionalExperiments": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Additional experiment flags for the time series forcasting training." + }, + "holidayRegions": { + "items": { + "type": "string" + }, + "type": "array", + "description": "The geographical region based on which the holiday effect is applied in modeling by adding holiday categorical array feature that include all holidays matching the date. This option only allowed when data_granularity is day. By default, holiday effect modeling is disabled. To turn it on, specify the holiday region using this option." + }, + "exportEvaluatedDataItemsConfig": { + "description": "Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig" + }, + "unavailableAtForecastColumns": { + "items": { + "type": "string" + }, + "description": "Names of columns that are unavailable when a forecast is requested. This column contains information for the given entity (identified by the time_series_identifier_column) that is unknown before the forecast For example, actual weather on a given day.", + "type": "array" + }, + "timeColumn": { + "type": "string", + "description": "The name of the column that identifies time order in the time series. This column must be available at forecast." + }, + "contextWindow": { + "type": "string", + "description": "The amount of time into the past training and prediction data is used for model training and prediction respectively. Expressed in number of units defined by the `data_granularity` field.", + "format": "int64" + }, + "trainBudgetMilliNodeHours": { + "description": "Required. The train budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The training cost of the model will not exceed this budget. The final cost will be attempted to be close to the budget, though may end up being (even) noticeably smaller - at the backend's discretion. This especially may happen when further model training ceases to provide any improvements. If the budget is set to a value known to be insufficient to train a model for the given dataset, the training won't be attempted and will error. The train budget must be between 1,000 and 72,000 milli node hours, inclusive.", + "format": "int64", + "type": "string" + }, + "forecastHorizon": { + "description": "The amount of time into the future for which forecasted values for the target are returned. Expressed in number of units defined by the `data_granularity` field.", + "format": "int64", + "type": "string" + }, + "hierarchyConfig": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHierarchyConfig", + "description": "Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies." + }, + "timeSeriesAttributeColumns": { + "type": "array", + "description": "Column names that should be used as attribute columns. The value of these columns does not vary as a function of time. For example, store ID or item color.", + "items": { + "type": "string" + } + }, + "availableAtForecastColumns": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Names of columns that are available and provided when a forecast is requested. These columns contain information for the given entity (identified by the time_series_identifier_column column) that is known at forecast. For example, predicted weather for a specific day." + }, + "weightColumn": { + "type": "string", + "description": "Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1. This column must be available at forecast." + }, + "quantiles": { + "type": "array", + "items": { + "format": "double", + "type": "number" + }, + "description": "Quantiles to use for minimize-quantile-loss `optimization_objective`. Up to 5 quantiles are allowed of values between 0 and 1, exclusive. Required if the value of optimization_objective is minimize-quantile-loss. Represents the percent quantiles to use for that objective. Quantiles must be unique." + }, + "windowConfig": { + "description": "Config containing strategy for generating sliding windows.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionWindowConfig" + }, + "validationOptions": { + "description": "Validation options for the data validation component. The available options are: * \"fail-pipeline\" - default, will validate against the validation and fail the pipeline if it fails. * \"ignore-validation\" - ignore the results of the validation and continue", + "type": "string" + }, + "dataGranularity": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsGranularity", + "description": "Expected difference in time granularity between rows in the data." + }, + "transformations": { + "description": "Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using \".\" as the delimiter.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformation" + }, + "type": "array" + }, + "optimizationObjective": { + "type": "string", + "description": "Objective function the model is optimizing towards. The training process creates a model that optimizes the value of the objective function over the validation set. The supported optimization objectives: * \"minimize-rmse\" (default) - Minimize root-mean-squared error (RMSE). * \"minimize-mae\" - Minimize mean-absolute error (MAE). * \"minimize-rmsle\" - Minimize root-mean-squared log error (RMSLE). * \"minimize-rmspe\" - Minimize root-mean-squared percentage error (RMSPE). * \"minimize-wape-mae\" - Minimize the combination of weighted absolute percentage error (WAPE) and mean-absolute-error (MAE). * \"minimize-quantile-loss\" - Minimize the quantile loss at the quantiles defined in `quantiles`. * \"minimize-mape\" - Minimize the mean absolute percentage error." + }, + "timeSeriesIdentifierColumn": { + "type": "string", + "description": "The name of the column that identifies the time series." + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputs", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigThresholdConfig": { + "type": "object", + "description": "The config for Featurestore Monitoring threshold.", + "id": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigThresholdConfig", + "properties": { + "value": { + "description": "Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.", + "format": "double", + "type": "number" + } + } + }, + "GoogleCloudAiplatformV1beta1ListDataItemsResponse": { + "description": "Response message for DatasetService.ListDataItems.", + "properties": { + "nextPageToken": { + "type": "string", + "description": "The standard List next-page token." + }, + "dataItems": { + "description": "A list of DataItems that matches the specified filter in the request.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1DataItem" + } + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ListDataItemsResponse" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValue": { + "properties": { + "distributionValue": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValueDistributionDataValue", + "description": "Distribution." + }, + "doubleValue": { + "description": "Double.", + "type": "number", + "format": "double" + } + }, + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValue", + "type": "object", + "description": "Typed value of the statistics." + }, + "GoogleCloudAiplatformV1beta1CreateMetadataStoreOperationMetadata": { + "properties": { + "genericMetadata": { + "description": "Operation metadata for creating a MetadataStore.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "description": "Details of operations that perform MetadataService.CreateMetadataStore.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1CreateMetadataStoreOperationMetadata" + }, + "GoogleCloudAiplatformV1beta1TensorboardBlobSequence": { + "description": "One point viewable on a blob metric plot, but mostly just a wrapper message to work around repeated fields can't be used directly within `oneof` fields.", + "id": "GoogleCloudAiplatformV1beta1TensorboardBlobSequence", + "properties": { + "values": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardBlob" + }, + "description": "List of blobs contained within the sequence.", + "type": "array" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1StudySpecTransferLearningConfig": { + "properties": { + "disableTransferLearning": { + "description": "Flag to to manually prevent vizier from using transfer learning on a new study. Otherwise, vizier will automatically determine whether or not to use transfer learning.", + "type": "boolean" + }, + "priorStudyNames": { + "readOnly": true, + "type": "array", + "description": "Output only. Names of previously completed studies", + "items": { + "type": "string" + } + } + }, + "id": "GoogleCloudAiplatformV1beta1StudySpecTransferLearningConfig", + "description": "This contains flag for manually disabling transfer learning for a study. The names of prior studies being used for transfer learning (if any) are also listed here.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessResult": { + "type": "object", + "properties": { + "confidence": { + "type": "number", + "format": "float", + "readOnly": true, + "description": "Output only. Confidence for question answering helpfulness score." + }, + "explanation": { + "readOnly": true, + "description": "Output only. Explanation for question answering helpfulness score.", + "type": "string" + }, + "score": { + "format": "float", + "type": "number", + "readOnly": true, + "description": "Output only. Question Answering Helpfulness score." + } + }, + "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessResult", + "description": "Spec for question answering helpfulness result." + }, + "GoogleCloudAiplatformV1beta1MutateDeployedModelRequest": { + "type": "object", + "properties": { + "updateMask": { + "type": "string", + "format": "google-fieldmask", + "description": "Required. The update mask applies to the resource. See google.protobuf.FieldMask." + }, + "deployedModel": { + "$ref": "GoogleCloudAiplatformV1beta1DeployedModel", + "description": "Required. The DeployedModel to be mutated within the Endpoint. Only the following fields can be mutated: * `min_replica_count` in either DedicatedResources or AutomaticResources * `max_replica_count` in either DedicatedResources or AutomaticResources * autoscaling_metric_specs * `disable_container_logging` (v1 only) * `enable_container_logging` (v1beta1 only)" + } + }, + "description": "Request message for EndpointService.MutateDeployedModel.", + "id": "GoogleCloudAiplatformV1beta1MutateDeployedModelRequest" + }, + "GoogleCloudAiplatformV1beta1TunedModel": { + "id": "GoogleCloudAiplatformV1beta1TunedModel", + "properties": { + "endpoint": { + "readOnly": true, + "type": "string", + "description": "Output only. A resource name of an Endpoint. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`." + }, + "model": { + "readOnly": true, + "description": "Output only. The resource name of the TunedModel. Format: `projects/{project}/locations/{location}/models/{model}`.", + "type": "string" + } + }, + "description": "The Model Registry Model and Online Prediction Endpoint assiociated with this TuningJob.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateRequest": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateRequest", + "description": "Request message for VizierService.CheckTrialEarlyStoppingState.", + "properties": {} + }, + "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceResult": { + "type": "object", + "description": "Spec for question answering relevance result.", + "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceResult", + "properties": { + "explanation": { + "type": "string", + "description": "Output only. Explanation for question answering relevance score.", + "readOnly": true + }, + "confidence": { + "description": "Output only. Confidence for question answering relevance score.", + "format": "float", + "type": "number", + "readOnly": true + }, + "score": { + "description": "Output only. Question Answering Relevance score.", + "type": "number", + "readOnly": true, + "format": "float" + } + } + }, + "GoogleCloudAiplatformV1beta1DataItem": { + "properties": { + "payload": { + "type": "any", + "description": "Required. The data that the DataItem represents (for example, an image or a text snippet). The schema of the payload is stored in the parent Dataset's metadata schema's dataItemSchemaUri field." + }, + "updateTime": { + "readOnly": true, + "description": "Output only. Timestamp when this DataItem was last updated.", + "type": "string", + "format": "google-datetime" + }, + "labels": { + "description": "Optional. The labels with user-defined metadata to organize your DataItems. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one DataItem(System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "name": { + "description": "Output only. The resource name of the DataItem.", + "type": "string", + "readOnly": true + }, + "etag": { + "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "createTime": { + "format": "google-datetime", + "readOnly": true, + "type": "string", + "description": "Output only. Timestamp when this DataItem was created." + } + }, + "type": "object", + "description": "A piece of data in a Dataset. Could be an image, a video, a document or plain text.", + "id": "GoogleCloudAiplatformV1beta1DataItem" + }, + "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecRange": { + "description": "A range of values for slice(s). `low` is inclusive, `high` is exclusive.", + "id": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecRange", + "properties": { + "low": { + "format": "float", + "description": "Inclusive low value for the range.", + "type": "number" + }, + "high": { + "type": "number", + "format": "float", + "description": "Exclusive high value for the range." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpec": { + "id": "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpec", + "type": "object", + "properties": { + "multiTrialAlgorithm": { + "enum": [ + "MULTI_TRIAL_ALGORITHM_UNSPECIFIED", + "REINFORCEMENT_LEARNING", + "GRID_SEARCH" + ], + "type": "string", + "description": "The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to `REINFORCEMENT_LEARNING`.", + "enumDescriptions": [ + "Defaults to `REINFORCEMENT_LEARNING`.", + "The Reinforcement Learning Algorithm for Multi-trial Neural Architecture Search (NAS).", + "The Grid Search Algorithm for Multi-trial Neural Architecture Search (NAS)." + ] + }, + "trainTrialSpec": { + "$ref": "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec", + "description": "Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched." + }, + "metric": { + "$ref": "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecMetricSpec", + "description": "Metric specs for the NAS job. Validation for this field is done at `multi_trial_algorithm_spec` field." + }, + "searchTrialSpec": { + "$ref": "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec", + "description": "Required. Spec for search trials." + } + }, + "description": "The spec of multi-trial Neural Architecture Search (NAS)." + }, + "GoogleCloudAiplatformV1beta1ListFeatureOnlineStoresResponse": { + "properties": { + "nextPageToken": { + "description": "A token, which can be sent as ListFeatureOnlineStoresRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + }, + "featureOnlineStores": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStore" + }, + "description": "The FeatureOnlineStores matching the request." + } + }, + "type": "object", + "description": "Response message for FeatureOnlineStoreAdminService.ListFeatureOnlineStores.", + "id": "GoogleCloudAiplatformV1beta1ListFeatureOnlineStoresResponse" + }, + "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateAutomlDatasetConfig": { + "id": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateAutomlDatasetConfig", + "properties": { + "dataset": { + "type": "string", + "description": "Required. Full resource name of automl Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`." + }, + "datasetDisplayName": { + "type": "string", + "description": "Required. Display name of the Dataset in Vertex AI. System will pick a display name if unspecified." + } + }, + "description": "Config for migrating Dataset in automl.googleapis.com to Vertex AI's Dataset.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1GenerateContentResponsePromptFeedback": { + "id": "GoogleCloudAiplatformV1beta1GenerateContentResponsePromptFeedback", + "description": "Content filter results for a prompt sent in the request.", + "type": "object", + "properties": { + "blockReason": { + "description": "Output only. Blocked reason.", + "readOnly": true, + "enum": [ + "BLOCKED_REASON_UNSPECIFIED", + "SAFETY", + "OTHER", + "BLOCKLIST", + "PROHIBITED_CONTENT" + ], + "type": "string", + "enumDescriptions": [ + "Unspecified blocked reason.", + "Candidates blocked due to safety.", + "Candidates blocked due to other reason.", + "Candidates blocked due to the terms which are included from the terminology blocklist.", + "Candidates blocked due to prohibited content." + ] + }, + "safetyRatings": { + "readOnly": true, + "description": "Output only. Safety ratings.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SafetyRating" + }, + "type": "array" + }, + "blockReasonMessage": { + "type": "string", + "description": "Output only. A readable block reason message.", + "readOnly": true + } + } + }, + "GoogleCloudAiplatformV1beta1BatchDeletePipelineJobsResponse": { + "type": "object", + "properties": { + "pipelineJobs": { + "description": "PipelineJobs deleted.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1PipelineJob" + }, + "type": "array" + } + }, + "description": "Response message for PipelineService.BatchDeletePipelineJobs.", + "id": "GoogleCloudAiplatformV1beta1BatchDeletePipelineJobsResponse" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringAnomalyTabularAnomaly": { + "properties": { + "anomaly": { + "type": "any", + "description": "Anomaly body." + }, + "anomalyUri": { + "type": "string", + "description": "Additional anomaly information. e.g. Google Cloud Storage uri." + }, + "summary": { + "type": "string", + "description": "Overview of this anomaly." + }, + "condition": { + "description": "The alert condition associated with this anomaly.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition" + }, + "triggerTime": { + "description": "The time the anomaly was triggered.", + "format": "google-datetime", + "type": "string" + } + }, + "description": "Tabular anomaly details.", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringAnomalyTabularAnomaly", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1CopyModelOperationMetadata": { + "id": "GoogleCloudAiplatformV1beta1CopyModelOperationMetadata", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "The common part of the operation metadata." + } + }, + "description": "Details of ModelService.CopyModel operation.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateMetatdata": { + "properties": { + "trial": { + "description": "The Trial name.", + "type": "string" + }, + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "Operation metadata for suggesting Trials." + }, + "study": { + "description": "The name of the Study that the Trial belongs to.", + "type": "string" + } + }, + "type": "object", + "description": "This message will be placed in the metadata field of a google.longrunning.Operation associated with a CheckTrialEarlyStoppingState request.", + "id": "GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateMetatdata" + }, + "GoogleCloudAiplatformV1beta1PurgeExecutionsResponse": { + "description": "Response message for MetadataService.PurgeExecutions.", + "id": "GoogleCloudAiplatformV1beta1PurgeExecutionsResponse", + "type": "object", + "properties": { + "purgeSample": { + "type": "array", + "description": "A sample of the Execution names that will be deleted. Only populated if `force` is set to false. The maximum number of samples is 100 (it is possible to return fewer).", + "items": { + "type": "string" + } + }, + "purgeCount": { + "format": "int64", + "type": "string", + "description": "The number of Executions that this request deleted (or, if `force` is false, the number of Executions that will be deleted). This can be an estimate." + } + } + }, + "GoogleCloudAiplatformV1beta1PurgeContextsResponse": { + "description": "Response message for MetadataService.PurgeContexts.", + "properties": { + "purgeSample": { + "items": { + "type": "string" + }, + "description": "A sample of the Context names that will be deleted. Only populated if `force` is set to false. The maximum number of samples is 100 (it is possible to return fewer).", + "type": "array" + }, + "purgeCount": { + "description": "The number of Contexts that this request deleted (or, if `force` is false, the number of Contexts that will be deleted). This can be an estimate.", + "type": "string", + "format": "int64" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1PurgeContextsResponse" + }, + "GoogleCloudAiplatformV1beta1SchemaTimeSegment": { + "description": "A time period inside of a DataItem that has a time dimension (e.g. video).", + "id": "GoogleCloudAiplatformV1beta1SchemaTimeSegment", + "type": "object", + "properties": { + "endTimeOffset": { + "format": "google-duration", + "type": "string", + "description": "End of the time segment (exclusive), represented as the duration since the start of the DataItem." + }, + "startTimeOffset": { + "description": "Start of the time segment (inclusive), represented as the duration since the start of the DataItem.", + "type": "string", + "format": "google-duration" + } + } + }, + "GoogleCloudAiplatformV1beta1BatchImportModelEvaluationSlicesResponse": { + "properties": { + "importedModelEvaluationSlices": { + "readOnly": true, + "description": "Output only. List of imported ModelEvaluationSlice.name.", + "items": { + "type": "string" + }, + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1beta1BatchImportModelEvaluationSlicesResponse", + "type": "object", + "description": "Response message for ModelService.BatchImportModelEvaluationSlices" + }, + "GoogleCloudAiplatformV1beta1ToolParameterKVMatchSpec": { + "description": "Spec for tool parameter key value match metric.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchSpec", + "properties": { + "useStrictStringMatch": { + "description": "Optional. Whether to use STRCIT string match on parameter values.", + "type": "boolean" + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetricsConfidenceMetrics": { + "properties": { + "f1Score": { + "description": "The harmonic mean of recall and precision.", + "format": "float", + "type": "number" + }, + "precision": { + "type": "number", + "description": "Precision under the given confidence threshold.", + "format": "float" + }, + "recall": { + "type": "number", + "format": "float", + "description": "Recall under the given confidence threshold." + }, + "confidenceThreshold": { + "description": "The confidence threshold value used to compute the metrics.", + "format": "float", + "type": "number" + } + }, + "description": "Metrics for a single confidence threshold.", + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetricsConfidenceMetrics", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataInputConfig": { + "id": "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataInputConfig", + "description": "The tables Dataset's data source. The Dataset doesn't store the data directly, but only pointer(s) to its data.", + "type": "object", + "properties": { + "gcsSource": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataGcsSource" + }, + "bigquerySource": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataBigQuerySource" + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationCategoricalTransformation": { + "description": "Training pipeline will perform following transformation functions. * The categorical string as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. * Categories that appear less than 5 times in the training dataset are treated as the \"unknown\" category. The \"unknown\" category gets its own special lookup index and resulting embedding.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationCategoricalTransformation", + "properties": { + "columnName": { + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1ImportRagFilesRequest": { + "type": "object", + "description": "Request message for VertexRagDataService.ImportRagFiles.", + "id": "GoogleCloudAiplatformV1beta1ImportRagFilesRequest", + "properties": { + "importRagFilesConfig": { + "$ref": "GoogleCloudAiplatformV1beta1ImportRagFilesConfig", + "description": "Required. The config for the RagFiles to be synced and imported into the RagCorpus. VertexRagDataService.ImportRagFiles." + } + } + }, + "GoogleCloudAiplatformV1beta1UploadRagFileConfig": { + "id": "GoogleCloudAiplatformV1beta1UploadRagFileConfig", + "description": "Config for uploading RagFile.", + "type": "object", + "properties": { + "ragFileChunkingConfig": { + "$ref": "GoogleCloudAiplatformV1beta1RagFileChunkingConfig", + "description": "Specifies the size and overlap of chunks after uploading RagFile." + } + } + }, + "GoogleCloudAiplatformV1beta1ActiveLearningConfig": { + "properties": { + "maxDataItemPercentage": { + "type": "integer", + "description": "Max percent of total DataItems for human labeling.", + "format": "int32" + }, + "trainingConfig": { + "description": "CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.", + "$ref": "GoogleCloudAiplatformV1beta1TrainingConfig" + }, + "sampleConfig": { + "description": "Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.", + "$ref": "GoogleCloudAiplatformV1beta1SampleConfig" + }, + "maxDataItemCount": { + "format": "int64", + "description": "Max number of human labeled DataItems.", + "type": "string" + } + }, + "type": "object", + "description": "Parameters that configure the active learning pipeline. Active learning will label the data incrementally by several iterations. For every iteration, it will select a batch of data based on the sampling strategy.", + "id": "GoogleCloudAiplatformV1beta1ActiveLearningConfig" + }, + "GoogleCloudAiplatformV1beta1ToolNameMatchSpec": { + "id": "GoogleCloudAiplatformV1beta1ToolNameMatchSpec", + "type": "object", + "properties": {}, + "description": "Spec for tool name match metric." + }, + "GoogleCloudAiplatformV1beta1SafetyInput": { + "description": "Input for safety metric.", + "properties": { + "instance": { + "description": "Required. Safety instance.", + "$ref": "GoogleCloudAiplatformV1beta1SafetyInstance" + }, + "metricSpec": { + "description": "Required. Spec for safety metric.", + "$ref": "GoogleCloudAiplatformV1beta1SafetySpec" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SafetyInput" + }, + "GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetailCustomJobDetail": { + "description": "The detailed info for a custom job executor.", + "type": "object", + "properties": { + "job": { + "readOnly": true, + "type": "string", + "description": "Output only. The name of the CustomJob." + }, + "failedJobs": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Output only. The names of the previously failed CustomJob. The list includes the all attempts in chronological order.", + "readOnly": true + } + }, + "id": "GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetailCustomJobDetail" + }, + "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityInput": { + "id": "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityInput", + "type": "object", + "description": "Input for pairwise summarization quality metric.", + "properties": { + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualitySpec", + "description": "Required. Spec for pairwise summarization quality score metric." + }, + "instance": { + "$ref": "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityInstance", + "description": "Required. Pairwise summarization quality instance." + } + } + }, + "GoogleCloudAiplatformV1beta1AuthConfigHttpBasicAuthConfig": { + "description": "Config for HTTP Basic Authentication.", + "id": "GoogleCloudAiplatformV1beta1AuthConfigHttpBasicAuthConfig", + "type": "object", + "properties": { + "credentialSecret": { + "description": "Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringConfig": { + "type": "object", + "description": "The model monitoring configuration used for Batch Prediction Job.", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringConfig", + "properties": { + "statsAnomaliesBaseDirectory": { + "description": "A Google Cloud Storage location for batch prediction model monitoring to dump statistics and anomalies. If not provided, a folder will be created in customer project to hold statistics and anomalies.", + "$ref": "GoogleCloudAiplatformV1beta1GcsDestination" + }, + "alertConfig": { + "description": "Model monitoring alert config.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfig" + }, + "analysisInstanceSchemaUri": { + "type": "string", + "description": "YAML schema file uri in Cloud Storage describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string." + }, + "objectiveConfigs": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfig" + }, + "description": "Model monitoring objective config." + } + } + }, + "GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponseSelectEntity": { + "description": "Response message if the request uses the SelectEntity option.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponseSelectEntity", + "properties": { + "offlineStorageDeletedEntityRowCount": { + "format": "int64", + "description": "The count of deleted entity rows in the offline storage. Each row corresponds to the combination of an entity ID and a timestamp. One entity ID can have multiple rows in the offline storage.", + "type": "string" + }, + "onlineStorageDeletedEntityCount": { + "format": "int64", + "description": "The count of deleted entities in the online storage. Each entity ID corresponds to one entity.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1ExportModelRequest": { + "properties": { + "outputConfig": { + "$ref": "GoogleCloudAiplatformV1beta1ExportModelRequestOutputConfig", + "description": "Required. The desired output location and configuration." + } + }, + "description": "Request message for ModelService.ExportModel.", + "id": "GoogleCloudAiplatformV1beta1ExportModelRequest", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ExactMatchInput": { + "id": "GoogleCloudAiplatformV1beta1ExactMatchInput", + "properties": { + "instances": { + "description": "Required. Repeated exact match instances.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ExactMatchInstance" + }, + "type": "array" + }, + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1beta1ExactMatchSpec", + "description": "Required. Spec for exact match metric." + } + }, + "description": "Input for exact match metric.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1RagQuery": { + "id": "GoogleCloudAiplatformV1beta1RagQuery", + "type": "object", + "properties": { + "similarityTopK": { + "type": "integer", + "description": "Optional. The number of contexts to retrieve.", + "format": "int32" + }, + "text": { + "type": "string", + "description": "Optional. The query in text format to get relevant contexts." + } + }, + "description": "A query to retrieve relevant contexts." + }, + "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringObjectiveConfig": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringObjectiveConfig", + "description": "ModelDeploymentMonitoringObjectiveConfig contains the pair of deployed_model_id to ModelMonitoringObjectiveConfig.", + "properties": { + "deployedModelId": { + "type": "string", + "description": "The DeployedModel ID of the objective config." + }, + "objectiveConfig": { + "description": "The objective config of for the modelmonitoring job of this deployed model.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfig" + } + } + }, + "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessInput": { + "description": "Input for question answering helpfulness metric.", + "properties": { + "metricSpec": { + "description": "Required. Spec for question answering helpfulness score metric.", + "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessSpec" + }, + "instance": { + "description": "Required. Question answering helpfulness instance.", + "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessInstance" + } + }, + "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessInput", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1Part": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1Part", + "properties": { + "videoMetadata": { + "description": "Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.", + "$ref": "GoogleCloudAiplatformV1beta1VideoMetadata" + }, + "fileData": { + "$ref": "GoogleCloudAiplatformV1beta1FileData", + "description": "Optional. URI based data." + }, + "inlineData": { + "$ref": "GoogleCloudAiplatformV1beta1Blob", + "description": "Optional. Inlined bytes data." + }, + "functionResponse": { + "$ref": "GoogleCloudAiplatformV1beta1FunctionResponse", + "description": "Optional. The result output of a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function call. It is used as context to the model." + }, + "functionCall": { + "$ref": "GoogleCloudAiplatformV1beta1FunctionCall", + "description": "Optional. A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] with the parameters and their values." + }, + "text": { + "description": "Optional. Text part (can be code).", + "type": "string" + } + }, + "description": "A datatype containing media that is part of a multi-part `Content` message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. A `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes." + }, + "GoogleCloudAiplatformV1beta1UserActionReference": { + "properties": { + "operation": { + "type": "string", + "description": "For API calls that return a long running operation. Resource name of the long running operation. Format: `projects/{project}/locations/{location}/operations/{operation}`" + }, + "dataLabelingJob": { + "description": "For API calls that start a LabelingJob. Resource name of the LabelingJob. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}`", + "type": "string" + }, + "method": { + "description": "The method name of the API RPC call. For example, \"/google.cloud.aiplatform.{apiVersion}.DatasetService.CreateDataset\"", + "type": "string" + } + }, + "description": "References an API call. It contains more information about long running operation and Jobs that are triggered by the API call.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1UserActionReference" + }, + "GoogleCloudAiplatformV1beta1ListModelDeploymentMonitoringJobsResponse": { + "type": "object", + "description": "Response message for JobService.ListModelDeploymentMonitoringJobs.", + "id": "GoogleCloudAiplatformV1beta1ListModelDeploymentMonitoringJobsResponse", + "properties": { + "nextPageToken": { + "type": "string", + "description": "The standard List next-page token." + }, + "modelDeploymentMonitoringJobs": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob" + }, + "type": "array", + "description": "A list of ModelDeploymentMonitoringJobs that matches the specified filter in the request." + } + } + }, + "GoogleCloudAiplatformV1beta1UpdateExplanationDatasetRequest": { + "description": "Request message for ModelService.UpdateExplanationDataset.", + "properties": { + "examples": { + "$ref": "GoogleCloudAiplatformV1beta1Examples", + "description": "The example config containing the location of the dataset." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1UpdateExplanationDatasetRequest" + }, + "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessInput": { + "description": "Input for question answering correctness metric.", + "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessInput", + "properties": { + "metricSpec": { + "description": "Required. Spec for question answering correctness score metric.", + "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessSpec" + }, + "instance": { + "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessInstance", + "description": "Required. Question answering correctness instance." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseFeatureDescriptor": { + "properties": { + "id": { + "type": "string", + "description": "Feature ID." + } + }, + "description": "Metadata for requested Features.", + "id": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseFeatureDescriptor", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTextTransformation": { + "properties": { + "columnName": { + "type": "string" + } + }, + "description": "Training pipeline will perform following transformation functions. * The text as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index.", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTextTransformation", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ListIndexEndpointsResponse": { + "id": "GoogleCloudAiplatformV1beta1ListIndexEndpointsResponse", + "description": "Response message for IndexEndpointService.ListIndexEndpoints.", + "properties": { + "nextPageToken": { + "description": "A token to retrieve next page of results. Pass to ListIndexEndpointsRequest.page_token to obtain that page.", + "type": "string" + }, + "indexEndpoints": { + "type": "array", + "description": "List of IndexEndpoints in the requested page.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1IndexEndpoint" + } + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTimestampTransformation": { + "properties": { + "invalidValuesAllowed": { + "description": "If invalid values is allowed, the training pipeline will create a boolean feature that indicated whether the value is valid. Otherwise, the training pipeline will discard the input row from trainining data.", + "type": "boolean" + }, + "columnName": { + "type": "string" + }, + "timeFormat": { + "type": "string", + "description": "The format in which that time field is expressed. The time_format must either be one of: * `unix-seconds` * `unix-milliseconds` * `unix-microseconds` * `unix-nanoseconds` (for respectively number of seconds, milliseconds, microseconds and nanoseconds since start of the Unix epoch); or be written in `strftime` syntax. If time_format is not set, then the default format is RFC 3339 `date-time` format, where `time-offset` = `\"Z\"` (e.g. 1985-04-12T23:20:50.52Z)" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTimestampTransformation", + "description": "Training pipeline will perform following transformation functions. * Apply the transformation functions for Numerical columns. * Determine the year, month, day,and weekday. Treat each value from the * timestamp as a Categorical column. * Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed." + }, + "GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigInputArtifact": { + "id": "GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigInputArtifact", + "type": "object", + "description": "The type of an input artifact.", + "properties": { + "artifactId": { + "type": "string", + "description": "Artifact resource id from MLMD. Which is the last portion of an artifact resource name: `projects/{project}/locations/{location}/metadataStores/default/artifacts/{artifact_id}`. The artifact must stay within the same project, location and default metadatastore as the pipeline." + } + } + }, + "GoogleCloudAiplatformV1beta1MergeVersionAliasesRequest": { + "type": "object", + "description": "Request message for ModelService.MergeVersionAliases.", + "id": "GoogleCloudAiplatformV1beta1MergeVersionAliasesRequest", + "properties": { + "versionAliases": { + "description": "Required. The set of version aliases to merge. The alias should be at most 128 characters, and match `a-z{0,126}[a-z-0-9]`. Add the `-` prefix to an alias means removing that alias from the version. `-` is NOT counted in the 128 characters. Example: `-golden` means removing the `golden` alias from the version. There is NO ordering in aliases, which means 1) The aliases returned from GetModel API might not have the exactly same order from this MergeVersionAliases API. 2) Adding and deleting the same alias in the request is not recommended, and the 2 operations will be cancelled out.", + "type": "array", + "items": { + "type": "string" + } + } + } + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringInputVertexEndpointLogs": { + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringInputVertexEndpointLogs", + "type": "object", + "properties": { + "endpoints": { + "description": "List of endpoint resource names. The endpoints must enable the logging with the [Endpoint].[request_response_logging_config], and must contain the deployed model corresponding to the model version specified in [ModelMonitor].[model_monitoring_target].", + "items": { + "type": "string" + }, + "type": "array" + } + }, + "description": "Data from Vertex AI Endpoint request response logging." + }, + "GoogleCloudAiplatformV1beta1NasTrial": { + "properties": { + "id": { + "readOnly": true, + "type": "string", + "description": "Output only. The identifier of the NasTrial assigned by the service." + }, + "state": { + "description": "Output only. The detailed state of the NasTrial.", + "readOnly": true, + "enum": [ + "STATE_UNSPECIFIED", + "REQUESTED", + "ACTIVE", + "STOPPING", + "SUCCEEDED", + "INFEASIBLE" + ], + "type": "string", + "enumDescriptions": [ + "The NasTrial state is unspecified.", + "Indicates that a specific NasTrial has been requested, but it has not yet been suggested by the service.", + "Indicates that the NasTrial has been suggested.", + "Indicates that the NasTrial should stop according to the service.", + "Indicates that the NasTrial is completed successfully.", + "Indicates that the NasTrial should not be attempted again. The service will set a NasTrial to INFEASIBLE when it's done but missing the final_measurement." + ] + }, + "endTime": { + "description": "Output only. Time when the NasTrial's status changed to `SUCCEEDED` or `INFEASIBLE`.", + "readOnly": true, + "format": "google-datetime", + "type": "string" + }, + "finalMeasurement": { + "readOnly": true, + "description": "Output only. The final measurement containing the objective value.", + "$ref": "GoogleCloudAiplatformV1beta1Measurement" + }, + "startTime": { + "type": "string", + "format": "google-datetime", + "description": "Output only. Time when the NasTrial was started.", + "readOnly": true + } + }, + "id": "GoogleCloudAiplatformV1beta1NasTrial", + "description": "Represents a uCAIP NasJob trial.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1QuestionAnsweringQualityInstance": { + "type": "object", + "properties": { + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + }, + "context": { + "type": "string", + "description": "Required. Text to answer the question." + }, + "reference": { + "description": "Optional. Ground truth used to compare against the prediction.", + "type": "string" + }, + "instruction": { + "description": "Required. Question Answering prompt for LLM.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringQualityInstance", + "description": "Spec for question answering quality instance." + }, + "GoogleCloudAiplatformV1beta1FulfillmentInstance": { + "type": "object", + "description": "Spec for fulfillment instance.", + "properties": { + "instruction": { + "description": "Required. Inference instruction prompt to compare prediction with.", + "type": "string" + }, + "prediction": { + "description": "Required. Output of the evaluated model.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1FulfillmentInstance" + }, + "GoogleCloudAiplatformV1beta1BatchImportModelEvaluationSlicesRequest": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1BatchImportModelEvaluationSlicesRequest", + "properties": { + "modelEvaluationSlices": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationSlice" + }, + "description": "Required. Model evaluation slice resource to be imported." + } + }, + "description": "Request message for ModelService.BatchImportModelEvaluationSlices" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionInputs": { + "properties": { + "tunableParameter": { + "description": "Trainer type for Vision TrainRequest.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter" + }, + "disableEarlyStopping": { + "description": "Use the entire training budget. This disables the early stopping feature. When false the early stopping feature is enabled, which means that AutoML Image Object Detection might stop training before the entire training budget has been used.", + "type": "boolean" + }, + "uptrainBaseModelId": { + "type": "string", + "description": "The ID of `base` model for upTraining. If it is specified, the new model will be upTrained based on the `base` model for upTraining. Otherwise, the new model will be trained from scratch. The `base` model for upTraining must be in the same Project and Location as the new Model to train, and have the same modelType." + }, + "budgetMilliNodeHours": { + "description": "The training budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The actual metadata.costMilliNodeHours will be equal or less than this value. If further model training ceases to provide any improvements, it will stop without using the full budget and the metadata.successfulStopReason will be `model-converged`. Note, node_hour = actual_hour * number_of_nodes_involved. For modelType `cloud`(default), the budget must be between 20,000 and 900,000 milli node hours, inclusive. The default value is 216,000 which represents one day in wall time, considering 9 nodes are used. For model types `mobile-tf-low-latency-1`, `mobile-tf-versatile-1`, `mobile-tf-high-accuracy-1` the training budget must be between 1,000 and 100,000 milli node hours, inclusive. The default value is 24,000 which represents one day in wall time on a single node that is used.", + "type": "string", + "format": "int64" + }, + "modelType": { + "enumDescriptions": [ + "Should not be set.", + "A model best tailored to be used within Google Cloud, and which cannot be exported. Expected to have a higher latency, but should also have a higher prediction quality than other cloud models.", + "A model best tailored to be used within Google Cloud, and which cannot be exported. Expected to have a low latency, but may have lower prediction quality than other cloud models.", + "A model best tailored to be used within Google Cloud, and which cannot be exported. Compared to the CLOUD_HIGH_ACCURACY_1 and CLOUD_LOW_LATENCY_1 models above, it is expected to have higher prediction quality and lower latency.", + "A model that, in addition to being available within Google Cloud can also be exported (see ModelService.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have low latency, but may have lower prediction quality than other mobile models.", + "A model that, in addition to being available within Google Cloud can also be exported (see ModelService.ExportModel) and used on a mobile or edge device with TensorFlow afterwards.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other mobile models.", + "A model best tailored to be used within Google Cloud, and which cannot be exported. Expected to best support predictions in streaming with lower latency and lower prediction quality than other cloud models.", + "SpineNet for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally.", + "YOLO for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally." + ], + "type": "string", + "enum": [ + "MODEL_TYPE_UNSPECIFIED", + "CLOUD_HIGH_ACCURACY_1", + "CLOUD_LOW_LATENCY_1", + "CLOUD_1", + "MOBILE_TF_LOW_LATENCY_1", + "MOBILE_TF_VERSATILE_1", + "MOBILE_TF_HIGH_ACCURACY_1", + "CLOUD_STREAMING_1", + "SPINENET", + "YOLO" + ] + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionInputs" + }, + "GoogleCloudAiplatformV1beta1BlurBaselineConfig": { + "type": "object", + "properties": { + "maxBlurSigma": { + "format": "float", + "type": "number", + "description": "The standard deviation of the blur kernel for the blurred baseline. The same blurring parameter is used for both the height and the width dimension. If not set, the method defaults to the zero (i.e. black for images) baseline." + } + }, + "id": "GoogleCloudAiplatformV1beta1BlurBaselineConfig", + "description": "Config for blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383" + }, + "GoogleIamV1TestIamPermissionsRequest": { + "type": "object", + "description": "Request message for `TestIamPermissions` method.", + "properties": { + "permissions": { + "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", + "items": { + "type": "string" + }, + "type": "array" + } + }, + "id": "GoogleIamV1TestIamPermissionsRequest" + }, + "GoogleCloudAiplatformV1beta1IndexDatapointRestriction": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1IndexDatapointRestriction", + "description": "Restriction of a datapoint which describe its attributes(tokens) from each of several attribute categories(namespaces).", + "properties": { + "denyList": { + "items": { + "type": "string" + }, + "type": "array", + "description": "The attributes to deny in this namespace. e.g.: 'blue'" + }, + "namespace": { + "description": "The namespace of this restriction. e.g.: color.", + "type": "string" + }, + "allowList": { + "items": { + "type": "string" + }, + "type": "array", + "description": "The attributes to allow in this namespace. e.g.: 'red'" + } + } + }, + "GoogleCloudAiplatformV1beta1SummarizationQualityInstance": { + "type": "object", + "properties": { + "context": { + "description": "Required. Text to be summarized.", + "type": "string" + }, + "reference": { + "type": "string", + "description": "Optional. Ground truth used to compare against the prediction." + }, + "prediction": { + "description": "Required. Output of the evaluated model.", + "type": "string" + }, + "instruction": { + "type": "string", + "description": "Required. Summarization prompt for LLM." + } + }, + "id": "GoogleCloudAiplatformV1beta1SummarizationQualityInstance", + "description": "Spec for summarization quality instance." + }, + "GoogleCloudAiplatformV1beta1NetworkSpec": { + "description": "Network spec.", + "id": "GoogleCloudAiplatformV1beta1NetworkSpec", + "type": "object", + "properties": { + "enableInternetAccess": { + "type": "boolean", + "description": "Whether to enable public internet access. Default false." + }, + "network": { + "description": "The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)", + "type": "string" + }, + "subnetwork": { + "description": "The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataBigQuerySource": { + "properties": { + "uri": { + "type": "string", + "description": "The URI of a BigQuery table." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataBigQuerySource" + }, + "GoogleCloudAiplatformV1beta1NasJobOutput": { + "id": "GoogleCloudAiplatformV1beta1NasJobOutput", + "description": "Represents a uCAIP NasJob output.", + "properties": { + "multiTrialJobOutput": { + "readOnly": true, + "description": "Output only. The output of this multi-trial Neural Architecture Search (NAS) job.", + "$ref": "GoogleCloudAiplatformV1beta1NasJobOutputMultiTrialJobOutput" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1PscAutomatedEndpoints": { + "id": "GoogleCloudAiplatformV1beta1PscAutomatedEndpoints", + "properties": { + "projectId": { + "type": "string", + "description": "Corresponding project_id in pscAutomationConfigs" + }, + "matchAddress": { + "type": "string", + "description": "Ip Address created by the automated forwarding rule." + }, + "network": { + "type": "string", + "description": "Corresponding network in pscAutomationConfigs." + } + }, + "description": "PscAutomatedEndpoints defines the output of the forwarding rule automatically created by each PscAutomationConfig.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1CreateModelMonitoringJobRequest": { + "properties": { + "parent": { + "description": "Required. The parent of the ModelMonitoringJob. Format: `projects/{project}/locations/{location}/modelMoniitors/{model_monitor}`", + "type": "string" + }, + "modelMonitoringJob": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringJob", + "description": "Required. The ModelMonitoringJob to create" + }, + "modelMonitoringJobId": { + "description": "Optional. The ID to use for the Model Monitoring Job, which will become the final component of the model monitoring job resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1CreateModelMonitoringJobRequest", + "description": "Request message for ModelMonitoringService.CreateModelMonitoringJob." + }, + "GoogleCloudAiplatformV1beta1PurgeExecutionsRequest": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1PurgeExecutionsRequest", + "properties": { + "filter": { + "type": "string", + "description": "Required. A required filter matching the Executions to be purged. E.g., `update_time \u003c= 2020-11-19T11:30:00-04:00`." + }, + "force": { + "type": "boolean", + "description": "Optional. Flag to indicate to actually perform the purge. If `force` is set to false, the method will return a sample of Execution names that would be deleted." + } + }, + "description": "Request message for MetadataService.PurgeExecutions." + }, + "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotation": { + "properties": { + "polygonAnnotation": { + "description": "Polygon annotation.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationPolygonAnnotation" + }, + "polylineAnnotation": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationPolylineAnnotation", + "description": "Polyline annotation." + }, + "maskAnnotation": { + "description": "Mask based segmentation annotation. Only one mask annotation can exist for one image.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationMaskAnnotation" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotation", + "type": "object", + "description": "Annotation details specific to image segmentation." + }, + "GoogleCloudAiplatformV1beta1TimeSeriesDataPoint": { + "type": "object", + "description": "A TensorboardTimeSeries data point.", + "id": "GoogleCloudAiplatformV1beta1TimeSeriesDataPoint", + "properties": { + "step": { + "format": "int64", + "type": "string", + "description": "Step index of this data point within the run." + }, + "blobs": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardBlobSequence", + "description": "A blob sequence value." + }, + "wallTime": { + "format": "google-datetime", + "description": "Wall clock timestamp when this data point is generated by the end user.", + "type": "string" + }, + "tensor": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardTensor", + "description": "A tensor value." + }, + "scalar": { + "$ref": "GoogleCloudAiplatformV1beta1Scalar", + "description": "A scalar value." + } + } + }, + "GoogleCloudAiplatformV1beta1Event": { + "type": "object", + "properties": { + "artifact": { + "type": "string", + "description": "Required. The relative resource name of the Artifact in the Event." + }, + "type": { + "enumDescriptions": [ + "Unspecified whether input or output of the Execution.", + "An input of the Execution.", + "An output of the Execution." + ], + "enum": [ + "TYPE_UNSPECIFIED", + "INPUT", + "OUTPUT" + ], + "description": "Required. The type of the Event.", + "type": "string" + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "description": "The labels with user-defined metadata to annotate Events. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Event (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", + "type": "object" + }, + "execution": { + "readOnly": true, + "type": "string", + "description": "Output only. The relative resource name of the Execution in the Event." + }, + "eventTime": { + "format": "google-datetime", + "type": "string", + "description": "Output only. Time the Event occurred.", + "readOnly": true + } + }, + "id": "GoogleCloudAiplatformV1beta1Event", + "description": "An edge describing the relationship between an Artifact and an Execution in a lineage graph." + }, + "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchMetricValue": { + "type": "object", + "description": "Tool parameter key match metric value for an instance.", + "properties": { + "score": { + "readOnly": true, + "description": "Output only. Tool parameter key match score.", + "type": "number", + "format": "float" + } + }, + "id": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchMetricValue" + }, + "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessSpec": { + "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessSpec", + "properties": { + "version": { + "type": "integer", + "description": "Optional. Which version to use for evaluation.", + "format": "int32" + }, + "useReference": { + "description": "Optional. Whether to use instance.reference to compute question answering helpfulness.", + "type": "boolean" + } + }, + "description": "Spec for question answering helpfulness metric.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaVertex": { + "description": "A vertex represents a 2D point in the image. NOTE: the normalized vertex coordinates are relative to the original image and range from 0 to 1.", + "type": "object", + "properties": { + "x": { + "format": "double", + "description": "X coordinate.", + "type": "number" + }, + "y": { + "format": "double", + "description": "Y coordinate.", + "type": "number" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaVertex" + }, + "GoogleCloudAiplatformV1beta1PredictRequest": { + "id": "GoogleCloudAiplatformV1beta1PredictRequest", + "description": "Request message for PredictionService.Predict.", + "properties": { + "parameters": { + "description": "The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri.", + "type": "any" + }, + "instances": { + "items": { + "type": "any" + }, + "type": "array", + "description": "Required. The instances that are the input to the prediction call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the prediction call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchSpec": { + "id": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchSpec", + "type": "object", + "properties": {}, + "description": "Spec for tool parameter key match metric." + }, + "GoogleCloudAiplatformV1beta1ListTrialsResponse": { + "properties": { + "nextPageToken": { + "type": "string", + "description": "Pass this token as the `page_token` field of the request for a subsequent call. If this field is omitted, there are no subsequent pages." + }, + "trials": { + "type": "array", + "description": "The Trials associated with the Study.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Trial" + } + } + }, + "description": "Response message for VizierService.ListTrials.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ListTrialsResponse" + }, + "GoogleCloudAiplatformV1beta1GenerateAccessTokenResponse": { + "description": "Response message for NotebookInternalService.GenerateToken.", + "type": "object", + "properties": { + "accessToken": { + "type": "string", + "description": "Short-lived access token string which may be used to access Google APIs." + }, + "expiresIn": { + "type": "integer", + "format": "int32", + "description": "The time in seconds when the access token expires. Typically that's 3600." + }, + "tokenType": { + "type": "string", + "description": "Type of the returned access token (e.g. \"Bearer\"). It specifies how the token must be used. Bearer tokens may be used by any entity without proof of identity." + }, + "scope": { + "type": "string", + "description": "Space-separated list of scopes contained in the returned token. https://cloud.google.com/docs/authentication/token-types#access-contents" + } + }, + "id": "GoogleCloudAiplatformV1beta1GenerateAccessTokenResponse" + }, + "GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequest": { + "id": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequest", + "properties": { + "selectTimeRangeAndFeature": { + "$ref": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequestSelectTimeRangeAndFeature", + "description": "Select feature values to be deleted by specifying time range and features." + }, + "selectEntity": { + "description": "Select feature values to be deleted by specifying entities.", + "$ref": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequestSelectEntity" + } + }, + "description": "Request message for FeaturestoreService.DeleteFeatureValues.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ImportFeatureValuesRequestFeatureSpec": { + "description": "Defines the Feature value(s) to import.", + "properties": { + "id": { + "type": "string", + "description": "Required. ID of the Feature to import values of. This Feature must exist in the target EntityType, or the request will fail." + }, + "sourceField": { + "description": "Source column to get the Feature values from. If not set, uses the column with the same name as the Feature ID.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ImportFeatureValuesRequestFeatureSpec" + }, + "GoogleCloudAiplatformV1beta1ModelEvaluationBiasConfig": { + "properties": { + "biasSlices": { + "description": "Specification for how the data should be sliced for bias. It contains a list of slices, with limitation of two slices. The first slice of data will be the slice_a. The second slice in the list (slice_b) will be compared against the first slice. If only a single slice is provided, then slice_a will be compared against \"not slice_a\". Below are examples with feature \"education\" with value \"low\", \"medium\", \"high\" in the dataset: Example 1: bias_slices = [{'education': 'low'}] A single slice provided. In this case, slice_a is the collection of data with 'education' equals 'low', and slice_b is the collection of data with 'education' equals 'medium' or 'high'. Example 2: bias_slices = [{'education': 'low'}, {'education': 'high'}] Two slices provided. In this case, slice_a is the collection of data with 'education' equals 'low', and slice_b is the collection of data with 'education' equals 'high'.", + "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpec" + }, + "labels": { + "description": "Positive labels selection on the target field.", + "items": { + "type": "string" + }, + "type": "array" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ModelEvaluationBiasConfig", + "description": "Configuration for bias detection." + }, + "GoogleCloudAiplatformV1beta1ResumeModelDeploymentMonitoringJobRequest": { + "id": "GoogleCloudAiplatformV1beta1ResumeModelDeploymentMonitoringJobRequest", + "type": "object", + "properties": {}, + "description": "Request message for JobService.ResumeModelDeploymentMonitoringJob." + }, + "GoogleCloudAiplatformV1beta1FeatureNoiseSigmaNoiseSigmaForFeature": { + "description": "Noise sigma for a single feature.", + "id": "GoogleCloudAiplatformV1beta1FeatureNoiseSigmaNoiseSigmaForFeature", + "properties": { + "sigma": { + "format": "float", + "type": "number", + "description": "This represents the standard deviation of the Gaussian kernel that will be used to add noise to the feature prior to computing gradients. Similar to noise_sigma but represents the noise added to the current feature. Defaults to 0.1." + }, + "name": { + "description": "The name of the input feature for which noise sigma is provided. The features are defined in explanation metadata inputs.", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ReadTensorboardTimeSeriesDataResponse": { + "properties": { + "timeSeriesData": { + "$ref": "GoogleCloudAiplatformV1beta1TimeSeriesData", + "description": "The returned time series data." + } + }, + "id": "GoogleCloudAiplatformV1beta1ReadTensorboardTimeSeriesDataResponse", + "type": "object", + "description": "Response message for TensorboardService.ReadTensorboardTimeSeriesData." + }, + "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesOperationMetadata": { + "id": "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesOperationMetadata", + "type": "object", + "properties": { + "genericMetadata": { + "description": "Operation metadata for Featurestore batch read Features values.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "description": "Details of operations that batch reads Feature values." + }, + "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataBigQuerySource": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataBigQuerySource", + "properties": { + "uri": { + "description": "The URI of a BigQuery table. e.g. bq://projectId.bqDatasetId.bqTableId", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1ModelContainerSpec": { + "id": "GoogleCloudAiplatformV1beta1ModelContainerSpec", + "type": "object", + "description": "Specification of a container for serving predictions. Some fields in this message correspond to fields in the [Kubernetes Container v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).", + "properties": { + "startupProbe": { + "description": "Immutable. Specification for Kubernetes startup probe.", + "$ref": "GoogleCloudAiplatformV1beta1Probe" + }, + "ports": { + "type": "array", + "description": "Immutable. List of ports to expose from the container. Vertex AI sends any prediction requests that it receives to the first port on this list. Vertex AI also sends [liveness and health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#liveness) to this port. If you do not specify this field, it defaults to following value: ```json [ { \"containerPort\": 8080 } ] ``` Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Port" + } + }, + "sharedMemorySizeMb": { + "format": "int64", + "description": "Immutable. The amount of the VM memory to reserve as the shared memory for the model in megabytes.", + "type": "string" + }, + "predictRoute": { + "description": "Immutable. HTTP path on the container to send prediction requests to. Vertex AI forwards requests sent using projects.locations.endpoints.predict to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response. For example, if you set this field to `/foo`, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)", + "type": "string" + }, + "healthProbe": { + "$ref": "GoogleCloudAiplatformV1beta1Probe", + "description": "Immutable. Specification for Kubernetes readiness probe." + }, + "imageUri": { + "description": "Required. Immutable. URI of the Docker image to be used as the custom container for serving predictions. This URI must identify an image in Artifact Registry or Container Registry. Learn more about the [container publishing requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#publishing), including permissions requirements for the Vertex AI Service Agent. The container image is ingested upon ModelService.UploadModel, stored internally, and this original path is afterwards not used. To learn about the requirements for the Docker image itself, see [Custom container requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#). You can use the URI to one of Vertex AI's [pre-built container images for prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre-built-containers) in this field.", + "type": "string" + }, + "grpcPorts": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Port" + }, + "description": "Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API." + }, + "healthRoute": { + "description": "Immutable. HTTP path on the container to send health checks to. Vertex AI intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#health). For example, if you set this field to `/bar`, then Vertex AI intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/ DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)", + "type": "string" + }, + "command": { + "description": "Immutable. Specifies the command that runs when the container starts. This overrides the container's [ENTRYPOINT](https://docs.docker.com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s \"exec\" form, not its \"shell\" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the args field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).", + "type": "array", + "items": { + "type": "string" + } + }, + "env": { + "description": "Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: ```json [ { \"name\": \"VAR_1\", \"value\": \"foo\" }, { \"name\": \"VAR_2\", \"value\": \"$(VAR_1) bar\" } ] ``` If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the `env` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1EnvVar" + } + }, + "args": { + "items": { + "type": "string" + }, + "description": "Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s \"default parameters\" form. If you don't specify this field but do specify the command field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).", + "type": "array" + }, + "deploymentTimeout": { + "type": "string", + "description": "Immutable. Deployment timeout. Limit for deployment timeout is 2 hours.", + "format": "google-duration" + } + } + }, + "GoogleCloudAiplatformV1beta1MachineSpec": { + "properties": { + "machineType": { + "description": "Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.", + "type": "string" + }, + "acceleratorCount": { + "type": "integer", + "description": "The number of accelerators to attach to the machine.", + "format": "int32" + }, + "tpuTopology": { + "description": "Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: \"2x2x1\").", + "type": "string" + }, + "acceleratorType": { + "type": "string", + "enum": [ + "ACCELERATOR_TYPE_UNSPECIFIED", + "NVIDIA_TESLA_K80", + "NVIDIA_TESLA_P100", + "NVIDIA_TESLA_V100", + "NVIDIA_TESLA_P4", + "NVIDIA_TESLA_T4", + "NVIDIA_TESLA_A100", + "NVIDIA_A100_80GB", + "NVIDIA_L4", + "NVIDIA_H100_80GB", + "TPU_V2", + "TPU_V3", + "TPU_V4_POD", + "TPU_V5_LITEPOD" + ], + "enumDescriptions": [ + "Unspecified accelerator type, which means no accelerator.", + "Nvidia Tesla K80 GPU.", + "Nvidia Tesla P100 GPU.", + "Nvidia Tesla V100 GPU.", + "Nvidia Tesla P4 GPU.", + "Nvidia Tesla T4 GPU.", + "Nvidia Tesla A100 GPU.", + "Nvidia A100 80GB GPU.", + "Nvidia L4 GPU.", + "Nvidia H100 80Gb GPU.", + "TPU v2.", + "TPU v3.", + "TPU v4.", + "TPU v5." + ], + "enumDeprecated": [ + false, + true, + false, + false, + false, + false, + false, + false, + false, + false, + false, + false, + false, + false + ], + "description": "Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count." + } + }, + "description": "Specification of a single machine.", + "id": "GoogleCloudAiplatformV1beta1MachineSpec", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1DestinationFeatureSetting": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1DestinationFeatureSetting", + "properties": { + "featureId": { + "type": "string", + "description": "Required. The ID of the Feature to apply the setting to." + }, + "destinationField": { + "description": "Specify the field name in the export destination. If not specified, Feature ID is used.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1PublisherModelCallToAction": { + "id": "GoogleCloudAiplatformV1beta1PublisherModelCallToAction", + "type": "object", + "properties": { + "openFineTuningPipelines": { + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionOpenFineTuningPipelines", + "description": "Optional. Open fine-tuning pipelines of the PublisherModel." + }, + "openNotebook": { + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences", + "description": "Optional. Open notebook of the PublisherModel." + }, + "openGenerationAiStudio": { + "description": "Optional. Open in Generation AI Studio.", + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences" + }, + "openFineTuningPipeline": { + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences", + "description": "Optional. Open fine-tuning pipeline of the PublisherModel." + }, + "viewRestApi": { + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionViewRestApi", + "description": "Optional. To view Rest API docs." + }, + "deploy": { + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeploy", + "description": "Optional. Deploy the PublisherModel to Vertex Endpoint." + }, + "openNotebooks": { + "description": "Optional. Open notebooks of the PublisherModel.", + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionOpenNotebooks" + }, + "requestAccess": { + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences", + "description": "Optional. Request for access." + }, + "openEvaluationPipeline": { + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences", + "description": "Optional. Open evaluation pipeline of the PublisherModel." + }, + "deployGke": { + "description": "Optional. Deploy PublisherModel to Google Kubernetes Engine.", + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployGke" + }, + "openGenie": { + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences", + "description": "Optional. Open Genie / Playground." + }, + "openPromptTuningPipeline": { + "description": "Optional. Open prompt-tuning pipeline of the PublisherModel.", + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences" + }, + "createApplication": { + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences", + "description": "Optional. Create application using the PublisherModel." + } + }, + "description": "Actions could take on this Publisher Model." + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationCategoricalTransformation": { + "type": "object", + "properties": { + "columnName": { + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationCategoricalTransformation", + "description": "Training pipeline will perform following transformation functions. * The categorical string as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. * Categories that appear less than 5 times in the training dataset are treated as the \"unknown\" category. The \"unknown\" category gets its own special lookup index and resulting embedding." + }, + "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseHeader": { + "description": "Response header with metadata for the requested ReadFeatureValuesRequest.entity_type and Features.", + "properties": { + "featureDescriptors": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseFeatureDescriptor" + }, + "description": "List of Feature metadata corresponding to each piece of ReadFeatureValuesResponse.EntityView.data." + }, + "entityType": { + "type": "string", + "description": "The resource name of the EntityType from the ReadFeatureValuesRequest. Value format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseHeader" + }, + "GoogleCloudAiplatformV1beta1XraiAttribution": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1XraiAttribution", + "description": "An explanation method that redistributes Integrated Gradients attributions to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Supported only by image Models.", + "properties": { + "smoothGradConfig": { + "$ref": "GoogleCloudAiplatformV1beta1SmoothGradConfig", + "description": "Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf" + }, + "blurBaselineConfig": { + "$ref": "GoogleCloudAiplatformV1beta1BlurBaselineConfig", + "description": "Config for XRAI with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383" + }, + "stepCount": { + "type": "integer", + "description": "Required. The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range. Valid range of its value is [1, 100], inclusively.", + "format": "int32" + } + } + }, + "GoogleCloudAiplatformV1beta1ReasoningEngineSpec": { + "properties": { + "classMethods": { + "items": { + "type": "object", + "additionalProperties": { + "description": "Properties of the object.", + "type": "any" + } + }, + "description": "Optional. Declarations for object class methods.", + "type": "array" + }, + "packageSpec": { + "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecPackageSpec", + "description": "Required. User provided package spec of the ReasoningEngine." + } + }, + "id": "GoogleCloudAiplatformV1beta1ReasoningEngineSpec", + "description": "ReasoningEngine configurations", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1InternalOsServiceStateInstance": { + "properties": { + "serviceState": { + "enum": [ + "UNKNOWN", + "HEALTHY", + "UNHEALTHY" + ], + "description": "Required. internal service state.", + "enumDescriptions": [ + "Health status is unknown: not initialized or failed to retrieve.", + "The resource is healthy.", + "The resource is unhealthy." + ], + "type": "string" + }, + "serviceName": { + "description": "Required. internal service name.", + "enum": [ + "INTERNAL_OS_SERVICE_ENUM_UNSPECIFIED", + "DOCKER_SERVICE_STATE", + "CONTROL_PLANE_API_DNS_STATE", + "PROXY_REGISTRATION_DNS_STATE", + "JUPYTER_STATE", + "JUPYTER_API_STATE", + "EUC_METADATA_API_STATE", + "EUC_AGENT_API_STATE", + "IDLE_SHUTDOWN_AGENT_STATE", + "PROXY_AGENT_STATE", + "GCR_DNS_STATE" + ], + "enumDescriptions": [ + "Service name unknown.", + "Represents the internal os docker client.", + "Represents resolving DNS for the control plane api endpoint.", + "Represents resolving DNS for the proxy registration endpoint.", + "Represents the jupyter endpoint.", + "Represents the jupyter/api endpoint.", + "Represents the EUC metadata server API endpoint.", + "Represents the EUC agent server API endpoint.", + "Represents the idle shutdown agent sidecar container.", + "Represents the proxy agent sidecar container.", + "Represents resolving DNS for the gcr.io endpoint." + ], + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1InternalOsServiceStateInstance", + "description": "Request message for [InternalOsServiceStateInstance].", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1GenerateContentResponseUsageMetadata": { + "description": "Usage metadata about response(s).", + "properties": { + "totalTokenCount": { + "type": "integer", + "format": "int32" + }, + "candidatesTokenCount": { + "format": "int32", + "description": "Number of tokens in the response(s).", + "type": "integer" + }, + "promptTokenCount": { + "format": "int32", + "type": "integer", + "description": "Number of tokens in the request." + } + }, + "id": "GoogleCloudAiplatformV1beta1GenerateContentResponseUsageMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1RagCorpus": { + "description": "A RagCorpus is a RagFile container and a project can have multiple RagCorpora.", + "id": "GoogleCloudAiplatformV1beta1RagCorpus", + "properties": { + "updateTime": { + "type": "string", + "readOnly": true, + "description": "Output only. Timestamp when this RagCorpus was last updated.", + "format": "google-datetime" + }, + "ragEmbeddingModelConfig": { + "$ref": "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfig", + "description": "Optional. Immutable. The embedding model config of the RagCorpus." + }, + "description": { + "description": "Optional. The description of the RagCorpus.", + "type": "string" + }, + "createTime": { + "format": "google-datetime", + "type": "string", + "description": "Output only. Timestamp when this RagCorpus was created.", + "readOnly": true + }, + "name": { + "type": "string", + "description": "Output only. The resource name of the RagCorpus.", + "readOnly": true + }, + "displayName": { + "description": "Required. The display name of the RagCorpus. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1DeployModelResponse": { + "type": "object", + "properties": { + "deployedModel": { + "$ref": "GoogleCloudAiplatformV1beta1DeployedModel", + "description": "The DeployedModel that had been deployed in the Endpoint." + } + }, + "description": "Response message for EndpointService.DeployModel.", + "id": "GoogleCloudAiplatformV1beta1DeployModelResponse" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTextTransformation": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTextTransformation", + "properties": { + "columnName": { + "type": "string" + } + }, + "description": "Training pipeline will perform following transformation functions. * The text as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1AutomaticResources": { + "type": "object", + "description": "A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration. Each Model supporting these resources documents its specific guidelines.", + "properties": { + "minReplicaCount": { + "type": "integer", + "description": "Immutable. The minimum number of replicas this DeployedModel will be always deployed on. If traffic against it increases, it may dynamically be deployed onto more replicas up to max_replica_count, and as traffic decreases, some of these extra replicas may be freed. If the requested value is too large, the deployment will error.", + "format": "int32" + }, + "maxReplicaCount": { + "type": "integer", + "format": "int32", + "description": "Immutable. The maximum number of replicas this DeployedModel may be deployed on when the traffic against it increases. If the requested value is too large, the deployment will error, but if deployment succeeds then the ability to scale the model to that many replicas is guaranteed (barring service outages). If traffic against the DeployedModel increases beyond what its replicas at maximum may handle, a portion of the traffic will be dropped. If this value is not provided, a no upper bound for scaling under heavy traffic will be assume, though Vertex AI may be unable to scale beyond certain replica number." + } + }, + "id": "GoogleCloudAiplatformV1beta1AutomaticResources" + }, + "GoogleCloudAiplatformV1beta1UpdatePersistentResourceOperationMetadata": { + "id": "GoogleCloudAiplatformV1beta1UpdatePersistentResourceOperationMetadata", + "type": "object", + "properties": { + "progressMessage": { + "description": "Progress Message for Update LRO", + "type": "string" + }, + "genericMetadata": { + "description": "Operation metadata for PersistentResource.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "description": "Details of operations that perform update PersistentResource." + }, + "GoogleCloudAiplatformV1beta1GenerationConfig": { + "type": "object", + "properties": { + "responseMimeType": { + "type": "string", + "description": "Optional. Output response mimetype of the generated candidate text. Supported mimetype: - `text/plain`: (default) Text output. - `application/json`: JSON response in the candidates. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. This is a preview feature." + }, + "presencePenalty": { + "format": "float", + "type": "number", + "description": "Optional. Positive penalties." + }, + "frequencyPenalty": { + "description": "Optional. Frequency penalties.", + "type": "number", + "format": "float" + }, + "responseSchema": { + "$ref": "GoogleCloudAiplatformV1beta1Schema", + "description": "Optional. The `Schema` object allows the definition of input and output data types. These types can be objects, but also primitives and arrays. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema). If set, a compatible response_mime_type must also be set. Compatible mimetypes: `application/json`: Schema for JSON response." + }, + "topK": { + "type": "number", + "format": "float", + "description": "Optional. If specified, top-k sampling will be used." + }, + "candidateCount": { + "format": "int32", + "type": "integer", + "description": "Optional. Number of candidates to generate." + }, + "stopSequences": { + "items": { + "type": "string" + }, + "description": "Optional. Stop sequences.", + "type": "array" + }, + "maxOutputTokens": { + "format": "int32", + "description": "Optional. The maximum number of output tokens to generate per message.", + "type": "integer" + }, + "topP": { + "description": "Optional. If specified, nucleus sampling will be used.", + "format": "float", + "type": "number" + }, + "temperature": { + "format": "float", + "description": "Optional. Controls the randomness of predictions.", + "type": "number" + } + }, + "id": "GoogleCloudAiplatformV1beta1GenerationConfig", + "description": "Generation config." + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextSentimentInputs": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextSentimentInputs", + "properties": { + "sentimentMax": { + "type": "integer", + "description": "A sentiment is expressed as an integer ordinal, where higher value means a more positive sentiment. The range of sentiments that will be used is between 0 and sentimentMax (inclusive on both ends), and all the values in the range must be represented in the dataset before a model can be created. Only the Annotations with this sentimentMax will be used for training. sentimentMax value must be between 1 and 10 (inclusive).", + "format": "int32" + } + } + }, + "GoogleCloudAiplatformV1beta1ExactMatchInstance": { + "id": "GoogleCloudAiplatformV1beta1ExactMatchInstance", + "properties": { + "reference": { + "type": "string", + "description": "Required. Ground truth used to compare against the prediction." + }, + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + } + }, + "type": "object", + "description": "Spec for exact match instance." + }, + "GoogleCloudAiplatformV1beta1UploadModelResponse": { + "id": "GoogleCloudAiplatformV1beta1UploadModelResponse", + "properties": { + "model": { + "description": "The name of the uploaded Model resource. Format: `projects/{project}/locations/{location}/models/{model}`", + "type": "string" + }, + "modelVersionId": { + "type": "string", + "readOnly": true, + "description": "Output only. The version ID of the model that is uploaded." + } + }, + "description": "Response message of ModelService.UploadModel operation.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1StudySpecParameterSpecIntegerValueSpec": { + "type": "object", + "properties": { + "minValue": { + "type": "string", + "format": "int64", + "description": "Required. Inclusive minimum value of the parameter." + }, + "defaultValue": { + "description": "A default value for an `INTEGER` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.", + "type": "string", + "format": "int64" + }, + "maxValue": { + "description": "Required. Inclusive maximum value of the parameter.", + "type": "string", + "format": "int64" + } + }, + "id": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecIntegerValueSpec", + "description": "Value specification for a parameter in `INTEGER` type." + }, + "GoogleCloudAiplatformV1beta1FeatureView": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1FeatureView", + "properties": { + "updateTime": { + "format": "google-datetime", + "readOnly": true, + "type": "string", + "description": "Output only. Timestamp when this FeatureView was last updated." + }, + "serviceAccountEmail": { + "readOnly": true, + "type": "string", + "description": "Output only. A Service Account unique to this FeatureView. The role bigquery.dataViewer should be granted to this service account to allow Vertex AI Feature Store to sync data to the online store." + }, + "etag": { + "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "syncConfig": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureViewSyncConfig", + "description": "Configures when data is to be synced/updated for this FeatureView. At the end of the sync the latest featureValues for each entityId of this FeatureView are made ready for online serving." + }, + "labels": { + "description": "Optional. The labels with user-defined metadata to organize your FeatureViews. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "vectorSearchConfig": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfig", + "description": "Optional. Deprecated: please use FeatureView.index_config instead.", + "deprecated": true + }, + "name": { + "type": "string", + "description": "Identifier. Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`" + }, + "createTime": { + "description": "Output only. Timestamp when this FeatureView was created.", + "format": "google-datetime", + "readOnly": true, + "type": "string" + }, + "indexConfig": { + "description": "Optional. Configuration for index preparation for vector search. It contains the required configurations to create an index from source data, so that approximate nearest neighbor (a.k.a ANN) algorithms search can be performed during online serving.", + "$ref": "GoogleCloudAiplatformV1beta1FeatureViewIndexConfig" + }, + "featureRegistrySource": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureViewFeatureRegistrySource", + "description": "Optional. Configures the features from a Feature Registry source that need to be loaded onto the FeatureOnlineStore." + }, + "bigQuerySource": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureViewBigQuerySource", + "description": "Optional. Configures how data is supposed to be extracted from a BigQuery source to be loaded onto the FeatureOnlineStore." + }, + "serviceAgentType": { + "description": "Optional. Service agent type used during data sync. By default, the Vertex AI Service Agent is used. When using an IAM Policy to isolate this FeatureView within a project, a separate service account should be provisioned by setting this field to `SERVICE_AGENT_TYPE_FEATURE_VIEW`. This will generate a separate service account to access the BigQuery source table.", + "enum": [ + "SERVICE_AGENT_TYPE_UNSPECIFIED", + "SERVICE_AGENT_TYPE_PROJECT", + "SERVICE_AGENT_TYPE_FEATURE_VIEW" + ], + "enumDescriptions": [ + "By default, the project-level Vertex AI Service Agent is enabled.", + "Indicates the project-level Vertex AI Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) will be used during sync jobs.", + "Enable a FeatureView service account to be created by Vertex AI and output in the field `service_account_email`. This service account will be used to read from the source BigQuery table during sync." + ], + "type": "string" + } + }, + "description": "FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig." + }, + "GoogleCloudAiplatformV1beta1ListMetadataSchemasResponse": { + "id": "GoogleCloudAiplatformV1beta1ListMetadataSchemasResponse", + "type": "object", + "description": "Response message for MetadataService.ListMetadataSchemas.", + "properties": { + "metadataSchemas": { + "type": "array", + "description": "The MetadataSchemas found for the MetadataStore.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1MetadataSchema" + } + }, + "nextPageToken": { + "description": "A token, which can be sent as ListMetadataSchemasRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1BatchCancelPipelineJobsRequest": { + "properties": { + "names": { + "description": "Required. The names of the PipelineJobs to cancel. A maximum of 32 PipelineJobs can be cancelled in a batch. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipelineJob}`", + "type": "array", + "items": { + "type": "string" + } + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1BatchCancelPipelineJobsRequest", + "description": "Request message for PipelineService.BatchCancelPipelineJobs." + }, + "GoogleCloudAiplatformV1beta1BatchPredictionJobOutputConfig": { + "type": "object", + "description": "Configures the output of BatchPredictionJob. See Model.supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them.", + "properties": { + "predictionsFormat": { + "type": "string", + "description": "Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats." + }, + "gcsDestination": { + "$ref": "GoogleCloudAiplatformV1beta1GcsDestination", + "description": "The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is `prediction--`, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files `predictions_0001.`, `predictions_0002.`, ..., `predictions_N.` are created where `` depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional `errors_0001.`, `errors_0002.`,..., `errors_N.` files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional `error` field which as value has google.rpc.Status containing only `code` and `message` fields." + }, + "bigqueryDestination": { + "description": "The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name `prediction__` where is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ \"based on ISO-8601\" format. In the dataset two tables will be created, `predictions`, and `errors`. If the Model has both instance and prediction schemata defined then the tables have columns as follows: The `predictions` table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The `errors` table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single \"errors\" column, which as values has google.rpc.Status represented as a STRUCT, and containing only `code` and `message`.", + "$ref": "GoogleCloudAiplatformV1beta1BigQueryDestination" + } + }, + "id": "GoogleCloudAiplatformV1beta1BatchPredictionJobOutputConfig" + }, + "GoogleCloudAiplatformV1beta1AddContextChildrenResponse": { + "properties": {}, + "id": "GoogleCloudAiplatformV1beta1AddContextChildrenResponse", + "type": "object", + "description": "Response message for MetadataService.AddContextChildren." + }, + "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchInput": { + "type": "object", + "properties": { + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchSpec", + "description": "Required. Spec for tool parameter key match metric." + }, + "instances": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchInstance" + }, + "description": "Required. Repeated tool parameter key match instances.", + "type": "array" + } + }, + "description": "Input for tool parameter key match metric.", + "id": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchInput" + }, + "GoogleCloudAiplatformV1beta1ExplainRequest": { + "id": "GoogleCloudAiplatformV1beta1ExplainRequest", + "properties": { + "explanationSpecOverride": { + "description": "If specified, overrides the explanation_spec of the DeployedModel. Can be used for explaining prediction results with different configurations, such as: - Explaining top-5 predictions results as opposed to top-1; - Increasing path count or step count of the attribution methods to reduce approximate errors; - Using different baselines for explaining the prediction results.", + "$ref": "GoogleCloudAiplatformV1beta1ExplanationSpecOverride" + }, + "instances": { + "type": "array", + "items": { + "type": "any" + }, + "description": "Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri." + }, + "deployedModelId": { + "description": "If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split.", + "type": "string" + }, + "parameters": { + "type": "any", + "description": "The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri." + }, + "concurrentExplanationSpecOverride": { + "type": "object", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1ExplanationSpecOverride" + }, + "description": "Optional. This field is the same as the one above, but supports multiple explanations to occur in parallel. The key can be any string. Each override will be run against the model, then its explanations will be grouped together. Note - these explanations are run **In Addition** to the default Explanation in the deployed model." + } + }, + "description": "Request message for PredictionService.Explain.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ModelExplanation": { + "type": "object", + "properties": { + "meanAttributions": { + "type": "array", + "description": "Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. Attribution.output_index can be used to identify which output this attribution is explaining. The baselineOutputValue, instanceOutputValue and featureAttributions fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. Attribution.approximation_error is not populated.", + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Attribution" + } + } + }, + "description": "Aggregated explanation metrics for a Model over a set of instances.", + "id": "GoogleCloudAiplatformV1beta1ModelExplanation" + }, + "GoogleCloudAiplatformV1beta1ComputeTokensResponse": { + "id": "GoogleCloudAiplatformV1beta1ComputeTokensResponse", + "properties": { + "tokensInfo": { + "description": "Lists of tokens info from the input. A ComputeTokensRequest could have multiple instances with a prompt in each instance. We also need to return lists of tokens info for the request with multiple instances.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1TokensInfo" + } + } + }, + "type": "object", + "description": "Response message for ComputeTokens RPC call." + }, + "GoogleCloudAiplatformV1beta1SummarizationVerbosityInput": { + "properties": { + "instance": { + "$ref": "GoogleCloudAiplatformV1beta1SummarizationVerbosityInstance", + "description": "Required. Summarization verbosity instance." + }, + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1beta1SummarizationVerbositySpec", + "description": "Required. Spec for summarization verbosity score metric." + } + }, + "description": "Input for summarization verbosity metric.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SummarizationVerbosityInput" + }, + "GoogleCloudAiplatformV1beta1ExplanationParameters": { + "properties": { + "integratedGradientsAttribution": { + "description": "An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365", + "$ref": "GoogleCloudAiplatformV1beta1IntegratedGradientsAttribution" + }, + "xraiAttribution": { + "description": "An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 XRAI currently performs better on natural images, like a picture of a house or an animal. If the images are taken in artificial environments, like a lab or manufacturing line, or from diagnostic equipment, like x-rays or quality-control cameras, use Integrated Gradients instead.", + "$ref": "GoogleCloudAiplatformV1beta1XraiAttribution" + }, + "examples": { + "description": "Example-based explanations that returns the nearest neighbors from the provided dataset.", + "$ref": "GoogleCloudAiplatformV1beta1Examples" + }, + "topK": { + "type": "integer", + "description": "If populated, returns attributions for top K indices of outputs (defaults to 1). Only applies to Models that predicts more than one outputs (e,g, multi-class Models). When set to -1, returns explanations for all outputs.", + "format": "int32" + }, + "outputIndices": { + "items": { + "type": "any" + }, + "description": "If populated, only returns attributions that have output_index contained in output_indices. It must be an ndarray of integers, with the same shape of the output it's explaining. If not populated, returns attributions for top_k indices of outputs. If neither top_k nor output_indices is populated, returns the argmax index of the outputs. Only applicable to Models that predict multiple outputs (e,g, multi-class Models that predict multiple classes).", + "type": "array" + }, + "sampledShapleyAttribution": { + "$ref": "GoogleCloudAiplatformV1beta1SampledShapleyAttribution", + "description": "An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features. Refer to this paper for model details: https://arxiv.org/abs/1306.4265." + } + }, + "type": "object", + "description": "Parameters to configure explaining for Model's predictions.", + "id": "GoogleCloudAiplatformV1beta1ExplanationParameters" + }, + "GoogleCloudAiplatformV1beta1EncryptionSpec": { + "type": "object", + "properties": { + "kmsKeyName": { + "type": "string", + "description": "Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created." + } + }, + "id": "GoogleCloudAiplatformV1beta1EncryptionSpec", + "description": "Represents a customer-managed encryption key spec that can be applied to a top-level resource." + }, + "GoogleCloudAiplatformV1beta1ExactMatchResults": { + "description": "Results for exact match metric.", + "type": "object", + "properties": { + "exactMatchMetricValues": { + "readOnly": true, + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ExactMatchMetricValue" + }, + "description": "Output only. Exact match metric values." + } + }, + "id": "GoogleCloudAiplatformV1beta1ExactMatchResults" + }, + "GoogleCloudAiplatformV1beta1ToolCallValidInstance": { + "properties": { + "reference": { + "type": "string", + "description": "Required. Ground truth used to compare against the prediction." + }, + "prediction": { + "description": "Required. Output of the evaluated model.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ToolCallValidInstance", + "description": "Spec for tool call valid instance." + }, + "GoogleCloudAiplatformV1beta1FulfillmentInput": { + "description": "Input for fulfillment metric.", + "id": "GoogleCloudAiplatformV1beta1FulfillmentInput", + "properties": { + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1beta1FulfillmentSpec", + "description": "Required. Spec for fulfillment score metric." + }, + "instance": { + "$ref": "GoogleCloudAiplatformV1beta1FulfillmentInstance", + "description": "Required. Fulfillment instance." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ListSavedQueriesResponse": { + "properties": { + "nextPageToken": { + "type": "string", + "description": "The standard List next-page token." + }, + "savedQueries": { + "type": "array", + "description": "A list of SavedQueries that match the specified filter in the request.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SavedQuery" + } + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ListSavedQueriesResponse", + "description": "Response message for DatasetService.ListSavedQueries." + }, + "GoogleCloudAiplatformV1beta1PublisherModelCallToActionOpenNotebooks": { + "description": "Open notebooks.", + "id": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionOpenNotebooks", + "type": "object", + "properties": { + "notebooks": { + "description": "Required. Regional resource references to notebooks.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences" + }, + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoActionRecognitionInputs": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoActionRecognitionInputs", + "properties": { + "modelType": { + "enum": [ + "MODEL_TYPE_UNSPECIFIED", + "CLOUD", + "MOBILE_VERSATILE_1", + "MOBILE_JETSON_VERSATILE_1", + "MOBILE_CORAL_VERSATILE_1" + ], + "type": "string", + "enumDescriptions": [ + "Should not be set.", + "A model best tailored to be used within Google Cloud, and which c annot be exported. Default.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as a TensorFlow or TensorFlow Lite model and used on a mobile or edge device afterwards.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) to a Jetson device afterwards.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as a TensorFlow or TensorFlow Lite model and used on a Coral device afterwards." + ] + } + } + }, + "GoogleCloudAiplatformV1beta1FunctionCall": { + "properties": { + "args": { + "additionalProperties": { + "type": "any", + "description": "Properties of the object." + }, + "description": "Optional. Required. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.", + "type": "object" + }, + "name": { + "description": "Required. The name of the function to call. Matches [FunctionDeclaration.name].", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1FunctionCall", + "type": "object", + "description": "A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values." + }, + "GoogleCloudAiplatformV1beta1AuthConfigOauthConfig": { + "description": "Config for user oauth.", + "id": "GoogleCloudAiplatformV1beta1AuthConfigOauthConfig", + "properties": { + "accessToken": { + "type": "string", + "description": "Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time." + }, + "serviceAccount": { + "type": "string", + "description": "The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTimeSeriesForecastingPredictionResult": { + "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTimeSeriesForecastingPredictionResult", + "description": "Prediction output format for Time Series Forecasting.", + "type": "object", + "properties": { + "tftFeatureImportance": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTftFeatureImportance", + "description": "Only use these if TFt is enabled." + }, + "quantileValues": { + "items": { + "format": "float", + "type": "number" + }, + "type": "array", + "description": "Quantile values." + }, + "value": { + "description": "The regression value.", + "format": "float", + "type": "number" + }, + "quantilePredictions": { + "items": { + "type": "number", + "format": "float" + }, + "type": "array", + "description": "Quantile predictions, in 1-1 correspondence with quantile_values." + } + } + }, + "GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistribution": { + "id": "GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistribution", + "type": "object", + "properties": { + "max": { + "type": "number", + "format": "double", + "description": "Output only. The maximum of the population values.", + "readOnly": true + }, + "billableSum": { + "readOnly": true, + "type": "string", + "format": "int64", + "description": "Output only. Sum of a given population of values that are billable." + }, + "mean": { + "format": "double", + "type": "number", + "readOnly": true, + "description": "Output only. The arithmetic mean of the values in the population." + }, + "p5": { + "readOnly": true, + "format": "double", + "type": "number", + "description": "Output only. The 5th percentile of the values in the population." + }, + "median": { + "readOnly": true, + "description": "Output only. The median of the values in the population.", + "format": "double", + "type": "number" + }, + "min": { + "readOnly": true, + "format": "double", + "description": "Output only. The minimum of the population values.", + "type": "number" + }, + "sum": { + "type": "string", + "format": "int64", + "description": "Output only. Sum of a given population of values.", + "readOnly": true + }, + "p95": { + "description": "Output only. The 95th percentile of the values in the population.", + "format": "double", + "readOnly": true, + "type": "number" + }, + "buckets": { + "description": "Output only. Defines the histogram bucket.", + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistributionDatasetBucket" + }, + "type": "array" + } + }, + "description": "Dataset distribution for Supervised Tuning." + }, + "GoogleCloudAiplatformV1beta1IndexStats": { + "description": "Stats of the Index.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1IndexStats", + "properties": { + "shardsCount": { + "type": "integer", + "format": "int32", + "description": "Output only. The number of shards in the Index.", + "readOnly": true + }, + "sparseVectorsCount": { + "readOnly": true, + "description": "Output only. The number of sparse vectors in the Index.", + "format": "int64", + "type": "string" + }, + "vectorsCount": { + "format": "int64", + "description": "Output only. The number of dense vectors in the Index.", + "readOnly": true, + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadataRecordError": { + "id": "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadataRecordError", + "properties": { + "errorType": { + "enumDescriptions": [ + "Default, shall not be used.", + "The record is empty.", + "Invalid json format.", + "Invalid csv format.", + "Invalid avro format.", + "The embedding id is not valid.", + "The size of the dense embedding vectors does not match with the specified dimension.", + "The `namespace` field is missing.", + "Generic catch-all error. Only used for validation failure where the root cause cannot be easily retrieved programmatically.", + "There are multiple restricts with the same `namespace` value.", + "Numeric restrict has operator specified in datapoint.", + "Numeric restrict has multiple values specified.", + "Numeric restrict has invalid numeric value specified.", + "File is not in UTF_8 format.", + "Error parsing sparse dimensions field.", + "Token restrict value is invalid.", + "Invalid sparse embedding.", + "Invalid dense embedding." + ], + "type": "string", + "description": "The error type of this record.", + "enum": [ + "ERROR_TYPE_UNSPECIFIED", + "EMPTY_LINE", + "INVALID_JSON_SYNTAX", + "INVALID_CSV_SYNTAX", + "INVALID_AVRO_SYNTAX", + "INVALID_EMBEDDING_ID", + "EMBEDDING_SIZE_MISMATCH", + "NAMESPACE_MISSING", + "PARSING_ERROR", + "DUPLICATE_NAMESPACE", + "OP_IN_DATAPOINT", + "MULTIPLE_VALUES", + "INVALID_NUMERIC_VALUE", + "INVALID_ENCODING", + "INVALID_SPARSE_DIMENSIONS", + "INVALID_TOKEN_VALUE", + "INVALID_SPARSE_EMBEDDING", + "INVALID_EMBEDDING" + ] + }, + "sourceGcsUri": { + "type": "string", + "description": "Cloud Storage URI pointing to the original file in user's bucket." + }, + "errorMessage": { + "type": "string", + "description": "A human-readable message that is shown to the user to help them fix the error. Note that this message may change from time to time, your code should check against error_type as the source of truth." + }, + "rawRecord": { + "description": "The original content of this record.", + "type": "string" + }, + "embeddingId": { + "type": "string", + "description": "Empty if the embedding id is failed to parse." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences", + "description": "The regional resource name or the URI. Key is region, e.g., us-central1, europe-west2, global, etc..", + "properties": { + "title": { + "type": "string", + "description": "Required. " + }, + "resourceUseCase": { + "type": "string", + "description": "Optional. Use case (CUJ) of the resource." + }, + "references": { + "type": "object", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelResourceReference" + }, + "description": "Required." + }, + "resourceTitle": { + "type": "string", + "description": "Optional. Title of the resource." + }, + "resourceDescription": { + "type": "string", + "description": "Optional. Description of the resource." + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaPredictionResultError": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaPredictionResultError", + "properties": { + "status": { + "type": "string", + "enumDescriptions": [ + "Not an error; returned on success. HTTP Mapping: 200 OK", + "The operation was cancelled, typically by the caller. HTTP Mapping: 499 Client Closed Request", + "Unknown error. For example, this error may be returned when a `Status` value received from another address space belongs to an error space that is not known in this address space. Also errors raised by APIs that do not return enough error information may be converted to this error. HTTP Mapping: 500 Internal Server Error", + "The client specified an invalid argument. Note that this differs from `FAILED_PRECONDITION`. `INVALID_ARGUMENT` indicates arguments that are problematic regardless of the state of the system (e.g., a malformed file name). HTTP Mapping: 400 Bad Request", + "The deadline expired before the operation could complete. For operations that change the state of the system, this error may be returned even if the operation has completed successfully. For example, a successful response from a server could have been delayed long enough for the deadline to expire. HTTP Mapping: 504 Gateway Timeout", + "Some requested entity (e.g., file or directory) was not found. Note to server developers: if a request is denied for an entire class of users, such as gradual feature rollout or undocumented allowlist, `NOT_FOUND` may be used. If a request is denied for some users within a class of users, such as user-based access control, `PERMISSION_DENIED` must be used. HTTP Mapping: 404 Not Found", + "The entity that a client attempted to create (e.g., file or directory) already exists. HTTP Mapping: 409 Conflict", + "The caller does not have permission to execute the specified operation. `PERMISSION_DENIED` must not be used for rejections caused by exhausting some resource (use `RESOURCE_EXHAUSTED` instead for those errors). `PERMISSION_DENIED` must not be used if the caller can not be identified (use `UNAUTHENTICATED` instead for those errors). This error code does not imply the request is valid or the requested entity exists or satisfies other pre-conditions. HTTP Mapping: 403 Forbidden", + "The request does not have valid authentication credentials for the operation. HTTP Mapping: 401 Unauthorized", + "Some resource has been exhausted, perhaps a per-user quota, or perhaps the entire file system is out of space. HTTP Mapping: 429 Too Many Requests", + "The operation was rejected because the system is not in a state required for the operation's execution. For example, the directory to be deleted is non-empty, an rmdir operation is applied to a non-directory, etc. Service implementors can use the following guidelines to decide between `FAILED_PRECONDITION`, `ABORTED`, and `UNAVAILABLE`: (a) Use `UNAVAILABLE` if the client can retry just the failing call. (b) Use `ABORTED` if the client should retry at a higher level. For example, when a client-specified test-and-set fails, indicating the client should restart a read-modify-write sequence. (c) Use `FAILED_PRECONDITION` if the client should not retry until the system state has been explicitly fixed. For example, if an \"rmdir\" fails because the directory is non-empty, `FAILED_PRECONDITION` should be returned since the client should not retry unless the files are deleted from the directory. HTTP Mapping: 400 Bad Request", + "The operation was aborted, typically due to a concurrency issue such as a sequencer check failure or transaction abort. See the guidelines above for deciding between `FAILED_PRECONDITION`, `ABORTED`, and `UNAVAILABLE`. HTTP Mapping: 409 Conflict", + "The operation was attempted past the valid range. E.g., seeking or reading past end-of-file. Unlike `INVALID_ARGUMENT`, this error indicates a problem that may be fixed if the system state changes. For example, a 32-bit file system will generate `INVALID_ARGUMENT` if asked to read at an offset that is not in the range [0,2^32-1], but it will generate `OUT_OF_RANGE` if asked to read from an offset past the current file size. There is a fair bit of overlap between `FAILED_PRECONDITION` and `OUT_OF_RANGE`. We recommend using `OUT_OF_RANGE` (the more specific error) when it applies so that callers who are iterating through a space can easily look for an `OUT_OF_RANGE` error to detect when they are done. HTTP Mapping: 400 Bad Request", + "The operation is not implemented or is not supported/enabled in this service. HTTP Mapping: 501 Not Implemented", + "Internal errors. This means that some invariants expected by the underlying system have been broken. This error code is reserved for serious errors. HTTP Mapping: 500 Internal Server Error", + "The service is currently unavailable. This is most likely a transient condition, which can be corrected by retrying with a backoff. Note that it is not always safe to retry non-idempotent operations. See the guidelines above for deciding between `FAILED_PRECONDITION`, `ABORTED`, and `UNAVAILABLE`. HTTP Mapping: 503 Service Unavailable", + "Unrecoverable data loss or corruption. HTTP Mapping: 500 Internal Server Error" + ], + "enum": [ + "OK", + "CANCELLED", + "UNKNOWN", + "INVALID_ARGUMENT", + "DEADLINE_EXCEEDED", + "NOT_FOUND", + "ALREADY_EXISTS", + "PERMISSION_DENIED", + "UNAUTHENTICATED", + "RESOURCE_EXHAUSTED", + "FAILED_PRECONDITION", + "ABORTED", + "OUT_OF_RANGE", + "UNIMPLEMENTED", + "INTERNAL", + "UNAVAILABLE", + "DATA_LOSS" + ], + "description": "Error status. This will be serialized into the enum name e.g. \"NOT_FOUND\"." + }, + "message": { + "type": "string", + "description": "Error message with additional details." + } + } + }, + "GoogleCloudAiplatformV1beta1SampledShapleyAttribution": { + "properties": { + "pathCount": { + "type": "integer", + "format": "int32", + "description": "Required. The number of feature permutations to consider when approximating the Shapley values. Valid range of its value is [1, 50], inclusively." + } + }, + "description": "An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.", + "id": "GoogleCloudAiplatformV1beta1SampledShapleyAttribution", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1RetrieveContextsRequest": { + "id": "GoogleCloudAiplatformV1beta1RetrieveContextsRequest", + "properties": { + "query": { + "$ref": "GoogleCloudAiplatformV1beta1RagQuery", + "description": "Required. Single RAG retrieve query." + }, + "vertexRagStore": { + "description": "The data source for Vertex RagStore.", + "$ref": "GoogleCloudAiplatformV1beta1RetrieveContextsRequestVertexRagStore" + } + }, + "type": "object", + "description": "Request message for VertexRagService.RetrieveContexts." + }, + "GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoClassificationPredictionResult": { + "description": "Prediction output format for Video Classification.", + "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoClassificationPredictionResult", + "type": "object", + "properties": { + "id": { + "type": "string", + "description": "The resource ID of the AnnotationSpec that had been identified." + }, + "confidence": { + "type": "number", + "format": "float", + "description": "The Model's confidence in correction of this prediction, higher value means higher confidence." + }, + "timeSegmentEnd": { + "type": "string", + "description": "The end, exclusive, of the video's time segment in which the AnnotationSpec has been identified. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end. Note that for 'segment-classification' prediction type, this equals the original 'timeSegmentEnd' from the input instance, for other types it is the end of a shot or a 1 second interval respectively.", + "format": "google-duration" + }, + "timeSegmentStart": { + "description": "The beginning, inclusive, of the video's time segment in which the AnnotationSpec has been identified. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end. Note that for 'segment-classification' prediction type, this equals the original 'timeSegmentStart' from the input instance, for other types it is the start of a shot or a 1 second interval respectively.", + "format": "google-duration", + "type": "string" + }, + "type": { + "description": "The type of the prediction. The requested types can be configured via parameters. This will be one of - segment-classification - shot-classification - one-sec-interval-classification", + "type": "string" + }, + "displayName": { + "description": "The display name of the AnnotationSpec that had been identified.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1NearestNeighborQueryParameters": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1NearestNeighborQueryParameters", + "properties": { + "leafNodesSearchFraction": { + "type": "number", + "format": "double", + "description": "Optional. The fraction of the number of leaves to search, set at query time allows user to tune search performance. This value increase result in both search accuracy and latency increase. The value should be between 0.0 and 1.0." + }, + "approximateNeighborCandidates": { + "description": "Optional. The number of neighbors to find via approximate search before exact reordering is performed; if set, this value must be \u003e neighbor_count.", + "type": "integer", + "format": "int32" + } + }, + "description": "Parameters that can be overrided in each query to tune query latency and recall." + }, + "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsRequest": { + "id": "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsRequest", + "description": "Request message for ModelMonitoringService.SearchModelMonitoringStats.", + "type": "object", + "properties": { + "timeInterval": { + "$ref": "GoogleTypeInterval", + "description": "The time interval for which results should be returned." + }, + "pageSize": { + "type": "integer", + "description": "The standard list page size.", + "format": "int32" + }, + "statsFilter": { + "description": "Filter for search different stats.", + "$ref": "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsFilter" + }, + "pageToken": { + "type": "string", + "description": "A page token received from a previous ModelMonitoringService.SearchModelMonitoringStats call." + } + } + }, + "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsFilterTabularStatsFilter": { + "properties": { + "modelMonitoringJob": { + "type": "string", + "description": "From a particular monitoring job." + }, + "modelMonitoringSchedule": { + "description": "From a particular monitoring schedule.", + "type": "string" + }, + "algorithm": { + "type": "string", + "description": "Specify the algorithm type used for distance calculation, eg: jensen_shannon_divergence, l_infinity." + }, + "objectiveType": { + "description": "One of the supported monitoring objectives: `raw-feature-drift` `prediction-output-drift` `feature-attribution`", + "type": "string" + }, + "statsName": { + "description": "If not specified, will return all the stats_names.", + "type": "string" + } + }, + "description": "Tabular statistics filter.", + "id": "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsFilterTabularStatsFilter", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1StreamingPredictRequest": { + "properties": { + "inputs": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Tensor" + }, + "description": "The prediction input.", + "type": "array" + }, + "parameters": { + "description": "The parameters that govern the prediction.", + "$ref": "GoogleCloudAiplatformV1beta1Tensor" + } + }, + "id": "GoogleCloudAiplatformV1beta1StreamingPredictRequest", + "type": "object", + "description": "Request message for PredictionService.StreamingPredict. The first message must contain endpoint field and optionally input. The subsequent messages must contain input." + }, + "GoogleCloudAiplatformV1beta1DatasetVersion": { + "id": "GoogleCloudAiplatformV1beta1DatasetVersion", + "type": "object", + "description": "Describes the dataset version.", + "properties": { + "name": { + "description": "Output only. Identifier. The resource name of the DatasetVersion.", + "readOnly": true, + "type": "string" + }, + "createTime": { + "format": "google-datetime", + "type": "string", + "description": "Output only. Timestamp when this DatasetVersion was created.", + "readOnly": true + }, + "bigQueryDatasetName": { + "readOnly": true, + "type": "string", + "description": "Output only. Name of the associated BigQuery dataset." + }, + "updateTime": { + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Timestamp when this DatasetVersion was last updated.", + "type": "string" + }, + "etag": { + "type": "string", + "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + }, + "displayName": { + "type": "string", + "description": "The user-defined name of the DatasetVersion. The name can be up to 128 characters long and can consist of any UTF-8 characters." + }, + "metadata": { + "readOnly": true, + "type": "any", + "description": "Required. Output only. Additional information about the DatasetVersion." + }, + "modelReference": { + "description": "Output only. Reference to the public base model last used by the dataset version. Only set for prompt dataset versions.", + "readOnly": true, + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1FulfillmentResult": { + "id": "GoogleCloudAiplatformV1beta1FulfillmentResult", + "type": "object", + "description": "Spec for fulfillment result.", + "properties": { + "confidence": { + "description": "Output only. Confidence for fulfillment score.", + "readOnly": true, + "format": "float", + "type": "number" + }, + "explanation": { + "description": "Output only. Explanation for fulfillment score.", + "type": "string", + "readOnly": true + }, + "score": { + "description": "Output only. Fulfillment score.", + "format": "float", + "type": "number", + "readOnly": true + } + } + }, + "GoogleCloudAiplatformV1beta1WorkerPoolSpec": { + "id": "GoogleCloudAiplatformV1beta1WorkerPoolSpec", + "description": "Represents the spec of a worker pool in a job.", + "type": "object", + "properties": { + "nfsMounts": { + "description": "Optional. List of NFS mount spec.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1NfsMount" + }, + "type": "array" + }, + "diskSpec": { + "$ref": "GoogleCloudAiplatformV1beta1DiskSpec", + "description": "Disk spec." + }, + "machineSpec": { + "$ref": "GoogleCloudAiplatformV1beta1MachineSpec", + "description": "Optional. Immutable. The specification of a single machine." + }, + "containerSpec": { + "description": "The custom container task.", + "$ref": "GoogleCloudAiplatformV1beta1ContainerSpec" + }, + "pythonPackageSpec": { + "$ref": "GoogleCloudAiplatformV1beta1PythonPackageSpec", + "description": "The Python packaged task." + }, + "replicaCount": { + "type": "string", + "description": "Optional. The number of worker replicas to use for this worker pool.", + "format": "int64" + } + } + }, + "GoogleCloudAiplatformV1beta1ListFeatureViewsResponse": { + "description": "Response message for FeatureOnlineStoreAdminService.ListFeatureViews.", + "id": "GoogleCloudAiplatformV1beta1ListFeatureViewsResponse", + "properties": { + "featureViews": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureView" + }, + "type": "array", + "description": "The FeatureViews matching the request." + }, + "nextPageToken": { + "description": "A token, which can be sent as ListFeatureViewsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1CreateFeatureGroupOperationMetadata": { + "properties": { + "genericMetadata": { + "description": "Operation metadata for FeatureGroup.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "id": "GoogleCloudAiplatformV1beta1CreateFeatureGroupOperationMetadata", + "type": "object", + "description": "Details of operations that perform create FeatureGroup." + }, + "GoogleCloudAiplatformV1beta1PersistentResource": { + "id": "GoogleCloudAiplatformV1beta1PersistentResource", + "type": "object", + "properties": { + "state": { + "description": "Output only. The detailed state of a Study.", + "enumDescriptions": [ + "Not set.", + "The PROVISIONING state indicates the persistent resources is being created.", + "The RUNNING state indicates the persistent resource is healthy and fully usable.", + "The STOPPING state indicates the persistent resource is being deleted.", + "The ERROR state indicates the persistent resource may be unusable. Details can be found in the `error` field.", + "The REBOOTING state indicates the persistent resource is being rebooted (PR is not available right now but is expected to be ready again later).", + "The UPDATING state indicates the persistent resource is being updated." + ], + "type": "string", + "enum": [ + "STATE_UNSPECIFIED", + "PROVISIONING", + "RUNNING", + "STOPPING", + "ERROR", + "REBOOTING", + "UPDATING" + ], + "readOnly": true + }, + "resourcePools": { + "description": "Required. The spec of the pools of different resources.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ResourcePool" + }, + "type": "array" + }, + "reservedIpRanges": { + "items": { + "type": "string" + }, + "description": "Optional. A list of names for the reserved IP ranges under the VPC network that can be used for this persistent resource. If set, we will deploy the persistent resource within the provided IP ranges. Otherwise, the persistent resource is deployed to any IP ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].", + "type": "array" + }, + "resourceRuntime": { + "$ref": "GoogleCloudAiplatformV1beta1ResourceRuntime", + "description": "Output only. Runtime information of the Persistent Resource.", + "readOnly": true + }, + "displayName": { + "description": "Optional. The display name of the PersistentResource. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + }, + "updateTime": { + "readOnly": true, + "format": "google-datetime", + "type": "string", + "description": "Output only. Time when the PersistentResource was most recently updated." + }, + "startTime": { + "format": "google-datetime", + "type": "string", + "readOnly": true, + "description": "Output only. Time when the PersistentResource for the first time entered the `RUNNING` state." + }, + "pscInterfaceConfig": { + "description": "Optional. Configuration for PSC-I for PersistentResource.", + "$ref": "GoogleCloudAiplatformV1beta1PscInterfaceConfig" + }, + "resourceRuntimeSpec": { + "$ref": "GoogleCloudAiplatformV1beta1ResourceRuntimeSpec", + "description": "Optional. Persistent Resource runtime spec. For example, used for Ray cluster configuration." + }, + "name": { + "type": "string", + "description": "Immutable. Resource name of a PersistentResource." + }, + "error": { + "description": "Output only. Only populated when persistent resource's state is `STOPPING` or `ERROR`.", + "readOnly": true, + "$ref": "GoogleRpcStatus" + }, + "createTime": { + "readOnly": true, + "description": "Output only. Time when the PersistentResource was created.", + "format": "google-datetime", + "type": "string" + }, + "network": { + "description": "Optional. The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to peered with Vertex AI to host the persistent resources. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. To specify this field, you must have already [configured VPC Network Peering for Vertex AI](https://cloud.google.com/vertex-ai/docs/general/vpc-peering). If this field is left unspecified, the resources aren't peered with any network.", + "type": "string" + }, + "labels": { + "description": "Optional. The labels with user-defined metadata to organize PersistentResource. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", + "additionalProperties": { + "type": "string" + }, + "type": "object" + }, + "encryptionSpec": { + "description": "Optional. Customer-managed encryption key spec for a PersistentResource. If set, this PersistentResource and all sub-resources of this PersistentResource will be secured by this key.", + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" + } + }, + "description": "Represents long-lasting resources that are dedicated to users to runs custom workloads. A PersistentResource can have multiple node pools and each node pool can have its own machine spec." + }, + "GoogleCloudAiplatformV1beta1ReadTensorboardSizeResponse": { + "type": "object", + "properties": { + "storageSizeByte": { + "description": "Payload storage size for the TensorBoard", + "format": "int64", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1ReadTensorboardSizeResponse", + "description": "Response message for TensorboardService.ReadTensorboardSize." + }, + "GoogleCloudAiplatformV1beta1NasJobSpec": { + "type": "object", + "description": "Represents the spec of a NasJob.", + "properties": { + "searchSpaceSpec": { + "description": "It defines the search space for Neural Architecture Search (NAS).", + "type": "string" + }, + "multiTrialAlgorithmSpec": { + "$ref": "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpec", + "description": "The spec of multi-trial algorithms." + }, + "resumeNasJobId": { + "type": "string", + "description": "The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob." + } + }, + "id": "GoogleCloudAiplatformV1beta1NasJobSpec" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecasting": { + "description": "A TrainingJob that trains and uploads an AutoML Forecasting Model.", + "properties": { + "inputs": { + "description": "The input parameters of this TrainingJob.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputs" + }, + "metadata": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingMetadata", + "description": "The metadata information." + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecasting", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextClassification": { + "description": "A TrainingJob that trains and uploads an AutoML Text Classification Model.", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextClassification", + "properties": { + "inputs": { + "description": "The input parameters of this TrainingJob.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextClassificationInputs" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SavedQuery": { + "properties": { + "annotationSpecCount": { + "description": "Output only. Number of AnnotationSpecs in the context of the SavedQuery.", + "format": "int32", + "readOnly": true, + "type": "integer" + }, + "updateTime": { + "readOnly": true, + "type": "string", + "format": "google-datetime", + "description": "Output only. Timestamp when SavedQuery was last updated." + }, + "displayName": { + "description": "Required. The user-defined name of the SavedQuery. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + }, + "createTime": { + "format": "google-datetime", + "readOnly": true, + "type": "string", + "description": "Output only. Timestamp when this SavedQuery was created." + }, + "supportAutomlTraining": { + "readOnly": true, + "description": "Output only. If the Annotations belonging to the SavedQuery can be used for AutoML training.", + "type": "boolean" + }, + "annotationFilter": { + "readOnly": true, + "description": "Output only. Filters on the Annotations in the dataset.", + "type": "string" + }, + "metadata": { + "description": "Some additional information about the SavedQuery.", + "type": "any" + }, + "problemType": { + "type": "string", + "description": "Required. Problem type of the SavedQuery. Allowed values: * IMAGE_CLASSIFICATION_SINGLE_LABEL * IMAGE_CLASSIFICATION_MULTI_LABEL * IMAGE_BOUNDING_POLY * IMAGE_BOUNDING_BOX * TEXT_CLASSIFICATION_SINGLE_LABEL * TEXT_CLASSIFICATION_MULTI_LABEL * TEXT_EXTRACTION * TEXT_SENTIMENT * VIDEO_CLASSIFICATION * VIDEO_OBJECT_TRACKING" + }, + "name": { + "readOnly": true, + "type": "string", + "description": "Output only. Resource name of the SavedQuery." + }, + "etag": { + "description": "Used to perform a consistent read-modify-write update. If not set, a blind \"overwrite\" update happens.", + "type": "string" + } + }, + "type": "object", + "description": "A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.", + "id": "GoogleCloudAiplatformV1beta1SavedQuery" + }, + "GoogleCloudAiplatformV1beta1CoherenceInput": { + "description": "Input for coherence metric.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1CoherenceInput", + "properties": { + "instance": { + "description": "Required. Coherence instance.", + "$ref": "GoogleCloudAiplatformV1beta1CoherenceInstance" + }, + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1beta1CoherenceSpec", + "description": "Required. Spec for coherence score metric." + } + } + }, + "GoogleCloudAiplatformV1beta1MigratableResourceDataLabelingDataset": { + "description": "Represents one Dataset in datalabeling.googleapis.com.", + "properties": { + "dataLabelingAnnotatedDatasets": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1MigratableResourceDataLabelingDatasetDataLabelingAnnotatedDataset" + }, + "description": "The migratable AnnotatedDataset in datalabeling.googleapis.com belongs to the data labeling Dataset." + }, + "datasetDisplayName": { + "description": "The Dataset's display name in datalabeling.googleapis.com.", + "type": "string" + }, + "dataset": { + "type": "string", + "description": "Full resource name of data labeling Dataset. Format: `projects/{project}/datasets/{dataset}`." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1MigratableResourceDataLabelingDataset" + }, + "GoogleCloudAiplatformV1beta1DirectRawPredictRequest": { + "properties": { + "input": { + "description": "The prediction input.", + "format": "byte", + "type": "string" + }, + "methodName": { + "description": "Fully qualified name of the API method being invoked to perform predictions. Format: `/namespace.Service/Method/` Example: `/tensorflow.serving.PredictionService/Predict`", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1DirectRawPredictRequest", + "description": "Request message for PredictionService.DirectRawPredict.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1MetadataStoreMetadataStoreState": { + "properties": { + "diskUtilizationBytes": { + "format": "int64", + "type": "string", + "description": "The disk utilization of the MetadataStore in bytes." + } + }, + "id": "GoogleCloudAiplatformV1beta1MetadataStoreMetadataStoreState", + "type": "object", + "description": "Represents state information for a MetadataStore." + }, + "GoogleCloudAiplatformV1beta1SearchModelMonitoringAlertsResponse": { + "type": "object", + "properties": { + "totalNumberAlerts": { + "description": "The total number of alerts retrieved by the requested objectives.", + "type": "string", + "format": "int64" + }, + "modelMonitoringAlerts": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlert" + }, + "type": "array", + "description": "Alerts retrieved for the requested objectives. Sorted by alert time descendingly." + }, + "nextPageToken": { + "description": "The page token that can be used by the next ModelMonitoringService.SearchModelMonitoringAlerts call.", + "type": "string" + } + }, + "description": "Response message for ModelMonitoringService.SearchModelMonitoringAlerts.", + "id": "GoogleCloudAiplatformV1beta1SearchModelMonitoringAlertsResponse" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecasting": { + "type": "object", + "description": "A TrainingJob that trains and uploads an AutoML Forecasting Model.", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecasting", + "properties": { + "metadata": { + "description": "The metadata information.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingMetadata" + }, + "inputs": { + "description": "The input parameters of this TrainingJob.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputs" + } + } + }, + "GoogleCloudAiplatformV1beta1QuestionAnsweringQualityInput": { + "type": "object", + "properties": { + "instance": { + "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringQualityInstance", + "description": "Required. Question answering quality instance." + }, + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringQualitySpec", + "description": "Required. Spec for question answering quality score metric." + } + }, + "description": "Input for question answering quality metric.", + "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringQualityInput" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningTask": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningTask", + "description": "A TrainingJob that tunes Hypererparameters of a custom code Model.", + "type": "object", + "properties": { + "metadata": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningJobMetadata", + "description": "The metadata information." + }, + "inputs": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningJobSpec", + "description": "The input parameters of this HyperparameterTuningTask." + } + } + }, + "GoogleCloudAiplatformV1beta1WriteTensorboardExperimentDataResponse": { + "properties": {}, + "description": "Response message for TensorboardService.WriteTensorboardExperimentData.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1WriteTensorboardExperimentDataResponse" + }, + "GoogleCloudAiplatformV1beta1PublisherModelParent": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1PublisherModelParent", + "properties": { + "displayName": { + "description": "Required. The display name of the parent. E.g., LaMDA, T5, Vision API, Natural Language API.", + "type": "string" + }, + "reference": { + "$ref": "GoogleCloudAiplatformV1beta1PublisherModelResourceReference", + "description": "Optional. The Google Cloud resource name or the URI reference." + } + }, + "description": "The information about the parent of a model." + }, + "GoogleCloudAiplatformV1beta1DirectPredictResponse": { + "type": "object", + "properties": { + "parameters": { + "$ref": "GoogleCloudAiplatformV1beta1Tensor", + "description": "The parameters that govern the prediction." + }, + "outputs": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Tensor" + }, + "type": "array", + "description": "The prediction output." + } + }, + "id": "GoogleCloudAiplatformV1beta1DirectPredictResponse", + "description": "Response message for PredictionService.DirectPredict." + }, + "GoogleCloudAiplatformV1beta1UpdateSpecialistPoolOperationMetadata": { + "type": "object", + "description": "Runtime operation metadata for SpecialistPoolService.UpdateSpecialistPool.", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "The operation generic information." + }, + "specialistPool": { + "type": "string", + "readOnly": true, + "description": "Output only. The name of the SpecialistPool to which the specialists are being added. Format: `projects/{project_id}/locations/{location_id}/specialistPools/{specialist_pool}`" + } + }, + "id": "GoogleCloudAiplatformV1beta1UpdateSpecialistPoolOperationMetadata" + }, + "GoogleCloudAiplatformV1beta1SchemaVideoObjectTrackingAnnotation": { + "description": "Annotation details specific to video object tracking.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaVideoObjectTrackingAnnotation", + "properties": { + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that this Annotation pertains to." + }, + "xMax": { + "format": "double", + "description": "The rightmost coordinate of the bounding box.", + "type": "number" + }, + "yMin": { + "description": "The topmost coordinate of the bounding box.", + "format": "double", + "type": "number" + }, + "annotationSpecId": { + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", + "type": "string" + }, + "xMin": { + "description": "The leftmost coordinate of the bounding box.", + "type": "number", + "format": "double" + }, + "yMax": { + "type": "number", + "description": "The bottommost coordinate of the bounding box.", + "format": "double" + }, + "timeOffset": { + "description": "A time (frame) of a video to which this annotation pertains. Represented as the duration since the video's start.", + "type": "string", + "format": "google-duration" + }, + "instanceId": { + "format": "int64", + "type": "string", + "description": "The instance of the object, expressed as a positive integer. Used to track the same object across different frames." + } + } + }, + "GoogleCloudAiplatformV1beta1CancelPipelineJobRequest": { + "properties": {}, + "id": "GoogleCloudAiplatformV1beta1CancelPipelineJobRequest", + "type": "object", + "description": "Request message for PipelineService.CancelPipelineJob." + }, + "GoogleCloudAiplatformV1beta1ListBatchPredictionJobsResponse": { + "type": "object", + "properties": { + "nextPageToken": { + "description": "A token to retrieve the next page of results. Pass to ListBatchPredictionJobsRequest.page_token to obtain that page.", + "type": "string" + }, + "batchPredictionJobs": { + "description": "List of BatchPredictionJobs in the requested page.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJob" + } + } + }, + "description": "Response message for JobService.ListBatchPredictionJobs", + "id": "GoogleCloudAiplatformV1beta1ListBatchPredictionJobsResponse" + }, + "GoogleCloudAiplatformV1beta1RemoveContextChildrenRequest": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1RemoveContextChildrenRequest", + "properties": { + "childContexts": { + "type": "array", + "items": { + "type": "string" + }, + "description": "The resource names of the child Contexts." + } + }, + "description": "Request message for MetadataService.DeleteContextChildrenRequest." + }, + "GoogleCloudAiplatformV1beta1ExactMatchSpec": { + "id": "GoogleCloudAiplatformV1beta1ExactMatchSpec", + "type": "object", + "description": "Spec for exact match metric - returns 1 if prediction and reference exactly matches, otherwise 0.", + "properties": {} + }, + "GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponse": { + "id": "GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponse", + "type": "object", + "properties": { + "monthlyUsageData": { + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponsePerMonthUsageData" + }, + "type": "object", + "description": "Maps year-month (YYYYMM) string to per month usage data." + } + }, + "description": "Response message for TensorboardService.ReadTensorboardUsage." + }, + "GoogleCloudAiplatformV1beta1Measurement": { + "id": "GoogleCloudAiplatformV1beta1Measurement", + "description": "A message representing a Measurement of a Trial. A Measurement contains the Metrics got by executing a Trial using suggested hyperparameter values.", + "properties": { + "metrics": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1MeasurementMetric" + }, + "description": "Output only. A list of metrics got by evaluating the objective functions using suggested Parameter values.", + "type": "array", + "readOnly": true + }, + "elapsedDuration": { + "readOnly": true, + "type": "string", + "description": "Output only. Time that the Trial has been running at the point of this Measurement.", + "format": "google-duration" + }, + "stepCount": { + "type": "string", + "description": "Output only. The number of steps the machine learning model has been trained for. Must be non-negative.", + "readOnly": true, + "format": "int64" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ManualBatchTuningParameters": { + "description": "Manual batch tuning parameters.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ManualBatchTuningParameters", + "properties": { + "batchSize": { + "description": "Immutable. The number of the records (e.g. instances) of the operation given in each batch to a machine replica. Machine type, and size of a single record should be considered when setting this parameter, higher value speeds up the batch operation's execution, but too high value will result in a whole batch not fitting in a machine's memory, and the whole operation will fail. The default value is 64.", + "type": "integer", + "format": "int32" + } + } + }, + "GoogleCloudAiplatformV1beta1ExportFeatureValuesResponse": { + "id": "GoogleCloudAiplatformV1beta1ExportFeatureValuesResponse", + "description": "Response message for FeaturestoreService.ExportFeatureValues.", + "properties": {}, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FluencyResult": { + "properties": { + "explanation": { + "description": "Output only. Explanation for fluency score.", + "type": "string", + "readOnly": true + }, + "confidence": { + "readOnly": true, + "format": "float", + "type": "number", + "description": "Output only. Confidence for fluency score." + }, + "score": { + "type": "number", + "readOnly": true, + "format": "float", + "description": "Output only. Fluency score." + } + }, + "type": "object", + "description": "Spec for fluency result.", + "id": "GoogleCloudAiplatformV1beta1FluencyResult" + }, + "GoogleCloudAiplatformV1beta1SampleConfig": { + "id": "GoogleCloudAiplatformV1beta1SampleConfig", + "properties": { + "initialBatchSamplePercentage": { + "description": "The percentage of data needed to be labeled in the first batch.", + "format": "int32", + "type": "integer" + }, + "sampleStrategy": { + "description": "Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.", + "type": "string", + "enumDescriptions": [ + "Default will be treated as UNCERTAINTY.", + "Sample the most uncertain data to label." + ], + "enum": [ + "SAMPLE_STRATEGY_UNSPECIFIED", + "UNCERTAINTY" + ] + }, + "followingBatchSamplePercentage": { + "description": "The percentage of data needed to be labeled in each following batch (except the first batch).", + "type": "integer", + "format": "int32" + } + }, + "description": "Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec": { + "properties": { + "maxTrialCount": { + "description": "Required. The maximum number of Neural Architecture Search (NAS) trials to run.", + "type": "integer", + "format": "int32" + }, + "maxParallelTrialCount": { + "type": "integer", + "format": "int32", + "description": "Required. The maximum number of trials to run in parallel." + }, + "maxFailedTrialCount": { + "format": "int32", + "type": "integer", + "description": "The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails." + }, + "searchTrialJobSpec": { + "description": "Required. The spec of a search trial job. The same spec applies to all search trials.", + "$ref": "GoogleCloudAiplatformV1beta1CustomJobSpec" + } + }, + "description": "Represent spec for search trials.", + "id": "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ListRagFilesResponse": { + "description": "Response message for VertexRagDataService.ListRagFiles.", + "type": "object", + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token to retrieve the next page of results. Pass to ListRagFilesRequest.page_token to obtain that page." + }, + "ragFiles": { + "description": "List of RagFiles in the requested page.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1RagFile" + } + } + }, + "id": "GoogleCloudAiplatformV1beta1ListRagFilesResponse" + }, + "GoogleCloudAiplatformV1beta1EntityType": { + "id": "GoogleCloudAiplatformV1beta1EntityType", + "description": "An entity type is a type of object in a system that needs to be modeled and have stored information about. For example, driver is an entity type, and driver0 is an instance of an entity type driver.", + "type": "object", + "properties": { + "etag": { + "description": "Optional. Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "createTime": { + "type": "string", + "description": "Output only. Timestamp when this EntityType was created.", + "format": "google-datetime", + "readOnly": true + }, + "monitoringConfig": { + "$ref": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfig", + "description": "Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled." + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." + }, + "description": { + "description": "Optional. Description of the EntityType.", + "type": "string" + }, + "offlineStorageTtlDays": { + "type": "integer", + "format": "int32", + "description": "Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than `offline_storage_ttl_days` since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL." + }, + "name": { + "description": "Immutable. Name of the EntityType. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.", + "type": "string" + }, + "updateTime": { + "type": "string", + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Timestamp when this EntityType was most recently updated." + } + } + }, + "GoogleCloudAiplatformV1beta1PredictResponse": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1PredictResponse", + "properties": { + "modelDisplayName": { + "readOnly": true, + "description": "Output only. The display name of the Model which is deployed as the DeployedModel that this prediction hits.", + "type": "string" + }, + "model": { + "type": "string", + "readOnly": true, + "description": "Output only. The resource name of the Model which is deployed as the DeployedModel that this prediction hits." + }, + "deployedModelId": { + "type": "string", + "description": "ID of the Endpoint's DeployedModel that served this prediction." + }, + "metadata": { + "readOnly": true, + "type": "any", + "description": "Output only. Request-level metadata returned by the model. The metadata type will be dependent upon the model implementation." + }, + "predictions": { + "description": "The predictions that are the output of the predictions call. The schema of any single prediction may be specified via Endpoint's DeployedModels' Model's PredictSchemata's prediction_schema_uri.", + "items": { + "type": "any" + }, + "type": "array" + }, + "modelVersionId": { + "readOnly": true, + "type": "string", + "description": "Output only. The version ID of the Model which is deployed as the DeployedModel that this prediction hits." + } + }, + "description": "Response message for PredictionService.Predict." + }, + "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfig": { + "id": "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfig", + "description": "Config for the embedding model to use for RAG.", + "properties": { + "vertexPredictionEndpoint": { + "$ref": "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigVertexPredictionEndpoint", + "description": "The Vertex AI Prediction Endpoint that either refers to a publisher model or an endpoint that is hosting a 1P fine-tuned text embedding model. Endpoints hosting non-1P fine-tuned text embedding models are currently not supported." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FractionSplit": { + "description": "Assigns the input data to training, validation, and test sets as per the given fractions. Any of `training_fraction`, `validation_fraction` and `test_fraction` may optionally be provided, they must sum to up to 1. If the provided ones sum to less than 1, the remainder is assigned to sets as decided by Vertex AI. If none of the fractions are set, by default roughly 80% of data is used for training, 10% for validation, and 10% for test.", + "properties": { + "validationFraction": { + "description": "The fraction of the input data that is to be used to validate the Model.", + "format": "double", + "type": "number" + }, + "testFraction": { + "type": "number", + "description": "The fraction of the input data that is to be used to evaluate the Model.", + "format": "double" + }, + "trainingFraction": { + "type": "number", + "format": "double", + "description": "The fraction of the input data that is to be used to train the Model." + } + }, + "id": "GoogleCloudAiplatformV1beta1FractionSplit", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringAlert": { + "description": "Represents a single monitoring alert. This is currently used in the SearchModelMonitoringAlerts api, thus the alert wrapped in this message belongs to the resource asked in the request.", + "properties": { + "anomaly": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAnomaly", + "description": "Anomaly details." + }, + "objectiveType": { + "type": "string", + "description": "One of the supported monitoring objectives: `raw-feature-drift` `prediction-output-drift` `feature-attribution`" + }, + "alertTime": { + "format": "google-datetime", + "description": "Alert creation time.", + "type": "string" + }, + "statsName": { + "type": "string", + "description": "The stats name." + } + }, + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringAlert", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1BatchDedicatedResources": { + "description": "A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration.", + "type": "object", + "properties": { + "machineSpec": { + "description": "Required. Immutable. The specification of a single machine.", + "$ref": "GoogleCloudAiplatformV1beta1MachineSpec" + }, + "startingReplicaCount": { + "format": "int32", + "type": "integer", + "description": "Immutable. The number of machine replicas used at the start of the batch operation. If not set, Vertex AI decides starting number, not greater than max_replica_count" + }, + "maxReplicaCount": { + "description": "Immutable. The maximum number of machine replicas the batch operation may be scaled to. The default value is 10.", + "format": "int32", + "type": "integer" + } + }, + "id": "GoogleCloudAiplatformV1beta1BatchDedicatedResources" + }, + "GoogleCloudAiplatformV1beta1CachedContent": { + "properties": { + "contents": { + "type": "array", + "description": "Optional. Input only. Immutable. The content to cache", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Content" + } + }, + "createTime": { + "type": "string", + "description": "Output only. Creatation time of the cache entry.", + "format": "google-datetime", + "readOnly": true + }, + "name": { + "type": "string", + "description": "Immutable. Identifier. The server-generated resource name of the cached content Format: projects/{project}/locations/{location}/cachedContents/{cached_content}" + }, + "displayName": { + "description": "Optional. Immutable. The user-generated meaningful display name of the cached content.", + "type": "string" + }, + "updateTime": { + "type": "string", + "description": "Output only. When the cache entry was last updated in UTC time.", + "format": "google-datetime", + "readOnly": true + }, + "systemInstruction": { + "$ref": "GoogleCloudAiplatformV1beta1Content", + "description": "Optional. Input only. Immutable. Developer set system instruction. Currently, text only" + }, + "tools": { + "description": "Optional. Input only. Immutable. A list of `Tools` the model may use to generate the next response", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Tool" + }, + "type": "array" + }, + "model": { + "description": "Immutable. The name of the publisher model to use for cached content. Format: projects/{project}/locations/{location}/publishers/{publisher}/models/{model}", + "type": "string" + }, + "toolConfig": { + "description": "Optional. Input only. Immutable. Tool config. This config is shared for all tools", + "$ref": "GoogleCloudAiplatformV1beta1ToolConfig" + }, + "expireTime": { + "type": "string", + "description": "Timestamp of when this resource is considered expired. This is *always* provided on output, regardless of what was sent on input.", + "format": "google-datetime" + }, + "ttl": { + "description": "Input only. The TTL for this resource. The expiration time is computed: now + TTL.", + "type": "string", + "format": "google-duration" + } + }, + "description": "A resource used in LLM queries for users to explicitly specify what to cache and how to cache.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1CachedContent" + }, + "GoogleCloudAiplatformV1beta1StudySpecMetricSpecSafetyMetricConfig": { + "id": "GoogleCloudAiplatformV1beta1StudySpecMetricSpecSafetyMetricConfig", + "type": "object", + "properties": { + "desiredMinSafeTrialsFraction": { + "format": "double", + "type": "number", + "description": "Desired minimum fraction of safe trials (over total number of trials) that should be targeted by the algorithm at any time during the study (best effort). This should be between 0.0 and 1.0 and a value of 0.0 means that there is no minimum and an algorithm proceeds without targeting any specific fraction. A value of 1.0 means that the algorithm attempts to only Suggest safe Trials." + }, + "safetyThreshold": { + "description": "Safety threshold (boundary value between safe and unsafe). NOTE that if you leave SafetyMetricConfig unset, a default value of 0 will be used.", + "type": "number", + "format": "double" + } + }, + "description": "Used in safe optimization to specify threshold levels and risk tolerance." + }, + "GoogleIamV1GetIamPolicyRequest": { + "id": "GoogleIamV1GetIamPolicyRequest", + "description": "Request message for `GetIamPolicy` method.", + "type": "object", + "properties": { + "options": { + "$ref": "GoogleIamV1GetPolicyOptions", + "description": "OPTIONAL: A `GetPolicyOptions` object for specifying options to `GetIamPolicy`." + } + } + }, + "GoogleCloudAiplatformV1beta1BigQuerySource": { + "type": "object", + "description": "The BigQuery location for the input content.", + "properties": { + "inputUri": { + "description": "Required. BigQuery URI to a table, up to 2000 characters long. Accepted forms: * BigQuery path. For example: `bq://projectId.bqDatasetId.bqTableId`.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1BigQuerySource" + }, + "GoogleCloudAiplatformV1beta1FeatureViewFeatureRegistrySource": { + "properties": { + "projectNumber": { + "format": "int64", + "description": "Optional. The project number of the parent project of the Feature Groups.", + "type": "string" + }, + "featureGroups": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureViewFeatureRegistrySourceFeatureGroup" + }, + "description": "Required. List of features that need to be synced to Online Store." + } + }, + "id": "GoogleCloudAiplatformV1beta1FeatureViewFeatureRegistrySource", + "type": "object", + "description": "A Feature Registry source for features that need to be synced to Online Store." + }, + "GoogleCloudAiplatformV1beta1UpdateExplanationDatasetResponse": { + "id": "GoogleCloudAiplatformV1beta1UpdateExplanationDatasetResponse", + "properties": {}, + "type": "object", + "description": "Response message of ModelService.UpdateExplanationDataset operation." + }, + "GoogleCloudAiplatformV1beta1UploadRagFileResponse": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1UploadRagFileResponse", + "description": "Response message for VertexRagDataService.UploadRagFile.", + "properties": { + "error": { + "description": "The error that occurred while processing the RagFile.", + "$ref": "GoogleRpcStatus" + }, + "ragFile": { + "$ref": "GoogleCloudAiplatformV1beta1RagFile", + "description": "The RagFile that had been uploaded into the RagCorpus." + } + } + }, + "GoogleCloudAiplatformV1beta1RougeInstance": { + "id": "GoogleCloudAiplatformV1beta1RougeInstance", + "properties": { + "reference": { + "description": "Required. Ground truth used to compare against the prediction.", + "type": "string" + }, + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + } + }, + "description": "Spec for rouge instance.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ExamplesRestrictionsNamespace": { + "description": "Restrictions namespace for example-based explanations overrides.", + "type": "object", + "properties": { + "deny": { + "items": { + "type": "string" + }, + "description": "The list of deny tags.", + "type": "array" + }, + "namespaceName": { + "type": "string", + "description": "The namespace name." + }, + "allow": { + "description": "The list of allowed tags.", + "type": "array", + "items": { + "type": "string" + } + } + }, + "id": "GoogleCloudAiplatformV1beta1ExamplesRestrictionsNamespace" + }, + "GoogleCloudAiplatformV1beta1BatchPredictionJobOutputInfo": { + "type": "object", + "properties": { + "bigqueryOutputTable": { + "readOnly": true, + "type": "string", + "description": "Output only. The name of the BigQuery table created, in `predictions_` format, into which the prediction output is written. Can be used by UI to generate the BigQuery output path, for example." + }, + "bigqueryOutputDataset": { + "type": "string", + "readOnly": true, + "description": "Output only. The path of the BigQuery dataset created, in `bq://projectId.bqDatasetId` format, into which the prediction output is written." + }, + "gcsOutputDirectory": { + "description": "Output only. The full path of the Cloud Storage directory created, into which the prediction output is written.", + "readOnly": true, + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1BatchPredictionJobOutputInfo", + "description": "Further describes this job's output. Supplements output_config." + }, + "GoogleCloudAiplatformV1beta1QueryExtensionRequest": { + "description": "Request message for ExtensionExecutionService.QueryExtension.", + "properties": { + "contents": { + "description": "Required. The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Content" + }, + "type": "array" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1QueryExtensionRequest" + }, + "GoogleCloudAiplatformV1beta1AuthConfigOidcConfig": { + "id": "GoogleCloudAiplatformV1beta1AuthConfigOidcConfig", + "description": "Config for user OIDC auth.", + "type": "object", + "properties": { + "idToken": { + "type": "string", + "description": "OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time." + }, + "serviceAccount": { + "type": "string", + "description": "The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents)." + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentationMetadata": { + "properties": { + "costMilliNodeHours": { + "format": "int64", + "description": "The actual training cost of creating this model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed inputs.budgetMilliNodeHours.", + "type": "string" + }, + "successfulStopReason": { + "description": "For successful job completions, this is the reason why the job has finished.", + "enum": [ + "SUCCESSFUL_STOP_REASON_UNSPECIFIED", + "BUDGET_REACHED", + "MODEL_CONVERGED" + ], + "enumDescriptions": [ + "Should not be set.", + "The inputs.budgetMilliNodeHours had been reached.", + "Further training of the Model ceased to increase its quality, since it already has converged." + ], + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentationMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1GenerateAccessTokenRequest": { + "description": "Request message for NotebookInternalService.GenerateAccessToken.", + "properties": { + "vmToken": { + "description": "Required. The VM identity token (a JWT) for authenticating the VM. https://cloud.google.com/compute/docs/instances/verifying-instance-identity", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1GenerateAccessTokenRequest", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTimestampTransformation": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTimestampTransformation", + "type": "object", + "description": "Training pipeline will perform following transformation functions. * Apply the transformation functions for Numerical columns. * Determine the year, month, day,and weekday. Treat each value from the timestamp as a Categorical column. * Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed.", + "properties": { + "timeFormat": { + "type": "string", + "description": "The format in which that time field is expressed. The time_format must either be one of: * `unix-seconds` * `unix-milliseconds` * `unix-microseconds` * `unix-nanoseconds` (for respectively number of seconds, milliseconds, microseconds and nanoseconds since start of the Unix epoch); or be written in `strftime` syntax. If time_format is not set, then the default format is RFC 3339 `date-time` format, where `time-offset` = `\"Z\"` (e.g. 1985-04-12T23:20:50.52Z)" + }, + "columnName": { + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1PurgeContextsMetadata": { + "description": "Details of operations that perform MetadataService.PurgeContexts.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1PurgeContextsMetadata", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "Operation metadata for purging Contexts." + } + } + }, + "GoogleCloudAiplatformV1beta1SummarizationVerbosityResult": { + "description": "Spec for summarization verbosity result.", + "type": "object", + "properties": { + "confidence": { + "format": "float", + "type": "number", + "readOnly": true, + "description": "Output only. Confidence for summarization verbosity score." + }, + "explanation": { + "type": "string", + "readOnly": true, + "description": "Output only. Explanation for summarization verbosity score." + }, + "score": { + "readOnly": true, + "type": "number", + "format": "float", + "description": "Output only. Summarization Verbosity score." + } + }, + "id": "GoogleCloudAiplatformV1beta1SummarizationVerbosityResult" + }, + "GoogleCloudAiplatformV1beta1ResourcesConsumed": { + "description": "Statistics information about resource consumption.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ResourcesConsumed", + "properties": { + "replicaHours": { + "description": "Output only. The number of replica hours used. Note that many replicas may run in parallel, and additionally any given work may be queued for some time. Therefore this value is not strictly related to wall time.", + "type": "number", + "format": "double", + "readOnly": true + } + } + }, + "GoogleCloudAiplatformV1beta1AuthConfigGoogleServiceAccountConfig": { + "description": "Config for Google Service Account Authentication.", + "id": "GoogleCloudAiplatformV1beta1AuthConfigGoogleServiceAccountConfig", + "properties": { + "serviceAccount": { + "type": "string", + "description": "Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1TrainingPipeline": { + "id": "GoogleCloudAiplatformV1beta1TrainingPipeline", + "description": "The TrainingPipeline orchestrates tasks associated with training a Model. It always executes the training task, and optionally may also export data from Vertex AI's Dataset which becomes the training input, upload the Model to Vertex AI, and evaluate the Model.", + "properties": { + "name": { + "type": "string", + "readOnly": true, + "description": "Output only. Resource name of the TrainingPipeline." + }, + "displayName": { + "type": "string", + "description": "Required. The user-defined name of this TrainingPipeline." + }, + "modelId": { + "description": "Optional. The ID to use for the uploaded Model, which will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen.", + "type": "string" + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", + "description": "Customer-managed encryption key spec for a TrainingPipeline. If set, this TrainingPipeline will be secured by this key. Note: Model trained by this TrainingPipeline is also secured by this key if model_to_upload is not set separately." + }, + "trainingTaskDefinition": { + "description": "Required. A Google Cloud Storage path to the YAML file that defines the training task which is responsible for producing the model artifact, and may also include additional auxiliary work. The definition files that can be used here are found in gs://google-cloud-aiplatform/schema/trainingjob/definition/. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.", + "type": "string" + }, + "error": { + "$ref": "GoogleRpcStatus", + "readOnly": true, + "description": "Output only. Only populated when the pipeline's state is `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`." + }, + "trainingTaskMetadata": { + "type": "any", + "description": "Output only. The metadata information as specified in the training_task_definition's `metadata`. This metadata is an auxiliary runtime and final information about the training task. While the pipeline is running this information is populated only at a best effort basis. Only present if the pipeline's training_task_definition contains `metadata` object.", + "readOnly": true + }, + "endTime": { + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Time when the TrainingPipeline entered any of the following states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`, `PIPELINE_STATE_CANCELLED`.", + "type": "string" + }, + "modelToUpload": { + "description": "Describes the Model that may be uploaded (via ModelService.UploadModel) by this TrainingPipeline. The TrainingPipeline's training_task_definition should make clear whether this Model description should be populated, and if there are any special requirements regarding how it should be filled. If nothing is mentioned in the training_task_definition, then it should be assumed that this field should not be filled and the training task either uploads the Model without a need of this information, or that training task does not support uploading a Model as part of the pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and the trained Model had been uploaded into Vertex AI, then the model_to_upload's resource name is populated. The Model is always uploaded into the Project and Location in which this pipeline is.", + "$ref": "GoogleCloudAiplatformV1beta1Model" + }, + "createTime": { + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Time when the TrainingPipeline was created.", + "type": "string" + }, + "labels": { + "type": "object", + "description": "The labels with user-defined metadata to organize TrainingPipelines. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", + "additionalProperties": { + "type": "string" + } + }, + "parentModel": { + "type": "string", + "description": "Optional. When specify this field, the `model_to_upload` will not be uploaded as a new model, instead, it will become a new version of this `parent_model`." + }, + "trainingTaskInputs": { + "type": "any", + "description": "Required. The training task's parameter(s), as specified in the training_task_definition's `inputs`." + }, + "updateTime": { + "format": "google-datetime", + "readOnly": true, + "type": "string", + "description": "Output only. Time when the TrainingPipeline was most recently updated." + }, + "state": { + "description": "Output only. The detailed state of the pipeline.", + "readOnly": true, + "enumDescriptions": [ + "The pipeline state is unspecified.", + "The pipeline has been created or resumed, and processing has not yet begun.", + "The service is preparing to run the pipeline.", + "The pipeline is in progress.", + "The pipeline completed successfully.", + "The pipeline failed.", + "The pipeline is being cancelled. From this state, the pipeline may only go to either PIPELINE_STATE_SUCCEEDED, PIPELINE_STATE_FAILED or PIPELINE_STATE_CANCELLED.", + "The pipeline has been cancelled.", + "The pipeline has been stopped, and can be resumed." + ], + "type": "string", + "enum": [ + "PIPELINE_STATE_UNSPECIFIED", + "PIPELINE_STATE_QUEUED", + "PIPELINE_STATE_PENDING", + "PIPELINE_STATE_RUNNING", + "PIPELINE_STATE_SUCCEEDED", + "PIPELINE_STATE_FAILED", + "PIPELINE_STATE_CANCELLING", + "PIPELINE_STATE_CANCELLED", + "PIPELINE_STATE_PAUSED" + ] + }, + "startTime": { + "description": "Output only. Time when the TrainingPipeline for the first time entered the `PIPELINE_STATE_RUNNING` state.", + "format": "google-datetime", + "type": "string", + "readOnly": true + }, + "inputDataConfig": { + "description": "Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's training_task_definition should make clear whether this config is used and if there are any special requirements on how it should be filled. If nothing about this config is mentioned in the training_task_definition, then it should be assumed that the TrainingPipeline does not depend on this configuration.", + "$ref": "GoogleCloudAiplatformV1beta1InputDataConfig" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ExamplesOverride": { + "id": "GoogleCloudAiplatformV1beta1ExamplesOverride", + "properties": { + "dataFormat": { + "type": "string", + "enumDescriptions": [ + "Unspecified format. Must not be used.", + "Provided data is a set of model inputs.", + "Provided data is a set of embeddings." + ], + "description": "The format of the data being provided with each call.", + "enum": [ + "DATA_FORMAT_UNSPECIFIED", + "INSTANCES", + "EMBEDDINGS" + ] + }, + "returnEmbeddings": { + "type": "boolean", + "description": "If true, return the embeddings instead of neighbors." + }, + "restrictions": { + "type": "array", + "description": "Restrict the resulting nearest neighbors to respect these constraints.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ExamplesRestrictionsNamespace" + } + }, + "neighborCount": { + "description": "The number of neighbors to return.", + "type": "integer", + "format": "int32" + }, + "crowdingCount": { + "type": "integer", + "description": "The number of neighbors to return that have the same crowding tag.", + "format": "int32" + } + }, + "description": "Overrides for example-based explanations.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetrics": { + "properties": { + "iouThreshold": { + "description": "The intersection-over-union threshold value used to compute this metrics entry.", + "format": "float", + "type": "number" + }, + "meanAveragePrecision": { + "format": "float", + "description": "The mean average precision, most often close to `auPrc`.", + "type": "number" + }, + "confidenceMetrics": { + "description": "Metrics for each label-match confidence_threshold from 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is derived from them.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetricsConfidenceMetrics" + } + } + }, + "description": "Bounding box matching model metrics for a single intersection-over-union threshold and multiple label match confidence thresholds.", + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetrics", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1CreateTensorboardRunRequest": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1CreateTensorboardRunRequest", + "description": "Request message for TensorboardService.CreateTensorboardRun.", + "properties": { + "parent": { + "type": "string", + "description": "Required. The resource name of the TensorboardExperiment to create the TensorboardRun in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`" + }, + "tensorboardRun": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardRun", + "description": "Required. The TensorboardRun to create." + }, + "tensorboardRunId": { + "description": "Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequestSelectTimeRangeAndFeature": { + "description": "Message to select time range and feature. Values of the selected feature generated within an inclusive time range will be deleted. Using this option permanently deletes the feature values from the specified feature IDs within the specified time range. This might include data from the online storage. If you want to retain any deleted historical data in the online storage, you must re-ingest it.", + "id": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequestSelectTimeRangeAndFeature", + "type": "object", + "properties": { + "timeRange": { + "description": "Required. Select feature generated within a half-inclusive time range. The time range is lower inclusive and upper exclusive.", + "$ref": "GoogleTypeInterval" + }, + "featureSelector": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureSelector", + "description": "Required. Selectors choosing which feature values to be deleted from the EntityType." + }, + "skipOnlineStorageDelete": { + "type": "boolean", + "description": "If set, data will not be deleted from online storage. When time range is older than the data in online storage, setting this to be true will make the deletion have no impact on online serving." + } + } + }, + "GoogleCloudAiplatformV1beta1Feature": { + "id": "GoogleCloudAiplatformV1beta1Feature", + "description": "Feature Metadata information. For example, color is a feature that describes an apple.", + "properties": { + "versionColumnName": { + "type": "string", + "description": "Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View column hosting data for this version. If no value is provided, will use feature_id." + }, + "pointOfContact": { + "description": "Entity responsible for maintaining this feature. Can be comma separated list of email addresses or URIs.", + "type": "string" + }, + "monitoringStats": { + "description": "Output only. Only applicable for Vertex AI Feature Store (Legacy). A list of historical SnapshotAnalysis stats requested by user, sorted by FeatureStatsAnomaly.start_time descending.", + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureStatsAnomaly" + }, + "type": "array" + }, + "valueType": { + "enum": [ + "VALUE_TYPE_UNSPECIFIED", + "BOOL", + "BOOL_ARRAY", + "DOUBLE", + "DOUBLE_ARRAY", + "INT64", + "INT64_ARRAY", + "STRING", + "STRING_ARRAY", + "BYTES", + "STRUCT" + ], + "enumDescriptions": [ + "The value type is unspecified.", + "Used for Feature that is a boolean.", + "Used for Feature that is a list of boolean.", + "Used for Feature that is double.", + "Used for Feature that is a list of double.", + "Used for Feature that is INT64.", + "Used for Feature that is a list of INT64.", + "Used for Feature that is string.", + "Used for Feature that is a list of String.", + "Used for Feature that is bytes.", + "Used for Feature that is struct." + ], + "type": "string", + "description": "Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value." + }, + "name": { + "description": "Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.", + "type": "string" + }, + "monitoringStatsAnomalies": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureMonitoringStatsAnomaly" + }, + "description": "Output only. Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.", + "readOnly": true, + "type": "array" + }, + "updateTime": { + "format": "google-datetime", + "description": "Output only. Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.", + "type": "string", + "readOnly": true + }, + "etag": { + "type": "string", + "description": "Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + }, + "disableMonitoring": { + "type": "boolean", + "description": "Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType." + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "description": "Optional. The labels with user-defined metadata to organize your Features. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", + "type": "object" + }, + "description": { + "type": "string", + "description": "Description of the Feature." + }, + "createTime": { + "type": "string", + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created." + }, + "monitoringConfig": { + "deprecated": true, + "description": "Optional. Only applicable for Vertex AI Feature Store (Legacy). Deprecated: The custom monitoring configuration for this Feature, if not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If this is populated with FeaturestoreMonitoringConfig.disabled = true, snapshot analysis monitoring is disabled; if FeaturestoreMonitoringConfig.monitoring_interval specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring config is same as the EntityType's this Feature belongs to.", + "$ref": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfig" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaVisualInspectionMaskSavedQueryMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaVisualInspectionMaskSavedQueryMetadata", + "properties": {} + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionWindowConfig": { + "description": "Config that contains the strategy used to generate sliding windows in time series training. A window is a series of rows that comprise the context up to the time of prediction, and the horizon following. The corresponding row for each window marks the start of the forecast horizon. Each window is used as an input example for training/evaluation.", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionWindowConfig", + "type": "object", + "properties": { + "strideLength": { + "description": "Stride length used to generate input examples. Within one time series, every {$STRIDE_LENGTH} rows will be used to generate a sliding window.", + "format": "int64", + "type": "string" + }, + "maxCount": { + "type": "string", + "description": "Maximum number of windows that should be generated across all time series.", + "format": "int64" + }, + "column": { + "type": "string", + "description": "Name of the column that should be used to generate sliding windows. The column should contain either booleans or string booleans; if the value of the row is True, generate a sliding window with the horizon starting at that row. The column will not be used as a feature in training." + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaPredictionResult": { + "id": "GoogleCloudAiplatformV1beta1SchemaPredictionResult", + "properties": { + "error": { + "description": "The error result. Do not set prediction if this is set.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaPredictionResultError" + }, + "key": { + "description": "Optional user-provided key from the input instance.", + "type": "string" + }, + "instance": { + "description": "User's input instance. Struct is used here instead of Any so that JsonFormat does not append an extra \"@type\" field when we convert the proto to JSON.", + "type": "object", + "additionalProperties": { + "description": "Properties of the object.", + "type": "any" + } + }, + "prediction": { + "type": "any", + "description": "The prediction result. Value is used here instead of Any so that JsonFormat does not append an extra \"@type\" field when we convert the proto to JSON and so we can represent array of objects. Do not set error if this is set." + } + }, + "type": "object", + "description": "Represents a line of JSONL in the batch prediction output file." + }, + "GoogleCloudAiplatformV1beta1FilterSplit": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1FilterSplit", + "properties": { + "trainingFilter": { + "type": "string", + "description": "Required. A filter on DataItems of the Dataset. DataItems that match this filter are used to train the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order." + }, + "validationFilter": { + "type": "string", + "description": "Required. A filter on DataItems of the Dataset. DataItems that match this filter are used to validate the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order." + }, + "testFilter": { + "description": "Required. A filter on DataItems of the Dataset. DataItems that match this filter are used to test the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.", + "type": "string" + } + }, + "description": "Assigns input data to training, validation, and test sets based on the given filters, data pieces not matched by any filter are ignored. Currently only supported for Datasets containing DataItems. If any of the filters in this message are to match nothing, then they can be set as '-' (the minus sign). Supported only for unstructured Datasets. " + }, + "GoogleCloudAiplatformV1beta1BigQueryDestination": { + "description": "The BigQuery location for the output content.", + "id": "GoogleCloudAiplatformV1beta1BigQueryDestination", + "type": "object", + "properties": { + "outputUri": { + "type": "string", + "description": "Required. BigQuery URI to a project or table, up to 2000 characters long. When only the project is specified, the Dataset and Table is created. When the full table reference is specified, the Dataset must exist and table must not exist. Accepted forms: * BigQuery path. For example: `bq://projectId` or `bq://projectId.bqDatasetId` or `bq://projectId.bqDatasetId.bqTableId`." + } + } + }, + "GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtable": { + "properties": { + "autoScaling": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtableAutoScaling", + "description": "Required. Autoscaling config applied to Bigtable Instance." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtable" + }, + "GoogleCloudAiplatformV1beta1SearchNearestEntitiesResponse": { + "type": "object", + "description": "Response message for FeatureOnlineStoreService.SearchNearestEntities", + "id": "GoogleCloudAiplatformV1beta1SearchNearestEntitiesResponse", + "properties": { + "nearestNeighbors": { + "description": "The nearest neighbors of the query entity.", + "$ref": "GoogleCloudAiplatformV1beta1NearestNeighbors" + } + } + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringInputTimeOffset": { + "properties": { + "window": { + "description": "[window] refers to the scope of data selected for analysis. It allows you to specify the quantity of data you wish to examine. Currently we support the following format: 'w|W': Week, 'd|D': Day, 'h|H': Hour E.g. '1h' stands for 1 hour, '2d' stands for 2 days.", + "type": "string" + }, + "offset": { + "type": "string", + "description": "[offset] is the time difference from the cut-off time. For scheduled jobs, the cut-off time is the scheduled time. For non-scheduled jobs, it's the time when the job was created. Currently we support the following format: 'w|W': Week, 'd|D': Day, 'h|H': Hour E.g. '1h' stands for 1 hour, '2d' stands for 2 days." + } + }, + "type": "object", + "description": "Time offset setting.", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringInputTimeOffset" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics": { + "properties": { + "confusionMatrix": { + "description": "Confusion matrix of the evaluation. Only set for ModelEvaluations, not for ModelEvaluationSlices.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix" + }, + "meanSquaredError": { + "description": "Mean squared error. Only set for ModelEvaluations, not for ModelEvaluationSlices.", + "type": "number", + "format": "float" + }, + "linearKappa": { + "description": "Linear weighted kappa. Only set for ModelEvaluations, not for ModelEvaluationSlices.", + "type": "number", + "format": "float" + }, + "recall": { + "description": "Recall.", + "format": "float", + "type": "number" + }, + "f1Score": { + "description": "The harmonic mean of recall and precision.", + "type": "number", + "format": "float" + }, + "quadraticKappa": { + "format": "float", + "description": "Quadratic weighted kappa. Only set for ModelEvaluations, not for ModelEvaluationSlices.", + "type": "number" + }, + "precision": { + "type": "number", + "format": "float", + "description": "Precision." + }, + "meanAbsoluteError": { + "description": "Mean absolute error. Only set for ModelEvaluations, not for ModelEvaluationSlices.", + "type": "number", + "format": "float" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics", + "type": "object", + "description": "Model evaluation metrics for text sentiment problems." + }, + "GoogleCloudAiplatformV1beta1EntityIdSelector": { + "properties": { + "entityIdField": { + "type": "string", + "description": "Source column that holds entity IDs. If not provided, entity IDs are extracted from the column named entity_id." + }, + "csvSource": { + "$ref": "GoogleCloudAiplatformV1beta1CsvSource", + "description": "Source of Csv" + } + }, + "description": "Selector for entityId. Getting ids from the given source.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1EntityIdSelector" + }, + "GoogleCloudAiplatformV1beta1PipelineTaskDetail": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1PipelineTaskDetail", + "description": "The runtime detail of a task execution.", + "properties": { + "outputs": { + "description": "Output only. The runtime output artifacts of the task.", + "readOnly": true, + "type": "object", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1PipelineTaskDetailArtifactList" + } + }, + "startTime": { + "format": "google-datetime", + "type": "string", + "description": "Output only. Task start time.", + "readOnly": true + }, + "state": { + "type": "string", + "description": "Output only. State of the task.", + "enum": [ + "STATE_UNSPECIFIED", + "PENDING", + "RUNNING", + "SUCCEEDED", + "CANCEL_PENDING", + "CANCELLING", + "CANCELLED", + "FAILED", + "SKIPPED", + "NOT_TRIGGERED" + ], + "readOnly": true, + "enumDescriptions": [ + "Unspecified.", + "Specifies pending state for the task.", + "Specifies task is being executed.", + "Specifies task completed successfully.", + "Specifies Task cancel is in pending state.", + "Specifies task is being cancelled.", + "Specifies task was cancelled.", + "Specifies task failed.", + "Specifies task was skipped due to cache hit.", + "Specifies that the task was not triggered because the task's trigger policy is not satisfied. The trigger policy is specified in the `condition` field of PipelineJob.pipeline_spec." + ] + }, + "taskName": { + "type": "string", + "description": "Output only. The user specified name of the task that is defined in pipeline_spec.", + "readOnly": true + }, + "inputs": { + "type": "object", + "description": "Output only. The runtime input artifacts of the task.", + "readOnly": true, + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1PipelineTaskDetailArtifactList" + } + }, + "taskId": { + "type": "string", + "description": "Output only. The system generated ID of the task.", + "format": "int64", + "readOnly": true + }, + "executorDetail": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetail", + "description": "Output only. The detailed execution info." + }, + "error": { + "$ref": "GoogleRpcStatus", + "readOnly": true, + "description": "Output only. The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED." + }, + "execution": { + "readOnly": true, + "description": "Output only. The execution metadata of the task.", + "$ref": "GoogleCloudAiplatformV1beta1Execution" + }, + "pipelineTaskStatus": { + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1beta1PipelineTaskDetailPipelineTaskStatus" + }, + "description": "Output only. A list of task status. This field keeps a record of task status evolving over time.", + "type": "array" + }, + "endTime": { + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Task end time.", + "type": "string" + }, + "parentTaskId": { + "readOnly": true, + "format": "int64", + "description": "Output only. The id of the parent task if the task is within a component scope. Empty if the task is at the root level.", + "type": "string" + }, + "createTime": { + "format": "google-datetime", + "description": "Output only. Task create time.", + "type": "string", + "readOnly": true + } + } + }, + "GoogleCloudAiplatformV1beta1PipelineJobDetail": { + "id": "GoogleCloudAiplatformV1beta1PipelineJobDetail", + "description": "The runtime detail of PipelineJob.", + "type": "object", + "properties": { + "pipelineRunContext": { + "description": "Output only. The context of the current pipeline run.", + "$ref": "GoogleCloudAiplatformV1beta1Context", + "readOnly": true + }, + "taskDetails": { + "description": "Output only. The runtime details of the tasks under the pipeline.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1PipelineTaskDetail" + }, + "readOnly": true, + "type": "array" + }, + "pipelineContext": { + "$ref": "GoogleCloudAiplatformV1beta1Context", + "description": "Output only. The context of the pipeline.", + "readOnly": true + } + } + }, + "GoogleCloudAiplatformV1beta1ExplanationMetadataOverrideInputMetadataOverride": { + "description": "The input metadata entries to be overridden.", + "id": "GoogleCloudAiplatformV1beta1ExplanationMetadataOverrideInputMetadataOverride", + "properties": { + "inputBaselines": { + "description": "Baseline inputs for this feature. This overrides the `input_baseline` field of the ExplanationMetadata.InputMetadata object of the corresponding feature's input metadata. If it's not specified, the original baselines are not overridden.", + "items": { + "type": "any" + }, + "type": "array" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SummarizationVerbositySpec": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SummarizationVerbositySpec", + "properties": { + "version": { + "type": "integer", + "description": "Optional. Which version to use for evaluation.", + "format": "int32" + }, + "useReference": { + "description": "Optional. Whether to use instance.reference to compute summarization verbosity.", + "type": "boolean" + } + }, + "description": "Spec for summarization verbosity score metric." + }, + "GoogleCloudAiplatformV1beta1StreamingFetchFeatureValuesRequest": { + "description": "Request message for FeatureOnlineStoreService.StreamingFetchFeatureValues. For the entities requested, all features under the requested feature view will be returned.", + "id": "GoogleCloudAiplatformV1beta1StreamingFetchFeatureValuesRequest", + "properties": { + "dataFormat": { + "type": "string", + "enum": [ + "FEATURE_VIEW_DATA_FORMAT_UNSPECIFIED", + "KEY_VALUE", + "PROTO_STRUCT" + ], + "description": "Specify response data format. If not set, KeyValue format will be used.", + "enumDescriptions": [ + "Not set. Will be treated as the KeyValue format.", + "Return response data in key-value format.", + "Return response data in proto Struct format." + ] + }, + "dataKeys": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDataKey" + } + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1GcsDestination": { + "description": "The Google Cloud Storage location where the output is to be written to.", + "properties": { + "outputUriPrefix": { + "type": "string", + "description": "Required. Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1GcsDestination" + }, + "GoogleCloudAiplatformV1beta1FeatureValueList": { + "id": "GoogleCloudAiplatformV1beta1FeatureValueList", + "type": "object", + "properties": { + "values": { + "description": "A list of feature values. All of them should be the same data type.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureValue" + } + } + }, + "description": "Container for list of values." + }, + "GoogleCloudAiplatformV1beta1ListPipelineJobsResponse": { + "id": "GoogleCloudAiplatformV1beta1ListPipelineJobsResponse", + "description": "Response message for PipelineService.ListPipelineJobs", + "type": "object", + "properties": { + "nextPageToken": { + "description": "A token to retrieve the next page of results. Pass to ListPipelineJobsRequest.page_token to obtain that page.", + "type": "string" + }, + "pipelineJobs": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1PipelineJob" + }, + "type": "array", + "description": "List of PipelineJobs in the requested page." + } + } + }, + "GoogleCloudAiplatformV1beta1ListTuningJobsResponse": { + "type": "object", + "properties": { + "nextPageToken": { + "description": "A token to retrieve the next page of results. Pass to ListTuningJobsRequest.page_token to obtain that page.", + "type": "string" + }, + "tuningJobs": { + "type": "array", + "description": "List of TuningJobs in the requested page.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1TuningJob" + } + } + }, + "id": "GoogleCloudAiplatformV1beta1ListTuningJobsResponse", + "description": "Response message for GenAiTuningService.ListTuningJobs" + }, + "GoogleCloudAiplatformV1beta1ReasoningEngineSpecPackageSpec": { + "properties": { + "pickleObjectGcsUri": { + "type": "string", + "description": "Optional. The Cloud Storage URI of the pickled python object." + }, + "requirementsGcsUri": { + "description": "Optional. The Cloud Storage URI of the `requirements.txt` file", + "type": "string" + }, + "dependencyFilesGcsUri": { + "description": "Optional. The Cloud Storage URI of the dependency files in tar.gz format.", + "type": "string" + }, + "pythonVersion": { + "type": "string", + "description": "Optional. The Python version. Currently support 3.8, 3.9, 3.10, 3.11. If not specified, default value is 3.10." + } + }, + "type": "object", + "description": "User provided package spec like pickled object and package requirements.", + "id": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecPackageSpec" + }, + "GoogleCloudAiplatformV1beta1GroundingMetadata": { + "id": "GoogleCloudAiplatformV1beta1GroundingMetadata", + "description": "Metadata returned to client when grounding is enabled.", + "type": "object", + "properties": { + "searchEntryPoint": { + "$ref": "GoogleCloudAiplatformV1beta1SearchEntryPoint", + "description": "Optional. Google search entry for the following-up web searches." + }, + "webSearchQueries": { + "description": "Optional. Web search queries for the following-up web search.", + "type": "array", + "items": { + "type": "string" + } + }, + "groundingSupports": { + "description": "Optional. List of grounding support.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1GroundingSupport" + } + }, + "groundingChunks": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1GroundingChunk" + }, + "description": "List of supporting references retrieved from specified grounding source." + }, + "retrievalQueries": { + "items": { + "type": "string" + }, + "description": "Optional. Queries executed by the retrieval tools.", + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaVideoClassificationAnnotation": { + "properties": { + "timeSegment": { + "description": "This Annotation applies to the time period represented by the TimeSegment. If it's not set, the Annotation applies to the whole video.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaTimeSegment" + }, + "annotationSpecId": { + "type": "string", + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." + }, + "displayName": { + "description": "The display name of the AnnotationSpec that this Annotation pertains to.", + "type": "string" + } + }, + "description": "Annotation details specific to video classification.", + "id": "GoogleCloudAiplatformV1beta1SchemaVideoClassificationAnnotation", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FeatureValueDestination": { + "properties": { + "tfrecordDestination": { + "$ref": "GoogleCloudAiplatformV1beta1TFRecordDestination", + "description": "Output in TFRecord format. Below are the mapping from Feature value type in Featurestore to Feature value type in TFRecord: Value type in Featurestore | Value type in TFRecord DOUBLE, DOUBLE_ARRAY | FLOAT_LIST INT64, INT64_ARRAY | INT64_LIST STRING, STRING_ARRAY, BYTES | BYTES_LIST true -\u003e byte_string(\"true\"), false -\u003e byte_string(\"false\") BOOL, BOOL_ARRAY (true, false) | BYTES_LIST" + }, + "csvDestination": { + "$ref": "GoogleCloudAiplatformV1beta1CsvDestination", + "description": "Output in CSV format. Array Feature value types are not allowed in CSV format." + }, + "bigqueryDestination": { + "$ref": "GoogleCloudAiplatformV1beta1BigQueryDestination", + "description": "Output in BigQuery format. BigQueryDestination.output_uri in FeatureValueDestination.bigquery_destination must refer to a table." + } + }, + "type": "object", + "description": "A destination location for Feature values and format.", + "id": "GoogleCloudAiplatformV1beta1FeatureValueDestination" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringInputBatchPredictionOutput": { + "properties": { + "batchPredictionJob": { + "type": "string", + "description": "Vertex AI Batch prediction job resource name. The job must match the model version specified in [ModelMonitor].[model_monitoring_target]." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringInputBatchPredictionOutput", + "description": "Data from Vertex AI Batch prediction job output." + }, + "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecIntValueCondition": { + "properties": { + "values": { + "type": "array", + "description": "Required. Matches values of the parent parameter of 'INTEGER' type. All values must lie in `integer_value_spec` of parent parameter.", + "items": { + "format": "int64", + "type": "string" + } + } + }, + "description": "Represents the spec to match integer values from parent parameter.", + "id": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecIntValueCondition", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1StudySpecParameterSpecCategoricalValueSpec": { + "id": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecCategoricalValueSpec", + "type": "object", + "properties": { + "defaultValue": { + "description": "A default value for a `CATEGORICAL` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.", + "type": "string" + }, + "values": { + "description": "Required. The list of possible categories.", + "type": "array", + "items": { + "type": "string" + } + } + }, + "description": "Value specification for a parameter in `CATEGORICAL` type." + }, + "GoogleCloudAiplatformV1beta1ListExtensionsResponse": { + "type": "object", + "description": "Response message for ExtensionRegistryService.ListExtensions", + "properties": { + "extensions": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Extension" + }, + "description": "List of Extension in the requested page.", + "type": "array" + }, + "nextPageToken": { + "type": "string", + "description": "A token to retrieve the next page of results. Pass to ListExtensionsRequest.page_token to obtain that page." + } + }, + "id": "GoogleCloudAiplatformV1beta1ListExtensionsResponse" + }, + "GoogleCloudAiplatformV1beta1ImportDataConfig": { + "id": "GoogleCloudAiplatformV1beta1ImportDataConfig", + "type": "object", + "properties": { + "gcsSource": { + "description": "The Google Cloud Storage location for the input content.", + "$ref": "GoogleCloudAiplatformV1beta1GcsSource" + }, + "importSchemaUri": { + "type": "string", + "description": "Required. Points to a YAML file stored on Google Cloud Storage describing the import format. Validation will be done against the schema. The schema is defined as an [OpenAPI 3.0.2 Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject)." + }, + "annotationLabels": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "Labels that will be applied to newly imported Annotations. If two Annotations are identical, one of them will be deduped. Two Annotations are considered identical if their payload, payload_schema_uri and all of their labels are the same. These labels will be overridden by Annotation labels specified inside index file referenced by import_schema_uri, e.g. jsonl file." + }, + "dataItemLabels": { + "description": "Labels that will be applied to newly imported DataItems. If an identical DataItem as one being imported already exists in the Dataset, then these labels will be appended to these of the already existing one, and if labels with identical key is imported before, the old label value will be overwritten. If two DataItems are identical in the same import data operation, the labels will be combined and if key collision happens in this case, one of the values will be picked randomly. Two DataItems are considered identical if their content bytes are identical (e.g. image bytes or pdf bytes). These labels will be overridden by Annotation labels specified inside index file referenced by import_schema_uri, e.g. jsonl file.", + "type": "object", + "additionalProperties": { + "type": "string" + } + } + }, + "description": "Describes the location from where we import data into a Dataset, together with the labels that will be applied to the DataItems and the Annotations." + }, + "GoogleCloudAiplatformV1beta1ExportModelRequestOutputConfig": { + "description": "Output configuration for the Model export.", + "properties": { + "imageDestination": { + "$ref": "GoogleCloudAiplatformV1beta1ContainerRegistryDestination", + "description": "The Google Container Registry or Artifact Registry uri where the Model container image will be copied to. This field should only be set when the `exportableContent` field of the [Model.supported_export_formats] object contains `IMAGE`." + }, + "artifactDestination": { + "$ref": "GoogleCloudAiplatformV1beta1GcsDestination", + "description": "The Cloud Storage location where the Model artifact is to be written to. Under the directory given as the destination a new one with name \"`model-export--`\", where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format, will be created. Inside, the Model and any of its supporting files will be written. This field should only be set when the `exportableContent` field of the [Model.supported_export_formats] object contains `ARTIFACT`." + }, + "exportFormatId": { + "description": "The ID of the format in which the Model must be exported. Each Model lists the export formats it supports. If no value is provided here, then the first from the list of the Model's supported formats is used by default.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1ExportModelRequestOutputConfig", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1PipelineJob": { + "description": "An instance of a machine learning PipelineJob.", + "properties": { + "startTime": { + "type": "string", + "format": "google-datetime", + "description": "Output only. Pipeline start time.", + "readOnly": true + }, + "createTime": { + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Pipeline creation time.", + "type": "string" + }, + "network": { + "description": "The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.", + "type": "string" + }, + "pipelineSpec": { + "description": "The spec of the pipeline.", + "additionalProperties": { + "description": "Properties of the object.", + "type": "any" + }, + "type": "object" + }, + "displayName": { + "description": "The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + }, + "updateTime": { + "readOnly": true, + "format": "google-datetime", + "type": "string", + "description": "Output only. Timestamp when this PipelineJob was most recently updated." + }, + "endTime": { + "readOnly": true, + "description": "Output only. Pipeline end time.", + "type": "string", + "format": "google-datetime" + }, + "templateUri": { + "type": "string", + "description": "A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template." + }, + "runtimeConfig": { + "description": "Runtime config of the pipeline.", + "$ref": "GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfig" + }, + "state": { + "description": "Output only. The detailed state of the job.", + "type": "string", + "enumDescriptions": [ + "The pipeline state is unspecified.", + "The pipeline has been created or resumed, and processing has not yet begun.", + "The service is preparing to run the pipeline.", + "The pipeline is in progress.", + "The pipeline completed successfully.", + "The pipeline failed.", + "The pipeline is being cancelled. From this state, the pipeline may only go to either PIPELINE_STATE_SUCCEEDED, PIPELINE_STATE_FAILED or PIPELINE_STATE_CANCELLED.", + "The pipeline has been cancelled.", + "The pipeline has been stopped, and can be resumed." + ], + "enum": [ + "PIPELINE_STATE_UNSPECIFIED", + "PIPELINE_STATE_QUEUED", + "PIPELINE_STATE_PENDING", + "PIPELINE_STATE_RUNNING", + "PIPELINE_STATE_SUCCEEDED", + "PIPELINE_STATE_FAILED", + "PIPELINE_STATE_CANCELLING", + "PIPELINE_STATE_CANCELLED", + "PIPELINE_STATE_PAUSED" + ], + "readOnly": true + }, + "satisfiesPzs": { + "readOnly": true, + "type": "boolean", + "description": "Output only. Reserved for future use." + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided." + }, + "scheduleName": { + "type": "string", + "description": "Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API.", + "readOnly": true + }, + "error": { + "description": "Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.", + "$ref": "GoogleRpcStatus", + "readOnly": true + }, + "jobDetail": { + "description": "Output only. The details of pipeline run. Not available in the list view.", + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1PipelineJobDetail" + }, + "reservedIpRanges": { + "description": "A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].", + "items": { + "type": "string" + }, + "type": "array" + }, + "name": { + "type": "string", + "description": "Output only. The resource name of the PipelineJob.", + "readOnly": true + }, + "encryptionSpec": { + "description": "Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.", + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" + }, + "serviceAccount": { + "type": "string", + "description": "The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account." + }, + "templateMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1PipelineTemplateMetadata", + "description": "Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.", + "readOnly": true + }, + "satisfiesPzi": { + "readOnly": true, + "type": "boolean", + "description": "Output only. Reserved for future use." + }, + "preflightValidations": { + "description": "Optional. Whether to do component level validations before job creation.", + "type": "boolean" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1PipelineJob" + }, + "GoogleCloudAiplatformV1beta1PurgeArtifactsMetadata": { + "description": "Details of operations that perform MetadataService.PurgeArtifacts.", + "properties": { + "genericMetadata": { + "description": "Operation metadata for purging Artifacts.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "id": "GoogleCloudAiplatformV1beta1PurgeArtifactsMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployGke": { + "id": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployGke", + "description": "Configurations for PublisherModel GKE deployment", + "type": "object", + "properties": { + "gkeYamlConfigs": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Optional. GKE deployment configuration in yaml format." + } + } + }, + "GoogleCloudAiplatformV1beta1ErrorAnalysisAnnotation": { + "properties": { + "outlierThreshold": { + "format": "double", + "type": "number", + "description": "The threshold used to determine if this annotation is an outlier or not." + }, + "attributedItems": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ErrorAnalysisAnnotationAttributedItem" + }, + "description": "Attributed items for a given annotation, typically representing neighbors from the training sets constrained by the query type.", + "type": "array" + }, + "queryType": { + "type": "string", + "enum": [ + "QUERY_TYPE_UNSPECIFIED", + "ALL_SIMILAR", + "SAME_CLASS_SIMILAR", + "SAME_CLASS_DISSIMILAR" + ], + "description": "The query type used for finding the attributed items.", + "enumDescriptions": [ + "Unspecified query type for model error analysis.", + "Query similar samples across all classes in the dataset.", + "Query similar samples from the same class of the input sample.", + "Query dissimilar samples from the same class of the input sample." + ] + }, + "outlierScore": { + "description": "The outlier score of this annotated item. Usually defined as the min of all distances from attributed items.", + "type": "number", + "format": "double" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ErrorAnalysisAnnotation", + "description": "Model error analysis for each annotation." + }, + "GoogleCloudAiplatformV1beta1CountTokensResponse": { + "properties": { + "totalBillableCharacters": { + "description": "The total number of billable characters counted across all instances from the request.", + "format": "int32", + "type": "integer" + }, + "totalTokens": { + "type": "integer", + "description": "The total number of tokens counted across all instances from the request.", + "format": "int32" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1CountTokensResponse", + "description": "Response message for PredictionService.CountTokens." + }, + "GoogleCloudAiplatformV1beta1SamplingStrategyRandomSampleConfig": { + "description": "Requests are randomly selected.", + "type": "object", + "properties": { + "sampleRate": { + "type": "number", + "description": "Sample rate (0, 1]", + "format": "double" + } + }, + "id": "GoogleCloudAiplatformV1beta1SamplingStrategyRandomSampleConfig" + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsPairwiseTextGenerationEvaluationMetrics": { + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsPairwiseTextGenerationEvaluationMetrics", + "properties": { + "f1Score": { + "description": "Harmonic mean of precision and recall.", + "format": "float", + "type": "number" + }, + "precision": { + "format": "float", + "type": "number", + "description": "Fraction of cases where the autorater and humans thought the model had a better response out of all cases where the autorater thought the model had a better response. True positive divided by all positive." + }, + "humanPreferenceModelWinRate": { + "format": "float", + "description": "Percentage of time humans decided the model had the better response.", + "type": "number" + }, + "trueNegativeCount": { + "description": "Number of examples where both the autorater and humans decided that the model had the worse response.", + "type": "string", + "format": "int64" + }, + "modelWinRate": { + "description": "Percentage of time the autorater decided the model had the better response.", + "type": "number", + "format": "float" + }, + "truePositiveCount": { + "format": "int64", + "description": "Number of examples where both the autorater and humans decided that the model had the better response.", + "type": "string" + }, + "falsePositiveCount": { + "description": "Number of examples where the autorater chose the model, but humans preferred the baseline model.", + "format": "int64", + "type": "string" + }, + "humanPreferenceBaselineModelWinRate": { + "type": "number", + "description": "Percentage of time humans decided the baseline model had the better response.", + "format": "float" + }, + "accuracy": { + "description": "Fraction of cases where the autorater agreed with the human raters.", + "type": "number", + "format": "float" + }, + "recall": { + "format": "float", + "type": "number", + "description": "Fraction of cases where the autorater and humans thought the model had a better response out of all cases where the humans thought the model had a better response." + }, + "falseNegativeCount": { + "description": "Number of examples where the autorater chose the baseline model, but humans preferred the model.", + "type": "string", + "format": "int64" + }, + "baselineModelWinRate": { + "type": "number", + "format": "float", + "description": "Percentage of time the autorater decided the baseline model had the better response." + }, + "cohensKappa": { + "type": "number", + "description": "A measurement of agreement between the autorater and human raters that takes the likelihood of random agreement into account.", + "format": "float" + } + }, + "type": "object", + "description": "Metrics for general pairwise text generation evaluation results." + }, + "GoogleCloudAiplatformV1beta1Citation": { + "description": "Source attributions for content.", + "properties": { + "endIndex": { + "description": "Output only. End index into the content.", + "format": "int32", + "readOnly": true, + "type": "integer" + }, + "startIndex": { + "format": "int32", + "description": "Output only. Start index into the content.", + "type": "integer", + "readOnly": true + }, + "publicationDate": { + "readOnly": true, + "description": "Output only. Publication date of the attribution.", + "$ref": "GoogleTypeDate" + }, + "title": { + "readOnly": true, + "type": "string", + "description": "Output only. Title of the attribution." + }, + "license": { + "type": "string", + "readOnly": true, + "description": "Output only. License of the attribution." + }, + "uri": { + "type": "string", + "description": "Output only. Url reference of the attribution.", + "readOnly": true + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1Citation" + }, + "GoogleCloudAiplatformV1beta1Port": { + "description": "Represents a network port in a container.", + "id": "GoogleCloudAiplatformV1beta1Port", + "type": "object", + "properties": { + "containerPort": { + "format": "int32", + "description": "The number of the port to expose on the pod's IP address. Must be a valid port number, between 1 and 65535 inclusive.", + "type": "integer" + } + } + }, + "GoogleCloudAiplatformV1beta1QueryReasoningEngineRequest": { + "description": "Request message for ReasoningEngineExecutionService.Query.", + "id": "GoogleCloudAiplatformV1beta1QueryReasoningEngineRequest", + "type": "object", + "properties": { + "input": { + "description": "Optional. Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc.", + "type": "object", + "additionalProperties": { + "type": "any", + "description": "Properties of the object." + } + } + } + }, + "GoogleCloudAiplatformV1beta1ExportFractionSplit": { + "id": "GoogleCloudAiplatformV1beta1ExportFractionSplit", + "description": "Assigns the input data to training, validation, and test sets as per the given fractions. Any of `training_fraction`, `validation_fraction` and `test_fraction` may optionally be provided, they must sum to up to 1. If the provided ones sum to less than 1, the remainder is assigned to sets as decided by Vertex AI. If none of the fractions are set, by default roughly 80% of data is used for training, 10% for validation, and 10% for test.", + "type": "object", + "properties": { + "validationFraction": { + "type": "number", + "description": "The fraction of the input data that is to be used to validate the Model.", + "format": "double" + }, + "trainingFraction": { + "type": "number", + "description": "The fraction of the input data that is to be used to train the Model.", + "format": "double" + }, + "testFraction": { + "format": "double", + "type": "number", + "description": "The fraction of the input data that is to be used to evaluate the Model." + } + } + }, + "GoogleCloudAiplatformV1beta1Schedule": { + "properties": { + "state": { + "type": "string", + "readOnly": true, + "enum": [ + "STATE_UNSPECIFIED", + "ACTIVE", + "PAUSED", + "COMPLETED" + ], + "enumDescriptions": [ + "Unspecified.", + "The Schedule is active. Runs are being scheduled on the user-specified timespec.", + "The schedule is paused. No new runs will be created until the schedule is resumed. Already started runs will be allowed to complete.", + "The Schedule is completed. No new runs will be scheduled. Already started runs will be allowed to complete. Schedules in completed state cannot be paused or resumed." + ], + "description": "Output only. The state of this Schedule." + }, + "endTime": { + "description": "Optional. Timestamp after which no new runs can be scheduled. If specified, The schedule will be completed when either end_time is reached or when scheduled_run_count \u003e= max_run_count. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.", + "type": "string", + "format": "google-datetime" + }, + "createModelMonitoringJobRequest": { + "description": "Request for ModelMonitoringService.CreateModelMonitoringJob.", + "$ref": "GoogleCloudAiplatformV1beta1CreateModelMonitoringJobRequest" + }, + "displayName": { + "description": "Required. User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + }, + "lastPauseTime": { + "readOnly": true, + "description": "Output only. Timestamp when this Schedule was last paused. Unset if never paused.", + "type": "string", + "format": "google-datetime" + }, + "lastResumeTime": { + "type": "string", + "readOnly": true, + "description": "Output only. Timestamp when this Schedule was last resumed. Unset if never resumed from pause.", + "format": "google-datetime" + }, + "lastScheduledRunResponse": { + "$ref": "GoogleCloudAiplatformV1beta1ScheduleRunResponse", + "readOnly": true, + "description": "Output only. Response of the last scheduled run. This is the response for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable). Unset if no run has been scheduled yet." + }, + "startTime": { + "type": "string", + "format": "google-datetime", + "description": "Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified." + }, + "allowQueueing": { + "type": "boolean", + "description": "Optional. Whether new scheduled runs can be queued when max_concurrent_runs limit is reached. If set to true, new runs will be queued instead of skipped. Default to false." + }, + "createPipelineJobRequest": { + "description": "Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).", + "$ref": "GoogleCloudAiplatformV1beta1CreatePipelineJobRequest" + }, + "nextRunTime": { + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Timestamp when this Schedule should schedule the next run. Having a next_run_time in the past means the runs are being started behind schedule.", + "type": "string" + }, + "createTime": { + "readOnly": true, + "type": "string", + "description": "Output only. Timestamp when this Schedule was created.", + "format": "google-datetime" + }, + "catchUp": { + "readOnly": true, + "type": "boolean", + "description": "Output only. Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. Default to false." + }, + "maxRunCount": { + "type": "string", + "description": "Optional. Maximum run count of the schedule. If specified, The schedule will be completed when either started_run_count \u003e= max_run_count or when end_time is reached. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.", + "format": "int64" + }, + "maxConcurrentRunCount": { + "type": "string", + "format": "int64", + "description": "Required. Maximum number of runs that can be started concurrently for this Schedule. This is the limit for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable)." + }, + "createNotebookExecutionJobRequest": { + "$ref": "GoogleCloudAiplatformV1beta1CreateNotebookExecutionJobRequest", + "description": "Request for NotebookService.CreateNotebookExecutionJob." + }, + "startedRunCount": { + "type": "string", + "description": "Output only. The number of runs started by this schedule.", + "format": "int64", + "readOnly": true + }, + "name": { + "description": "Immutable. The resource name of the Schedule.", + "type": "string" + }, + "cron": { + "description": "Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: \"CRON_TZ=${IANA_TIME_ZONE}\" or \"TZ=${IANA_TIME_ZONE}\". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, \"CRON_TZ=America/New_York 1 * * * *\", or \"TZ=America/New_York 1 * * * *\".", + "type": "string" + }, + "updateTime": { + "format": "google-datetime", + "description": "Output only. Timestamp when this Schedule was updated.", + "readOnly": true, + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1Schedule", + "description": "An instance of a Schedule periodically schedules runs to make API calls based on user specified time specification and API request type." + }, + "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityInstance": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityInstance", + "description": "Spec for pairwise question answering quality instance.", + "properties": { + "prediction": { + "type": "string", + "description": "Required. Output of the candidate model." + }, + "context": { + "description": "Required. Text to answer the question.", + "type": "string" + }, + "baselinePrediction": { + "description": "Required. Output of the baseline model.", + "type": "string" + }, + "instruction": { + "type": "string", + "description": "Required. Question Answering prompt for LLM." + }, + "reference": { + "type": "string", + "description": "Optional. Ground truth used to compare against the prediction." + } + } + }, + "GoogleCloudAiplatformV1beta1Execution": { + "properties": { + "schemaVersion": { + "description": "The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.", + "type": "string" + }, + "labels": { + "description": "The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded).", + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "description": { + "type": "string", + "description": "Description of the Execution" + }, + "metadata": { + "description": "Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.", + "type": "object", + "additionalProperties": { + "type": "any", + "description": "Properties of the object." + } + }, + "displayName": { + "type": "string", + "description": "User provided display name of the Execution. May be up to 128 Unicode characters." + }, + "name": { + "readOnly": true, + "type": "string", + "description": "Output only. The resource name of the Execution." + }, + "etag": { + "type": "string", + "description": "An eTag used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + }, + "createTime": { + "readOnly": true, + "description": "Output only. Timestamp when this Execution was created.", + "format": "google-datetime", + "type": "string" + }, + "state": { + "type": "string", + "description": "The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.", + "enum": [ + "STATE_UNSPECIFIED", + "NEW", + "RUNNING", + "COMPLETE", + "FAILED", + "CACHED", + "CANCELLED" + ], + "enumDescriptions": [ + "Unspecified Execution state", + "The Execution is new", + "The Execution is running", + "The Execution has finished running", + "The Execution has failed", + "The Execution completed through Cache hit.", + "The Execution was cancelled." + ] + }, + "schemaTitle": { + "description": "The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.", + "type": "string" + }, + "updateTime": { + "description": "Output only. Timestamp when this Execution was last updated.", + "format": "google-datetime", + "type": "string", + "readOnly": true + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1Execution", + "description": "Instance of a general execution." + }, + "GoogleCloudAiplatformV1beta1CreateDatasetVersionOperationMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1CreateDatasetVersionOperationMetadata", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "The common part of the operation metadata." + } + }, + "description": "Runtime operation information for DatasetService.CreateDatasetVersion." + }, + "GoogleCloudAiplatformV1beta1FeatureOnlineStoreDedicatedServingEndpoint": { + "id": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreDedicatedServingEndpoint", + "description": "The dedicated serving endpoint for this FeatureOnlineStore. Only need to set when you choose Optimized storage type. Public endpoint is provisioned by default.", + "type": "object", + "properties": { + "serviceAttachment": { + "description": "Output only. The name of the service attachment resource. Populated if private service connect is enabled and after FeatureViewSync is created.", + "type": "string", + "readOnly": true + }, + "publicEndpointDomainName": { + "readOnly": true, + "type": "string", + "description": "Output only. This field will be populated with the domain name to use for this FeatureOnlineStore" + }, + "privateServiceConnectConfig": { + "description": "Optional. Private service connect config. The private service connection is available only for Optimized storage type, not for embedding management now. If PrivateServiceConnectConfig.enable_private_service_connect set to true, customers will use private service connection to send request. Otherwise, the connection will set to public endpoint.", + "$ref": "GoogleCloudAiplatformV1beta1PrivateServiceConnectConfig" + } + } + }, + "GoogleCloudAiplatformV1beta1ListTensorboardsResponse": { + "description": "Response message for TensorboardService.ListTensorboards.", + "id": "GoogleCloudAiplatformV1beta1ListTensorboardsResponse", + "type": "object", + "properties": { + "nextPageToken": { + "type": "string", + "description": "A token, which can be sent as ListTensorboardsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages." + }, + "tensorboards": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Tensorboard" + }, + "type": "array", + "description": "The Tensorboards mathching the request." + } + } + }, + "GoogleCloudAiplatformV1beta1ExplanationMetadata": { + "type": "object", + "description": "Metadata describing the Model's input and output for explanation.", + "properties": { + "outputs": { + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1ExplanationMetadataOutputMetadata" + }, + "description": "Required. Map from output names to output metadata. For Vertex AI-provided Tensorflow images, keys can be any user defined string that consists of any UTF-8 characters. For custom images, keys are the name of the output field in the prediction to be explained. Currently only one key is allowed.", + "type": "object" + }, + "featureAttributionsSchemaUri": { + "type": "string", + "description": "Points to a YAML file stored on Google Cloud Storage describing the format of the feature attributions. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML tabular Models always have this field populated by Vertex AI. Note: The URI given on output may be different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access." + }, + "inputs": { + "description": "Required. Map from feature names to feature input metadata. Keys are the name of the features. Values are the specification of the feature. An empty InputMetadata is valid. It describes a text feature which has the name specified as the key in ExplanationMetadata.inputs. The baseline of the empty feature is chosen by Vertex AI. For Vertex AI-provided Tensorflow images, the key can be any friendly name of the feature. Once specified, featureAttributions are keyed by this key (if not grouped with another feature). For custom images, the key must match with the key in instance.", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadata" + }, + "type": "object" + }, + "latentSpaceSource": { + "type": "string", + "description": "Name of the source to generate embeddings for example based explanations." + } + }, + "id": "GoogleCloudAiplatformV1beta1ExplanationMetadata" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTimestampTransformation": { + "properties": { + "columnName": { + "type": "string" + }, + "timeFormat": { + "type": "string", + "description": "The format in which that time field is expressed. The time_format must either be one of: * `unix-seconds` * `unix-milliseconds` * `unix-microseconds` * `unix-nanoseconds` (for respectively number of seconds, milliseconds, microseconds and nanoseconds since start of the Unix epoch); or be written in `strftime` syntax. If time_format is not set, then the default format is RFC 3339 `date-time` format, where `time-offset` = `\"Z\"` (e.g. 1985-04-12T23:20:50.52Z)" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTimestampTransformation", + "type": "object", + "description": "Training pipeline will perform following transformation functions. * Apply the transformation functions for Numerical columns. * Determine the year, month, day,and weekday. Treat each value from the timestamp as a Categorical column. * Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed." + }, + "GoogleCloudAiplatformV1beta1JiraSourceJiraQueries": { + "id": "GoogleCloudAiplatformV1beta1JiraSourceJiraQueries", + "type": "object", + "properties": { + "customQueries": { + "items": { + "type": "string" + }, + "type": "array", + "description": "A list of custom Jira queries to import. For information about JQL (Jira Query Language), see https://support.atlassian.com/jira-service-management-cloud/docs/use-advanced-search-with-jira-query-language-jql/" + }, + "apiKeyConfig": { + "$ref": "GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig", + "description": "Required. The SecretManager secret version resource name (e.g. projects/{project}/secrets/{secret}/versions/{version}) storing the Jira API key (https://support.atlassian.com/atlassian-account/docs/manage-api-tokens-for-your-atlassian-account/)." + }, + "serverUri": { + "description": "Required. The Jira server URI.", + "type": "string" + }, + "projects": { + "items": { + "type": "string" + }, + "type": "array", + "description": "A list of Jira projects to import in their entirety." + }, + "email": { + "description": "Required. The Jira email address.", + "type": "string" + } + }, + "description": "JiraQueries contains the Jira queries and corresponding authentication." + }, + "GoogleCloudAiplatformV1beta1ResourcePool": { + "id": "GoogleCloudAiplatformV1beta1ResourcePool", + "properties": { + "diskSpec": { + "$ref": "GoogleCloudAiplatformV1beta1DiskSpec", + "description": "Optional. Disk spec for the machine in this node pool." + }, + "id": { + "description": "Immutable. The unique ID in a PersistentResource for referring to this resource pool. User can specify it if necessary. Otherwise, it's generated automatically.", + "type": "string" + }, + "usedReplicaCount": { + "type": "string", + "description": "Output only. The number of machines currently in use by training jobs for this resource pool. Will replace idle_replica_count.", + "readOnly": true, + "format": "int64" + }, + "machineSpec": { + "$ref": "GoogleCloudAiplatformV1beta1MachineSpec", + "description": "Required. Immutable. The specification of a single machine." + }, + "autoscalingSpec": { + "description": "Optional. Optional spec to configure GKE or Ray-on-Vertex autoscaling", + "$ref": "GoogleCloudAiplatformV1beta1ResourcePoolAutoscalingSpec" + }, + "replicaCount": { + "format": "int64", + "description": "Optional. The total number of machines to use for this resource pool.", + "type": "string" + } + }, + "type": "object", + "description": "Represents the spec of a group of resources of the same type, for example machine type, disk, and accelerators, in a PersistentResource." + }, + "GoogleCloudAiplatformV1beta1CustomJobSpec": { + "id": "GoogleCloudAiplatformV1beta1CustomJobSpec", + "description": "Represents the spec of a CustomJob.", + "type": "object", + "properties": { + "scheduling": { + "description": "Scheduling options for a CustomJob.", + "$ref": "GoogleCloudAiplatformV1beta1Scheduling" + }, + "tensorboard": { + "type": "string", + "description": "Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`" + }, + "workerPoolSpecs": { + "type": "array", + "description": "Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1WorkerPoolSpec" + } + }, + "persistentResourceId": { + "type": "string", + "description": "Optional. The ID of the PersistentResource in the same Project and Location which to run If this is specified, the job will be run on existing machines held by the PersistentResource instead of on-demand short-live machines. The network and CMEK configs on the job should be consistent with those on the PersistentResource, otherwise, the job will be rejected." + }, + "reservedIpRanges": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range']." + }, + "serviceAccount": { + "type": "string", + "description": "Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the [Vertex AI Custom Code Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) for the CustomJob's project is used." + }, + "enableWebAccess": { + "type": "boolean", + "description": "Optional. Whether you want Vertex AI to enable [interactive shell access](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) to training containers. If set to `true`, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials)." + }, + "network": { + "type": "string", + "description": "Optional. The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Job should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. To specify this field, you must have already [configured VPC Network Peering for Vertex AI](https://cloud.google.com/vertex-ai/docs/general/vpc-peering). If this field is left unspecified, the job is not peered with any network." + }, + "experimentRun": { + "type": "string", + "description": "Optional. The Experiment Run associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}`" + }, + "models": { + "description": "Optional. The name of the Model resources for which to generate a mapping to artifact URIs. Applicable only to some of the Google-provided custom jobs. Format: `projects/{project}/locations/{location}/models/{model}` In order to retrieve a specific version of the model, also provide the version ID or version alias. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` If no version ID or alias is specified, the \"default\" version will be returned. The \"default\" version alias is created for the first version of the model, and can be moved to other versions later on. There will be exactly one default version.", + "type": "array", + "items": { + "type": "string" + } + }, + "experiment": { + "type": "string", + "description": "Optional. The Experiment associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}`" + }, + "baseOutputDirectory": { + "description": "The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = `/model/` * AIP_CHECKPOINT_DIR = `/checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `/logs/` For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = `//model/` * AIP_CHECKPOINT_DIR = `//checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `//logs/`", + "$ref": "GoogleCloudAiplatformV1beta1GcsDestination" + }, + "protectedArtifactLocationId": { + "description": "The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations", + "type": "string" + }, + "enableDashboardAccess": { + "type": "boolean", + "description": "Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to `true`, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials)." + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationPolylineAnnotation": { + "description": "Represents a polyline in image.", + "type": "object", + "properties": { + "displayName": { + "type": "string", + "description": "The display name of the AnnotationSpec that this Annotation pertains to." + }, + "vertexes": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaVertex" + }, + "description": "The vertexes are connected one by one and the last vertex in not connected to the first one." + }, + "annotationSpecId": { + "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationPolylineAnnotation" + }, + "GoogleCloudAiplatformV1beta1ExportFeatureValuesRequestFullExport": { + "description": "Describes exporting all historical Feature values of all entities of the EntityType between [start_time, end_time].", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ExportFeatureValuesRequestFullExport", + "properties": { + "endTime": { + "description": "Exports Feature values as of this timestamp. If not set, retrieve values as of now. Timestamp, if present, must not have higher than millisecond precision.", + "format": "google-datetime", + "type": "string" + }, + "startTime": { + "format": "google-datetime", + "description": "Excludes Feature values with feature generation timestamp before this timestamp. If not set, retrieve oldest values kept in Feature Store. Timestamp, if present, must not have higher than millisecond precision.", + "type": "string" + } + } + }, + "CloudAiLargeModelsVisionMedia": { + "type": "object", + "properties": { + "video": { + "$ref": "CloudAiLargeModelsVisionVideo", + "description": "Video" + }, + "image": { + "$ref": "CloudAiLargeModelsVisionImage", + "description": "Image." + } + }, + "description": "Media.", + "id": "CloudAiLargeModelsVisionMedia" + }, + "GoogleCloudAiplatformV1beta1LargeModelReference": { + "properties": { + "name": { + "type": "string", + "description": "Required. The unique name of the large Foundation or pre-built model. Like \"chat-bison\", \"text-bison\". Or model name with version ID, like \"chat-bison@001\", \"text-bison@005\", etc." + } + }, + "type": "object", + "description": "Contains information about the Large Model.", + "id": "GoogleCloudAiplatformV1beta1LargeModelReference" + }, + "GoogleCloudAiplatformV1beta1DeleteMetadataStoreOperationMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1DeleteMetadataStoreOperationMetadata", + "description": "Details of operations that perform MetadataService.DeleteMetadataStore.", + "properties": { + "genericMetadata": { + "description": "Operation metadata for deleting a MetadataStore.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTextTransformation": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTextTransformation", + "description": "Training pipeline will perform following transformation functions. * The text as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index.", + "properties": { + "columnName": { + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1BleuInput": { + "id": "GoogleCloudAiplatformV1beta1BleuInput", + "description": "Input for bleu metric.", + "type": "object", + "properties": { + "instances": { + "description": "Required. Repeated bleu instances.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1BleuInstance" + }, + "type": "array" + }, + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1beta1BleuSpec", + "description": "Required. Spec for bleu score metric." + } + } + }, + "GoogleCloudAiplatformV1beta1CreateEndpointOperationMetadata": { + "description": "Runtime operation information for EndpointService.CreateEndpoint.", + "id": "GoogleCloudAiplatformV1beta1CreateEndpointOperationMetadata", + "type": "object", + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + } + }, + "GoogleCloudAiplatformV1beta1UnmanagedContainerModel": { + "id": "GoogleCloudAiplatformV1beta1UnmanagedContainerModel", + "properties": { + "artifactUri": { + "type": "string", + "description": "The path to the directory containing the Model artifact and any of its supporting files." + }, + "containerSpec": { + "$ref": "GoogleCloudAiplatformV1beta1ModelContainerSpec", + "description": "Input only. The specification of the container that is to be used when deploying this Model." + }, + "predictSchemata": { + "description": "Contains the schemata used in Model's predictions and explanations", + "$ref": "GoogleCloudAiplatformV1beta1PredictSchemata" + } + }, + "type": "object", + "description": "Contains model information necessary to perform batch prediction without requiring a full model import." + }, + "GoogleCloudAiplatformV1beta1MigrateResourceResponse": { + "id": "GoogleCloudAiplatformV1beta1MigrateResourceResponse", + "type": "object", + "properties": { + "dataset": { + "type": "string", + "description": "Migrated Dataset's resource name." + }, + "migratableResource": { + "$ref": "GoogleCloudAiplatformV1beta1MigratableResource", + "description": "Before migration, the identifier in ml.googleapis.com, automl.googleapis.com or datalabeling.googleapis.com." + }, + "model": { + "type": "string", + "description": "Migrated Model's resource name." + } + }, + "description": "Describes a successfully migrated resource." + }, + "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTextSentimentPredictionResult": { + "properties": { + "sentiment": { + "format": "int32", + "description": "The integer sentiment labels between 0 (inclusive) and sentimentMax label (inclusive), while 0 maps to the least positive sentiment and sentimentMax maps to the most positive one. The higher the score is, the more positive the sentiment in the text snippet is. Note: sentimentMax is an integer value between 1 (inclusive) and 10 (inclusive).", + "type": "integer" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTextSentimentPredictionResult", + "description": "Prediction output format for Text Sentiment", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1CreateTensorboardTimeSeriesRequest": { + "id": "GoogleCloudAiplatformV1beta1CreateTensorboardTimeSeriesRequest", + "properties": { + "tensorboardTimeSeries": { + "description": "Required. The TensorboardTimeSeries to create.", + "$ref": "GoogleCloudAiplatformV1beta1TensorboardTimeSeries" + }, + "parent": { + "description": "Required. The resource name of the TensorboardRun to create the TensorboardTimeSeries in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", + "type": "string" + }, + "tensorboardTimeSeriesId": { + "type": "string", + "description": "Optional. The user specified unique ID to use for the TensorboardTimeSeries, which becomes the final component of the TensorboardTimeSeries's resource name. This value should match \"a-z0-9{0, 127}\"" + } + }, + "description": "Request message for TensorboardService.CreateTensorboardTimeSeries.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SafetySpec": { + "description": "Spec for safety metric.", + "properties": { + "version": { + "description": "Optional. Which version to use for evaluation.", + "format": "int32", + "type": "integer" + } + }, + "id": "GoogleCloudAiplatformV1beta1SafetySpec", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1NotebookEucConfig": { + "properties": { + "bypassActasCheck": { + "description": "Output only. Whether ActAs check is bypassed for service account attached to the VM. If false, we need ActAs check for the default Compute Engine Service account. When a Runtime is created, a VM is allocated using Default Compute Engine Service Account. Any user requesting to use this Runtime requires Service Account User (ActAs) permission over this SA. If true, Runtime owner is using EUC and does not require the above permission as VM no longer use default Compute Engine SA, but a P4SA.", + "readOnly": true, + "type": "boolean" + }, + "eucDisabled": { + "type": "boolean", + "description": "Input only. Whether EUC is disabled in this NotebookRuntimeTemplate. In proto3, the default value of a boolean is false. In this way, by default EUC will be enabled for NotebookRuntimeTemplate." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1NotebookEucConfig", + "description": "The euc configuration of NotebookRuntimeTemplate." + }, + "GoogleCloudAiplatformV1beta1GroundingSupport": { + "properties": { + "groundingChunkIndices": { + "description": "A list of indices (into 'grounding_chunk') specifying the citations associated with the claim. For instance [1,3,4] means that grounding_chunk[1], grounding_chunk[3], grounding_chunk[4] are the retrieved content attributed to the claim.", + "type": "array", + "items": { + "format": "int32", + "type": "integer" + } + }, + "segment": { + "$ref": "GoogleCloudAiplatformV1beta1Segment", + "description": "Segment of the content this support belongs to." + }, + "confidenceScores": { + "description": "Confidence score of the support references. Ranges from 0 to 1. 1 is the most confident. This list must have the same size as the grounding_chunk_indices.", + "type": "array", + "items": { + "format": "float", + "type": "number" + } + } + }, + "description": "Grounding support.", + "id": "GoogleCloudAiplatformV1beta1GroundingSupport", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1TensorboardTensor": { + "properties": { + "versionNumber": { + "format": "int32", + "description": "Optional. Version number of TensorProto used to serialize value.", + "type": "integer" + }, + "value": { + "type": "string", + "format": "byte", + "description": "Required. Serialized form of https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/tensor.proto" + } + }, + "type": "object", + "description": "One point viewable on a tensor metric plot.", + "id": "GoogleCloudAiplatformV1beta1TensorboardTensor" + }, + "GoogleCloudAiplatformV1beta1FeatureViewSyncSyncSummary": { + "properties": { + "rowSynced": { + "format": "int64", + "readOnly": true, + "description": "Output only. Total number of rows synced.", + "type": "string" + }, + "totalSlot": { + "readOnly": true, + "type": "string", + "description": "Output only. BigQuery slot milliseconds consumed for the sync job.", + "format": "int64" + } + }, + "id": "GoogleCloudAiplatformV1beta1FeatureViewSyncSyncSummary", + "type": "object", + "description": "Summary from the Sync job. For continuous syncs, the summary is updated periodically. For batch syncs, it gets updated on completion of the sync." + }, + "GoogleCloudAiplatformV1beta1RuntimeConfigVertexAISearchRuntimeConfig": { + "type": "object", + "properties": { + "engineId": { + "type": "string", + "description": "Optional. Vertex AI Search engine ID. This is used to construct the search request. By setting this engine_id, API will construct the serving config using the default value to call search API for the user. The engine_id and serving_config_name cannot both be empty at the same time." + }, + "servingConfigName": { + "type": "string", + "description": "Optional. Vertex AI Search serving config name. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}/servingConfigs/{serving_config}`" + } + }, + "id": "GoogleCloudAiplatformV1beta1RuntimeConfigVertexAISearchRuntimeConfig" + }, + "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityInput": { + "properties": { + "instance": { + "description": "Required. Pairwise question answering quality instance.", + "$ref": "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityInstance" + }, + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualitySpec", + "description": "Required. Spec for pairwise question answering quality score metric." + } + }, + "id": "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityInput", + "description": "Input for pairwise question answering quality metric.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1Candidate": { + "description": "A response candidate generated from the model.", + "type": "object", + "properties": { + "score": { + "format": "double", + "readOnly": true, + "description": "Output only. Confidence score of the candidate.", + "type": "number" + }, + "safetyRatings": { + "description": "Output only. List of ratings for the safety of a response candidate. There is at most one rating per category.", + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SafetyRating" + }, + "type": "array" + }, + "finishReason": { + "enum": [ + "FINISH_REASON_UNSPECIFIED", + "STOP", + "MAX_TOKENS", + "SAFETY", + "RECITATION", + "OTHER", + "BLOCKLIST", + "PROHIBITED_CONTENT", + "SPII", + "MALFORMED_FUNCTION_CALL" + ], + "readOnly": true, + "description": "Output only. The reason why the model stopped generating tokens. If empty, the model has not stopped generating the tokens.", + "enumDescriptions": [ + "The finish reason is unspecified.", + "Natural stop point of the model or provided stop sequence.", + "The maximum number of tokens as specified in the request was reached.", + "The token generation was stopped as the response was flagged for safety reasons. NOTE: When streaming the Candidate.content will be empty if content filters blocked the output.", + "The token generation was stopped as the response was flagged for unauthorized citations.", + "All other reasons that stopped the token generation", + "The token generation was stopped as the response was flagged for the terms which are included from the terminology blocklist.", + "The token generation was stopped as the response was flagged for the prohibited contents.", + "The token generation was stopped as the response was flagged for Sensitive Personally Identifiable Information (SPII) contents.", + "The function call generated by the model is invalid." + ], + "type": "string" + }, + "citationMetadata": { + "readOnly": true, + "description": "Output only. Source attribution of the generated content.", + "$ref": "GoogleCloudAiplatformV1beta1CitationMetadata" + }, + "groundingMetadata": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1GroundingMetadata", + "description": "Output only. Metadata specifies sources used to ground generated content." + }, + "content": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1Content", + "description": "Output only. Content parts of the candidate." + }, + "finishMessage": { + "type": "string", + "description": "Output only. Describes the reason the mode stopped generating tokens in more detail. This is only filled when `finish_reason` is set.", + "readOnly": true + }, + "index": { + "format": "int32", + "description": "Output only. Index of the candidate.", + "type": "integer", + "readOnly": true + } + }, + "id": "GoogleCloudAiplatformV1beta1Candidate" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpec": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpec", + "properties": { + "notificationChannelConfigs": { + "description": "Notification channel config.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpecNotificationChannelConfig" + } + }, + "emailConfig": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpecEmailConfig", + "description": "Email alert config." + }, + "enableCloudLogging": { + "description": "Dump the anomalies to Cloud Logging. The anomalies will be put to json payload encoded from proto google.cloud.aiplatform.logging.ModelMonitoringAnomaliesLogEntry. This can be further sinked to Pub/Sub or any other services supported by Cloud Logging.", + "type": "boolean" + } + }, + "description": "Notification spec(email, notification channel) for model monitoring statistics/alerts." + }, + "GoogleCloudAiplatformV1beta1EvaluatedAnnotation": { + "description": "True positive, false positive, or false negative. EvaluatedAnnotation is only available under ModelEvaluationSlice with slice of `annotationSpec` dimension.", + "id": "GoogleCloudAiplatformV1beta1EvaluatedAnnotation", + "type": "object", + "properties": { + "type": { + "readOnly": true, + "type": "string", + "description": "Output only. Type of the EvaluatedAnnotation.", + "enum": [ + "EVALUATED_ANNOTATION_TYPE_UNSPECIFIED", + "TRUE_POSITIVE", + "FALSE_POSITIVE", + "FALSE_NEGATIVE" + ], + "enumDescriptions": [ + "Invalid value.", + "The EvaluatedAnnotation is a true positive. It has a prediction created by the Model and a ground truth Annotation which the prediction matches.", + "The EvaluatedAnnotation is false positive. It has a prediction created by the Model which does not match any ground truth annotation.", + "The EvaluatedAnnotation is false negative. It has a ground truth annotation which is not matched by any of the model created predictions." + ] + }, + "predictions": { + "readOnly": true, + "type": "array", + "items": { + "type": "any" + }, + "description": "Output only. The model predicted annotations. For true positive, there is one and only one prediction, which matches the only one ground truth annotation in ground_truths. For false positive, there is one and only one prediction, which doesn't match any ground truth annotation of the corresponding data_item_view_id. For false negative, there are zero or more predictions which are similar to the only ground truth annotation in ground_truths but not enough for a match. The schema of the prediction is stored in ModelEvaluation.annotation_schema_uri" + }, + "evaluatedDataItemViewId": { + "readOnly": true, + "type": "string", + "description": "Output only. ID of the EvaluatedDataItemView under the same ancestor ModelEvaluation. The EvaluatedDataItemView consists of all ground truths and predictions on data_item_payload." + }, + "errorAnalysisAnnotations": { + "description": "Annotations of model error analysis results.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ErrorAnalysisAnnotation" + } + }, + "explanations": { + "description": "Explanations of predictions. Each element of the explanations indicates the explanation for one explanation Method. The attributions list in the EvaluatedAnnotationExplanation.explanation object corresponds to the predictions list. For example, the second element in the attributions list explains the second element in the predictions list.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1EvaluatedAnnotationExplanation" + }, + "type": "array" + }, + "groundTruths": { + "type": "array", + "description": "Output only. The ground truth Annotations, i.e. the Annotations that exist in the test data the Model is evaluated on. For true positive, there is one and only one ground truth annotation, which matches the only prediction in predictions. For false positive, there are zero or more ground truth annotations that are similar to the only prediction in predictions, but not enough for a match. For false negative, there is one and only one ground truth annotation, which doesn't match any predictions created by the model. The schema of the ground truth is stored in ModelEvaluation.annotation_schema_uri", + "readOnly": true, + "items": { + "type": "any" + } + }, + "dataItemPayload": { + "readOnly": true, + "description": "Output only. The data item payload that the Model predicted this EvaluatedAnnotation on.", + "type": "any" + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentationInputs": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentationInputs", + "type": "object", + "properties": { + "baseModelId": { + "description": "The ID of the `base` model. If it is specified, the new model will be trained based on the `base` model. Otherwise, the new model will be trained from scratch. The `base` model must be in the same Project and Location as the new Model to train, and have the same modelType.", + "type": "string" + }, + "modelType": { + "enum": [ + "MODEL_TYPE_UNSPECIFIED", + "CLOUD_HIGH_ACCURACY_1", + "CLOUD_LOW_ACCURACY_1", + "MOBILE_TF_LOW_LATENCY_1" + ], + "type": "string", + "enumDescriptions": [ + "Should not be set.", + "A model to be used via prediction calls to uCAIP API. Expected to have a higher latency, but should also have a higher prediction quality than other models.", + "A model to be used via prediction calls to uCAIP API. Expected to have a lower latency but relatively lower prediction quality.", + "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow model and used on a mobile or edge device afterwards. Expected to have low latency, but may have lower prediction quality than other mobile models." + ] + }, + "budgetMilliNodeHours": { + "format": "int64", + "type": "string", + "description": "The training budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The actual metadata.costMilliNodeHours will be equal or less than this value. If further model training ceases to provide any improvements, it will stop without using the full budget and the metadata.successfulStopReason will be `model-converged`. Note, node_hour = actual_hour * number_of_nodes_involved. Or actual_wall_clock_hours = train_budget_milli_node_hours / (number_of_nodes_involved * 1000) For modelType `cloud-high-accuracy-1`(default), the budget must be between 20,000 and 2,000,000 milli node hours, inclusive. The default value is 192,000 which represents one day in wall time (1000 milli * 24 hours * 8 nodes)." + } + } + }, + "GoogleCloudAiplatformV1beta1Featurestore": { + "description": "Vertex AI Feature Store provides a centralized repository for organizing, storing, and serving ML features. The Featurestore is a top-level container for your features and their values.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1Featurestore", + "properties": { + "encryptionSpec": { + "description": "Optional. Customer-managed encryption key spec for data storage. If set, both of the online and offline data storage will be secured by this key.", + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" + }, + "state": { + "readOnly": true, + "description": "Output only. State of the featurestore.", + "enum": [ + "STATE_UNSPECIFIED", + "STABLE", + "UPDATING" + ], + "enumDescriptions": [ + "Default value. This value is unused.", + "State when the featurestore configuration is not being updated and the fields reflect the current configuration of the featurestore. The featurestore is usable in this state.", + "The state of the featurestore configuration when it is being updated. During an update, the fields reflect either the original configuration or the updated configuration of the featurestore. For example, `online_serving_config.fixed_node_count` can take minutes to update. While the update is in progress, the featurestore is in the UPDATING state, and the value of `fixed_node_count` can be the original value or the updated value, depending on the progress of the operation. Until the update completes, the actual number of nodes can still be the original value of `fixed_node_count`. The featurestore is still usable in this state." + ], + "type": "string" + }, + "onlineStorageTtlDays": { + "format": "int32", + "type": "integer", + "description": "Optional. TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than `online_storage_ttl_days` since the feature generation time. Note that `online_storage_ttl_days` should be less than or equal to `offline_storage_ttl_days` for each EntityType under a featurestore. If not set, default to 4000 days" + }, + "onlineServingConfig": { + "description": "Optional. Config for online storage resources. The field should not co-exist with the field of `OnlineStoreReplicationConfig`. If both of it and OnlineStoreReplicationConfig are unset, the feature store will not have an online store and cannot be used for online serving.", + "$ref": "GoogleCloudAiplatformV1beta1FeaturestoreOnlineServingConfig" + }, + "name": { + "readOnly": true, + "type": "string", + "description": "Output only. Name of the Featurestore. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`" + }, + "etag": { + "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "updateTime": { + "description": "Output only. Timestamp when this Featurestore was last updated.", + "readOnly": true, + "type": "string", + "format": "google-datetime" + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "Optional. The labels with user-defined metadata to organize your Featurestore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Featurestore(System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." + }, + "createTime": { + "type": "string", + "readOnly": true, + "description": "Output only. Timestamp when this Featurestore was created.", + "format": "google-datetime" + } + } + }, + "GoogleCloudAiplatformV1beta1ExportDataResponse": { + "type": "object", + "properties": { + "exportedFiles": { + "description": "All of the files that are exported in this export operation. For custom code training export, only three (training, validation and test) Cloud Storage paths in wildcard format are populated (for example, gs://.../training-*).", + "type": "array", + "items": { + "type": "string" + } + } + }, + "id": "GoogleCloudAiplatformV1beta1ExportDataResponse", + "description": "Response message for DatasetService.ExportData." + }, + "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequestEntityTypeSpec": { + "properties": { + "settings": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1DestinationFeatureSetting" + }, + "type": "array", + "description": "Per-Feature settings for the batch read." + }, + "entityTypeId": { + "type": "string", + "description": "Required. ID of the EntityType to select Features. The EntityType id is the entity_type_id specified during EntityType creation." + }, + "featureSelector": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureSelector", + "description": "Required. Selectors choosing which Feature values to read from the EntityType." + } + }, + "description": "Selects Features of an EntityType to read values of and specifies read settings.", + "id": "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequestEntityTypeSpec", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadataVisualization": { + "description": "Visualization configurations for image explanation.", + "properties": { + "polarity": { + "enumDescriptions": [ + "Default value. This is the same as POSITIVE.", + "Highlights the pixels/outlines that were most influential to the model's prediction.", + "Setting polarity to negative highlights areas that does not lead to the models's current prediction.", + "Shows both positive and negative attributions." + ], + "enum": [ + "POLARITY_UNSPECIFIED", + "POSITIVE", + "NEGATIVE", + "BOTH" + ], + "type": "string", + "description": "Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE." + }, + "colorMap": { + "description": "The color scheme used for the highlighted areas. Defaults to PINK_GREEN for Integrated Gradients attribution, which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for XRAI attribution, which highlights the most influential regions in yellow and the least influential in blue.", + "enum": [ + "COLOR_MAP_UNSPECIFIED", + "PINK_GREEN", + "VIRIDIS", + "RED", + "GREEN", + "RED_GREEN", + "PINK_WHITE_GREEN" + ], + "type": "string", + "enumDescriptions": [ + "Should not be used.", + "Positive: green. Negative: pink.", + "Viridis color map: A perceptually uniform color mapping which is easier to see by those with colorblindness and progresses from yellow to green to blue. Positive: yellow. Negative: blue.", + "Positive: red. Negative: red.", + "Positive: green. Negative: green.", + "Positive: green. Negative: red.", + "PiYG palette." + ] + }, + "clipPercentLowerbound": { + "description": "Excludes attributions below the specified percentile, from the highlighted areas. Defaults to 62.", + "format": "float", + "type": "number" + }, + "type": { + "enum": [ + "TYPE_UNSPECIFIED", + "PIXELS", + "OUTLINES" + ], + "enumDescriptions": [ + "Should not be used.", + "Shows which pixel contributed to the image prediction.", + "Shows which region contributed to the image prediction by outlining the region." + ], + "description": "Type of the image visualization. Only applicable to Integrated Gradients attribution. OUTLINES shows regions of attribution, while PIXELS shows per-pixel attribution. Defaults to OUTLINES.", + "type": "string" + }, + "overlayType": { + "description": "How the original image is displayed in the visualization. Adjusting the overlay can help increase visual clarity if the original image makes it difficult to view the visualization. Defaults to NONE.", + "enum": [ + "OVERLAY_TYPE_UNSPECIFIED", + "NONE", + "ORIGINAL", + "GRAYSCALE", + "MASK_BLACK" + ], + "type": "string", + "enumDescriptions": [ + "Default value. This is the same as NONE.", + "No overlay.", + "The attributions are shown on top of the original image.", + "The attributions are shown on top of grayscaled version of the original image.", + "The attributions are used as a mask to reveal predictive parts of the image and hide the un-predictive parts." + ] + }, + "clipPercentUpperbound": { + "format": "float", + "type": "number", + "description": "Excludes attributions above the specified percentile from the highlighted areas. Using the clip_percent_upperbound and clip_percent_lowerbound together can be useful for filtering out noise and making it easier to see areas of strong attribution. Defaults to 99.9." + } + }, + "id": "GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadataVisualization", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1Annotation": { + "description": "Used to assign specific AnnotationSpec to a particular area of a DataItem or the whole part of the DataItem.", + "properties": { + "updateTime": { + "description": "Output only. Timestamp when this Annotation was last updated.", + "type": "string", + "format": "google-datetime", + "readOnly": true + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "Optional. The labels with user-defined metadata to organize your Annotations. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Annotation(System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable. Following system labels exist for each Annotation: * \"aiplatform.googleapis.com/annotation_set_name\": optional, name of the UI's annotation set this Annotation belongs to. If not set, the Annotation is not visible in the UI. * \"aiplatform.googleapis.com/payload_schema\": output only, its value is the payload_schema's title." + }, + "etag": { + "type": "string", + "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + }, + "payload": { + "description": "Required. The schema of the payload can be found in payload_schema.", + "type": "any" + }, + "name": { + "readOnly": true, + "type": "string", + "description": "Output only. Resource name of the Annotation." + }, + "annotationSource": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1UserActionReference", + "description": "Output only. The source of the Annotation." + }, + "payloadSchemaUri": { + "description": "Required. Google Cloud Storage URI points to a YAML file describing payload. The schema is defined as an [OpenAPI 3.0.2 Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/annotation/, note that the chosen schema must be consistent with the parent Dataset's metadata.", + "type": "string" + }, + "createTime": { + "type": "string", + "description": "Output only. Timestamp when this Annotation was created.", + "readOnly": true, + "format": "google-datetime" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1Annotation" + }, + "GoogleCloudAiplatformV1beta1GenerateContentRequest": { + "properties": { + "tools": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Tool" + }, + "description": "Optional. A list of `Tools` the model may use to generate the next response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model.", + "type": "array" + }, + "cachedContent": { + "type": "string", + "description": "Optional. The name of the cached content used as context to serve the prediction. Note: only used in explicit caching, where users can have control over caching (e.g. what content to cache) and enjoy guaranteed cost savings. Format: `projects/{project}/locations/{location}/cachedContents/{cachedContent}`" + }, + "systemInstruction": { + "$ref": "GoogleCloudAiplatformV1beta1Content", + "description": "Optional. The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph." + }, + "toolConfig": { + "$ref": "GoogleCloudAiplatformV1beta1ToolConfig", + "description": "Optional. Tool config. This config is shared for all tools provided in the request." + }, + "safetySettings": { + "description": "Optional. Per request settings for blocking unsafe content. Enforced on GenerateContentResponse.candidates.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SafetySetting" + }, + "type": "array" + }, + "generationConfig": { + "description": "Optional. Generation config.", + "$ref": "GoogleCloudAiplatformV1beta1GenerationConfig" + }, + "contents": { + "description": "Required. The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Content" + }, + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1beta1GenerateContentRequest", + "description": "Request message for [PredictionService.GenerateContent].", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1Endpoint": { + "description": "Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations.", + "id": "GoogleCloudAiplatformV1beta1Endpoint", + "properties": { + "network": { + "type": "string", + "description": "Optional. The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks) to which the Endpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. Only one of the fields, network or enable_private_service_connect, can be set. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert): `projects/{project}/global/networks/{network}`. Where `{project}` is a project number, as in `12345`, and `{network}` is network name." + }, + "etag": { + "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "dedicatedEndpointEnabled": { + "type": "boolean", + "description": "If true, the endpoint will be exposed through a dedicated DNS [Endpoint.dedicated_endpoint_dns]. Your request to the dedicated DNS will be isolated from other users' traffic and will have better performance and reliability. Note: Once you enabled dedicated endpoint, you won't be able to send request to the shared DNS {region}-aiplatform.googleapis.com. The limitation will be removed soon." + }, + "enablePrivateServiceConnect": { + "deprecated": true, + "type": "boolean", + "description": "Deprecated: If true, expose the Endpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set." + }, + "privateServiceConnectConfig": { + "$ref": "GoogleCloudAiplatformV1beta1PrivateServiceConnectConfig", + "description": "Optional. Configuration for private service connect. network and private_service_connect_config are mutually exclusive." + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "The labels with user-defined metadata to organize your Endpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels." + }, + "trafficSplit": { + "description": "A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If a DeployedModel's ID is not listed in this map, then it receives no traffic. The traffic percentage values must add up to 100, or map must be empty if the Endpoint is to not accept any traffic at a moment.", + "type": "object", + "additionalProperties": { + "format": "int32", + "type": "integer" + } + }, + "updateTime": { + "type": "string", + "description": "Output only. Timestamp when this Endpoint was last updated.", + "readOnly": true, + "format": "google-datetime" + }, + "dedicatedEndpointDns": { + "type": "string", + "description": "Output only. DNS of the dedicated endpoint. Will only be populated if dedicated_endpoint_enabled is true. Format: `https://{endpoint_id}.{region}-{project_number}.prediction.vertexai.goog`.", + "readOnly": true + }, + "name": { + "type": "string", + "readOnly": true, + "description": "Output only. The resource name of the Endpoint." + }, + "createTime": { + "readOnly": true, + "type": "string", + "description": "Output only. Timestamp when this Endpoint was created.", + "format": "google-datetime" + }, + "predictRequestResponseLoggingConfig": { + "$ref": "GoogleCloudAiplatformV1beta1PredictRequestResponseLoggingConfig", + "description": "Configures the request-response logging for online prediction." + }, + "description": { + "type": "string", + "description": "The description of the Endpoint." + }, + "modelDeploymentMonitoringJob": { + "readOnly": true, + "description": "Output only. Resource name of the Model Monitoring job associated with this Endpoint if monitoring is enabled by JobService.CreateModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`", + "type": "string" + }, + "encryptionSpec": { + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", + "description": "Customer-managed encryption key spec for an Endpoint. If set, this Endpoint and all sub-resources of this Endpoint will be secured by this key." + }, + "deployedModels": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1DeployedModel" + }, + "readOnly": true, + "description": "Output only. The models deployed in this Endpoint. To add or remove DeployedModels use EndpointService.DeployModel and EndpointService.UndeployModel respectively." + }, + "displayName": { + "type": "string", + "description": "Required. The display name of the Endpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FeatureViewBigQuerySource": { + "type": "object", + "properties": { + "uri": { + "type": "string", + "description": "Required. The BigQuery view URI that will be materialized on each sync trigger based on FeatureView.SyncConfig." + }, + "entityIdColumns": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Required. Columns to construct entity_id / row keys." + } + }, + "id": "GoogleCloudAiplatformV1beta1FeatureViewBigQuerySource" + }, + "GoogleCloudAiplatformV1beta1DirectUploadSource": { + "type": "object", + "properties": {}, + "id": "GoogleCloudAiplatformV1beta1DirectUploadSource", + "description": "The input content is encapsulated and uploaded in the request." + }, + "GoogleCloudAiplatformV1beta1TensorboardTimeSeries": { + "type": "object", + "description": "TensorboardTimeSeries maps to times series produced in training runs", + "id": "GoogleCloudAiplatformV1beta1TensorboardTimeSeries", + "properties": { + "pluginData": { + "format": "byte", + "type": "string", + "description": "Data of the current plugin, with the size limited to 65KB." + }, + "description": { + "type": "string", + "description": "Description of this TensorboardTimeSeries." + }, + "valueType": { + "enum": [ + "VALUE_TYPE_UNSPECIFIED", + "SCALAR", + "TENSOR", + "BLOB_SEQUENCE" + ], + "enumDescriptions": [ + "The value type is unspecified.", + "Used for TensorboardTimeSeries that is a list of scalars. E.g. accuracy of a model over epochs/time.", + "Used for TensorboardTimeSeries that is a list of tensors. E.g. histograms of weights of layer in a model over epoch/time.", + "Used for TensorboardTimeSeries that is a list of blob sequences. E.g. set of sample images with labels over epochs/time." + ], + "description": "Required. Immutable. Type of TensorboardTimeSeries value.", + "type": "string" + }, + "metadata": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1TensorboardTimeSeriesMetadata", + "description": "Output only. Scalar, Tensor, or Blob metadata for this TensorboardTimeSeries." + }, + "pluginName": { + "type": "string", + "description": "Immutable. Name of the plugin this time series pertain to. Such as Scalar, Tensor, Blob" + }, + "name": { + "readOnly": true, + "type": "string", + "description": "Output only. Name of the TensorboardTimeSeries." + }, + "updateTime": { + "description": "Output only. Timestamp when this TensorboardTimeSeries was last updated.", + "type": "string", + "readOnly": true, + "format": "google-datetime" + }, + "displayName": { + "type": "string", + "description": "Required. User provided name of this TensorboardTimeSeries. This value should be unique among all TensorboardTimeSeries resources belonging to the same TensorboardRun resource (parent resource)." + }, + "etag": { + "description": "Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "createTime": { + "type": "string", + "description": "Output only. Timestamp when this TensorboardTimeSeries was created.", + "format": "google-datetime", + "readOnly": true + } + } + }, + "GoogleCloudAiplatformV1beta1FeatureMonitoringStatsAnomaly": { + "properties": { + "objective": { + "type": "string", + "enum": [ + "OBJECTIVE_UNSPECIFIED", + "IMPORT_FEATURE_ANALYSIS", + "SNAPSHOT_ANALYSIS" + ], + "enumDescriptions": [ + "If it's OBJECTIVE_UNSPECIFIED, monitoring_stats will be empty.", + "Stats are generated by Import Feature Analysis.", + "Stats are generated by Snapshot Analysis." + ], + "readOnly": true, + "description": "Output only. The objective for each stats." + }, + "featureStatsAnomaly": { + "description": "Output only. The stats and anomalies generated at specific timestamp.", + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1FeatureStatsAnomaly" + } + }, + "id": "GoogleCloudAiplatformV1beta1FeatureMonitoringStatsAnomaly", + "description": "A list of historical SnapshotAnalysis or ImportFeaturesAnalysis stats requested by user, sorted by FeatureStatsAnomaly.start_time descending.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessInput": { + "type": "object", + "description": "Input for summarization helpfulness metric.", + "properties": { + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessSpec", + "description": "Required. Spec for summarization helpfulness score metric." + }, + "instance": { + "$ref": "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessInstance", + "description": "Required. Summarization helpfulness instance." + } + }, + "id": "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessInput" + }, + "GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesResponse": { + "id": "GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesResponse", + "description": "Response message for JobService.SearchModelDeploymentMonitoringStatsAnomalies.", + "type": "object", + "properties": { + "monitoringStats": { + "description": "Stats retrieved for requested objectives. There are at most 1000 ModelMonitoringStatsAnomalies.FeatureHistoricStatsAnomalies.prediction_stats in the response.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomalies" + }, + "type": "array" + }, + "nextPageToken": { + "description": "The page token that can be used by the next JobService.SearchModelDeploymentMonitoringStatsAnomalies call.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecDiscreteValueCondition": { + "id": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecDiscreteValueCondition", + "description": "Represents the spec to match discrete values from parent parameter.", + "type": "object", + "properties": { + "values": { + "type": "array", + "items": { + "format": "double", + "type": "number" + }, + "description": "Required. Matches values of the parent parameter of 'DISCRETE' type. All values must exist in `discrete_value_spec` of parent parameter. The Epsilon of the value matching is 1e-10." + } + } + }, + "GoogleCloudAiplatformV1beta1FeatureViewSync": { + "properties": { + "finalStatus": { + "$ref": "GoogleRpcStatus", + "readOnly": true, + "description": "Output only. Final status of the FeatureViewSync." + }, + "runTime": { + "readOnly": true, + "$ref": "GoogleTypeInterval", + "description": "Output only. Time when this FeatureViewSync is finished." + }, + "createTime": { + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Time when this FeatureViewSync is created. Creation of a FeatureViewSync means that the job is pending / waiting for sufficient resources but may not have started the actual data transfer yet.", + "type": "string" + }, + "syncSummary": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureViewSyncSyncSummary", + "readOnly": true, + "description": "Output only. Summary of the sync job." + }, + "name": { + "description": "Identifier. Name of the FeatureViewSync. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}/featureViewSyncs/{feature_view_sync}`", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1FeatureViewSync", + "type": "object", + "description": "FeatureViewSync is a representation of sync operation which copies data from data source to Feature View in Online Store." + }, + "GoogleCloudAiplatformV1beta1SchemaVideoDataItem": { + "id": "GoogleCloudAiplatformV1beta1SchemaVideoDataItem", + "type": "object", + "description": "Payload of Video DataItem.", + "properties": { + "mimeType": { + "description": "Output only. The mime type of the content of the video. Only the videos in below listed mime types are supported. Supported mime_type: - video/mp4 - video/avi - video/quicktime", + "type": "string", + "readOnly": true + }, + "gcsUri": { + "description": "Required. Google Cloud Storage URI points to the original video in user's bucket. The video is up to 50 GB in size and up to 3 hour in duration.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1MigratableResource": { + "id": "GoogleCloudAiplatformV1beta1MigratableResource", + "description": "Represents one resource that exists in automl.googleapis.com, datalabeling.googleapis.com or ml.googleapis.com.", + "properties": { + "lastUpdateTime": { + "readOnly": true, + "description": "Output only. Timestamp when this MigratableResource was last updated.", + "type": "string", + "format": "google-datetime" + }, + "dataLabelingDataset": { + "readOnly": true, + "description": "Output only. Represents one Dataset in datalabeling.googleapis.com.", + "$ref": "GoogleCloudAiplatformV1beta1MigratableResourceDataLabelingDataset" + }, + "automlModel": { + "description": "Output only. Represents one Model in automl.googleapis.com.", + "$ref": "GoogleCloudAiplatformV1beta1MigratableResourceAutomlModel", + "readOnly": true + }, + "lastMigrateTime": { + "type": "string", + "format": "google-datetime", + "description": "Output only. Timestamp when the last migration attempt on this MigratableResource started. Will not be set if there's no migration attempt on this MigratableResource.", + "readOnly": true + }, + "mlEngineModelVersion": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1MigratableResourceMlEngineModelVersion", + "description": "Output only. Represents one Version in ml.googleapis.com." + }, + "automlDataset": { + "description": "Output only. Represents one Dataset in automl.googleapis.com.", + "$ref": "GoogleCloudAiplatformV1beta1MigratableResourceAutomlDataset", + "readOnly": true + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecFeatureAttributionSpec": { + "type": "object", + "properties": { + "featureAlertConditions": { + "description": "Per feature alert condition will override default alert condition.", + "type": "object", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition" + } + }, + "batchExplanationDedicatedResources": { + "description": "The config of resources used by the Model Monitoring during the batch explanation for non-AutoML models. If not set, `n1-standard-2` machine type will be used by default.", + "$ref": "GoogleCloudAiplatformV1beta1BatchDedicatedResources" + }, + "defaultAlertCondition": { + "description": "Default alert condition for all the features.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition" + }, + "features": { + "type": "array", + "items": { + "type": "string" + }, + "description": "Feature names interested in monitoring. These should be a subset of the input feature names specified in the monitoring schema. If the field is not specified all features outlied in the monitoring schema will be used." + } + }, + "description": "Feature attribution monitoring spec.", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecFeatureAttributionSpec" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigExplanationConfig": { + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigExplanationConfig", + "type": "object", + "properties": { + "explanationBaseline": { + "description": "Predictions generated by the BatchPredictionJob using baseline dataset.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaseline" + }, + "enableFeatureAttributes": { + "description": "If want to analyze the Vertex Explainable AI feature attribute scores or not. If set to true, Vertex AI will log the feature attributions from explain response and do the skew/drift detection for them.", + "type": "boolean" + } + }, + "description": "The config for integrating with Vertex Explainable AI. Only applicable if the Model has explanation_spec populated." + }, + "GoogleCloudAiplatformV1beta1WriteTensorboardRunDataResponse": { + "description": "Response message for TensorboardService.WriteTensorboardRunData.", + "type": "object", + "properties": {}, + "id": "GoogleCloudAiplatformV1beta1WriteTensorboardRunDataResponse" + }, + "GoogleCloudAiplatformV1beta1UpsertDatapointsResponse": { + "description": "Response message for IndexService.UpsertDatapoints", + "type": "object", + "properties": {}, + "id": "GoogleCloudAiplatformV1beta1UpsertDatapointsResponse" + }, + "GoogleCloudAiplatformV1beta1CreateNotebookRuntimeTemplateOperationMetadata": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1CreateNotebookRuntimeTemplateOperationMetadata", + "description": "Metadata information for NotebookService.CreateNotebookRuntimeTemplate.", + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + } + }, + "GoogleCloudAiplatformV1beta1RaySpec": { + "id": "GoogleCloudAiplatformV1beta1RaySpec", + "type": "object", + "properties": { + "imageUri": { + "type": "string", + "description": "Optional. Default image for user to choose a preferred ML framework (for example, TensorFlow or Pytorch) by choosing from [Vertex prebuilt images](https://cloud.google.com/vertex-ai/docs/training/pre-built-containers). Either this or the resource_pool_images is required. Use this field if you need all the resource pools to have the same Ray image. Otherwise, use the {@code resource_pool_images} field." + }, + "headNodeResourcePoolId": { + "type": "string", + "description": "Optional. This will be used to indicate which resource pool will serve as the Ray head node(the first node within that pool). Will use the machine from the first workerpool as the head node by default if this field isn't set." + }, + "rayLogsSpec": { + "$ref": "GoogleCloudAiplatformV1beta1RayLogsSpec", + "description": "Optional. OSS Ray logging configurations." + }, + "rayMetricSpec": { + "$ref": "GoogleCloudAiplatformV1beta1RayMetricSpec", + "description": "Optional. Ray metrics configurations." + }, + "resourcePoolImages": { + "type": "object", + "additionalProperties": { + "type": "string" + }, + "description": "Optional. Required if image_uri isn't set. A map of resource_pool_id to prebuild Ray image if user need to use different images for different head/worker pools. This map needs to cover all the resource pool ids. Example: { \"ray_head_node_pool\": \"head image\" \"ray_worker_node_pool1\": \"worker image\" \"ray_worker_node_pool2\": \"another worker image\" }" + } + }, + "description": "Configuration information for the Ray cluster. For experimental launch, Ray cluster creation and Persistent cluster creation are 1:1 mapping: We will provision all the nodes within the Persistent cluster as Ray nodes." + }, + "GoogleCloudAiplatformV1beta1MutateDeployedIndexOperationMetadata": { + "description": "Runtime operation information for IndexEndpointService.MutateDeployedIndex.", + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + }, + "deployedIndexId": { + "type": "string", + "description": "The unique index id specified by user" + } + }, + "id": "GoogleCloudAiplatformV1beta1MutateDeployedIndexOperationMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTextSegment": { + "properties": { + "content": { + "description": "The text content in the segment for output only.", + "type": "string" + }, + "startOffset": { + "type": "string", + "format": "uint64", + "description": "Zero-based character index of the first character of the text segment (counting characters from the beginning of the text)." + }, + "endOffset": { + "type": "string", + "format": "uint64", + "description": "Zero-based character index of the first character past the end of the text segment (counting character from the beginning of the text). The character at the end_offset is NOT included in the text segment." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTextSegment", + "description": "The text segment inside of DataItem." + }, + "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceInput": { + "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceInput", + "description": "Input for question answering relevance metric.", + "type": "object", + "properties": { + "instance": { + "description": "Required. Question answering relevance instance.", + "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceInstance" + }, + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceSpec", + "description": "Required. Spec for question answering relevance score metric." + } + } + }, + "GoogleCloudAiplatformV1beta1Segment": { + "properties": { + "endIndex": { + "readOnly": true, + "type": "integer", + "description": "Output only. End index in the given Part, measured in bytes. Offset from the start of the Part, exclusive, starting at zero.", + "format": "int32" + }, + "text": { + "description": "Output only. The text corresponding to the segment from the response.", + "readOnly": true, + "type": "string" + }, + "partIndex": { + "type": "integer", + "description": "Output only. The index of a Part object within its parent Content object.", + "readOnly": true, + "format": "int32" + }, + "startIndex": { + "type": "integer", + "readOnly": true, + "description": "Output only. Start index in the given Part, measured in bytes. Offset from the start of the Part, inclusive, starting at zero.", + "format": "int32" + } + }, + "id": "GoogleCloudAiplatformV1beta1Segment", + "description": "Segment of the content.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1UpdateModelDeploymentMonitoringJobOperationMetadata": { + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "description": "Runtime operation information for JobService.UpdateModelDeploymentMonitoringJob.", + "id": "GoogleCloudAiplatformV1beta1UpdateModelDeploymentMonitoringJobOperationMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetailContainerDetail": { + "id": "GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetailContainerDetail", + "properties": { + "failedPreCachingCheckJobs": { + "items": { + "type": "string" + }, + "readOnly": true, + "description": "Output only. The names of the previously failed CustomJob for the pre-caching-check container executions. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events. The list includes the all attempts in chronological order.", + "type": "array" + }, + "failedMainJobs": { + "readOnly": true, + "items": { + "type": "string" + }, + "type": "array", + "description": "Output only. The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order." + }, + "mainJob": { + "description": "Output only. The name of the CustomJob for the main container execution.", + "type": "string", + "readOnly": true + }, + "preCachingCheckJob": { + "description": "Output only. The name of the CustomJob for the pre-caching-check container execution. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events.", + "readOnly": true, + "type": "string" + } + }, + "type": "object", + "description": "The detail of a container execution. It contains the job names of the lifecycle of a container execution." + }, + "GoogleCloudAiplatformV1beta1DeployedModelRef": { + "properties": { + "endpoint": { + "description": "Immutable. A resource name of an Endpoint.", + "type": "string" + }, + "deployedModelId": { + "type": "string", + "description": "Immutable. An ID of a DeployedModel in the above Endpoint." + } + }, + "description": "Points to a DeployedModel.", + "id": "GoogleCloudAiplatformV1beta1DeployedModelRef", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1DataItemView": { + "description": "A container for a single DataItem and Annotations on it.", + "id": "GoogleCloudAiplatformV1beta1DataItemView", + "type": "object", + "properties": { + "hasTruncatedAnnotations": { + "type": "boolean", + "description": "True if and only if the Annotations field has been truncated. It happens if more Annotations for this DataItem met the request's annotation_filter than are allowed to be returned by annotations_limit. Note that if Annotations field is not being returned due to field mask, then this field will not be set to true no matter how many Annotations are there." + }, + "annotations": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Annotation" + }, + "description": "The Annotations on the DataItem. If too many Annotations should be returned for the DataItem, this field will be truncated per annotations_limit in request. If it was, then the has_truncated_annotations will be set to true." + }, + "dataItem": { + "description": "The DataItem.", + "$ref": "GoogleCloudAiplatformV1beta1DataItem" + } + } + }, + "GoogleCloudAiplatformV1beta1SupervisedTuningSpec": { + "properties": { + "validationDatasetUri": { + "description": "Optional. Cloud Storage path to file containing validation dataset for tuning. The dataset must be formatted as a JSONL file.", + "type": "string" + }, + "hyperParameters": { + "description": "Optional. Hyperparameters for SFT.", + "$ref": "GoogleCloudAiplatformV1beta1SupervisedHyperParameters" + }, + "trainingDatasetUri": { + "description": "Required. Cloud Storage path to file containing training dataset for tuning. The dataset must be formatted as a JSONL file.", + "type": "string" + } + }, + "type": "object", + "description": "Tuning Spec for Supervised Tuning.", + "id": "GoogleCloudAiplatformV1beta1SupervisedTuningSpec" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecasting": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecasting", + "properties": { + "metadata": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingMetadata", + "description": "The metadata information." + }, + "inputs": { + "description": "The input parameters of this TrainingJob.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputs" + } + }, + "description": "A TrainingJob that trains and uploads an AutoML Forecasting Model.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1UndeployModelOperationMetadata": { + "id": "GoogleCloudAiplatformV1beta1UndeployModelOperationMetadata", + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "type": "object", + "description": "Runtime operation information for EndpointService.UndeployModel." + }, + "GoogleCloudAiplatformV1beta1ToolNameMatchInstance": { + "id": "GoogleCloudAiplatformV1beta1ToolNameMatchInstance", + "description": "Spec for tool name match instance.", + "properties": { + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + }, + "reference": { + "type": "string", + "description": "Required. Ground truth used to compare against the prediction." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1RawPredictRequest": { + "id": "GoogleCloudAiplatformV1beta1RawPredictRequest", + "description": "Request message for PredictionService.RawPredict.", + "properties": { + "httpBody": { + "description": "The prediction input. Supports HTTP headers and arbitrary data payload. A DeployedModel may have an upper limit on the number of instances it supports per request. When this limit it is exceeded for an AutoML model, the RawPredict method returns an error. When this limit is exceeded for a custom-trained model, the behavior varies depending on the model. You can specify the schema for each instance in the predict_schemata.instance_schema_uri field when you create a Model. This schema applies when you deploy the `Model` as a `DeployedModel` to an Endpoint and use the `RawPredict` method.", + "$ref": "GoogleApiHttpBody" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1IndexEndpoint": { + "properties": { + "publicEndpointEnabled": { + "description": "Optional. If true, the deployed index will be accessible through public endpoint.", + "type": "boolean" + }, + "encryptionSpec": { + "description": "Immutable. Customer-managed encryption key spec for an IndexEndpoint. If set, this IndexEndpoint and all sub-resources of this IndexEndpoint will be secured by this key.", + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" + }, + "description": { + "type": "string", + "description": "The description of the IndexEndpoint." + }, + "publicEndpointDomainName": { + "description": "Output only. If public_endpoint_enabled is true, this field will be populated with the domain name to use for this index endpoint.", + "type": "string", + "readOnly": true + }, + "enablePrivateServiceConnect": { + "deprecated": true, + "description": "Optional. Deprecated: If true, expose the IndexEndpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.", + "type": "boolean" + }, + "updateTime": { + "type": "string", + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Timestamp when this IndexEndpoint was last updated. This timestamp is not updated when the endpoint's DeployedIndexes are updated, e.g. due to updates of the original Indexes they are the deployments of." + }, + "createTime": { + "description": "Output only. Timestamp when this IndexEndpoint was created.", + "type": "string", + "readOnly": true, + "format": "google-datetime" + }, + "privateServiceConnectConfig": { + "$ref": "GoogleCloudAiplatformV1beta1PrivateServiceConnectConfig", + "description": "Optional. Configuration for private service connect. network and private_service_connect_config are mutually exclusive." + }, + "name": { + "type": "string", + "description": "Output only. The resource name of the IndexEndpoint.", + "readOnly": true + }, + "network": { + "type": "string", + "description": "Optional. The full name of the Google Compute Engine [network](https://cloud.google.com/compute/docs/networks-and-firewalls#networks) to which the IndexEndpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. network and private_service_connect_config are mutually exclusive. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert): `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in '12345', and {network} is network name." + }, + "deployedIndexes": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1DeployedIndex" + }, + "description": "Output only. The indexes deployed in this endpoint.", + "type": "array", + "readOnly": true + }, + "labels": { + "type": "object", + "description": "The labels with user-defined metadata to organize your IndexEndpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", + "additionalProperties": { + "type": "string" + } + }, + "etag": { + "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", + "type": "string" + }, + "displayName": { + "description": "Required. The display name of the IndexEndpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.", + "type": "string" + } + }, + "description": "Indexes are deployed into it. An IndexEndpoint can have multiple DeployedIndexes.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1IndexEndpoint" + }, + "GoogleCloudAiplatformV1beta1MetadataStore": { + "properties": { + "encryptionSpec": { + "description": "Customer-managed encryption key spec for a Metadata Store. If set, this Metadata Store and all sub-resources of this Metadata Store are secured using this key.", + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" + }, + "createTime": { + "readOnly": true, + "description": "Output only. Timestamp when this MetadataStore was created.", + "type": "string", + "format": "google-datetime" + }, + "description": { + "type": "string", + "description": "Description of the MetadataStore." + }, + "name": { + "readOnly": true, + "description": "Output only. The resource name of the MetadataStore instance.", + "type": "string" + }, + "updateTime": { + "type": "string", + "format": "google-datetime", + "description": "Output only. Timestamp when this MetadataStore was last updated.", + "readOnly": true + }, + "dataplexConfig": { + "$ref": "GoogleCloudAiplatformV1beta1MetadataStoreDataplexConfig", + "description": "Optional. Dataplex integration settings." + }, + "state": { + "$ref": "GoogleCloudAiplatformV1beta1MetadataStoreMetadataStoreState", + "readOnly": true, + "description": "Output only. State information of the MetadataStore." + } + }, + "description": "Instance of a metadata store. Contains a set of metadata that can be queried.", + "id": "GoogleCloudAiplatformV1beta1MetadataStore", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesRequest": { + "type": "object", + "description": "Request message for JobService.SearchModelDeploymentMonitoringStatsAnomalies.", + "properties": { + "pageSize": { + "description": "The standard list page size.", + "type": "integer", + "format": "int32" + }, + "deployedModelId": { + "type": "string", + "description": "Required. The DeployedModel ID of the [ModelDeploymentMonitoringObjectiveConfig.deployed_model_id]." + }, + "startTime": { + "description": "The earliest timestamp of stats being generated. If not set, indicates fetching stats till the earliest possible one.", + "format": "google-datetime", + "type": "string" + }, + "endTime": { + "type": "string", + "description": "The latest timestamp of stats being generated. If not set, indicates feching stats till the latest possible one.", + "format": "google-datetime" + }, + "pageToken": { + "type": "string", + "description": "A page token received from a previous JobService.SearchModelDeploymentMonitoringStatsAnomalies call." + }, + "featureDisplayName": { + "type": "string", + "description": "The feature display name. If specified, only return the stats belonging to this feature. Format: ModelMonitoringStatsAnomalies.FeatureHistoricStatsAnomalies.feature_display_name, example: \"user_destination\"." + }, + "objectives": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesRequestStatsAnomaliesObjective" + }, + "description": "Required. Objectives of the stats to retrieve.", + "type": "array" + } + }, + "id": "GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesRequest" + }, + "GoogleCloudAiplatformV1beta1CreateFeaturestoreOperationMetadata": { + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "Operation metadata for Featurestore." + } + }, + "description": "Details of operations that perform create Featurestore.", + "id": "GoogleCloudAiplatformV1beta1CreateFeaturestoreOperationMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1DiskSpec": { + "description": "Represents the spec of disk options.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1DiskSpec", + "properties": { + "bootDiskType": { + "type": "string", + "description": "Type of the boot disk (default is \"pd-ssd\"). Valid values: \"pd-ssd\" (Persistent Disk Solid State Drive) or \"pd-standard\" (Persistent Disk Hard Disk Drive)." + }, + "bootDiskSizeGb": { + "type": "integer", + "format": "int32", + "description": "Size in GB of the boot disk (default is 100GB)." + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation", + "type": "object", + "properties": { + "text": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTextTransformation" + }, + "numeric": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationNumericTransformation" + }, + "timestamp": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTimestampTransformation" + }, + "auto": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationAutoTransformation" + }, + "categorical": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationCategoricalTransformation" + } + } + }, + "GoogleCloudAiplatformV1beta1BatchCreateTensorboardTimeSeriesRequest": { + "description": "Request message for TensorboardService.BatchCreateTensorboardTimeSeries.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1BatchCreateTensorboardTimeSeriesRequest", + "properties": { + "requests": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1CreateTensorboardTimeSeriesRequest" + }, + "description": "Required. The request message specifying the TensorboardTimeSeries to create. A maximum of 1000 TensorboardTimeSeries can be created in a batch.", + "type": "array" + } + } + }, + "GoogleCloudAiplatformV1beta1BatchCreateTensorboardTimeSeriesResponse": { + "properties": { + "tensorboardTimeSeries": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardTimeSeries" + }, + "type": "array", + "description": "The created TensorboardTimeSeries." + } + }, + "id": "GoogleCloudAiplatformV1beta1BatchCreateTensorboardTimeSeriesResponse", + "type": "object", + "description": "Response message for TensorboardService.BatchCreateTensorboardTimeSeries." + }, + "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigSnapshotAnalysis": { + "description": "Configuration of the Featurestore's Snapshot Analysis Based Monitoring. This type of analysis generates statistics for each Feature based on a snapshot of the latest feature value of each entities every monitoring_interval.", + "properties": { + "monitoringInterval": { + "format": "google-duration", + "deprecated": true, + "description": "Configuration of the snapshot analysis based monitoring pipeline running interval. The value is rolled up to full day. If both monitoring_interval_days and the deprecated `monitoring_interval` field are set when creating/updating EntityTypes/Features, monitoring_interval_days will be used.", + "type": "string" + }, + "disabled": { + "description": "The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.", + "type": "boolean" + }, + "stalenessDays": { + "type": "integer", + "format": "int32", + "description": "Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days." + }, + "monitoringIntervalDays": { + "description": "Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.", + "format": "int32", + "type": "integer" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigSnapshotAnalysis" + }, + "GoogleCloudAiplatformV1beta1IndexPrivateEndpoints": { + "description": "IndexPrivateEndpoints proto is used to provide paths for users to send requests via private endpoints (e.g. private service access, private service connect). To send request via private service access, use match_grpc_address. To send request via private service connect, use service_attachment.", + "id": "GoogleCloudAiplatformV1beta1IndexPrivateEndpoints", + "properties": { + "serviceAttachment": { + "type": "string", + "readOnly": true, + "description": "Output only. The name of the service attachment resource. Populated if private service connect is enabled." + }, + "pscAutomatedEndpoints": { + "type": "array", + "description": "Output only. PscAutomatedEndpoints is populated if private service connect is enabled if PscAutomatedConfig is set.", + "readOnly": true, + "items": { + "$ref": "GoogleCloudAiplatformV1beta1PscAutomatedEndpoints" + } + }, + "matchGrpcAddress": { + "type": "string", + "readOnly": true, + "description": "Output only. The ip address used to send match gRPC requests." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ListEntityTypesResponse": { + "properties": { + "entityTypes": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1EntityType" + }, + "description": "The EntityTypes matching the request." + }, + "nextPageToken": { + "description": "A token, which can be sent as ListEntityTypesRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", + "type": "string" + } + }, + "description": "Response message for FeaturestoreService.ListEntityTypes.", + "id": "GoogleCloudAiplatformV1beta1ListEntityTypesResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1MutateDeployedModelResponse": { + "type": "object", + "description": "Response message for EndpointService.MutateDeployedModel.", + "id": "GoogleCloudAiplatformV1beta1MutateDeployedModelResponse", + "properties": { + "deployedModel": { + "$ref": "GoogleCloudAiplatformV1beta1DeployedModel", + "description": "The DeployedModel that's being mutated." + } + } + }, + "GoogleCloudAiplatformV1beta1ExportDataRequest": { + "description": "Request message for DatasetService.ExportData.", + "id": "GoogleCloudAiplatformV1beta1ExportDataRequest", + "properties": { + "exportConfig": { + "$ref": "GoogleCloudAiplatformV1beta1ExportDataConfig", + "description": "Required. The desired output location." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1NotebookRuntime": { + "description": "A runtime is a virtual machine allocated to a particular user for a particular Notebook file on temporary basis with lifetime limited to 24 hours.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1NotebookRuntime", + "properties": { + "displayName": { + "type": "string", + "description": "Required. The display name of the NotebookRuntime. The name can be up to 128 characters long and can consist of any UTF-8 characters." + }, + "version": { + "description": "Output only. The VM os image version of NotebookRuntime.", + "readOnly": true, + "type": "string" + }, + "createTime": { + "description": "Output only. Timestamp when this NotebookRuntime was created.", + "type": "string", + "readOnly": true, + "format": "google-datetime" + }, + "idleShutdownConfig": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1NotebookIdleShutdownConfig", + "description": "Output only. The idle shutdown configuration of the notebook runtime." + }, + "proxyUri": { + "type": "string", + "readOnly": true, + "description": "Output only. The proxy endpoint used to access the NotebookRuntime." + }, + "isUpgradable": { + "type": "boolean", + "readOnly": true, + "description": "Output only. Whether NotebookRuntime is upgradable." + }, + "networkTags": { + "type": "array", + "description": "Optional. The Compute Engine tags to add to runtime (see [Tagging instances](https://cloud.google.com/vpc/docs/add-remove-network-tags)).", + "items": { + "type": "string" + } + }, + "encryptionSpec": { + "description": "Output only. Customer-managed encryption key spec for the notebook runtime.", + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" + }, + "healthState": { + "enumDescriptions": [ + "Unspecified health state.", + "NotebookRuntime is in healthy state. Applies to ACTIVE state.", + "NotebookRuntime is in unhealthy state. Applies to ACTIVE state." + ], + "type": "string", + "enum": [ + "HEALTH_STATE_UNSPECIFIED", + "HEALTHY", + "UNHEALTHY" + ], + "readOnly": true, + "description": "Output only. The health state of the NotebookRuntime." + }, + "description": { + "description": "The description of the NotebookRuntime.", + "type": "string" + }, + "runtimeState": { + "type": "string", + "enum": [ + "RUNTIME_STATE_UNSPECIFIED", + "RUNNING", + "BEING_STARTED", + "BEING_STOPPED", + "STOPPED", + "BEING_UPGRADED", + "ERROR", + "INVALID" + ], + "description": "Output only. The runtime (instance) state of the NotebookRuntime.", + "readOnly": true, + "enumDescriptions": [ + "Unspecified runtime state.", + "NotebookRuntime is in running state.", + "NotebookRuntime is in starting state.", + "NotebookRuntime is in stopping state.", + "NotebookRuntime is in stopped state.", + "NotebookRuntime is in upgrading state. It is in the middle of upgrading process.", + "NotebookRuntime was unable to start/stop properly.", + "NotebookRuntime is in invalid state. Cannot be recovered." + ] + }, + "updateTime": { + "type": "string", + "readOnly": true, + "format": "google-datetime", + "description": "Output only. Timestamp when this NotebookRuntime was most recently updated." + }, + "serviceAccount": { + "type": "string", + "readOnly": true, + "description": "Output only. The service account that the NotebookRuntime workload runs as." + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "description": "The labels with user-defined metadata to organize your NotebookRuntime. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one NotebookRuntime (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable. Following system labels exist for NotebookRuntime: * \"aiplatform.googleapis.com/notebook_runtime_gce_instance_id\": output only, its value is the Compute Engine instance id. * \"aiplatform.googleapis.com/colab_enterprise_entry_service\": its value is either \"bigquery\" or \"vertex\"; if absent, it should be \"vertex\". This is to describe the entry service, either BigQuery or Vertex.", + "type": "object" + }, + "runtimeUser": { + "description": "Required. The user email of the NotebookRuntime.", + "type": "string" + }, + "satisfiesPzi": { + "readOnly": true, + "type": "boolean", + "description": "Output only. Reserved for future use." + }, + "notebookRuntimeType": { + "description": "Output only. The type of the notebook runtime.", + "type": "string", + "enumDescriptions": [ + "Unspecified notebook runtime type, NotebookRuntimeType will default to USER_DEFINED.", + "runtime or template with coustomized configurations from user.", + "runtime or template with system defined configurations." + ], + "readOnly": true, + "enum": [ + "NOTEBOOK_RUNTIME_TYPE_UNSPECIFIED", + "USER_DEFINED", + "ONE_CLICK" + ] + }, + "satisfiesPzs": { + "readOnly": true, + "type": "boolean", + "description": "Output only. Reserved for future use." + }, + "expirationTime": { + "type": "string", + "description": "Output only. Timestamp when this NotebookRuntime will be expired: 1. System Predefined NotebookRuntime: 24 hours after creation. After expiration, system predifined runtime will be deleted. 2. User created NotebookRuntime: 6 months after last upgrade. After expiration, user created runtime will be stopped and allowed for upgrade.", + "format": "google-datetime", + "readOnly": true + }, + "notebookRuntimeTemplateRef": { + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplateRef", + "description": "Output only. The pointer to NotebookRuntimeTemplate this NotebookRuntime is created from." + }, + "name": { + "description": "Output only. The resource name of the NotebookRuntime.", + "readOnly": true, + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfig": { + "description": "The objective configuration for model monitoring, including the information needed to detect anomalies for one particular model.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfig", + "properties": { + "trainingPredictionSkewDetectionConfig": { + "description": "The config for skew between training data and prediction data.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig" + }, + "explanationConfig": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigExplanationConfig", + "description": "The config for integrating with Vertex Explainable AI." + }, + "trainingDataset": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigTrainingDataset", + "description": "Training dataset for models. This field has to be set only if TrainingPredictionSkewDetectionConfig is specified." + }, + "predictionDriftDetectionConfig": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig", + "description": "The config for drift of prediction data." + } + } + }, + "GoogleCloudAiplatformV1beta1ReadFeatureValuesRequest": { + "description": "Request message for FeaturestoreOnlineServingService.ReadFeatureValues.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ReadFeatureValuesRequest", + "properties": { + "featureSelector": { + "description": "Required. Selector choosing Features of the target EntityType.", + "$ref": "GoogleCloudAiplatformV1beta1FeatureSelector" + }, + "entityId": { + "type": "string", + "description": "Required. ID for a specific entity. For example, for a machine learning model predicting user clicks on a website, an entity ID could be `user_123`." + } + } + }, + "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessResult": { + "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessResult", + "type": "object", + "description": "Spec for question answering correctness result.", + "properties": { + "explanation": { + "type": "string", + "readOnly": true, + "description": "Output only. Explanation for question answering correctness score." + }, + "score": { + "type": "number", + "description": "Output only. Question Answering Correctness score.", + "readOnly": true, + "format": "float" + }, + "confidence": { + "format": "float", + "readOnly": true, + "type": "number", + "description": "Output only. Confidence for question answering correctness score." + } + } + }, + "GoogleIamV1SetIamPolicyRequest": { + "type": "object", + "description": "Request message for `SetIamPolicy` method.", + "properties": { + "policy": { + "description": "REQUIRED: The complete policy to be applied to the `resource`. The size of the policy is limited to a few 10s of KB. An empty policy is a valid policy but certain Google Cloud services (such as Projects) might reject them.", + "$ref": "GoogleIamV1Policy" + } + }, + "id": "GoogleIamV1SetIamPolicyRequest" + }, + "GoogleCloudAiplatformV1beta1PauseModelDeploymentMonitoringJobRequest": { + "id": "GoogleCloudAiplatformV1beta1PauseModelDeploymentMonitoringJobRequest", + "description": "Request message for JobService.PauseModelDeploymentMonitoringJob.", + "type": "object", + "properties": {} + }, + "GoogleCloudAiplatformV1beta1BatchPredictionJobInstanceConfig": { + "type": "object", + "description": "Configuration defining how to transform batch prediction input instances to the instances that the Model accepts.", + "properties": { + "instanceType": { + "description": "The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format. Supported values are: * `object`: Each input is converted to JSON object format. * For `bigquery`, each row is converted to an object. * For `jsonl`, each line of the JSONL input must be an object. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. * `array`: Each input is converted to JSON array format. * For `bigquery`, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders. * For `jsonl`, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. If not specified, Vertex AI converts the batch prediction input as follows: * For `bigquery` and `csv`, the behavior is the same as `array`. The order of columns is the same as defined in the file or table, unless included_fields is populated. * For `jsonl`, the prediction instance format is determined by each line of the input. * For `tf-record`/`tf-record-gzip`, each record will be converted to an object in the format of `{\"b64\": }`, where `` is the Base64-encoded string of the content of the record. * For `file-list`, each file in the list will be converted to an object in the format of `{\"b64\": }`, where `` is the Base64-encoded string of the content of the file.", + "type": "string" + }, + "includedFields": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Fields that will be included in the prediction instance that is sent to the Model. If instance_type is `array`, the order of field names in included_fields also determines the order of the values in the array. When included_fields is populated, excluded_fields must be empty. The input must be JSONL with objects at each line, BigQuery or TfRecord." + }, + "keyField": { + "description": "The name of the field that is considered as a key. The values identified by the key field is not included in the transformed instances that is sent to the Model. This is similar to specifying this name of the field in excluded_fields. In addition, the batch prediction output will not include the instances. Instead the output will only include the value of the key field, in a field named `key` in the output: * For `jsonl` output format, the output will have a `key` field instead of the `instance` field. * For `csv`/`bigquery` output format, the output will have have a `key` column instead of the instance feature columns. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.", + "type": "string" + }, + "excludedFields": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Fields that will be excluded in the prediction instance that is sent to the Model. Excluded will be attached to the batch prediction output if key_field is not specified. When excluded_fields is populated, included_fields must be empty. The input must be JSONL with objects at each line, BigQuery or TfRecord." + } + }, + "id": "GoogleCloudAiplatformV1beta1BatchPredictionJobInstanceConfig" + }, + "GoogleCloudAiplatformV1beta1UpdateModelMonitorOperationMetadata": { + "description": "Runtime operation information for ModelMonitoringService.UpdateModelMonitor.", + "id": "GoogleCloudAiplatformV1beta1UpdateModelMonitorOperationMetadata", + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ListTrainingPipelinesResponse": { + "id": "GoogleCloudAiplatformV1beta1ListTrainingPipelinesResponse", + "description": "Response message for PipelineService.ListTrainingPipelines", + "properties": { + "nextPageToken": { + "description": "A token to retrieve the next page of results. Pass to ListTrainingPipelinesRequest.page_token to obtain that page.", + "type": "string" + }, + "trainingPipelines": { + "description": "List of TrainingPipelines in the requested page.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1TrainingPipeline" + } + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1NotebookExecutionJobDirectNotebookSource": { + "id": "GoogleCloudAiplatformV1beta1NotebookExecutionJobDirectNotebookSource", + "type": "object", + "properties": { + "content": { + "type": "string", + "description": "The base64-encoded contents of the input notebook file.", + "format": "byte" + } + }, + "description": "The content of the input notebook in ipynb format." + }, + "GoogleCloudAiplatformV1beta1RougeInput": { + "id": "GoogleCloudAiplatformV1beta1RougeInput", + "description": "Input for rouge metric.", + "properties": { + "metricSpec": { + "$ref": "GoogleCloudAiplatformV1beta1RougeSpec", + "description": "Required. Spec for rouge score metric." + }, + "instances": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1RougeInstance" + }, + "description": "Required. Repeated rouge instances." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ReadTensorboardBlobDataResponse": { + "properties": { + "blobs": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardBlob" + }, + "description": "Blob messages containing blob bytes." + } + }, + "description": "Response message for TensorboardService.ReadTensorboardBlobData.", + "id": "GoogleCloudAiplatformV1beta1ReadTensorboardBlobDataResponse", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ResumeScheduleRequest": { + "properties": { + "catchUp": { + "description": "Optional. Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. This will also update Schedule.catch_up field. Default to false.", + "type": "boolean" + } + }, + "description": "Request message for ScheduleService.ResumeSchedule.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ResumeScheduleRequest" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDataset": { + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDataset", + "type": "object", + "description": "Input dataset spec.", + "properties": { + "timestampField": { + "description": "The timestamp field. Usually for serving data.", + "type": "string" + }, + "vertexDataset": { + "type": "string", + "description": "Resource name of the Vertex AI managed dataset." + }, + "gcsSource": { + "description": "Google Cloud Storage data source.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDatasetModelMonitoringGcsSource" + }, + "bigquerySource": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDatasetModelMonitoringBigQuerySource", + "description": "BigQuery data source." + } + } + }, + "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpec": { + "description": "Specification for how the data should be sliced.", + "properties": { + "configs": { + "description": "Mapping configuration for this SliceSpec. The key is the name of the feature. By default, the key will be prefixed by \"instance\" as a dictionary prefix for Vertex Batch Predictions output format.", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecSliceConfig" + }, + "type": "object" + } + }, + "id": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpec", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ListArtifactsResponse": { + "id": "GoogleCloudAiplatformV1beta1ListArtifactsResponse", + "description": "Response message for MetadataService.ListArtifacts.", + "properties": { + "artifacts": { + "description": "The Artifacts retrieved from the MetadataStore.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Artifact" + }, + "type": "array" + }, + "nextPageToken": { + "description": "A token, which can be sent as ListArtifactsRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages.", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FetchFeatureValuesRequest": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1FetchFeatureValuesRequest", + "description": "Request message for FeatureOnlineStoreService.FetchFeatureValues. All the features under the requested feature view will be returned.", + "properties": { + "format": { + "enumDescriptions": [ + "Not set. Will be treated as the KeyValue format.", + "Return response data in key-value format.", + "Return response data in proto Struct format." + ], + "description": "Specify response data format. If not set, KeyValue format will be used. Deprecated. Use FetchFeatureValuesRequest.data_format.", + "deprecated": true, + "enum": [ + "FORMAT_UNSPECIFIED", + "KEY_VALUE", + "PROTO_STRUCT" + ], + "type": "string" + }, + "id": { + "deprecated": true, + "type": "string", + "description": "Simple ID. The whole string will be used as is to identify Entity to fetch feature values for." + }, + "dataKey": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDataKey", + "description": "Optional. The request key to fetch feature values for." + }, + "dataFormat": { + "enum": [ + "FEATURE_VIEW_DATA_FORMAT_UNSPECIFIED", + "KEY_VALUE", + "PROTO_STRUCT" + ], + "type": "string", + "description": "Optional. Response data format. If not set, FeatureViewDataFormat.KEY_VALUE will be used.", + "enumDescriptions": [ + "Not set. Will be treated as the KeyValue format.", + "Return response data in key-value format.", + "Return response data in proto Struct format." + ] + } + } + }, + "GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfig": { + "description": "The runtime config of a PipelineJob.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfig", + "properties": { + "inputArtifacts": { + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigInputArtifact" + }, + "description": "The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.", + "type": "object" + }, + "gcsOutputDirectory": { + "description": "Required. A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.", + "type": "string" + }, + "failurePolicy": { + "type": "string", + "description": "Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.", + "enum": [ + "PIPELINE_FAILURE_POLICY_UNSPECIFIED", + "PIPELINE_FAILURE_POLICY_FAIL_SLOW", + "PIPELINE_FAILURE_POLICY_FAIL_FAST" + ], + "enumDescriptions": [ + "Default value, and follows fail slow behavior.", + "Indicates that the pipeline should continue to run until all possible tasks have been scheduled and completed.", + "Indicates that the pipeline should stop scheduling new tasks after a task has failed." + ] + }, + "parameters": { + "description": "Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.", + "type": "object", + "deprecated": true, + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1Value" + } + }, + "parameterValues": { + "type": "object", + "description": "The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.", + "additionalProperties": { + "type": "any" + } + } + } + }, + "GoogleCloudAiplatformV1beta1ReportExecutionEventRequest": { + "type": "object", + "properties": { + "vmToken": { + "description": "Required. The VM identity token (a JWT) for authenticating the VM. https://cloud.google.com/compute/docs/instances/verifying-instance-identity", + "type": "string" + }, + "status": { + "$ref": "GoogleRpcStatus", + "description": "Optional. The error details of the event." + }, + "eventType": { + "type": "string", + "enumDescriptions": [ + "Unspecified.", + "Notebook execution process has started. Expect this message within expected time to provision compute.", + "Notebook execution process is completed. Expect this message within timeout.", + "Notebook execution process has failed. Expect this message within timeout." + ], + "description": "Required. The type of the event.", + "enum": [ + "EVENT_TYPE_UNSPECIFIED", + "ACTIVE", + "DONE", + "FAILED" + ] + } + }, + "description": "Request message for NotebookInternalService.ReportExecutionEvent.", + "id": "GoogleCloudAiplatformV1beta1ReportExecutionEventRequest" + }, + "GoogleCloudAiplatformV1beta1ModelMonitor": { + "properties": { + "notificationSpec": { + "description": "Optional default notification spec, it can be overridden in the ModelMonitoringJob notification spec.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpec" + }, + "outputSpec": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringOutputSpec", + "description": "Optional default monitoring metrics/logs export spec, it can be overridden in the ModelMonitoringJob output spec. If not specified, a default Google Cloud Storage bucket will be created under your project." + }, + "tabularObjective": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecTabularObjective", + "description": "Optional default tabular model monitoring objective." + }, + "trainingDataset": { + "description": "Optional training dataset used to train the model. It can serve as a reference dataset to identify changes in production.", + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringInput" + }, + "satisfiesPzs": { + "description": "Output only. Reserved for future use.", + "type": "boolean", + "readOnly": true + }, + "updateTime": { + "readOnly": true, + "type": "string", + "description": "Output only. Timestamp when this ModelMonitor was updated most recently.", + "format": "google-datetime" + }, + "satisfiesPzi": { + "type": "boolean", + "description": "Output only. Reserved for future use.", + "readOnly": true + }, + "modelMonitoringTarget": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitorModelMonitoringTarget", + "description": "The entity that is subject to analysis. Currently only models in Vertex AI Model Registry are supported. If you want to analyze the model which is outside the Vertex AI, you could register a model in Vertex AI Model Registry using just a display name." + }, + "displayName": { + "type": "string", + "description": "The display name of the ModelMonitor. The name can be up to 128 characters long and can consist of any UTF-8." + }, + "explanationSpec": { + "$ref": "GoogleCloudAiplatformV1beta1ExplanationSpec", + "description": "Optional model explanation spec. It is used for feature attribution monitoring." + }, + "name": { + "type": "string", + "description": "Immutable. Resource name of the ModelMonitor. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`." + }, + "createTime": { + "type": "string", + "format": "google-datetime", + "readOnly": true, + "description": "Output only. Timestamp when this ModelMonitor was created." + }, + "modelMonitoringSchema": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringSchema", + "description": "Monitoring Schema is to specify the model's features, prediction outputs and ground truth properties. It is used to extract pertinent data from the dataset and to process features based on their properties. Make sure that the schema aligns with your dataset, if it does not, we will be unable to extract data from the dataset. It is required for most models, but optional for Vertex AI AutoML Tables unless the schem information is not available." + } + }, + "id": "GoogleCloudAiplatformV1beta1ModelMonitor", + "description": "Vertex AI Model Monitoring Service serves as a central hub for the analysis and visualization of data quality and performance related to models. ModelMonitor stands as a top level resource for overseeing your model monitoring tasks.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig": { + "description": "The config for Training & Prediction data skew detection. It specifies the training dataset sources and the skew detection parameters.", + "properties": { + "skewThresholds": { + "type": "object", + "description": "Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature.", + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1ThresholdConfig" + } + }, + "defaultSkewThreshold": { + "$ref": "GoogleCloudAiplatformV1beta1ThresholdConfig", + "description": "Skew anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features." + }, + "attributionScoreSkewThresholds": { + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1ThresholdConfig" + }, + "type": "object", + "description": "Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature." + } + }, + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecSliceConfig": { + "properties": { + "value": { + "description": "A unique specific value for a given feature. Example: `{ \"value\": { \"string_value\": \"12345\" } }`", + "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecValue" + }, + "range": { + "description": "A range of values for a numerical feature. Example: `{\"range\":{\"low\":10000.0,\"high\":50000.0}}` will capture 12345 and 23334 in the slice.", + "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecRange" + }, + "allValues": { + "type": "boolean", + "description": "If all_values is set to true, then all possible labels of the keyed feature will have another slice computed. Example: `{\"all_values\":{\"value\":true}}`" + } + }, + "description": "Specification message containing the config for this SliceSpec. When `kind` is selected as `value` and/or `range`, only a single slice will be computed. When `all_values` is present, a separate slice will be computed for each possible label/value for the corresponding key in `config`. Examples, with feature zip_code with values 12345, 23334, 88888 and feature country with values \"US\", \"Canada\", \"Mexico\" in the dataset: Example 1: { \"zip_code\": { \"value\": { \"float_value\": 12345.0 } } } A single slice for any data with zip_code 12345 in the dataset. Example 2: { \"zip_code\": { \"range\": { \"low\": 12345, \"high\": 20000 } } } A single slice containing data where the zip_codes between 12345 and 20000 For this example, data with the zip_code of 12345 will be in this slice. Example 3: { \"zip_code\": { \"range\": { \"low\": 10000, \"high\": 20000 } }, \"country\": { \"value\": { \"string_value\": \"US\" } } } A single slice containing data where the zip_codes between 10000 and 20000 has the country \"US\". For this example, data with the zip_code of 12345 and country \"US\" will be in this slice. Example 4: { \"country\": {\"all_values\": { \"value\": true } } } Three slices are computed, one for each unique country in the dataset. Example 5: { \"country\": { \"all_values\": { \"value\": true } }, \"zip_code\": { \"value\": { \"float_value\": 12345.0 } } } Three slices are computed, one for each unique country in the dataset where the zip_code is also 12345. For this example, data with zip_code 12345 and country \"US\" will be in one slice, zip_code 12345 and country \"Canada\" in another slice, and zip_code 12345 and country \"Mexico\" in another slice, totaling 3 slices.", + "id": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecSliceConfig", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1DeployedModel": { + "properties": { + "model": { + "description": "Required. The resource name of the Model that this is the deployment of. Note that the Model may be in a different location than the DeployedModel's Endpoint. The resource name may contain version id or version alias to specify the version. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` if no version is specified, the default version will be deployed.", + "type": "string" + }, + "privateEndpoints": { + "description": "Output only. Provide paths for users to send predict/explain/health requests directly to the deployed model services running on Cloud via private services access. This field is populated if network is configured.", + "readOnly": true, + "$ref": "GoogleCloudAiplatformV1beta1PrivateEndpoints" + }, + "disableExplanations": { + "type": "boolean", + "description": "If true, deploy the model without explainable feature, regardless the existence of Model.explanation_spec or explanation_spec." + }, + "dedicatedResources": { + "$ref": "GoogleCloudAiplatformV1beta1DedicatedResources", + "description": "A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration." + }, + "explanationSpec": { + "$ref": "GoogleCloudAiplatformV1beta1ExplanationSpec", + "description": "Explanation configuration for this DeployedModel. When deploying a Model using EndpointService.DeployModel, this value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of explanation_spec is not populated, the value of the same field of Model.explanation_spec is inherited. If the corresponding Model.explanation_spec is not populated, all fields of the explanation_spec will be used for the explanation configuration." + }, + "id": { + "type": "string", + "description": "Immutable. The ID of the DeployedModel. If not provided upon deployment, Vertex AI will generate a value for this ID. This value should be 1-10 characters, and valid characters are `/[0-9]/`." + }, + "serviceAccount": { + "description": "The service account that the DeployedModel's container runs as. Specify the email address of the service account. If this service account is not specified, the container runs as a service account that doesn't have access to the resource project. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account.", + "type": "string" + }, + "createTime": { + "type": "string", + "readOnly": true, + "description": "Output only. Timestamp when the DeployedModel was created.", + "format": "google-datetime" + }, + "modelVersionId": { + "readOnly": true, + "description": "Output only. The version ID of the model that is deployed.", + "type": "string" + }, + "displayName": { + "type": "string", + "description": "The display name of the DeployedModel. If not provided upon creation, the Model's display_name is used." + }, + "enableContainerLogging": { + "type": "boolean", + "description": "If true, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging. Only supported for custom-trained Models and AutoML Tabular Models." + }, + "sharedResources": { + "description": "The resource name of the shared DeploymentResourcePool to deploy on. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", + "type": "string" + }, + "enableAccessLogging": { + "type": "boolean", + "description": "If true, online prediction access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each prediction request. Note that logs may incur a cost, especially if your project receives prediction requests at a high queries per second rate (QPS). Estimate your costs before enabling this option." + }, + "automaticResources": { + "$ref": "GoogleCloudAiplatformV1beta1AutomaticResources", + "description": "A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration." + } + }, + "type": "object", + "description": "A deployment of a Model. Endpoints contain one or more DeployedModels.", + "id": "GoogleCloudAiplatformV1beta1DeployedModel" + }, + "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateAutomlModelConfig": { + "properties": { + "modelDisplayName": { + "description": "Optional. Display name of the model in Vertex AI. System will pick a display name if unspecified.", + "type": "string" + }, + "model": { + "description": "Required. Full resource name of automl Model. Format: `projects/{project}/locations/{location}/models/{model}`.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateAutomlModelConfig", + "description": "Config for migrating Model in automl.googleapis.com to Vertex AI's Model." + }, + "GoogleCloudAiplatformV1beta1BatchMigrateResourcesOperationMetadata": { + "description": "Runtime operation information for MigrationService.BatchMigrateResources.", + "id": "GoogleCloudAiplatformV1beta1BatchMigrateResourcesOperationMetadata", + "properties": { + "partialResults": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1BatchMigrateResourcesOperationMetadataPartialResult" + }, + "description": "Partial results that reflect the latest migration operation progress.", + "type": "array" + }, + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "The common part of the operation metadata." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecDataDriftSpec": { + "description": "Data drift monitoring spec. Data drift measures the distribution distance between the current dataset and a baseline dataset. A typical use case is to detect data drift between the recent production serving dataset and the training dataset, or to compare the recent production dataset with a dataset from a previous period.", + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecDataDriftSpec", + "properties": { + "features": { + "type": "array", + "description": "Feature names / Prediction output names interested in monitoring. These should be a subset of the input feature names or prediction output names specified in the monitoring schema. If the field is not specified all features / prediction outputs outlied in the monitoring schema will be used.", + "items": { + "type": "string" + } + }, + "categoricalMetricType": { + "type": "string", + "description": "Supported metrics type: * l_infinity * jensen_shannon_divergence" + }, + "numericMetricType": { + "type": "string", + "description": "Supported metrics type: * jensen_shannon_divergence" + }, + "defaultNumericAlertCondition": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition", + "description": "Default alert condition for all the numeric features." + }, + "defaultCategoricalAlertCondition": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition", + "description": "Default alert condition for all the categorical features." + }, + "featureAlertConditions": { + "additionalProperties": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition" + }, + "type": "object", + "description": "Per feature alert condition will override default alert condition." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ListDatasetVersionsResponse": { + "id": "GoogleCloudAiplatformV1beta1ListDatasetVersionsResponse", + "type": "object", + "description": "Response message for DatasetService.ListDatasetVersions.", + "properties": { + "datasetVersions": { + "description": "A list of DatasetVersions that matches the specified filter in the request.", + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1DatasetVersion" + } + }, + "nextPageToken": { + "description": "The standard List next-page token.", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1Study": { + "type": "object", + "properties": { + "createTime": { + "description": "Output only. Time at which the study was created.", + "type": "string", + "readOnly": true, + "format": "google-datetime" + }, + "inactiveReason": { + "type": "string", + "description": "Output only. A human readable reason why the Study is inactive. This should be empty if a study is ACTIVE or COMPLETED.", + "readOnly": true + }, + "displayName": { + "type": "string", + "description": "Required. Describes the Study, default value is empty string." + }, + "state": { + "enumDescriptions": [ + "The study state is unspecified.", + "The study is active.", + "The study is stopped due to an internal error.", + "The study is done when the service exhausts the parameter search space or max_trial_count is reached." + ], + "description": "Output only. The detailed state of a Study.", + "readOnly": true, + "type": "string", + "enum": [ + "STATE_UNSPECIFIED", + "ACTIVE", + "INACTIVE", + "COMPLETED" + ] + }, + "name": { + "description": "Output only. The name of a study. The study's globally unique identifier. Format: `projects/{project}/locations/{location}/studies/{study}`", + "type": "string", + "readOnly": true + }, + "studySpec": { + "description": "Required. Configuration of the Study.", + "$ref": "GoogleCloudAiplatformV1beta1StudySpec" + } + }, + "description": "A message representing a Study.", + "id": "GoogleCloudAiplatformV1beta1Study" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningJobSpec": { + "properties": { + "trialJobSpec": { + "$ref": "GoogleCloudAiplatformV1beta1CustomJobSpec", + "description": "The spec of a trial job. The same spec applies to the CustomJobs created in all the trials." + }, + "maxTrialCount": { + "type": "integer", + "format": "int32", + "description": "The desired total number of Trials." + }, + "studySpec": { + "description": "Study configuration of the HyperparameterTuningJob.", + "$ref": "GoogleCloudAiplatformV1beta1StudySpec" + }, + "parallelTrialCount": { + "description": "The desired number of Trials to run in parallel.", + "format": "int32", + "type": "integer" + }, + "maxFailedTrialCount": { + "type": "integer", + "format": "int32", + "description": "The number of failed Trials that need to be seen before failing the HyperparameterTuningJob. If set to 0, Vertex AI decides how many Trials must fail before the whole job fails." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningJobSpec" + }, + "GoogleCloudAiplatformV1beta1ModelSourceInfo": { + "description": "Detail description of the source information of the model.", + "id": "GoogleCloudAiplatformV1beta1ModelSourceInfo", + "properties": { + "sourceType": { + "description": "Type of the model source.", + "enum": [ + "MODEL_SOURCE_TYPE_UNSPECIFIED", + "AUTOML", + "CUSTOM", + "BQML", + "MODEL_GARDEN", + "GENIE", + "CUSTOM_TEXT_EMBEDDING", + "MARKETPLACE" + ], + "enumDescriptions": [ + "Should not be used.", + "The Model is uploaded by automl training pipeline.", + "The Model is uploaded by user or custom training pipeline.", + "The Model is registered and sync'ed from BigQuery ML.", + "The Model is saved or tuned from Model Garden.", + "The Model is saved or tuned from Genie.", + "The Model is uploaded by text embedding finetuning pipeline.", + "The Model is saved or tuned from Marketplace." + ], + "type": "string" + }, + "copy": { + "description": "If this Model is copy of another Model. If true then source_type pertains to the original.", + "type": "boolean" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig": { + "properties": { + "overrideExistingTable": { + "type": "boolean", + "description": "If true and an export destination is specified, then the contents of the destination are overwritten. Otherwise, if the export destination already exists, then the export operation fails." + }, + "destinationBigqueryUri": { + "description": "URI of desired destination BigQuery table. Expected format: `bq://{project_id}:{dataset_id}:{table}` If not specified, then results are exported to the following auto-created BigQuery table: `{project_id}:export_evaluated_examples_{model_name}_{yyyy_MM_dd'T'HH_mm_ss_SSS'Z'}.evaluated_examples`", + "type": "string" + } + }, + "description": "Configuration for exporting test set predictions to a BigQuery table.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig" + }, + "GoogleCloudAiplatformV1beta1MigratableResourceMlEngineModelVersion": { + "id": "GoogleCloudAiplatformV1beta1MigratableResourceMlEngineModelVersion", + "type": "object", + "properties": { + "version": { + "type": "string", + "description": "Full resource name of ml engine model Version. Format: `projects/{project}/models/{model}/versions/{version}`." + }, + "endpoint": { + "type": "string", + "description": "The ml.googleapis.com endpoint that this model Version currently lives in. Example values: * ml.googleapis.com * us-centrall-ml.googleapis.com * europe-west4-ml.googleapis.com * asia-east1-ml.googleapis.com" + } + }, + "description": "Represents one model Version in ml.googleapis.com." + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationAutoTransformation": { + "description": "Training pipeline will infer the proper transformation based on the statistic of dataset.", + "type": "object", + "properties": { + "columnName": { + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationAutoTransformation" + }, + "GoogleCloudAiplatformV1beta1UndeployIndexRequest": { + "type": "object", + "properties": { + "deployedIndexId": { + "description": "Required. The ID of the DeployedIndex to be undeployed from the IndexEndpoint.", + "type": "string" + } + }, + "id": "GoogleCloudAiplatformV1beta1UndeployIndexRequest", + "description": "Request message for IndexEndpointService.UndeployIndex." + }, + "GoogleCloudAiplatformV1beta1ImportDataOperationMetadata": { + "properties": { + "genericMetadata": { + "description": "The common part of the operation metadata.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + }, + "description": "Runtime operation information for DatasetService.ImportData.", + "id": "GoogleCloudAiplatformV1beta1ImportDataOperationMetadata", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1GroundednessSpec": { + "id": "GoogleCloudAiplatformV1beta1GroundednessSpec", + "properties": { + "version": { + "description": "Optional. Which version to use for evaluation.", + "type": "integer", + "format": "int32" + } + }, + "description": "Spec for groundedness metric.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsFilter": { + "type": "object", + "properties": { + "tabularStatsFilter": { + "description": "Tabular statistics filter.", + "$ref": "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsFilterTabularStatsFilter" + } + }, + "id": "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsFilter", + "description": "Filter for searching ModelMonitoringStats." + }, + "GoogleCloudAiplatformV1beta1ToolNameMatchInput": { + "description": "Input for tool name match metric.", + "properties": { + "instances": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ToolNameMatchInstance" + }, + "description": "Required. Repeated tool name match instances.", + "type": "array" + }, + "metricSpec": { + "description": "Required. Spec for tool name match metric.", + "$ref": "GoogleCloudAiplatformV1beta1ToolNameMatchSpec" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ToolNameMatchInput" + }, + "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringBigQueryTable": { + "id": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringBigQueryTable", + "properties": { + "requestResponseLoggingSchemaVersion": { + "description": "Output only. The schema version of the request/response logging BigQuery table. Default to v1 if unset.", + "readOnly": true, + "type": "string" + }, + "logType": { + "type": "string", + "description": "The type of log.", + "enumDescriptions": [ + "Unspecified type.", + "Predict logs.", + "Explain logs." + ], + "enum": [ + "LOG_TYPE_UNSPECIFIED", + "PREDICT", + "EXPLAIN" + ] + }, + "bigqueryTablePath": { + "description": "The created BigQuery table to store logs. Customer could do their own query & analysis. Format: `bq://.model_deployment_monitoring_._`", + "type": "string" + }, + "logSource": { + "enumDescriptions": [ + "Unspecified source.", + "Logs coming from Training dataset.", + "Logs coming from Serving traffic." + ], + "type": "string", + "description": "The source of log.", + "enum": [ + "LOG_SOURCE_UNSPECIFIED", + "TRAINING", + "SERVING" + ] + } + }, + "type": "object", + "description": "ModelDeploymentMonitoringBigQueryTable specifies the BigQuery table name as well as some information of the logs stored in this table." + }, + "GoogleCloudAiplatformV1beta1FeatureViewDataKey": { + "description": "Lookup key for a feature view.", + "properties": { + "compositeKey": { + "description": "The actual Entity ID will be composed from this struct. This should match with the way ID is defined in the FeatureView spec.", + "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDataKeyCompositeKey" + }, + "key": { + "description": "String key to use for lookup.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1FeatureViewDataKey" + }, + "GoogleCloudAiplatformV1beta1WriteTensorboardExperimentDataRequest": { + "type": "object", + "properties": { + "writeRunDataRequests": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1WriteTensorboardRunDataRequest" + }, + "description": "Required. Requests containing per-run TensorboardTimeSeries data to write." + } + }, + "description": "Request message for TensorboardService.WriteTensorboardExperimentData.", + "id": "GoogleCloudAiplatformV1beta1WriteTensorboardExperimentDataRequest" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingMetadata": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingMetadata", + "description": "Model metadata specific to TFT Forecasting.", + "properties": { + "evaluatedDataItemsBigqueryUri": { + "type": "string", + "description": "BigQuery destination uri for exported evaluated examples." + }, + "trainCostMilliNodeHours": { + "description": "Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget.", + "type": "string", + "format": "int64" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1TensorboardTimeSeriesMetadata": { + "description": "Describes metadata for a TensorboardTimeSeries.", + "id": "GoogleCloudAiplatformV1beta1TensorboardTimeSeriesMetadata", + "properties": { + "maxWallTime": { + "type": "string", + "format": "google-datetime", + "description": "Output only. Max wall clock timestamp of all data points within a TensorboardTimeSeries.", + "readOnly": true + }, + "maxStep": { + "format": "int64", + "description": "Output only. Max step index of all data points within a TensorboardTimeSeries.", + "type": "string", + "readOnly": true + }, + "maxBlobSequenceLength": { + "format": "int64", + "type": "string", + "readOnly": true, + "description": "Output only. The largest blob sequence length (number of blobs) of all data points in this time series, if its ValueType is BLOB_SEQUENCE." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1CreateExtensionControllerOperationMetadata": { + "description": "Details of ExtensionControllerService.CreateExtensionController operation.", + "type": "object", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "The common part of the operation metadata." + } + }, + "id": "GoogleCloudAiplatformV1beta1CreateExtensionControllerOperationMetadata" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionCustomJobMetadata": { + "properties": { + "backingCustomJob": { + "description": "The resource name of the CustomJob that has been created to carry out this custom task.", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionCustomJobMetadata" + }, + "GoogleCloudAiplatformV1beta1ModelGardenSource": { + "description": "Contains information about the source of the models generated from Model Garden.", + "id": "GoogleCloudAiplatformV1beta1ModelGardenSource", + "properties": { + "publicModelName": { + "type": "string", + "description": "Required. The model garden source model resource name." + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityResult": { + "id": "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityResult", + "description": "Spec for pairwise summarization quality result.", + "properties": { + "explanation": { + "description": "Output only. Explanation for summarization quality score.", + "readOnly": true, + "type": "string" + }, + "pairwiseChoice": { + "readOnly": true, + "enumDescriptions": [ + "Unspecified prediction choice.", + "Baseline prediction wins", + "Candidate prediction wins", + "Winner cannot be determined" + ], + "enum": [ + "PAIRWISE_CHOICE_UNSPECIFIED", + "BASELINE", + "CANDIDATE", + "TIE" + ], + "description": "Output only. Pairwise summarization prediction choice.", + "type": "string" + }, + "confidence": { + "type": "number", + "description": "Output only. Confidence for summarization quality score.", + "format": "float", + "readOnly": true + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessResult": { + "properties": { + "score": { + "type": "number", + "description": "Output only. Summarization Helpfulness score.", + "readOnly": true, + "format": "float" + }, + "explanation": { + "readOnly": true, + "type": "string", + "description": "Output only. Explanation for summarization helpfulness score." + }, + "confidence": { + "format": "float", + "type": "number", + "readOnly": true, + "description": "Output only. Confidence for summarization helpfulness score." + } + }, + "type": "object", + "description": "Spec for summarization helpfulness result.", + "id": "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessResult" + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringTabularStats": { + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringTabularStats", + "description": "A collection of data points that describes the time-varying values of a tabular metric.", + "properties": { + "dataPoints": { + "type": "array", + "description": "The data points of this time series. When listing time series, points are returned in reverse time order.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPoint" + } + }, + "statsName": { + "description": "The stats name.", + "type": "string" + }, + "objectiveType": { + "description": "One of the supported monitoring objectives: `raw-feature-drift` `prediction-output-drift` `feature-attribution`", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FeatureValue": { + "id": "GoogleCloudAiplatformV1beta1FeatureValue", + "type": "object", + "description": "Value for a feature.", + "properties": { + "boolArrayValue": { + "$ref": "GoogleCloudAiplatformV1beta1BoolArray", + "description": "A list of bool type feature value." + }, + "int64Value": { + "format": "int64", + "description": "Int64 feature value.", + "type": "string" + }, + "int64ArrayValue": { + "$ref": "GoogleCloudAiplatformV1beta1Int64Array", + "description": "A list of int64 type feature value." + }, + "boolValue": { + "type": "boolean", + "description": "Bool type feature value." + }, + "metadata": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureValueMetadata", + "description": "Metadata of feature value." + }, + "structValue": { + "description": "A struct type feature value.", + "$ref": "GoogleCloudAiplatformV1beta1StructValue" + }, + "bytesValue": { + "format": "byte", + "description": "Bytes feature value.", + "type": "string" + }, + "doubleValue": { + "description": "Double type feature value.", + "format": "double", + "type": "number" + }, + "doubleArrayValue": { + "$ref": "GoogleCloudAiplatformV1beta1DoubleArray", + "description": "A list of double type feature value." + }, + "stringArrayValue": { + "$ref": "GoogleCloudAiplatformV1beta1StringArray", + "description": "A list of string type feature value." + }, + "stringValue": { + "type": "string", + "description": "String feature value." + } + } + }, + "GoogleCloudAiplatformV1beta1BatchCreateTensorboardRunsResponse": { + "id": "GoogleCloudAiplatformV1beta1BatchCreateTensorboardRunsResponse", + "properties": { + "tensorboardRuns": { + "description": "The created TensorboardRuns.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardRun" + }, + "type": "array" + } + }, + "description": "Response message for TensorboardService.BatchCreateTensorboardRuns.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassification": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassification", + "description": "A TrainingJob that trains and uploads an AutoML Image Classification Model.", + "type": "object", + "properties": { + "inputs": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs", + "description": "The input parameters of this TrainingJob." + }, + "metadata": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationMetadata", + "description": "The metadata information." + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingMetadata": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingMetadata", + "type": "object", + "description": "Model metadata specific to Seq2Seq Plus Forecasting.", + "properties": { + "trainCostMilliNodeHours": { + "type": "string", + "description": "Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget.", + "format": "int64" + }, + "evaluatedDataItemsBigqueryUri": { + "type": "string", + "description": "BigQuery destination uri for exported evaluated examples." + } + } + }, + "GoogleCloudAiplatformV1beta1ResourceRuntime": { + "type": "object", + "properties": { + "accessUris": { + "additionalProperties": { + "type": "string" + }, + "description": "Output only. URIs for user to connect to the Cluster. Example: { \"RAY_HEAD_NODE_INTERNAL_IP\": \"head-node-IP:10001\" \"RAY_DASHBOARD_URI\": \"ray-dashboard-address:8888\" }", + "readOnly": true, + "type": "object" + }, + "notebookRuntimeTemplate": { + "readOnly": true, + "type": "string", + "deprecated": true, + "description": "Output only. The resource name of NotebookRuntimeTemplate for the RoV Persistent Cluster The NotebokRuntimeTemplate is created in the same VPC (if set), and with the same Ray and Python version as the Persistent Cluster. Example: \"projects/1000/locations/us-central1/notebookRuntimeTemplates/abc123\"" + } + }, + "description": "Persistent Cluster runtime information as output", + "id": "GoogleCloudAiplatformV1beta1ResourceRuntime" + }, + "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessSpec": { + "properties": { + "version": { + "type": "integer", + "description": "Optional. Which version to use for evaluation.", + "format": "int32" + }, + "useReference": { + "type": "boolean", + "description": "Optional. Whether to use instance.reference to compute question answering correctness." + } + }, + "description": "Spec for question answering correctness metric.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessSpec" + }, + "CloudAiLargeModelsVisionRaiInfoDetectedLabelsBoundingBox": { + "type": "object", + "description": "An integer bounding box of original pixels of the image for the detected labels.", + "properties": { + "y2": { + "format": "int32", + "description": "The Y coordinate of the bottom-right corner, in pixels.", + "type": "integer" + }, + "y1": { + "format": "int32", + "description": "The Y coordinate of the top-left corner, in pixels.", + "type": "integer" + }, + "x1": { + "description": "The X coordinate of the top-left corner, in pixels.", + "type": "integer", + "format": "int32" + }, + "x2": { + "description": "The X coordinate of the bottom-right corner, in pixels.", + "format": "int32", + "type": "integer" + } + }, + "id": "CloudAiLargeModelsVisionRaiInfoDetectedLabelsBoundingBox" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericTransformation": { + "properties": { + "columnName": { + "type": "string" + }, + "invalidValuesAllowed": { + "type": "boolean", + "description": "If invalid values is allowed, the training pipeline will create a boolean feature that indicated whether the value is valid. Otherwise, the training pipeline will discard the input row from trainining data." + } + }, + "description": "Training pipeline will perform following transformation functions. * The value converted to float32. * The z_score of the value. * log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * A boolean value that indicates whether the value is valid.", + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericTransformation", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1FeaturestoreOnlineServingConfig": { + "type": "object", + "description": "OnlineServingConfig specifies the details for provisioning online serving resources.", + "id": "GoogleCloudAiplatformV1beta1FeaturestoreOnlineServingConfig", + "properties": { + "fixedNodeCount": { + "description": "The number of nodes for the online store. The number of nodes doesn't scale automatically, but you can manually update the number of nodes. If set to 0, the featurestore will not have an online store and cannot be used for online serving.", + "format": "int32", + "type": "integer" + }, + "scaling": { + "$ref": "GoogleCloudAiplatformV1beta1FeaturestoreOnlineServingConfigScaling", + "description": "Online serving scaling configuration. Only one of `fixed_node_count` and `scaling` can be set. Setting one will reset the other." + } + } + }, + "GoogleCloudAiplatformV1beta1ToolParameterKVMatchInstance": { + "properties": { + "reference": { + "type": "string", + "description": "Required. Ground truth used to compare against the prediction." + }, + "prediction": { + "type": "string", + "description": "Required. Output of the evaluated model." + } + }, + "type": "object", + "description": "Spec for tool parameter key value match instance.", + "id": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchInstance" + }, + "GoogleCloudAiplatformV1beta1SmoothGradConfig": { + "id": "GoogleCloudAiplatformV1beta1SmoothGradConfig", + "description": "Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf", + "properties": { + "featureNoiseSigma": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureNoiseSigma", + "description": "This is similar to noise_sigma, but provides additional flexibility. A separate noise sigma can be provided for each feature, which is useful if their distributions are different. No noise is added to features that are not set. If this field is unset, noise_sigma will be used for all features." + }, + "noiseSigma": { + "format": "float", + "description": "This is a single float value and will be used to add noise to all the features. Use this field when all features are normalized to have the same distribution: scale to range [0, 1], [-1, 1] or z-scoring, where features are normalized to have 0-mean and 1-variance. Learn more about [normalization](https://developers.google.com/machine-learning/data-prep/transform/normalization). For best results the recommended value is about 10% - 20% of the standard deviation of the input feature. Refer to section 3.2 of the SmoothGrad paper: https://arxiv.org/pdf/1706.03825.pdf. Defaults to 0.1. If the distribution is different per feature, set feature_noise_sigma instead for each feature.", + "type": "number" + }, + "noisySampleCount": { + "type": "integer", + "description": "The number of gradient samples to use for approximation. The higher this number, the more accurate the gradient is, but the runtime complexity increases by this factor as well. Valid range of its value is [1, 50]. Defaults to 3.", + "format": "int32" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1AddContextArtifactsAndExecutionsRequest": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1AddContextArtifactsAndExecutionsRequest", + "properties": { + "executions": { + "description": "The resource names of the Executions to associate with the Context. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`", + "items": { + "type": "string" + }, + "type": "array" + }, + "artifacts": { + "description": "The resource names of the Artifacts to attribute to the Context. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`", + "items": { + "type": "string" + }, + "type": "array" + } + }, + "description": "Request message for MetadataService.AddContextArtifactsAndExecutions." + }, + "GoogleCloudAiplatformV1beta1ListAnnotationsResponse": { + "properties": { + "annotations": { + "type": "array", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1Annotation" + }, + "description": "A list of Annotations that matches the specified filter in the request." + }, + "nextPageToken": { + "type": "string", + "description": "The standard List next-page token." + } + }, + "type": "object", + "description": "Response message for DatasetService.ListAnnotations.", + "id": "GoogleCloudAiplatformV1beta1ListAnnotationsResponse" + }, + "GoogleCloudAiplatformV1beta1RetrieveContextsRequestVertexRagStoreRagResource": { + "id": "GoogleCloudAiplatformV1beta1RetrieveContextsRequestVertexRagStoreRagResource", + "description": "The definition of the Rag resource.", + "properties": { + "ragFileIds": { + "items": { + "type": "string" + }, + "type": "array", + "description": "Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field." + }, + "ragCorpus": { + "description": "Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", + "type": "string" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1ModelEvaluationModelEvaluationExplanationSpec": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ModelEvaluationModelEvaluationExplanationSpec", + "properties": { + "explanationType": { + "type": "string", + "description": "Explanation type. For AutoML Image Classification models, possible values are: * `image-integrated-gradients` * `image-xrai`" + }, + "explanationSpec": { + "$ref": "GoogleCloudAiplatformV1beta1ExplanationSpec", + "description": "Explanation spec details." + } + } + }, + "GoogleCloudAiplatformV1beta1GroundingChunk": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1GroundingChunk", + "properties": { + "retrievedContext": { + "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkRetrievedContext", + "description": "Grounding chunk from context retrieved by the retrieval tools." + }, + "web": { + "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkWeb", + "description": "Grounding chunk from the web." + } + }, + "description": "Grounding chunk." + }, + "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionMetrics": { + "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionMetrics", + "description": "The Evaluation metrics given a specific precision_window_length.", + "type": "object", + "properties": { + "confidenceMetrics": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionMetricsConfidenceMetrics" + }, + "type": "array", + "description": "Metrics for each label-match confidence_threshold from 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99." + }, + "precisionWindowLength": { + "type": "string", + "format": "google-duration", + "description": "This VideoActionMetrics is calculated based on this prediction window length. If the predicted action's timestamp is inside the time window whose center is the ground truth action's timestamp with this specific length, the prediction result is treated as a true positive." + }, + "meanAveragePrecision": { + "type": "number", + "description": "The mean average precision.", + "format": "float" + } + } + }, + "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequest": { + "properties": { + "passThroughFields": { + "items": { + "$ref": "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequestPassThroughField" + }, + "type": "array", + "description": "When not empty, the specified fields in the *_read_instances source will be joined as-is in the output, in addition to those fields from the Featurestore Entity. For BigQuery source, the type of the pass-through values will be automatically inferred. For CSV source, the pass-through values will be passed as opaque bytes." + }, + "bigqueryReadInstances": { + "$ref": "GoogleCloudAiplatformV1beta1BigQuerySource", + "description": "Similar to csv_read_instances, but from BigQuery source." + }, + "entityTypeSpecs": { + "type": "array", + "description": "Required. Specifies EntityType grouping Features to read values of and settings.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequestEntityTypeSpec" + } + }, + "startTime": { + "format": "google-datetime", + "type": "string", + "description": "Optional. Excludes Feature values with feature generation timestamp before this timestamp. If not set, retrieve oldest values kept in Feature Store. Timestamp, if present, must not have higher than millisecond precision." + }, + "destination": { + "description": "Required. Specifies output location and format.", + "$ref": "GoogleCloudAiplatformV1beta1FeatureValueDestination" + }, + "csvReadInstances": { + "$ref": "GoogleCloudAiplatformV1beta1CsvSource", + "description": "Each read instance consists of exactly one read timestamp and one or more entity IDs identifying entities of the corresponding EntityTypes whose Features are requested. Each output instance contains Feature values of requested entities concatenated together as of the read time. An example read instance may be `foo_entity_id, bar_entity_id, 2020-01-01T10:00:00.123Z`. An example output instance may be `foo_entity_id, bar_entity_id, 2020-01-01T10:00:00.123Z, foo_entity_feature1_value, bar_entity_feature2_value`. Timestamp in each read instance must be millisecond-aligned. `csv_read_instances` are read instances stored in a plain-text CSV file. The header should be: [ENTITY_TYPE_ID1], [ENTITY_TYPE_ID2], ..., timestamp The columns can be in any order. Values in the timestamp column must use the RFC 3339 format, e.g. `2012-07-30T10:43:17.123Z`." + } + }, + "id": "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequest", + "description": "Request message for FeaturestoreService.BatchReadFeatureValues.", + "type": "object" + }, + "GoogleCloudAiplatformV1beta1SchemaTextDataItem": { + "id": "GoogleCloudAiplatformV1beta1SchemaTextDataItem", + "type": "object", + "properties": { + "gcsUri": { + "description": "Output only. Google Cloud Storage URI points to the original text in user's bucket. The text file is up to 10MB in size.", + "type": "string", + "readOnly": true + } + }, + "description": "Payload of Text DataItem." + }, + "GoogleCloudAiplatformV1beta1BatchReadTensorboardTimeSeriesDataResponse": { + "id": "GoogleCloudAiplatformV1beta1BatchReadTensorboardTimeSeriesDataResponse", + "description": "Response message for TensorboardService.BatchReadTensorboardTimeSeriesData.", + "properties": { + "timeSeriesData": { + "description": "The returned time series data.", + "items": { + "$ref": "GoogleCloudAiplatformV1beta1TimeSeriesData" + }, + "type": "array" + } + }, + "type": "object" + }, + "GoogleCloudAiplatformV1beta1StudySpecDecayCurveAutomatedStoppingSpec": { + "type": "object", + "description": "The decay curve automated stopping rule builds a Gaussian Process Regressor to predict the final objective value of a Trial based on the already completed Trials and the intermediate measurements of the current Trial. Early stopping is requested for the current Trial if there is very low probability to exceed the optimal value found so far.", + "id": "GoogleCloudAiplatformV1beta1StudySpecDecayCurveAutomatedStoppingSpec", + "properties": { + "useElapsedDuration": { + "type": "boolean", + "description": "True if Measurement.elapsed_duration is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.step_count will be used as the x-axis." + } + } + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformation": { + "type": "object", + "properties": { + "categorical": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationCategoricalTransformation" + }, + "numeric": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationNumericTransformation" + }, + "text": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTextTransformation" + }, + "auto": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationAutoTransformation" + }, + "timestamp": { + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTimestampTransformation" + } + }, + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformation" + }, + "GoogleCloudAiplatformV1beta1TrainingConfig": { + "properties": { + "timeoutTrainingMilliHours": { + "type": "string", + "description": "The timeout hours for the CMLE training job, expressed in milli hours i.e. 1,000 value in this field means 1 hour.", + "format": "int64" + } + }, + "type": "object", + "description": "CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.", + "id": "GoogleCloudAiplatformV1beta1TrainingConfig" + }, + "GoogleCloudAiplatformV1beta1UndeployIndexOperationMetadata": { + "id": "GoogleCloudAiplatformV1beta1UndeployIndexOperationMetadata", + "type": "object", + "description": "Runtime operation information for IndexEndpointService.UndeployIndex.", + "properties": { + "genericMetadata": { + "description": "The operation generic information.", + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" + } + } + }, + "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPoint": { + "id": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPoint", + "type": "object", + "properties": { + "baselineStats": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValue", + "description": "Statistics from baseline dataset." + }, + "thresholdValue": { + "type": "number", + "format": "double", + "description": "Threshold value." + }, + "createTime": { + "format": "google-datetime", + "description": "Statistics create time.", + "type": "string" + }, + "modelMonitoringJob": { + "description": "Model monitoring job resource name.", + "type": "string" + }, + "schedule": { + "type": "string", + "description": "Schedule resource name." + }, + "currentStats": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValue", + "description": "Statistics from current dataset." + }, + "algorithm": { + "type": "string", + "description": "Algorithm used to calculated the metrics, eg: jensen_shannon_divergence, l_infinity." + }, + "hasAnomaly": { + "description": "Indicate if the statistics has anomaly.", + "type": "boolean" + } + }, + "description": "Represents a single statistics data point." + }, + "GoogleCloudAiplatformV1beta1SchemaPredictInstanceVideoClassificationPredictionInstance": { + "type": "object", + "description": "Prediction input format for Video Classification.", + "id": "GoogleCloudAiplatformV1beta1SchemaPredictInstanceVideoClassificationPredictionInstance", + "properties": { + "content": { + "type": "string", + "description": "The Google Cloud Storage location of the video on which to perform the prediction." + }, + "timeSegmentStart": { + "type": "string", + "description": "The beginning, inclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with \"s\" appended at the end. Fractions are allowed, up to a microsecond precision." + }, + "timeSegmentEnd": { + "type": "string", + "description": "The end, exclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with \"s\" appended at the end. Fractions are allowed, up to a microsecond precision, and \"inf\" or \"Infinity\" is allowed, which means the end of the video." + }, + "mimeType": { + "description": "The MIME type of the content of the video. Only the following are supported: video/mp4 video/avi video/quicktime", + "type": "string" + } + } + }, + "GoogleCloudAiplatformV1beta1ErrorAnalysisAnnotationAttributedItem": { + "type": "object", + "properties": { + "annotationResourceName": { + "type": "string", + "description": "The unique ID for each annotation. Used by FE to allocate the annotation in DB." + }, + "distance": { + "format": "double", + "type": "number", + "description": "The distance of this item to the annotation." + } + }, + "description": "Attributed items for a given annotation, typically representing neighbors from the training sets constrained by the query type.", + "id": "GoogleCloudAiplatformV1beta1ErrorAnalysisAnnotationAttributedItem" + }, + "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextExtraction": { + "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextExtraction", + "type": "object", + "description": "A TrainingJob that trains and uploads an AutoML Text Extraction Model.", + "properties": { + "inputs": { + "description": "The input parameters of this TrainingJob.", + "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextExtractionInputs" + } + } + }, + "GoogleCloudAiplatformV1beta1MetadataSchema": { + "type": "object", + "id": "GoogleCloudAiplatformV1beta1MetadataSchema", + "properties": { + "createTime": { + "readOnly": true, + "type": "string", + "format": "google-datetime", + "description": "Output only. Timestamp when this MetadataSchema was created." + }, + "schema": { + "description": "Required. The raw YAML string representation of the MetadataSchema. The combination of [MetadataSchema.version] and the schema name given by `title` in [MetadataSchema.schema] must be unique within a MetadataStore. The schema is defined as an OpenAPI 3.0.2 [MetadataSchema Object](https://github.com/OAI/OpenAPI-Specification/blob/master/versions/3.0.2.md#schemaObject)", + "type": "string" + }, + "schemaType": { + "enumDescriptions": [ + "Unspecified type for the MetadataSchema.", + "A type indicating that the MetadataSchema will be used by Artifacts.", + "A typee indicating that the MetadataSchema will be used by Executions.", + "A state indicating that the MetadataSchema will be used by Contexts." + ], + "type": "string", + "enum": [ + "METADATA_SCHEMA_TYPE_UNSPECIFIED", + "ARTIFACT_TYPE", + "EXECUTION_TYPE", + "CONTEXT_TYPE" + ], + "description": "The type of the MetadataSchema. This is a property that identifies which metadata types will use the MetadataSchema." + }, + "description": { + "type": "string", + "description": "Description of the Metadata Schema" + }, + "name": { + "type": "string", + "readOnly": true, + "description": "Output only. The resource name of the MetadataSchema." + }, + "schemaVersion": { + "type": "string", + "description": "The version of the MetadataSchema. The version's format must match the following regular expression: `^[0-9]+.+.+$`, which would allow to order/compare different versions. Example: 1.0.0, 1.0.1, etc." + } + }, + "description": "Instance of a general MetadataSchema." + }, + "GoogleCloudAiplatformV1beta1UpgradeNotebookRuntimeRequest": { + "id": "GoogleCloudAiplatformV1beta1UpgradeNotebookRuntimeRequest", + "description": "Request message for NotebookService.UpgradeNotebookRuntime.", + "type": "object", + "properties": {} + }, + "GoogleCloudAiplatformV1beta1RuntimeConfigCodeInterpreterRuntimeConfig": { + "properties": { + "fileOutputGcsBucket": { + "description": "Optional. The Cloud Storage bucket for file output of this Extension. If specified, write all output files to the Cloud Storage bucket. Vertex Extension Custom Code Service Agent should be granted file writer to this bucket. If not specified, the file content will be output in response body.", + "type": "string" + }, + "fileInputGcsBucket": { + "type": "string", + "description": "Optional. The Cloud Storage bucket for file input of this Extension. If specified, support input from the Cloud Storage bucket. Vertex Extension Custom Code Service Agent should be granted file reader to this bucket. If not specified, the extension will only accept file contents from request body and reject Cloud Storage file inputs." + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1RuntimeConfigCodeInterpreterRuntimeConfig" + }, + "GoogleCloudAiplatformV1beta1DeployIndexOperationMetadata": { + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "The operation generic information." + }, + "deployedIndexId": { + "description": "The unique index id specified by user", + "type": "string" + } + }, + "type": "object", + "id": "GoogleCloudAiplatformV1beta1DeployIndexOperationMetadata", + "description": "Runtime operation information for IndexEndpointService.DeployIndex." + }, + "GoogleCloudAiplatformV1beta1ExportFeatureValuesOperationMetadata": { + "description": "Details of operations that exports Features values.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1ExportFeatureValuesOperationMetadata", + "properties": { + "genericMetadata": { + "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", + "description": "Operation metadata for Featurestore export Feature values." + } + } + }, + "GoogleCloudAiplatformV1beta1FeatureGroup": { + "id": "GoogleCloudAiplatformV1beta1FeatureGroup", + "type": "object", + "description": "Vertex AI Feature Group.", + "properties": { + "updateTime": { + "description": "Output only. Timestamp when this FeatureGroup was last updated.", + "readOnly": true, + "format": "google-datetime", + "type": "string" + }, + "name": { + "description": "Identifier. Name of the FeatureGroup. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}`", + "type": "string" + }, + "description": { + "description": "Optional. Description of the FeatureGroup.", + "type": "string" + }, + "createTime": { + "format": "google-datetime", + "description": "Output only. Timestamp when this FeatureGroup was created.", + "readOnly": true, + "type": "string" + }, + "etag": { + "type": "string", + "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + }, + "bigQuery": { + "description": "Indicates that features for this group come from BigQuery Table/View. By default treats the source as a sparse time series source. The BigQuery source table or view must have at least one entity ID column and a column named `feature_timestamp`.", + "$ref": "GoogleCloudAiplatformV1beta1FeatureGroupBigQuery" + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "type": "object", + "description": "Optional. The labels with user-defined metadata to organize your FeatureGroup. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureGroup(System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." + } + } + }, + "GoogleCloudAiplatformV1beta1TensorboardExperiment": { + "type": "object", + "description": "A TensorboardExperiment is a group of TensorboardRuns, that are typically the results of a training job run, in a Tensorboard.", + "properties": { + "updateTime": { + "readOnly": true, + "type": "string", + "description": "Output only. Timestamp when this TensorboardExperiment was last updated.", + "format": "google-datetime" + }, + "source": { + "description": "Immutable. Source of the TensorboardExperiment. Example: a custom training job.", + "type": "string" + }, + "description": { + "type": "string", + "description": "Description of this TensorboardExperiment." + }, + "createTime": { + "type": "string", + "description": "Output only. Timestamp when this TensorboardExperiment was created.", + "readOnly": true, + "format": "google-datetime" + }, + "labels": { + "additionalProperties": { + "type": "string" + }, + "description": "The labels with user-defined metadata to organize your TensorboardExperiment. Label keys and values cannot be longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with `aiplatform.googleapis.com/` and are immutable. The following system labels exist for each Dataset: * `aiplatform.googleapis.com/dataset_metadata_schema`: output only. Its value is the metadata_schema's title.", + "type": "object" + }, + "etag": { + "type": "string", + "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." + }, + "displayName": { + "description": "User provided name of this TensorboardExperiment.", + "type": "string" + }, + "name": { + "type": "string", + "description": "Output only. Name of the TensorboardExperiment. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", + "readOnly": true + } + }, + "id": "GoogleCloudAiplatformV1beta1TensorboardExperiment" + }, + "GoogleCloudAiplatformV1beta1UploadModelRequest": { + "properties": { + "serviceAccount": { + "description": "Optional. The user-provided custom service account to use to do the model upload. If empty, [Vertex AI Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) will be used to access resources needed to upload the model. This account must belong to the target project where the model is uploaded to, i.e., the project specified in the `parent` field of this request and have necessary read permissions (to Google Cloud Storage, Artifact Registry, etc.).", + "type": "string" + }, + "parentModel": { + "type": "string", + "description": "Optional. The resource name of the model into which to upload the version. Only specify this field when uploading a new version." + }, + "modelId": { + "description": "Optional. The ID to use for the uploaded Model, which will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen.", + "type": "string" + }, + "model": { + "$ref": "GoogleCloudAiplatformV1beta1Model", + "description": "Required. The Model to create." + } + }, + "description": "Request message for ModelService.UploadModel.", + "type": "object", + "id": "GoogleCloudAiplatformV1beta1UploadModelRequest" + }, + "GoogleCloudAiplatformV1beta1RayMetricSpec": { + "properties": { + "disabled": { + "type": "boolean", + "description": "Optional. Flag to disable the Ray metrics collection." + } + }, + "id": "GoogleCloudAiplatformV1beta1RayMetricSpec", + "description": "Configuration for the Ray metrics.", + "type": "object" + } + }, + "id": "aiplatform:v1beta1", + "documentationLink": "https://cloud.google.com/vertex-ai/", + "servicePath": "", + "parameters": { + "uploadType": { + "type": "string", + "location": "query", + "description": "Legacy upload protocol for media (e.g. \"media\", \"multipart\")." + }, + "alt": { + "default": "json", + "description": "Data format for response.", + "location": "query", + "enum": [ + "json", + "media", + "proto" + ], + "type": "string", + "enumDescriptions": [ + "Responses with Content-Type of application/json", + "Media download with context-dependent Content-Type", + "Responses with Content-Type of application/x-protobuf" + ] + }, + "upload_protocol": { + "type": "string", + "description": "Upload protocol for media (e.g. \"raw\", \"multipart\").", + "location": "query" + }, + "fields": { + "location": "query", + "type": "string", + "description": "Selector specifying which fields to include in a partial response." + }, + "quotaUser": { + "description": "Available to use for quota purposes for server-side applications. Can be any arbitrary string assigned to a user, but should not exceed 40 characters.", + "type": "string", + "location": "query" + }, + "access_token": { + "location": "query", + "description": "OAuth access token.", + "type": "string" + }, + "$.xgafv": { + "enumDescriptions": [ + "v1 error format", + "v2 error format" + ], + "type": "string", + "description": "V1 error format.", + "enum": [ + "1", + "2" + ], + "location": "query" + }, + "oauth_token": { + "location": "query", + "description": "OAuth 2.0 token for the current user.", + "type": "string" + }, + "prettyPrint": { + "default": "true", + "description": "Returns response with indentations and line breaks.", + "type": "boolean", + "location": "query" + }, + "callback": { + "description": "JSONP", + "location": "query", + "type": "string" + }, + "key": { + "location": "query", + "description": "API key. Your API key identifies your project and provides you with API access, quota, and reports. Required unless you provide an OAuth 2.0 token.", + "type": "string" + } + }, + "protocol": "rest", + "version": "v1beta1", + "ownerDomain": "google.com", + "canonicalName": "Aiplatform", + "discoveryVersion": "v1", + "kind": "discovery#restDescription", + "icons": { + "x16": "http://www.google.com/images/icons/product/search-16.gif", + "x32": "http://www.google.com/images/icons/product/search-32.gif" + }, + "resources": { + "publishers": { + "resources": { + "models": { + "methods": { + "get": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets a Model Garden publisher model.", + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1PublisherModel" + }, + "httpMethod": "GET", + "flatPath": "v1beta1/publishers/{publishersId}/models/{modelsId}", + "id": "aiplatform.publishers.models.get", + "parameters": { + "isHuggingFaceModel": { + "location": "query", + "description": "Optional. Boolean indicates whether the requested model is a Hugging Face model.", + "type": "boolean" + }, + "view": { + "description": "Optional. PublisherModel view specifying which fields to read.", + "type": "string", + "location": "query", + "enum": [ + "PUBLISHER_MODEL_VIEW_UNSPECIFIED", + "PUBLISHER_MODEL_VIEW_BASIC", + "PUBLISHER_MODEL_VIEW_FULL", + "PUBLISHER_MODEL_VERSION_VIEW_BASIC" + ], + "enumDescriptions": [ + "The default / unset value. The API will default to the BASIC view.", + "Include basic metadata about the publisher model, but not the full contents.", + "Include everything.", + "Include: VersionId, ModelVersionExternalName, and SupportedActions." + ] + }, + "languageCode": { + "description": "Optional. The IETF BCP-47 language code representing the language in which the publisher model's text information should be written in.", + "location": "query", + "type": "string" + }, + "name": { + "type": "string", + "location": "path", + "description": "Required. The name of the PublisherModel resource. Format: `publishers/{publisher}/models/{publisher_model}`", + "required": true, + "pattern": "^publishers/[^/]+/models/[^/]+$" + } + } + }, + "list": { + "id": "aiplatform.publishers.models.list", + "parameterOrder": [ + "parent" + ], + "path": "v1beta1/{+parent}/models", + "flatPath": "v1beta1/publishers/{publishersId}/models", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListPublisherModelsResponse" + }, + "description": "Lists publisher models in Model Garden.", + "parameters": { + "pageToken": { + "type": "string", + "description": "Optional. The standard list page token. Typically obtained via ListPublisherModelsResponse.next_page_token of the previous ModelGardenService.ListPublisherModels call.", + "location": "query" + }, + "filter": { + "description": "Optional. The standard list filter.", + "type": "string", + "location": "query" + }, + "pageSize": { + "location": "query", + "description": "Optional. The standard list page size.", + "format": "int32", + "type": "integer" + }, + "languageCode": { + "description": "Optional. The IETF BCP-47 language code representing the language in which the publisher models' text information should be written in. If not set, by default English (en).", + "location": "query", + "type": "string" + }, + "parent": { + "required": true, + "type": "string", + "description": "Required. The name of the Publisher from which to list the PublisherModels. Format: `publishers/{publisher}`", + "pattern": "^publishers/[^/]+$", + "location": "path" + }, + "orderBy": { + "location": "query", + "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending.", + "type": "string" + }, + "view": { + "enumDescriptions": [ + "The default / unset value. The API will default to the BASIC view.", + "Include basic metadata about the publisher model, but not the full contents.", + "Include everything.", + "Include: VersionId, ModelVersionExternalName, and SupportedActions." + ], + "type": "string", + "enum": [ + "PUBLISHER_MODEL_VIEW_UNSPECIFIED", + "PUBLISHER_MODEL_VIEW_BASIC", + "PUBLISHER_MODEL_VIEW_FULL", + "PUBLISHER_MODEL_VERSION_VIEW_BASIC" + ], + "description": "Optional. PublisherModel view specifying which fields to read.", + "location": "query" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET" + } + } + } + } + }, + "media": { + "methods": { + "upload": { + "httpMethod": "POST", + "parameters": { + "parent": { + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", + "description": "Required. The name of the RagCorpus resource into which to upload the file. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", + "type": "string" + } + }, + "id": "aiplatform.media.upload", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles:upload", + "path": "v1beta1/{+parent}/ragFiles:upload", + "description": "Upload a file into a RagCorpus.", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1UploadRagFileResponse" + }, + "supportsMediaUpload": true, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1UploadRagFileRequest" + }, + "parameterOrder": [ + "parent" + ], + "mediaUpload": { + "protocols": { + "simple": { + "path": "/upload/v1beta1/{+parent}/ragFiles:upload", + "multipart": true + } + }, + "accept": [ + "*/*" + ] + } + } + } + }, + "projects": { + "resources": { + "locations": { + "resources": { + "notebookRuntimes": { + "resources": { + "operations": { + "methods": { + "get": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource.", + "location": "path", + "type": "string" + } + }, + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.notebookRuntimes.operations.get" + }, + "wait": { + "httpMethod": "POST", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}:wait", + "path": "v1beta1/{+name}:wait", + "id": "aiplatform.projects.locations.notebookRuntimes.operations.wait", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "type": "string", + "location": "query" + }, + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+/operations/[^/]+$", + "required": true, + "description": "The name of the operation resource to wait on.", + "type": "string" + } + } + }, + "cancel": { + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "id": "aiplatform.projects.locations.notebookRuntimes.operations.cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "required": true + } + }, + "path": "v1beta1/{+name}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.notebookRuntimes.operations.delete", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}", + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "parameters": { + "name": { + "required": true, + "type": "string", + "description": "The name of the operation resource to be deleted.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+/operations/[^/]+$" + } + } + }, + "list": { + "id": "aiplatform.projects.locations.notebookRuntimes.operations.list", + "path": "v1beta1/{+name}/operations", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "parameters": { + "pageSize": { + "location": "query", + "type": "integer", + "description": "The standard list page size.", + "format": "int32" + }, + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + }, + "name": { + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", + "required": true, + "type": "string", + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + } + } + } + }, + "methods": { + "assign": { + "description": "Assigns a NotebookRuntime to a user for a particular Notebook file. This method will either returns an existing assignment or generates a new one.", + "httpMethod": "POST", + "id": "aiplatform.projects.locations.notebookRuntimes.assign", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1AssignNotebookRuntimeRequest" + }, + "parameters": { + "parent": { + "location": "path", + "description": "Required. The resource name of the Location to get the NotebookRuntime assignment. Format: `projects/{project}/locations/{location}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes:assign", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+parent}/notebookRuntimes:assign", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "parent" + ] + }, + "generateAccessToken": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1GenerateAccessTokenRequest" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", + "type": "string", + "location": "path", + "description": "Required. The name of the resource requesting the OAuth2 token. Format: `projects/{project}/locations/{location}/notebookRuntimes/{notebook_runtime}` `projects/{project}/locations/{location}/notebookExecutionJobs/{notebook_execution_job}`", + "required": true + } + }, + "httpMethod": "POST", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1GenerateAccessTokenResponse" + }, + "id": "aiplatform.projects.locations.notebookRuntimes.generateAccessToken", + "description": "Internal only: Called from Compute Engine instance to obtain EUC for owner Anonymous access: authenticates caller using VM identity JWT. Design doc: go/colab-on-vertex-euc-dd", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}:generateAccessToken", + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}:generateAccessToken" + }, + "upgrade": { + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.notebookRuntimes.upgrade", + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", + "location": "path", + "description": "Required. The name of the NotebookRuntime resource to be upgrade. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner.", + "type": "string" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "POST", + "description": "Upgrades a NotebookRuntime.", + "path": "v1beta1/{+name}:upgrade", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}:upgrade", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1UpgradeNotebookRuntimeRequest" + } + }, + "list": { + "description": "Lists NotebookRuntimes in a Location.", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListNotebookRuntimesResponse" + }, + "parameters": { + "filter": { + "location": "query", + "description": "Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `notebookRuntime` supports = and !=. `notebookRuntime` represents the NotebookRuntime ID, i.e. the last segment of the NotebookRuntime's resource name. * `displayName` supports = and != and regex. * `notebookRuntimeTemplate` supports = and !=. `notebookRuntimeTemplate` represents the NotebookRuntimeTemplate ID, i.e. the last segment of the NotebookRuntimeTemplate's resource name. * `healthState` supports = and !=. healthState enum: [HEALTHY, UNHEALTHY, HEALTH_STATE_UNSPECIFIED]. * `runtimeState` supports = and !=. runtimeState enum: [RUNTIME_STATE_UNSPECIFIED, RUNNING, BEING_STARTED, BEING_STOPPED, STOPPED, BEING_UPGRADED, ERROR, INVALID]. * `runtimeUser` supports = and !=. * API version is UI only: `uiState` supports = and !=. uiState enum: [UI_RESOURCE_STATE_UNSPECIFIED, UI_RESOURCE_STATE_BEING_CREATED, UI_RESOURCE_STATE_ACTIVE, UI_RESOURCE_STATE_BEING_DELETED, UI_RESOURCE_STATE_CREATION_FAILED]. * `notebookRuntimeType` supports = and !=. notebookRuntimeType enum: [USER_DEFINED, ONE_CLICK]. Some examples: * `notebookRuntime=\"notebookRuntime123\"` * `displayName=\"myDisplayName\"` and `displayName=~\"myDisplayNameRegex\"` * `notebookRuntimeTemplate=\"notebookRuntimeTemplate321\"` * `healthState=HEALTHY` * `runtimeState=RUNNING` * `runtimeUser=\"test@google.com\"` * `uiState=UI_RESOURCE_STATE_BEING_DELETED` * `notebookRuntimeType=USER_DEFINED`", + "type": "string" + }, + "pageToken": { + "description": "Optional. The standard list page token. Typically obtained via ListNotebookRuntimesResponse.next_page_token of the previous NotebookService.ListNotebookRuntimes call.", + "type": "string", + "location": "query" + }, + "parent": { + "description": "Required. The resource name of the Location from which to list the NotebookRuntimes. Format: `projects/{project}/locations/{location}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string", + "location": "path" + }, + "orderBy": { + "type": "string", + "location": "query", + "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`." + }, + "readMask": { + "format": "google-fieldmask", + "type": "string", + "location": "query", + "description": "Optional. Mask specifying which fields to read." + }, + "pageSize": { + "description": "Optional. The standard list page size.", + "location": "query", + "format": "int32", + "type": "integer" + } + }, + "path": "v1beta1/{+parent}/notebookRuntimes", + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes", + "id": "aiplatform.projects.locations.notebookRuntimes.list", + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "delete": { + "httpMethod": "DELETE", + "description": "Deletes a NotebookRuntime.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.notebookRuntimes.delete", + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", + "description": "Required. The name of the NotebookRuntime resource to be deleted. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner.", + "required": true, + "type": "string", + "location": "path" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "reportEvent": { + "parameters": { + "name": { + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", + "location": "path", + "description": "Required. The name of the NotebookRuntime resource. Format: `projects/{project}/locations/{location}/notebookRuntimes/{notebook_runtime}`" + } + }, + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ReportRuntimeEventResponse" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ReportRuntimeEventRequest" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}:reportEvent", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.notebookRuntimes.reportEvent", + "description": "", + "httpMethod": "POST", + "path": "v1beta1/{+name}:reportEvent" + }, + "get": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets a NotebookRuntime.", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}", + "httpMethod": "GET", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", + "description": "Required. The name of the NotebookRuntime resource. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner.", + "type": "string", + "required": true + } + }, + "id": "aiplatform.projects.locations.notebookRuntimes.get", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1NotebookRuntime" + }, + "path": "v1beta1/{+name}" + }, + "start": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}:start", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1StartNotebookRuntimeRequest" + }, + "path": "v1beta1/{+name}:start", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.notebookRuntimes.start", + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "type": "string", + "required": true, + "description": "Required. The name of the NotebookRuntime resource to be started. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner.", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", + "location": "path" + } + }, + "description": "Starts a NotebookRuntime." + } + } + }, + "apps": { + "resources": { + "operations": { + "methods": { + "cancel": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/apps/{appsId}/operations/{operationsId}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "httpMethod": "POST", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.apps.operations.cancel", + "path": "v1beta1/{+name}:cancel", + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/apps/[^/]+/operations/[^/]+$", + "location": "path", + "required": true + } + } + }, + "list": { + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/apps/{appsId}/operations", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "parameters": { + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token." + }, + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/apps/[^/]+$", + "required": true, + "type": "string", + "description": "The name of the operation's parent resource." + }, + "pageSize": { + "type": "integer", + "location": "query", + "description": "The standard list page size.", + "format": "int32" + }, + "filter": { + "type": "string", + "description": "The standard list filter.", + "location": "query" + } + }, + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.apps.operations.list", + "path": "v1beta1/{+name}/operations" + }, + "wait": { + "httpMethod": "POST", + "path": "v1beta1/{+name}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "required": true, + "location": "path", + "description": "The name of the operation resource to wait on.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/apps/[^/]+/operations/[^/]+$" + }, + "timeout": { + "location": "query", + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/apps/{appsId}/operations/{operationsId}:wait", + "id": "aiplatform.projects.locations.apps.operations.wait", + "parameterOrder": [ + "name" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.apps.operations.delete", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "parameters": { + "name": { + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/apps/[^/]+/operations/[^/]+$", + "type": "string", + "description": "The name of the operation resource to be deleted." + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/apps/{appsId}/operations/{operationsId}", + "httpMethod": "DELETE" + }, + "get": { + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+name}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameters": { + "name": { + "description": "The name of the operation resource.", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/apps/[^/]+/operations/[^/]+$", + "location": "path" + } + }, + "id": "aiplatform.projects.locations.apps.operations.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/apps/{appsId}/operations/{operationsId}" + } + } + } + } + }, + "notebookRuntimeTemplates": { + "resources": { + "operations": { + "methods": { + "list": { + "parameters": { + "filter": { + "type": "string", + "description": "The standard list filter.", + "location": "query" + }, + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + }, + "name": { + "description": "The name of the operation's parent resource.", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", + "type": "string" + }, + "pageSize": { + "description": "The standard list page size.", + "type": "integer", + "format": "int32", + "location": "query" + } + }, + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}/operations", + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.list", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations", + "httpMethod": "GET", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." + }, + "wait": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "path": "v1beta1/{+name}:wait", + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.wait", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}:wait", + "httpMethod": "POST", + "parameters": { + "name": { + "description": "The name of the operation resource to wait on.", + "required": true, + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+/operations/[^/]+$" + }, + "timeout": { + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string", + "format": "google-duration" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "delete": { + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.delete", + "parameters": { + "name": { + "description": "The name of the operation resource to be deleted.", + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+/operations/[^/]+$" + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1beta1/{+name}", + "httpMethod": "DELETE", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "cancel": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "httpMethod": "POST", + "parameterOrder": [ + "name" + ], + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "path": "v1beta1/{+name}:cancel", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}:cancel", + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be cancelled.", + "required": true, + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.cancel" + }, + "get": { + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.get", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "type": "string", + "required": true, + "location": "path", + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+/operations/[^/]+$" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET" + } + } + } + }, + "methods": { + "getIamPolicy": { + "parameterOrder": [ + "resource" + ], + "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", + "parameters": { + "resource": { + "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", + "location": "path", + "type": "string" + }, + "options.requestedPolicyVersion": { + "location": "query", + "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", + "format": "int32", + "type": "integer" + } + }, + "response": { + "$ref": "GoogleIamV1Policy" + }, + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.getIamPolicy", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}:getIamPolicy", + "path": "v1beta1/{+resource}:getIamPolicy", + "httpMethod": "POST" + }, + "testIamPermissions": { + "parameters": { + "permissions": { + "type": "string", + "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", + "repeated": true, + "location": "query" + }, + "resource": { + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", + "type": "string", + "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "location": "path", + "required": true + } + }, + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}:testIamPermissions", + "path": "v1beta1/{+resource}:testIamPermissions", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "resource" + ], + "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.testIamPermissions", + "response": { + "$ref": "GoogleIamV1TestIamPermissionsResponse" + } + }, + "setIamPolicy": { + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.setIamPolicy", + "path": "v1beta1/{+resource}:setIamPolicy", + "request": { + "$ref": "GoogleIamV1SetIamPolicyRequest" + }, + "parameters": { + "resource": { + "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", + "location": "path", + "type": "string", + "required": true + } + }, + "httpMethod": "POST", + "response": { + "$ref": "GoogleIamV1Policy" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", + "parameterOrder": [ + "resource" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}:setIamPolicy" + }, + "get": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate" + }, + "description": "Gets a NotebookRuntimeTemplate.", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", + "location": "path", + "description": "Required. The name of the NotebookRuntimeTemplate resource. Format: `projects/{project}/locations/{location}/notebookRuntimeTemplates/{notebook_runtime_template}`", + "type": "string", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.get", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "path": "v1beta1/{+name}" + }, + "list": { + "description": "Lists NotebookRuntimeTemplates in a Location.", + "parameters": { + "parent": { + "description": "Required. The resource name of the Location from which to list the NotebookRuntimeTemplates. Format: `projects/{project}/locations/{location}`", + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$" + }, + "filter": { + "location": "query", + "description": "Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `notebookRuntimeTemplate` supports = and !=. `notebookRuntimeTemplate` represents the NotebookRuntimeTemplate ID, i.e. the last segment of the NotebookRuntimeTemplate's resource name. * `display_name` supports = and != * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels.\"a key\"`. * `notebookRuntimeType` supports = and !=. notebookRuntimeType enum: [USER_DEFINED, ONE_CLICK]. Some examples: * `notebookRuntimeTemplate=notebookRuntimeTemplate123` * `displayName=\"myDisplayName\"` * `labels.myKey=\"myValue\"` * `notebookRuntimeType=USER_DEFINED`", + "type": "string" + }, + "pageToken": { + "location": "query", + "description": "Optional. The standard list page token. Typically obtained via ListNotebookRuntimeTemplatesResponse.next_page_token of the previous NotebookService.ListNotebookRuntimeTemplates call.", + "type": "string" + }, + "pageSize": { + "format": "int32", + "description": "Optional. The standard list page size.", + "type": "integer", + "location": "query" + }, + "readMask": { + "location": "query", + "format": "google-fieldmask", + "type": "string", + "description": "Optional. Mask specifying which fields to read." + }, + "orderBy": { + "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`.", + "type": "string", + "location": "query" + } + }, + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.list", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListNotebookRuntimeTemplatesResponse" + }, + "path": "v1beta1/{+parent}/notebookRuntimeTemplates", + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates", + "parameterOrder": [ + "parent" + ] + }, + "patch": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate" + }, + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}", + "description": "Updates a NotebookRuntimeTemplate.", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", + "required": true, + "description": "The resource name of the NotebookRuntimeTemplate.", + "location": "path", + "type": "string" + }, + "updateMask": { + "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Input format: `{paths: \"${updated_filed}\"}` Updatable fields: * `encryption_spec.kms_key_name`", + "location": "query", + "format": "google-fieldmask", + "type": "string" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate" + }, + "httpMethod": "PATCH", + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.patch" + }, + "delete": { + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", + "description": "Required. The name of the NotebookRuntimeTemplate resource to be deleted. Format: `projects/{project}/locations/{location}/notebookRuntimeTemplates/{notebook_runtime_template}`", + "location": "path", + "type": "string" + } + }, + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}", + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ], + "description": "Deletes a NotebookRuntimeTemplate.", + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.delete", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "create": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+parent}/notebookRuntimeTemplates", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate" + }, + "id": "aiplatform.projects.locations.notebookRuntimeTemplates.create", + "parameters": { + "notebookRuntimeTemplateId": { + "description": "Optional. User specified ID for the notebook runtime template.", + "location": "query", + "type": "string" + }, + "parent": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "description": "Required. The resource name of the Location to create the NotebookRuntimeTemplate. Format: `projects/{project}/locations/{location}`", + "type": "string" + } + }, + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Creates a NotebookRuntimeTemplate.", + "parameterOrder": [ + "parent" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates" + } + } + }, + "hyperparameterTuningJobs": { + "resources": { + "operations": { + "methods": { + "get": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "parameters": { + "name": { + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "type": "string" + } + }, + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.get" + }, + "delete": { + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.delete", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "parameters": { + "name": { + "description": "The name of the operation resource to be deleted.", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}", + "path": "v1beta1/{+name}", + "httpMethod": "DELETE" + }, + "cancel": { + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.cancel", + "path": "v1beta1/{+name}:cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}:cancel", + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+/operations/[^/]+$", + "location": "path", + "required": true + } + } + }, + "list": { + "parameters": { + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + }, + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter." + }, + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+$", + "description": "The name of the operation's parent resource.", + "type": "string" + }, + "pageSize": { + "location": "query", + "format": "int32", + "description": "The standard list page size.", + "type": "integer" + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.list", + "path": "v1beta1/{+name}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "httpMethod": "GET" + }, + "wait": { + "httpMethod": "POST", + "path": "v1beta1/{+name}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string", + "description": "The name of the operation resource to wait on." + }, + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "type": "string", + "location": "query" + } + }, + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}:wait", + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." + } + } + } + }, + "methods": { + "get": { + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "required": true, + "location": "path", + "description": "Required. The name of the HyperparameterTuningJob resource. Format: `projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyperparameter_tuning_job}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+$" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets a HyperparameterTuningJob", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1HyperparameterTuningJob" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}", + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.get", + "path": "v1beta1/{+name}" + }, + "cancel": { + "description": "Cancels a HyperparameterTuningJob. Starts asynchronous cancellation on the HyperparameterTuningJob. The server makes a best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetHyperparameterTuningJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On successful cancellation, the HyperparameterTuningJob is not deleted; instead it becomes a job with a HyperparameterTuningJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and HyperparameterTuningJob.state is set to `CANCELLED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.cancel", + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}:cancel", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1CancelHyperparameterTuningJobRequest" + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "required": true, + "description": "Required. The name of the HyperparameterTuningJob to cancel. Format: `projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyperparameter_tuning_job}`", + "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+$", + "type": "string", + "location": "path" + } + }, + "path": "v1beta1/{+name}:cancel" + }, + "delete": { + "description": "Deletes a HyperparameterTuningJob.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}", + "parameters": { + "name": { + "location": "path", + "required": true, + "description": "Required. The name of the HyperparameterTuningJob resource to be deleted. Format: `projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyperparameter_tuning_job}`", + "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+$", + "type": "string" + } + }, + "path": "v1beta1/{+name}", + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ] + }, + "create": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+parent}/hyperparameterTuningJobs", + "httpMethod": "POST", + "parameters": { + "parent": { + "location": "path", + "description": "Required. The resource name of the Location to create the HyperparameterTuningJob in. Format: `projects/{project}/locations/{location}`", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "parameterOrder": [ + "parent" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1HyperparameterTuningJob" + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1HyperparameterTuningJob" + }, + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.create", + "description": "Creates a HyperparameterTuningJob" + }, + "list": { + "id": "aiplatform.projects.locations.hyperparameterTuningJobs.list", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "parameters": { + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`" + }, + "pageToken": { + "description": "The standard list page token. Typically obtained via ListHyperparameterTuningJobsResponse.next_page_token of the previous JobService.ListHyperparameterTuningJobs call.", + "location": "query", + "type": "string" + }, + "pageSize": { + "description": "The standard list page size.", + "format": "int32", + "type": "integer", + "location": "query" + }, + "readMask": { + "type": "string", + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask", + "location": "query" + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string", + "description": "Required. The resource name of the Location to list the HyperparameterTuningJobs from. Format: `projects/{project}/locations/{location}`", + "location": "path", + "required": true + } + }, + "parameterOrder": [ + "parent" + ], + "path": "v1beta1/{+parent}/hyperparameterTuningJobs", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListHyperparameterTuningJobsResponse" + }, + "description": "Lists HyperparameterTuningJobs in a Location.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs" + } + } + }, + "endpoints": { + "resources": { + "chat": { + "methods": { + "completions": { + "description": "Exposes an OpenAI-compatible endpoint for chat completions.", + "parameters": { + "endpoint": { + "required": true, + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/openapi`" + } + }, + "response": { + "$ref": "GoogleApiHttpBody" + }, + "request": { + "$ref": "GoogleApiHttpBody" + }, + "path": "v1beta1/{+endpoint}/chat/completions", + "parameterOrder": [ + "endpoint" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/chat/completions", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "id": "aiplatform.projects.locations.endpoints.chat.completions", + "httpMethod": "POST" + } + } + }, + "operations": { + "methods": { + "delete": { + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be deleted.", + "type": "string", + "location": "path" + } + }, + "httpMethod": "DELETE", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.endpoints.operations.delete" + }, + "cancel": { + "path": "v1beta1/{+name}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.endpoints.operations.cancel", + "httpMethod": "POST", + "parameters": { + "name": { + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+/operations/[^/]+$" + } + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations/{operationsId}:cancel" + }, + "wait": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations/{operationsId}:wait", + "path": "v1beta1/{+name}:wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "type": "string", + "required": true + }, + "timeout": { + "type": "string", + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.endpoints.operations.wait", + "parameterOrder": [ + "name" + ] + }, + "list": { + "httpMethod": "GET", + "id": "aiplatform.projects.locations.endpoints.operations.list", + "path": "v1beta1/{+name}/operations", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "required": true, + "description": "The name of the operation's parent resource.", + "type": "string", + "location": "path" + }, + "pageSize": { + "format": "int32", + "location": "query", + "description": "The standard list page size.", + "type": "integer" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + } + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "get": { + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+/operations/[^/]+$", + "location": "path", + "required": true, + "type": "string", + "description": "The name of the operation resource." + } + }, + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations/{operationsId}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.endpoints.operations.get" + } + } + } + }, + "methods": { + "deployModel": { + "description": "Deploys a Model into this Endpoint, creating a DeployedModel within it.", + "path": "v1beta1/{+endpoint}:deployModel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "endpoint" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1DeployModelRequest" + }, + "parameters": { + "endpoint": { + "type": "string", + "required": true, + "description": "Required. The name of the Endpoint resource into which to deploy a Model. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:deployModel", + "httpMethod": "POST", + "id": "aiplatform.projects.locations.endpoints.deployModel" + }, + "serverStreamingPredict": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "id": "aiplatform.projects.locations.endpoints.serverStreamingPredict", + "path": "v1beta1/{+endpoint}:serverStreamingPredict", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:serverStreamingPredict", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1StreamingPredictRequest" + }, + "parameters": { + "endpoint": { + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "type": "string", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1StreamingPredictResponse" + }, + "description": "Perform a server-side streaming online prediction request for Vertex LLM streaming.", + "parameterOrder": [ + "endpoint" + ], + "httpMethod": "POST" + }, + "create": { + "id": "aiplatform.projects.locations.endpoints.create", + "description": "Creates an Endpoint.", + "httpMethod": "POST", + "parameterOrder": [ + "parent" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Endpoint" + }, + "parameters": { + "endpointId": { + "location": "query", + "description": "Immutable. The ID to use for endpoint, which will become the final component of the endpoint resource name. If not provided, Vertex AI will generate a value for this ID. If the first character is a letter, this value may be up to 63 characters, and valid characters are `[a-z0-9-]`. The last character must be a letter or number. If the first character is a number, this value may be up to 9 characters, and valid characters are `[0-9]` with no leading zeros. When using HTTP/JSON, this field is populated based on a query string argument, such as `?endpoint_id=12345`. This is the fallback for fields that are not included in either the URI or the body.", + "type": "string" + }, + "parent": { + "description": "Required. The resource name of the Location to create the Endpoint in. Format: `projects/{project}/locations/{location}`", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints", + "path": "v1beta1/{+parent}/endpoints" + }, + "getIamPolicy": { + "response": { + "$ref": "GoogleIamV1Policy" + }, + "parameters": { + "options.requestedPolicyVersion": { + "format": "int32", + "type": "integer", + "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", + "location": "query" + }, + "resource": { + "type": "string", + "location": "path", + "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$" + } + }, + "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:getIamPolicy", + "path": "v1beta1/{+resource}:getIamPolicy", + "id": "aiplatform.projects.locations.endpoints.getIamPolicy", + "parameterOrder": [ + "resource" + ], + "httpMethod": "POST" + }, + "setIamPolicy": { + "id": "aiplatform.projects.locations.endpoints.setIamPolicy", + "parameters": { + "resource": { + "required": true, + "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "type": "string", + "location": "path" + } + }, + "response": { + "$ref": "GoogleIamV1Policy" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:setIamPolicy", + "request": { + "$ref": "GoogleIamV1SetIamPolicyRequest" + }, + "parameterOrder": [ + "resource" + ], + "httpMethod": "POST", + "path": "v1beta1/{+resource}:setIamPolicy", + "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "rawPredict": { + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "response": { + "$ref": "GoogleApiHttpBody" + }, + "parameters": { + "endpoint": { + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "required": true, + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "location": "path", + "type": "string" + } + }, + "parameterOrder": [ + "endpoint" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1RawPredictRequest" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:rawPredict", + "id": "aiplatform.projects.locations.endpoints.rawPredict", + "description": "Perform an online prediction with an arbitrary HTTP payload. The response includes the following HTTP headers: * `X-Vertex-AI-Endpoint-Id`: ID of the Endpoint that served this prediction. * `X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's DeployedModel that served this prediction.", + "path": "v1beta1/{+endpoint}:rawPredict" + }, + "undeployModel": { + "id": "aiplatform.projects.locations.endpoints.undeployModel", + "parameterOrder": [ + "endpoint" + ], + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Undeploys a Model from an Endpoint, removing a DeployedModel from it, and freeing all resources it's using.", + "parameters": { + "endpoint": { + "description": "Required. The name of the Endpoint resource from which to undeploy a Model. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "location": "path", + "type": "string" + } + }, + "path": "v1beta1/{+endpoint}:undeployModel", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:undeployModel", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1UndeployModelRequest" + } + }, + "generateContent": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1GenerateContentRequest" + }, + "path": "v1beta1/{+model}:generateContent", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponse" + }, + "description": "Generate content with multimodal inputs.", + "parameters": { + "model": { + "location": "path", + "required": true, + "description": "Required. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "type": "string" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:generateContent", + "id": "aiplatform.projects.locations.endpoints.generateContent", + "httpMethod": "POST", + "parameterOrder": [ + "model" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ] + }, + "directPredict": { + "description": "Perform an unary online prediction request to a gRPC model server for Vertex first-party products and frameworks.", + "parameters": { + "endpoint": { + "required": true, + "type": "string", + "location": "path", + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$" + } + }, + "id": "aiplatform.projects.locations.endpoints.directPredict", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1DirectPredictRequest" + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1DirectPredictResponse" + }, + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:directPredict", + "path": "v1beta1/{+endpoint}:directPredict", + "parameterOrder": [ + "endpoint" + ] + }, + "delete": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes an Endpoint.", + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "type": "string", + "location": "path", + "required": true, + "description": "Required. The name of the Endpoint resource to be deleted. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.endpoints.delete", + "path": "v1beta1/{+name}" + }, + "computeTokens": { + "id": "aiplatform.projects.locations.endpoints.computeTokens", + "parameterOrder": [ + "endpoint" + ], + "description": "Return a list of tokens based on the input text.", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ComputeTokensRequest" + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ComputeTokensResponse" + }, + "path": "v1beta1/{+endpoint}:computeTokens", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "endpoint": { + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "description": "Required. The name of the Endpoint requested to get lists of tokens and token ids.", + "required": true, + "location": "path", + "type": "string" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:computeTokens" + }, + "explain": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ExplainResponse" + }, + "parameters": { + "endpoint": { + "description": "Required. The name of the Endpoint requested to serve the explanation. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "type": "string" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ExplainRequest" + }, + "path": "v1beta1/{+endpoint}:explain", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "httpMethod": "POST", + "id": "aiplatform.projects.locations.endpoints.explain", + "description": "Perform an online explanation. If deployed_model_id is specified, the corresponding DeployModel must have explanation_spec populated. If deployed_model_id is not specified, all DeployedModels must have explanation_spec populated.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:explain", + "parameterOrder": [ + "endpoint" + ] + }, + "patch": { + "path": "v1beta1/{+name}", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Endpoint" + }, + "parameters": { + "updateMask": { + "description": "Required. The update mask applies to the resource. See google.protobuf.FieldMask.", + "format": "google-fieldmask", + "location": "query", + "type": "string" + }, + "name": { + "description": "Output only. The resource name of the Endpoint.", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "location": "path", + "type": "string", + "required": true + } + }, + "httpMethod": "PATCH", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Endpoint" + }, + "id": "aiplatform.projects.locations.endpoints.patch", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Updates an Endpoint.", + "parameterOrder": [ + "name" + ] + }, + "predict": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1PredictResponse" + }, + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "description": "Perform an online prediction.", + "path": "v1beta1/{+endpoint}:predict", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:predict", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1PredictRequest" + }, + "parameterOrder": [ + "endpoint" + ], + "parameters": { + "endpoint": { + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" + } + }, + "id": "aiplatform.projects.locations.endpoints.predict" + }, + "get": { + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Endpoint" + }, + "path": "v1beta1/{+name}", + "description": "Gets an Endpoint.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "location": "path", + "type": "string", + "required": true, + "description": "Required. The name of the Endpoint resource. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" + } + }, + "id": "aiplatform.projects.locations.endpoints.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ] + }, + "list": { + "parameters": { + "readMask": { + "location": "query", + "description": "Optional. Mask specifying which fields to read.", + "format": "google-fieldmask", + "type": "string" + }, + "pageToken": { + "description": "Optional. The standard list page token. Typically obtained via ListEndpointsResponse.next_page_token of the previous EndpointService.ListEndpoints call.", + "location": "query", + "type": "string" + }, + "pageSize": { + "format": "int32", + "description": "Optional. The standard list page size.", + "location": "query", + "type": "integer" + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location from which to list the Endpoints. Format: `projects/{project}/locations/{location}`", + "type": "string", + "required": true, + "location": "path" + }, + "filter": { + "location": "query", + "description": "Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `endpoint` supports `=` and `!=`. `endpoint` represents the Endpoint ID, i.e. the last segment of the Endpoint's resource name. * `display_name` supports `=` and `!=`. * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:*` or `labels:key` - key existence * A key including a space must be quoted. `labels.\"a key\"`. * `base_model_name` only supports `=`. Some examples: * `endpoint=1` * `displayName=\"myDisplayName\"` * `labels.myKey=\"myValue\"` * `baseModelName=\"text-bison\"`", + "type": "string" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints", + "path": "v1beta1/{+parent}/endpoints", + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListEndpointsResponse" + }, + "description": "Lists Endpoints in a Location.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.endpoints.list", + "parameterOrder": [ + "parent" + ] + }, + "directRawPredict": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "parameters": { + "endpoint": { + "location": "path", + "required": true, + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "type": "string" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:directRawPredict", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1DirectRawPredictResponse" + }, + "path": "v1beta1/{+endpoint}:directRawPredict", + "description": "Perform an unary online prediction request to a gRPC model server for custom containers.", + "httpMethod": "POST", + "parameterOrder": [ + "endpoint" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1DirectRawPredictRequest" + }, + "id": "aiplatform.projects.locations.endpoints.directRawPredict" + }, + "mutateDeployedModel": { + "parameters": { + "endpoint": { + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "description": "Required. The name of the Endpoint resource into which to mutate a DeployedModel. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "required": true, + "location": "path", + "type": "string" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1MutateDeployedModelRequest" + }, + "description": "Updates an existing deployed model. Updatable fields include `min_replica_count`, `max_replica_count`, `autoscaling_metric_specs`, `disable_container_logging` (v1 only), and `enable_container_logging` (v1beta1 only).", + "path": "v1beta1/{+endpoint}:mutateDeployedModel", + "parameterOrder": [ + "endpoint" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:mutateDeployedModel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "id": "aiplatform.projects.locations.endpoints.mutateDeployedModel" + }, + "countTokens": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1CountTokensResponse" + }, + "parameterOrder": [ + "endpoint" + ], + "id": "aiplatform.projects.locations.endpoints.countTokens", + "parameters": { + "endpoint": { + "type": "string", + "description": "Required. The name of the Endpoint requested to perform token counting. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "location": "path" + } + }, + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1CountTokensRequest" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:countTokens", + "path": "v1beta1/{+endpoint}:countTokens", + "description": "Perform a token counting." + }, + "streamRawPredict": { + "id": "aiplatform.projects.locations.endpoints.streamRawPredict", + "parameterOrder": [ + "endpoint" + ], + "description": "Perform a streaming online prediction with an arbitrary HTTP payload.", + "parameters": { + "endpoint": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "type": "string", + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:streamRawPredict", + "path": "v1beta1/{+endpoint}:streamRawPredict", + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1StreamRawPredictRequest" + }, + "response": { + "$ref": "GoogleApiHttpBody" + } + }, + "streamGenerateContent": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1GenerateContentRequest" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "id": "aiplatform.projects.locations.endpoints.streamGenerateContent", + "description": "Generate content with multimodal inputs with streaming support.", + "parameterOrder": [ + "model" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponse" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:streamGenerateContent", + "httpMethod": "POST", + "parameters": { + "model": { + "required": true, + "location": "path", + "description": "Required. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "type": "string" + } + }, + "path": "v1beta1/{+model}:streamGenerateContent" + }, + "testIamPermissions": { + "httpMethod": "POST", + "parameters": { + "resource": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", + "required": true, + "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "type": "string" + }, + "permissions": { + "location": "query", + "type": "string", + "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", + "repeated": true + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:testIamPermissions", + "id": "aiplatform.projects.locations.endpoints.testIamPermissions", + "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", + "path": "v1beta1/{+resource}:testIamPermissions", + "parameterOrder": [ + "resource" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleIamV1TestIamPermissionsResponse" + } + } + } + }, + "schedules": { + "resources": { + "operations": { + "methods": { + "wait": { + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.schedules.operations.wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "timeout": { + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string", + "location": "query" + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+/operations/[^/]+$", + "required": true, + "description": "The name of the operation resource to wait on.", + "type": "string", + "location": "path" + } + }, + "httpMethod": "POST", + "path": "v1beta1/{+name}:wait", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations/{operationsId}:wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." + }, + "list": { + "path": "v1beta1/{+name}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "filter": { + "location": "query", + "description": "The standard list filter.", + "type": "string" + }, + "name": { + "description": "The name of the operation's parent resource.", + "required": true, + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$" + }, + "pageToken": { + "location": "query", + "description": "The standard list page token.", + "type": "string" + }, + "pageSize": { + "description": "The standard list page size.", + "format": "int32", + "type": "integer", + "location": "query" + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.schedules.operations.list", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "httpMethod": "GET" + }, + "get": { + "parameters": { + "name": { + "required": true, + "type": "string", + "location": "path", + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+/operations/[^/]+$" + } + }, + "httpMethod": "GET", + "id": "aiplatform.projects.locations.schedules.operations.get", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations/{operationsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+name}" + }, + "cancel": { + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "type": "string" + } + }, + "path": "v1beta1/{+name}:cancel", + "id": "aiplatform.projects.locations.schedules.operations.cancel", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations/{operationsId}:cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST" + }, + "delete": { + "parameters": { + "name": { + "location": "path", + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+/operations/[^/]+$", + "required": true, + "type": "string" + } + }, + "httpMethod": "DELETE", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations/{operationsId}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.schedules.operations.delete", + "path": "v1beta1/{+name}" + } + } + } + }, + "methods": { + "resume": { + "id": "aiplatform.projects.locations.schedules.resume", + "path": "v1beta1/{+name}:resume", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Resumes a paused Schedule to start scheduling new runs. Will mark Schedule.state to 'ACTIVE'. Only paused Schedule can be resumed. When the Schedule is resumed, new runs will be scheduled starting from the next execution time after the current time based on the time_specification in the Schedule. If Schedule.catchUp is set up true, all missed runs will be scheduled for backfill first.", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ResumeScheduleRequest" + }, + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "type": "string", + "location": "path", + "description": "Required. The name of the Schedule resource to be resumed. Format: `projects/{project}/locations/{location}/schedules/{schedule}`", + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}:resume" + }, + "list": { + "parameterOrder": [ + "parent" + ], + "httpMethod": "GET", + "parameters": { + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token. Typically obtained via ListSchedulesResponse.next_page_token of the previous ScheduleService.ListSchedules call." + }, + "orderBy": { + "location": "query", + "type": "string", + "description": "A comma-separated list of fields to order by. The default sort order is in ascending order. Use \"desc\" after a field name for descending. You can have multiple order_by fields provided. For example, using \"create_time desc, end_time\" will order results by create time in descending order, and if there are multiple schedules having the same create time, order them by the end time in ascending order. If order_by is not specified, it will order by default with create_time in descending order. Supported fields: * `create_time` * `start_time` * `end_time` * `next_run_time`" + }, + "parent": { + "required": true, + "location": "path", + "description": "Required. The resource name of the Location to list the Schedules from. Format: `projects/{project}/locations/{location}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$" + }, + "filter": { + "location": "query", + "type": "string", + "description": "Lists the Schedules that match the filter expression. The following fields are supported: * `display_name`: Supports `=`, `!=` comparisons, and `:` wildcard. * `state`: Supports `=` and `!=` comparisons. * `request`: Supports existence of the check. (e.g. `create_pipeline_job_request:*` --\u003e Schedule has create_pipeline_job_request). * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `start_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `end_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, `\u003e=` comparisons and `:*` existence check. Values must be in RFC 3339 format. * `next_run_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. Filter expressions can be combined together using logical operators (`NOT`, `AND` & `OR`). The syntax to define filter expression is based on https://google.aip.dev/160. Examples: * `state=\"ACTIVE\" AND display_name:\"my_schedule_*\"` * `NOT display_name=\"my_schedule\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `end_time\u003e\"2021-05-18T00:00:00Z\" OR NOT end_time:*` * `create_pipeline_job_request:*`" + }, + "pageSize": { + "description": "The standard list page size. Default to 100 if not specified.", + "type": "integer", + "location": "query", + "format": "int32" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListSchedulesResponse" + }, + "id": "aiplatform.projects.locations.schedules.list", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules", + "path": "v1beta1/{+parent}/schedules", + "description": "Lists Schedules in a Location.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "create": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Schedule" + }, + "description": "Creates a Schedule.", + "path": "v1beta1/{+parent}/schedules", + "id": "aiplatform.projects.locations.schedules.create", + "parameters": { + "parent": { + "type": "string", + "location": "path", + "required": true, + "description": "Required. The resource name of the Location to create the Schedule in. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Schedule" + }, + "parameterOrder": [ + "parent" + ], + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a Schedule.", + "id": "aiplatform.projects.locations.schedules.delete", + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", + "description": "Required. The name of the Schedule resource to be deleted. Format: `projects/{project}/locations/{location}/schedules/{schedule}`", + "type": "string" + } + }, + "httpMethod": "DELETE", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}" + }, + "get": { + "id": "aiplatform.projects.locations.schedules.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}", + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", + "type": "string", + "required": true, + "location": "path", + "description": "Required. The name of the Schedule resource. Format: `projects/{project}/locations/{location}/schedules/{schedule}`" + } + }, + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Schedule" + }, + "description": "Gets a Schedule." + }, + "pause": { + "path": "v1beta1/{+name}:pause", + "description": "Pauses a Schedule. Will mark Schedule.state to 'PAUSED'. If the schedule is paused, no new runs will be created. Already created runs will NOT be paused or canceled.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "description": "Required. The name of the Schedule resource to be paused. Format: `projects/{project}/locations/{location}/schedules/{schedule}`", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", + "required": true + } + }, + "id": "aiplatform.projects.locations.schedules.pause", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1PauseScheduleRequest" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}:pause", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST" + }, + "patch": { + "description": "Updates an active or paused Schedule. When the Schedule is updated, new runs will be scheduled starting from the updated next execution time after the update time based on the time_specification in the updated Schedule. All unstarted runs before the update time will be skipped while already created runs will NOT be paused or canceled.", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.schedules.patch", + "path": "v1beta1/{+name}", + "parameters": { + "updateMask": { + "type": "string", + "format": "google-fieldmask", + "description": "Required. The update mask applies to the resource. See google.protobuf.FieldMask.", + "location": "query" + }, + "name": { + "required": true, + "description": "Immutable. The resource name of the Schedule.", + "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", + "location": "path", + "type": "string" + } + }, + "httpMethod": "PATCH", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Schedule" + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Schedule" + } + } + } + }, + "nasJobs": { + "methods": { + "create": { + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string", + "required": true, + "location": "path", + "description": "Required. The resource name of the Location to create the NasJob in. Format: `projects/{project}/locations/{location}`" + } + }, + "path": "v1beta1/{+parent}/nasJobs", + "description": "Creates a NasJob", + "id": "aiplatform.projects.locations.nasJobs.create", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/nasJobs", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1NasJob" + }, + "httpMethod": "POST", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1NasJob" + }, + "parameterOrder": [ + "parent" + ] + }, + "get": { + "httpMethod": "GET", + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1NasJob" + }, + "parameters": { + "name": { + "type": "string", + "description": "Required. The name of the NasJob resource. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+$", + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.nasJobs.get", + "description": "Gets a NasJob", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}" + }, + "cancel": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1beta1/{+name}:cancel", + "httpMethod": "POST", + "id": "aiplatform.projects.locations.nasJobs.cancel", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1CancelNasJobRequest" + }, + "description": "Cancels a NasJob. Starts asynchronous cancellation on the NasJob. The server makes a best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetNasJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On successful cancellation, the NasJob is not deleted; instead it becomes a job with a NasJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and NasJob.state is set to `CANCELLED`.", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}:cancel", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+$", + "description": "Required. The name of the NasJob to cancel. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}`", + "type": "string", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token. Typically obtained via ListNasJobsResponse.next_page_token of the previous JobService.ListNasJobs call." + }, + "parent": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location to list the NasJobs from. Format: `projects/{project}/locations/{location}`", + "type": "string", + "required": true + }, + "pageSize": { + "location": "query", + "description": "The standard list page size.", + "format": "int32", + "type": "integer" + }, + "readMask": { + "type": "string", + "format": "google-fieldmask", + "description": "Mask specifying which fields to read.", + "location": "query" + }, + "filter": { + "location": "query", + "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.nasJobs.list", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/nasJobs", + "path": "v1beta1/{+parent}/nasJobs", + "parameterOrder": [ + "parent" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListNasJobsResponse" + }, + "httpMethod": "GET", + "description": "Lists NasJobs in a Location." + }, + "delete": { + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a NasJob.", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+$", + "location": "path", + "description": "Required. The name of the NasJob resource to be deleted. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}`", + "type": "string", + "required": true + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.nasJobs.delete", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}", + "path": "v1beta1/{+name}" + } + }, + "resources": { + "nasTrialDetails": { + "methods": { + "get": { + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1NasTrialDetail" + }, + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.nasJobs.nasTrialDetails.get", + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+/nasTrialDetails/[^/]+$", + "location": "path", + "description": "Required. The name of the NasTrialDetail resource. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}/nasTrialDetails/{nas_trial_detail}`", + "required": true + } + }, + "description": "Gets a NasTrialDetail.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}/nasTrialDetails/{nasTrialDetailsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListNasTrialDetailsResponse" + }, + "path": "v1beta1/{+parent}/nasTrialDetails", + "parameters": { + "pageSize": { + "location": "query", + "type": "integer", + "description": "The standard list page size.", + "format": "int32" + }, + "pageToken": { + "location": "query", + "description": "The standard list page token. Typically obtained via ListNasTrialDetailsResponse.next_page_token of the previous JobService.ListNasTrialDetails call.", + "type": "string" + }, + "parent": { + "description": "Required. The name of the NasJob resource. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+$", + "required": true, + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "List top NasTrialDetails of a NasJob.", + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}/nasTrialDetails", + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.nasJobs.nasTrialDetails.list" + } + } + } + } + }, + "edgeDevices": { + "resources": { + "operations": { + "methods": { + "list": { + "id": "aiplatform.projects.locations.edgeDevices.operations.list", + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/edgeDevices/{edgeDevicesId}/operations", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "path": "v1beta1/{+name}/operations", + "parameterOrder": [ + "name" + ], + "parameters": { + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + }, + "filter": { + "location": "query", + "description": "The standard list filter.", + "type": "string" + }, + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/edgeDevices/[^/]+$", + "required": true, + "description": "The name of the operation's parent resource.", + "type": "string" + }, + "pageSize": { + "location": "query", + "type": "integer", + "format": "int32", + "description": "The standard list page size." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + } + }, + "delete": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/edgeDevices/{edgeDevicesId}/operations/{operationsId}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "DELETE", + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "type": "string", + "description": "The name of the operation resource to be deleted.", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/edgeDevices/[^/]+/operations/[^/]+$" + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.edgeDevices.operations.delete" + }, + "cancel": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/edgeDevices/[^/]+/operations/[^/]+$", + "required": true, + "description": "The name of the operation resource to be cancelled.", + "location": "path", + "type": "string" + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.edgeDevices.operations.cancel", + "httpMethod": "POST", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/edgeDevices/{edgeDevicesId}/operations/{operationsId}:cancel", + "path": "v1beta1/{+name}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`." + }, + "get": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/edgeDevices/{edgeDevicesId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameters": { + "name": { + "description": "The name of the operation resource.", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/edgeDevices/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.edgeDevices.operations.get", + "path": "v1beta1/{+name}" + }, + "wait": { + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "type": "string", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/edgeDevices/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on." + }, + "timeout": { + "location": "query", + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration" + } + }, + "httpMethod": "POST", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/edgeDevices/{edgeDevicesId}/operations/{operationsId}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.edgeDevices.operations.wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+name}:wait" + } + } + } + } + }, + "extensions": { + "methods": { + "execute": { + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "path": "v1beta1/{+name}:execute", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+$", + "required": true, + "type": "string", + "description": "Required. Name (identifier) of the extension; Format: `projects/{project}/locations/{location}/extensions/{extension}`" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}:execute", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ExecuteExtensionResponse" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ExecuteExtensionRequest" + }, + "id": "aiplatform.projects.locations.extensions.execute", + "description": "Executes the request against a given extension.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "get": { + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+$", + "location": "path", + "required": true, + "description": "Required. The name of the Extension resource. Format: `projects/{project}/locations/{location}/extensions/{extension}`", + "type": "string" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.extensions.get", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Extension" + }, + "httpMethod": "GET", + "description": "Gets an Extension." + }, + "list": { + "parameters": { + "parent": { + "required": true, + "description": "Required. The resource name of the Location to list the Extensions from. Format: `projects/{project}/locations/{location}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path" + }, + "pageSize": { + "description": "Optional. The standard list page size.", + "format": "int32", + "type": "integer", + "location": "query" + }, + "pageToken": { + "location": "query", + "description": "Optional. The standard list page token.", + "type": "string" + }, + "orderBy": { + "location": "query", + "type": "string", + "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`." + }, + "filter": { + "location": "query", + "type": "string", + "description": "Optional. The standard list filter. Supported fields: * `display_name` * `create_time` * `update_time` More detail in [AIP-160](https://google.aip.dev/160)." + } + }, + "path": "v1beta1/{+parent}/extensions", + "id": "aiplatform.projects.locations.extensions.list", + "httpMethod": "GET", + "description": "Lists Extensions in a location.", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListExtensionsResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions" + }, + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.extensions.delete", + "description": "Deletes an Extension.", + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+$", + "required": true, + "description": "Required. The name of the Extension resource to be deleted. Format: `projects/{project}/locations/{location}/extensions/{extension}`", + "type": "string", + "location": "path" + } + }, + "httpMethod": "DELETE", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}" + }, + "patch": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Extension" + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.extensions.patch", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Extension" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "PATCH", + "description": "Updates an Extension.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+$", + "location": "path", + "type": "string", + "description": "Identifier. The resource name of the Extension.", + "required": true + }, + "updateMask": { + "type": "string", + "format": "google-fieldmask", + "location": "query", + "description": "Required. Mask specifying which fields to update. Supported fields: * `display_name` * `description` * `runtime_config` * `tool_use_examples` * `manifest.description`" + } + }, + "path": "v1beta1/{+name}" + }, + "import": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions:import", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Extension" + }, + "description": "Imports an Extension.", + "httpMethod": "POST", + "path": "v1beta1/{+parent}/extensions:import", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.extensions.import", + "parameters": { + "parent": { + "description": "Required. The resource name of the Location to import the Extension in. Format: `projects/{project}/locations/{location}`", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path" + } + } + }, + "query": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1QueryExtensionRequest" + }, + "id": "aiplatform.projects.locations.extensions.query", + "path": "v1beta1/{+name}:query", + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}:query", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1QueryExtensionResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Queries an extension with a default controller.", + "parameters": { + "name": { + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+$", + "description": "Required. Name (identifier) of the extension; Format: `projects/{project}/locations/{location}/extensions/{extension}`" + } + }, + "parameterOrder": [ + "name" + ] + } + }, + "resources": { + "operations": { + "methods": { + "cancel": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+/operations/[^/]+$", + "required": true, + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}:cancel", + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}/operations/{operationsId}:cancel", + "id": "aiplatform.projects.locations.extensions.operations.cancel" + }, + "delete": { + "parameters": { + "name": { + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string", + "required": true + } + }, + "id": "aiplatform.projects.locations.extensions.operations.delete", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1beta1/{+name}", + "httpMethod": "DELETE", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}/operations/{operationsId}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "wait": { + "id": "aiplatform.projects.locations.extensions.operations.wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}/operations/{operationsId}:wait", + "path": "v1beta1/{+name}:wait", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on." + }, + "timeout": { + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "format": "google-duration" + } + } + }, + "list": { + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "path": "v1beta1/{+name}/operations", + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "parameters": { + "pageToken": { + "location": "query", + "description": "The standard list page token.", + "type": "string" + }, + "name": { + "description": "The name of the operation's parent resource.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+$", + "required": true, + "type": "string" + }, + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + }, + "pageSize": { + "location": "query", + "description": "The standard list page size.", + "type": "integer", + "format": "int32" + } + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "id": "aiplatform.projects.locations.extensions.operations.list" + }, + "get": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.extensions.operations.get", + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "GET", + "parameters": { + "name": { + "type": "string", + "required": true, + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+/operations/[^/]+$", + "location": "path" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}/operations/{operationsId}" + } + } + } + } + }, + "reasoningEngines": { + "methods": { + "query": { + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.reasoningEngines.query", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}:query", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1QueryReasoningEngineRequest" + }, + "parameters": { + "name": { + "required": true, + "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", + "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", + "location": "path", + "type": "string" + } + }, + "path": "v1beta1/{+name}:query", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1QueryReasoningEngineResponse" + }, + "description": "Queries using a reasoning engine.", + "httpMethod": "POST" + }, + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a reasoning engine.", + "id": "aiplatform.projects.locations.reasoningEngines.delete", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", + "description": "Required. The name of the ReasoningEngine resource to be deleted. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", + "type": "string", + "required": true, + "location": "path" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+name}", + "httpMethod": "DELETE" + }, + "create": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngine" + }, + "parameterOrder": [ + "parent" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines", + "parameters": { + "parent": { + "location": "path", + "description": "Required. The resource name of the Location to create the ReasoningEngine in. Format: `projects/{project}/locations/{location}`", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "description": "Creates a reasoning engine.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "POST", + "id": "aiplatform.projects.locations.reasoningEngines.create", + "path": "v1beta1/{+parent}/reasoningEngines", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "description": "Lists reasoning engines in a location.", + "httpMethod": "GET", + "path": "v1beta1/{+parent}/reasoningEngines", + "parameters": { + "pageToken": { + "type": "string", + "location": "query", + "description": "Optional. The standard list page token." + }, + "pageSize": { + "description": "Optional. The standard list page size.", + "format": "int32", + "location": "query", + "type": "integer" + }, + "parent": { + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location to list the ReasoningEngines from. Format: `projects/{project}/locations/{location}`" + }, + "filter": { + "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160).", + "type": "string", + "location": "query" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines", + "id": "aiplatform.projects.locations.reasoningEngines.list", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListReasoningEnginesResponse" + }, + "parameterOrder": [ + "parent" + ] + }, + "patch": { + "id": "aiplatform.projects.locations.reasoningEngines.patch", + "parameters": { + "name": { + "type": "string", + "required": true, + "description": "Identifier. The resource name of the ReasoningEngine.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$" + }, + "updateMask": { + "format": "google-fieldmask", + "description": "Required. Mask specifying which fields to update.", + "location": "query", + "type": "string" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngine" + }, + "description": "Updates a reasoning engine.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "PATCH", + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "get": { + "description": "Gets a reasoning engine.", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngine" + }, + "httpMethod": "GET", + "id": "aiplatform.projects.locations.reasoningEngines.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}", + "parameters": { + "name": { + "type": "string", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", + "description": "Required. The name of the ReasoningEngine resource. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" + } + }, + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}" + } + }, + "resources": { + "operations": { + "methods": { + "delete": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.reasoningEngines.operations.delete", + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "description": "The name of the operation resource to be deleted." + } + }, + "parameterOrder": [ + "name" + ] + }, + "get": { + "id": "aiplatform.projects.locations.reasoningEngines.operations.get", + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "location": "path", + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/operations/[^/]+$", + "required": true, + "type": "string" + } + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/operations/{operationsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ] + }, + "wait": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/operations/{operationsId}:wait", + "parameters": { + "timeout": { + "type": "string", + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query" + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/operations/[^/]+$", + "type": "string", + "description": "The name of the operation resource to wait on.", + "required": true, + "location": "path" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "id": "aiplatform.projects.locations.reasoningEngines.operations.wait", + "path": "v1beta1/{+name}:wait" + }, + "list": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/operations", + "path": "v1beta1/{+name}/operations", + "id": "aiplatform.projects.locations.reasoningEngines.operations.list", + "httpMethod": "GET", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "parameters": { + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + }, + "pageSize": { + "type": "integer", + "format": "int32", + "description": "The standard list page size.", + "location": "query" + }, + "filter": { + "location": "query", + "description": "The standard list filter.", + "type": "string" + }, + "name": { + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", + "description": "The name of the operation's parent resource." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + } + }, + "cancel": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/operations/{operationsId}:cancel", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.reasoningEngines.operations.cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "parameters": { + "name": { + "required": true, + "type": "string", + "description": "The name of the operation resource to be cancelled.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/operations/[^/]+$" + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1beta1/{+name}:cancel" + } + } + } + } + }, + "pipelineJobs": { + "methods": { + "get": { + "id": "aiplatform.projects.locations.pipelineJobs.get", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}", + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1PipelineJob" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+$", + "description": "Required. The name of the PipelineJob resource. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}`", + "required": true, + "type": "string" + } + }, + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "description": "Gets a PipelineJob." + }, + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a PipelineJob.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+$", + "type": "string", + "location": "path", + "description": "Required. The name of the PipelineJob resource to be deleted. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}`", + "required": true + } + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.pipelineJobs.delete", + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "create": { + "httpMethod": "POST", + "id": "aiplatform.projects.locations.pipelineJobs.create", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1PipelineJob" + }, + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "pipelineJobId": { + "description": "The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.", + "type": "string", + "location": "query" + }, + "parent": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "type": "string", + "description": "Required. The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1PipelineJob" + }, + "description": "Creates a PipelineJob. A PipelineJob will run immediately when created.", + "path": "v1beta1/{+parent}/pipelineJobs" + }, + "batchDelete": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1BatchDeletePipelineJobsRequest" + }, + "path": "v1beta1/{+parent}/pipelineJobs:batchDelete", + "description": "Batch deletes PipelineJobs The Operation is atomic. If it fails, none of the PipelineJobs are deleted. If it succeeds, all of the PipelineJobs are deleted.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.pipelineJobs.batchDelete", + "parameters": { + "parent": { + "location": "path", + "description": "Required. The name of the PipelineJobs' parent resource. Format: `projects/{project}/locations/{location}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true + } + }, + "parameterOrder": [ + "parent" + ], + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs:batchDelete" + }, + "list": { + "description": "Lists PipelineJobs in a Location.", + "id": "aiplatform.projects.locations.pipelineJobs.list", + "parameters": { + "pageToken": { + "type": "string", + "description": "The standard list page token. Typically obtained via ListPipelineJobsResponse.next_page_token of the previous PipelineService.ListPipelineJobs call.", + "location": "query" + }, + "readMask": { + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask", + "type": "string", + "location": "query" + }, + "pageSize": { + "type": "integer", + "location": "query", + "format": "int32", + "description": "The standard list page size." + }, + "filter": { + "type": "string", + "description": "Lists the PipelineJobs that match the filter expression. The following fields are supported: * `pipeline_name`: Supports `=` and `!=` comparisons. * `display_name`: Supports `=`, `!=` comparisons, and `:` wildcard. * `pipeline_job_user_id`: Supports `=`, `!=` comparisons, and `:` wildcard. for example, can check if pipeline's display_name contains *step* by doing display_name:\\\"*step*\\\" * `state`: Supports `=` and `!=` comparisons. * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `end_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality and key presence. * `template_uri`: Supports `=`, `!=` comparisons, and `:` wildcard. * `template_metadata.version`: Supports `=`, `!=` comparisons, and `:` wildcard. Filter expressions can be combined together using logical operators (`AND` & `OR`). For example: `pipeline_name=\"test\" AND create_time\u003e\"2020-05-18T13:30:00Z\"`. The syntax to define filter expression is based on https://google.aip.dev/160. Examples: * `create_time\u003e\"2021-05-18T00:00:00Z\" OR update_time\u003e\"2020-05-18T00:00:00Z\"` PipelineJobs created or updated after 2020-05-18 00:00:00 UTC. * `labels.env = \"prod\"` PipelineJobs with label \"env\" set to \"prod\".", + "location": "query" + }, + "orderBy": { + "type": "string", + "description": "A comma-separated list of fields to order by. The default sort order is in ascending order. Use \"desc\" after a field name for descending. You can have multiple order_by fields provided e.g. \"create_time desc, end_time\", \"end_time, start_time, update_time\" For example, using \"create_time desc, end_time\" will order results by create time in descending order, and if there are multiple jobs having the same create time, order them by the end time in ascending order. if order_by is not specified, it will order by default order is create time in descending order. Supported fields: * `create_time` * `update_time` * `end_time` * `start_time`", + "location": "query" + }, + "parent": { + "type": "string", + "required": true, + "description": "Required. The resource name of the Location to list the PipelineJobs from. Format: `projects/{project}/locations/{location}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+parent}/pipelineJobs", + "parameterOrder": [ + "parent" + ], + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListPipelineJobsResponse" + } + }, + "cancel": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}:cancel", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1CancelPipelineJobRequest" + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Cancels a PipelineJob. Starts asynchronous cancellation on the PipelineJob. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use PipelineService.GetPipelineJob or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the PipelineJob is not deleted; instead it becomes a pipeline with a PipelineJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and PipelineJob.state is set to `CANCELLED`.", + "id": "aiplatform.projects.locations.pipelineJobs.cancel", + "path": "v1beta1/{+name}:cancel", + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+$", + "type": "string", + "location": "path", + "description": "Required. The name of the PipelineJob to cancel. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}`" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "httpMethod": "POST" + }, + "batchCancel": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1BatchCancelPipelineJobsRequest" + }, + "description": "Batch cancel PipelineJobs. Firstly the server will check if all the jobs are in non-terminal states, and skip the jobs that are already terminated. If the operation failed, none of the pipeline jobs are cancelled. The server will poll the states of all the pipeline jobs periodically to check the cancellation status. This operation will return an LRO.", + "path": "v1beta1/{+parent}/pipelineJobs:batchCancel", + "id": "aiplatform.projects.locations.pipelineJobs.batchCancel", + "httpMethod": "POST", + "parameterOrder": [ + "parent" + ], + "parameters": { + "parent": { + "type": "string", + "description": "Required. The name of the PipelineJobs' parent resource. Format: `projects/{project}/locations/{location}`", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs:batchCancel", + "response": { + "$ref": "GoogleLongrunningOperation" + } + } + }, + "resources": { + "operations": { + "methods": { + "wait": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations/{operationsId}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "timeout": { + "type": "string", + "format": "google-duration", + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+/operations/[^/]+$", + "type": "string", + "location": "path", + "description": "The name of the operation resource to wait on.", + "required": true + } + }, + "id": "aiplatform.projects.locations.pipelineJobs.operations.wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "path": "v1beta1/{+name}:wait", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST" + }, + "cancel": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations/{operationsId}:cancel", + "path": "v1beta1/{+name}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "required": true, + "description": "The name of the operation resource to be cancelled.", + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+/operations/[^/]+$" + } + }, + "id": "aiplatform.projects.locations.pipelineJobs.operations.cancel", + "httpMethod": "POST", + "parameterOrder": [ + "name" + ], + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`." + }, + "list": { + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "filter": { + "type": "string", + "description": "The standard list filter.", + "location": "query" + }, + "pageSize": { + "type": "integer", + "location": "query", + "description": "The standard list page size.", + "format": "int32" + }, + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + }, + "name": { + "location": "path", + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+$", + "type": "string", + "required": true + } + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations", + "httpMethod": "GET", + "id": "aiplatform.projects.locations.pipelineJobs.operations.list" + }, + "delete": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "required": true, + "location": "path", + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "id": "aiplatform.projects.locations.pipelineJobs.operations.delete", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations/{operationsId}", + "httpMethod": "DELETE", + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "get": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+/operations/[^/]+$", + "type": "string", + "location": "path", + "description": "The name of the operation resource.", + "required": true + } + }, + "path": "v1beta1/{+name}", + "httpMethod": "GET", + "id": "aiplatform.projects.locations.pipelineJobs.operations.get", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + } + } + } + } + }, + "featurestores": { + "methods": { + "list": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores", + "path": "v1beta1/{+parent}/featurestores", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "readMask": { + "format": "google-fieldmask", + "description": "Mask specifying which fields to read.", + "location": "query", + "type": "string" + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location to list Featurestores. Format: `projects/{project}/locations/{location}`", + "required": true, + "type": "string", + "location": "path" + }, + "orderBy": { + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported Fields: * `create_time` * `update_time` * `online_serving_config.fixed_node_count`", + "location": "query", + "type": "string" + }, + "pageToken": { + "type": "string", + "description": "A page token, received from a previous FeaturestoreService.ListFeaturestores call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.ListFeaturestores must match the call that provided the page token.", + "location": "query" + }, + "pageSize": { + "location": "query", + "format": "int32", + "type": "integer", + "description": "The maximum number of Featurestores to return. The service may return fewer than this value. If unspecified, at most 100 Featurestores will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100." + }, + "filter": { + "location": "query", + "description": "Lists the featurestores that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `online_serving_config.fixed_node_count`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. * `labels`: Supports key-value equality and key presence. Examples: * `create_time \u003e \"2020-01-01\" OR update_time \u003e \"2020-01-01\"` Featurestores created or updated after 2020-01-01. * `labels.env = \"prod\"` Featurestores with label \"env\" set to \"prod\".", + "type": "string" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListFeaturestoresResponse" + }, + "id": "aiplatform.projects.locations.featurestores.list", + "httpMethod": "GET", + "parameterOrder": [ + "parent" + ], + "description": "Lists Featurestores in a given project and location." + }, + "testIamPermissions": { + "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", + "parameters": { + "resource": { + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", + "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "location": "path" + } + }, + "parameterOrder": [ + "resource" + ], + "id": "aiplatform.projects.locations.featurestores.testIamPermissions", + "httpMethod": "POST", + "path": "v1beta1/{+resource}:testIamPermissions", + "request": { + "$ref": "GoogleIamV1TestIamPermissionsRequest" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}:testIamPermissions", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleIamV1TestIamPermissionsResponse" + } + }, + "setIamPolicy": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+resource}:setIamPolicy", + "id": "aiplatform.projects.locations.featurestores.setIamPolicy", + "response": { + "$ref": "GoogleIamV1Policy" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}:setIamPolicy", + "request": { + "$ref": "GoogleIamV1SetIamPolicyRequest" + }, + "parameterOrder": [ + "resource" + ], + "httpMethod": "POST", + "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", + "parameters": { + "resource": { + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", + "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field." + } + } + }, + "batchReadFeatureValues": { + "path": "v1beta1/{+featurestore}:batchReadFeatureValues", + "parameterOrder": [ + "featurestore" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "featurestore": { + "required": true, + "description": "Required. The resource name of the Featurestore from which to query Feature values. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$" + } + }, + "description": "Batch reads Feature values from a Featurestore. This API enables batch reading Feature values, where each read instance in the batch may read Feature values of entities from one or more EntityTypes. Point-in-time correctness is guaranteed for Feature values of each read instance as of each instance's read timestamp.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}:batchReadFeatureValues", + "id": "aiplatform.projects.locations.featurestores.batchReadFeatureValues", + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequest" + } + }, + "getIamPolicy": { + "httpMethod": "POST", + "response": { + "$ref": "GoogleIamV1Policy" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}:getIamPolicy", + "parameters": { + "resource": { + "type": "string", + "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", + "required": true, + "location": "path" + } + }, + "parameterOrder": [ + "resource" + ], + "id": "aiplatform.projects.locations.featurestores.getIamPolicy", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", + "path": "v1beta1/{+resource}:getIamPolicy", + "request": { + "$ref": "GoogleIamV1GetIamPolicyRequest" + } + }, + "delete": { + "id": "aiplatform.projects.locations.featurestores.delete", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", + "required": true, + "description": "Required. The name of the Featurestore to be deleted. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", + "location": "path", + "type": "string" + }, + "force": { + "description": "If set to true, any EntityTypes and Features for this Featurestore will also be deleted. (Otherwise, the request will only work if the Featurestore has no EntityTypes.)", + "type": "boolean", + "location": "query" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}", + "description": "Deletes a single Featurestore. The Featurestore must not contain any EntityTypes or `force` must be set to true for the request to succeed.", + "httpMethod": "DELETE" + }, + "patch": { + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}", + "description": "Updates the parameters of a single Featurestore.", + "httpMethod": "PATCH", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", + "type": "string", + "required": true, + "location": "path", + "description": "Output only. Name of the Featurestore. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`" + }, + "updateMask": { + "format": "google-fieldmask", + "location": "query", + "type": "string", + "description": "Field mask is used to specify the fields to be overwritten in the Featurestore resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `online_serving_config.fixed_node_count` * `online_serving_config.scaling` * `online_storage_ttl_days`" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Featurestore" + }, + "id": "aiplatform.projects.locations.featurestores.patch", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "create": { + "id": "aiplatform.projects.locations.featurestores.create", + "parameters": { + "featurestoreId": { + "description": "Required. The ID to use for this Featurestore, which will become the final component of the Featurestore's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location.", + "location": "query", + "type": "string" + }, + "parent": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location to create Featurestores. Format: `projects/{project}/locations/{location}`", + "location": "path", + "required": true + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Featurestore" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores", + "description": "Creates a new Featurestore in a given project and location.", + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+parent}/featurestores" + }, + "get": { + "httpMethod": "GET", + "id": "aiplatform.projects.locations.featurestores.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "description": "Required. The name of the Featurestore resource.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", + "location": "path", + "type": "string" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Featurestore" + }, + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}", + "description": "Gets details of a single Featurestore." + }, + "searchFeatures": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1SearchFeaturesResponse" + }, + "parameterOrder": [ + "location" + ], + "description": "Searches Features matching a query in a given project.", + "parameters": { + "query": { + "description": "Query string that is a conjunction of field-restricted queries and/or field-restricted filters. Field-restricted queries and filters can be combined using `AND` to form a conjunction. A field query is in the form FIELD:QUERY. This implicitly checks if QUERY exists as a substring within Feature's FIELD. The QUERY and the FIELD are converted to a sequence of words (i.e. tokens) for comparison. This is done by: * Removing leading/trailing whitespace and tokenizing the search value. Characters that are not one of alphanumeric `[a-zA-Z0-9]`, underscore `_`, or asterisk `*` are treated as delimiters for tokens. `*` is treated as a wildcard that matches characters within a token. * Ignoring case. * Prepending an asterisk to the first and appending an asterisk to the last token in QUERY. A QUERY must be either a singular token or a phrase. A phrase is one or multiple words enclosed in double quotation marks (\"). With phrases, the order of the words is important. Words in the phrase must be matching in order and consecutively. Supported FIELDs for field-restricted queries: * `feature_id` * `description` * `entity_type_id` Examples: * `feature_id: foo` --\u003e Matches a Feature with ID containing the substring `foo` (eg. `foo`, `foofeature`, `barfoo`). * `feature_id: foo*feature` --\u003e Matches a Feature with ID containing the substring `foo*feature` (eg. `foobarfeature`). * `feature_id: foo AND description: bar` --\u003e Matches a Feature with ID containing the substring `foo` and description containing the substring `bar`. Besides field queries, the following exact-match filters are supported. The exact-match filters do not support wildcards. Unlike field-restricted queries, exact-match filters are case-sensitive. * `feature_id`: Supports = comparisons. * `description`: Supports = comparisons. Multi-token filters should be enclosed in quotes. * `entity_type_id`: Supports = comparisons. * `value_type`: Supports = and != comparisons. * `labels`: Supports key-value equality as well as key presence. * `featurestore_id`: Supports = comparisons. Examples: * `description = \"foo bar\"` --\u003e Any Feature with description exactly equal to `foo bar` * `value_type = DOUBLE` --\u003e Features whose type is DOUBLE. * `labels.active = yes AND labels.env = prod` --\u003e Features having both (active: yes) and (env: prod) labels. * `labels.env: *` --\u003e Any Feature which has a label with `env` as the key.", + "location": "query", + "type": "string" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "A page token, received from a previous FeaturestoreService.SearchFeatures call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.SearchFeatures, except `page_size`, must match the call that provided the page token." + }, + "pageSize": { + "format": "int32", + "description": "The maximum number of Features to return. The service may return fewer than this value. If unspecified, at most 100 Features will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100.", + "type": "integer", + "location": "query" + }, + "location": { + "type": "string", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location to search Features. Format: `projects/{project}/locations/{location}`" + } + }, + "id": "aiplatform.projects.locations.featurestores.searchFeatures", + "httpMethod": "GET", + "path": "v1beta1/{+location}/featurestores:searchFeatures", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores:searchFeatures" + } + }, + "resources": { + "entityTypes": { + "resources": { + "operations": { + "methods": { + "list": { + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.list", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations", + "parameters": { + "pageSize": { + "description": "The standard list page size.", + "format": "int32", + "type": "integer", + "location": "query" + }, + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + }, + "name": { + "required": true, + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "description": "The name of the operation's parent resource." + }, + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + } + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "path": "v1beta1/{+name}/operations" + }, + "wait": { + "path": "v1beta1/{+name}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "POST", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}:wait", + "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.wait", + "parameters": { + "timeout": { + "format": "google-duration", + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query" + }, + "name": { + "required": true, + "location": "path", + "type": "string", + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$" + } + }, + "parameterOrder": [ + "name" + ] + }, + "get": { + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.get", + "httpMethod": "GET", + "path": "v1beta1/{+name}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameters": { + "name": { + "required": true, + "location": "path", + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", + "type": "string" + } + } + }, + "cancel": { + "path": "v1beta1/{+name}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "type": "string" + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "httpMethod": "POST", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}:cancel", + "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.cancel", + "parameterOrder": [ + "name" + ] + }, + "delete": { + "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.delete", + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "description": "The name of the operation resource to be deleted." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1beta1/{+name}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}", + "httpMethod": "DELETE" + } + } + }, + "features": { + "resources": { + "operations": { + "methods": { + "wait": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}:wait", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.wait", + "path": "v1beta1/{+name}:wait", + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "format": "google-duration", + "type": "string" + }, + "name": { + "description": "The name of the operation resource to wait on.", + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "cancel": { + "path": "v1beta1/{+name}:cancel", + "httpMethod": "POST", + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}:cancel", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + } + }, + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "type": "string" + } + }, + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.delete", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}" + }, + "get": { + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.get", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", + "location": "path", + "required": true, + "description": "The name of the operation resource.", + "type": "string" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "GET" + }, + "list": { + "parameters": { + "pageSize": { + "description": "The standard list page size.", + "format": "int32", + "location": "query", + "type": "integer" + }, + "pageToken": { + "location": "query", + "description": "The standard list page token.", + "type": "string" + }, + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+$", + "type": "string", + "required": true, + "description": "The name of the operation's parent resource.", + "location": "path" + } + }, + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.list", + "httpMethod": "GET", + "path": "v1beta1/{+name}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations" + } + } + } + }, + "methods": { + "patch": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Feature" + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Feature" + }, + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}", + "httpMethod": "PATCH", + "parameterOrder": [ + "name" + ], + "description": "Updates the parameters of a single Feature.", + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.patch", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+$", + "description": "Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.", + "required": true, + "type": "string", + "location": "path" + }, + "updateMask": { + "location": "query", + "type": "string", + "format": "google-fieldmask", + "description": "Field mask is used to specify the fields to be overwritten in the Features resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `description` * `labels` * `disable_monitoring` (Not supported for FeatureRegistryService Feature) * `point_of_contact` (Not supported for FeaturestoreService FeatureStore)" + } + } + }, + "batchCreate": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.batchCreate", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1BatchCreateFeaturesRequest" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features:batchCreate", + "parameterOrder": [ + "parent" + ], + "path": "v1beta1/{+parent}/features:batchCreate", + "parameters": { + "parent": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "description": "Required. The resource name of the EntityType to create the batch of Features under. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`", + "required": true + } + }, + "description": "Creates a batch of Features in a given EntityType.", + "httpMethod": "POST" + }, + "get": { + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+$", + "description": "Required. The name of the Feature resource. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", + "location": "path", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets details of a single Feature.", + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.get", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Feature" + } + }, + "delete": { + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}", + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+$", + "location": "path", + "required": true, + "description": "Required. The name of the Features to be deleted. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}`" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Deletes a single Feature.", + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.delete", + "path": "v1beta1/{+name}" + }, + "list": { + "description": "Lists Features in a given EntityType.", + "path": "v1beta1/{+parent}/features", + "parameters": { + "latestStatsCount": { + "format": "int32", + "description": "Only applicable for Vertex AI Feature Store (Legacy). If set, return the most recent ListFeaturesRequest.latest_stats_count of stats for each Feature in response. Valid value is [0, 10]. If number of stats exists \u003c ListFeaturesRequest.latest_stats_count, return all existing stats.", + "type": "integer", + "location": "query" + }, + "pageToken": { + "description": "A page token, received from a previous FeaturestoreService.ListFeatures call or FeatureRegistryService.ListFeatures call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.ListFeatures or FeatureRegistryService.ListFeatures must match the call that provided the page token.", + "location": "query", + "type": "string" + }, + "pageSize": { + "type": "integer", + "description": "The maximum number of Features to return. The service may return fewer than this value. If unspecified, at most 1000 Features will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000.", + "location": "query", + "format": "int32" + }, + "parent": { + "description": "Required. The resource name of the Location to list Features. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "location": "path" + }, + "readMask": { + "description": "Mask specifying which fields to read.", + "location": "query", + "type": "string", + "format": "google-fieldmask" + }, + "filter": { + "location": "query", + "type": "string", + "description": "Lists the Features that match the filter expression. The following filters are supported: * `value_type`: Supports = and != comparisons. * `create_time`: Supports =, !=, \u003c, \u003e, \u003e=, and \u003c= comparisons. Values must be in RFC 3339 format. * `update_time`: Supports =, !=, \u003c, \u003e, \u003e=, and \u003c= comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality as well as key presence. Examples: * `value_type = DOUBLE` --\u003e Features whose type is DOUBLE. * `create_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\" OR update_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\"` --\u003e EntityTypes created or updated after 2020-01-31T15:30:00.000000Z. * `labels.active = yes AND labels.env = prod` --\u003e Features having both (active: yes) and (env: prod) labels. * `labels.env: *` --\u003e Any Feature which has a label with 'env' as the key." + }, + "orderBy": { + "type": "string", + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `feature_id` * `value_type` (Not supported for FeatureRegistry Feature) * `create_time` * `update_time`", + "location": "query" + } + }, + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListFeaturesResponse" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features", + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.list", + "parameterOrder": [ + "parent" + ] + }, + "create": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features", + "httpMethod": "POST", + "description": "Creates a new Feature in a given EntityType.", + "path": "v1beta1/{+parent}/features", + "id": "aiplatform.projects.locations.featurestores.entityTypes.features.create", + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "required": true, + "location": "path", + "description": "Required. The resource name of the EntityType or FeatureGroup to create a Feature. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", + "type": "string" + }, + "featureId": { + "description": "Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.", + "location": "query", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Feature" + } + } + } + } + }, + "methods": { + "readFeatureValues": { + "description": "Reads Feature values of a specific entity of an EntityType. For reading feature values of multiple entities of an EntityType, please use StreamingReadFeatureValues.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ReadFeatureValuesRequest" + }, + "parameterOrder": [ + "entityType" + ], + "path": "v1beta1/{+entityType}:readFeatureValues", + "id": "aiplatform.projects.locations.featurestores.entityTypes.readFeatureValues", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:readFeatureValues", + "parameters": { + "entityType": { + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "type": "string", + "description": "Required. The resource name of the EntityType for the entity being read. Value format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`. For example, for a machine learning model predicting user clicks on a website, an EntityType ID could be `user`." + } + }, + "httpMethod": "POST", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponse" + } + }, + "streamingReadFeatureValues": { + "httpMethod": "POST", + "path": "v1beta1/{+entityType}:streamingReadFeatureValues", + "description": "Reads Feature values for multiple entities. Depending on their size, data for different entities may be broken up across multiple responses.", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1StreamingReadFeatureValuesRequest" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:streamingReadFeatureValues", + "id": "aiplatform.projects.locations.featurestores.entityTypes.streamingReadFeatureValues", + "parameters": { + "entityType": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "required": true, + "location": "path", + "description": "Required. The resource name of the entities' type. Value format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`. For example, for a machine learning model predicting user clicks on a website, an EntityType ID could be `user`." + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "entityType" + ] + }, + "deleteFeatureValues": { + "parameters": { + "entityType": { + "description": "Required. The resource name of the EntityType grouping the Features for which values are being deleted from. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`", + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "required": true + } + }, + "path": "v1beta1/{+entityType}:deleteFeatureValues", + "parameterOrder": [ + "entityType" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequest" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.featurestores.entityTypes.deleteFeatureValues", + "description": "Delete Feature values from Featurestore. The progress of the deletion is tracked by the returned operation. The deleted feature values are guaranteed to be invisible to subsequent read operations after the operation is marked as successfully done. If a delete feature values operation fails, the feature values returned from reads and exports may be inconsistent. If consistency is required, the caller must retry the same delete request again and wait till the new operation returned is marked as successfully done.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:deleteFeatureValues", + "httpMethod": "POST" + }, + "getIamPolicy": { + "id": "aiplatform.projects.locations.featurestores.entityTypes.getIamPolicy", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:getIamPolicy", + "parameters": { + "options.requestedPolicyVersion": { + "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", + "type": "integer", + "format": "int32", + "location": "query" + }, + "resource": { + "type": "string", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field." + } + }, + "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+resource}:getIamPolicy", + "response": { + "$ref": "GoogleIamV1Policy" + }, + "parameterOrder": [ + "resource" + ] + }, + "importFeatureValues": { + "parameters": { + "entityType": { + "location": "path", + "description": "Required. The resource name of the EntityType grouping the Features for which values are being imported. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ImportFeatureValuesRequest" + }, + "description": "Imports Feature values into the Featurestore from a source storage. The progress of the import is tracked by the returned operation. The imported features are guaranteed to be visible to subsequent read operations after the operation is marked as successfully done. If an import operation fails, the Feature values returned from reads and exports may be inconsistent. If consistency is required, the caller must retry the same import request again and wait till the new operation returned is marked as successfully done. There are also scenarios where the caller can cause inconsistency. - Source data for import contains multiple distinct Feature values for the same entity ID and timestamp. - Source is modified during an import. This includes adding, updating, or removing source data and/or metadata. Examples of updating metadata include but are not limited to changing storage location, storage class, or retention policy. - Online serving cluster is under-provisioned.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:importFeatureValues", + "path": "v1beta1/{+entityType}:importFeatureValues", + "parameterOrder": [ + "entityType" + ], + "id": "aiplatform.projects.locations.featurestores.entityTypes.importFeatureValues", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST" + }, + "list": { + "description": "Lists EntityTypes in a given Featurestore.", + "path": "v1beta1/{+parent}/entityTypes", + "id": "aiplatform.projects.locations.featurestores.entityTypes.list", + "parameters": { + "parent": { + "type": "string", + "description": "Required. The resource name of the Featurestore to list EntityTypes. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$" + }, + "readMask": { + "format": "google-fieldmask", + "location": "query", + "type": "string", + "description": "Mask specifying which fields to read." + }, + "pageToken": { + "type": "string", + "description": "A page token, received from a previous FeaturestoreService.ListEntityTypes call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.ListEntityTypes must match the call that provided the page token.", + "location": "query" + }, + "filter": { + "type": "string", + "location": "query", + "description": "Lists the EntityTypes that match the filter expression. The following filters are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003e=`, and `\u003c=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003e=`, and `\u003c=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality as well as key presence. Examples: * `create_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\" OR update_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\"` --\u003e EntityTypes created or updated after 2020-01-31T15:30:00.000000Z. * `labels.active = yes AND labels.env = prod` --\u003e EntityTypes having both (active: yes) and (env: prod) labels. * `labels.env: *` --\u003e Any EntityType which has a label with 'env' as the key." + }, + "pageSize": { + "location": "query", + "type": "integer", + "description": "The maximum number of EntityTypes to return. The service may return fewer than this value. If unspecified, at most 1000 EntityTypes will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000.", + "format": "int32" + }, + "orderBy": { + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `entity_type_id` * `create_time` * `update_time`", + "location": "query", + "type": "string" + } + }, + "parameterOrder": [ + "parent" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListEntityTypesResponse" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes", + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "create": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1EntityType" + }, + "parameters": { + "entityTypeId": { + "description": "Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within a featurestore.", + "type": "string", + "location": "query" + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", + "description": "Required. The resource name of the Featurestore to create EntityTypes. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", + "type": "string", + "required": true, + "location": "path" + } + }, + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes", + "description": "Creates a new EntityType in a given Featurestore.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+parent}/entityTypes", + "id": "aiplatform.projects.locations.featurestores.entityTypes.create" + }, + "writeFeatureValues": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "entityType" + ], + "parameters": { + "entityType": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "type": "string", + "location": "path", + "required": true, + "description": "Required. The resource name of the EntityType for the entities being written. Value format: `projects/{project}/locations/{location}/featurestores/ {featurestore}/entityTypes/{entityType}`. For example, for a machine learning model predicting user clicks on a website, an EntityType ID could be `user`." + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:writeFeatureValues", + "httpMethod": "POST", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1WriteFeatureValuesResponse" + }, + "description": "Writes Feature values of one or more entities of an EntityType. The Feature values are merged into existing entities if any. The Feature values to be written must have timestamp within the online storage retention.", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1WriteFeatureValuesRequest" + }, + "id": "aiplatform.projects.locations.featurestores.entityTypes.writeFeatureValues", + "path": "v1beta1/{+entityType}:writeFeatureValues" + }, + "testIamPermissions": { + "path": "v1beta1/{+resource}:testIamPermissions", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:testIamPermissions", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "parameterOrder": [ + "resource" + ], + "parameters": { + "resource": { + "type": "string", + "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$" + }, + "permissions": { + "location": "query", + "type": "string", + "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", + "repeated": true + } + }, + "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", + "response": { + "$ref": "GoogleIamV1TestIamPermissionsResponse" + }, + "id": "aiplatform.projects.locations.featurestores.entityTypes.testIamPermissions" + }, + "setIamPolicy": { + "id": "aiplatform.projects.locations.featurestores.entityTypes.setIamPolicy", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleIamV1SetIamPolicyRequest" + }, + "parameters": { + "resource": { + "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "required": true + } + }, + "parameterOrder": [ + "resource" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:setIamPolicy", + "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", + "response": { + "$ref": "GoogleIamV1Policy" + }, + "httpMethod": "POST", + "path": "v1beta1/{+resource}:setIamPolicy" + }, + "patch": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "description": "Updates the parameters of a single EntityType.", + "parameterOrder": [ + "name" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1EntityType" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}", + "httpMethod": "PATCH", + "parameters": { + "updateMask": { + "description": "Field mask is used to specify the fields to be overwritten in the EntityType resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `description` * `labels` * `monitoring_config.snapshot_analysis.disabled` * `monitoring_config.snapshot_analysis.monitoring_interval_days` * `monitoring_config.snapshot_analysis.staleness_days` * `monitoring_config.import_features_analysis.state` * `monitoring_config.import_features_analysis.anomaly_detection_baseline` * `monitoring_config.numerical_threshold_config.value` * `monitoring_config.categorical_threshold_config.value` * `offline_storage_ttl_days`", + "location": "query", + "format": "google-fieldmask", + "type": "string" + }, + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "location": "path", + "required": true, + "description": "Immutable. Name of the EntityType. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore." + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1EntityType" + }, + "id": "aiplatform.projects.locations.featurestores.entityTypes.patch" + }, + "get": { + "id": "aiplatform.projects.locations.featurestores.entityTypes.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1EntityType" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}", + "description": "Gets details of a single EntityType.", + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "required": true, + "location": "path", + "description": "Required. The name of the EntityType resource. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`" + } + }, + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET" + }, + "exportFeatureValues": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:exportFeatureValues", + "path": "v1beta1/{+entityType}:exportFeatureValues", + "id": "aiplatform.projects.locations.featurestores.entityTypes.exportFeatureValues", + "parameterOrder": [ + "entityType" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ExportFeatureValuesRequest" + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "POST", + "description": "Exports Feature values from all the entities of a target EntityType.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "entityType": { + "description": "Required. The resource name of the EntityType from which to export Feature values. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "location": "path", + "required": true, + "type": "string" + } + } + }, + "delete": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}", + "description": "Deletes a single EntityType. The EntityType must not have any Features or `force` must be set to true for the request to succeed.", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", + "type": "string", + "description": "Required. The name of the EntityType to be deleted. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`", + "location": "path", + "required": true + }, + "force": { + "location": "query", + "description": "If set to true, any Features for this EntityType will also be deleted. (Otherwise, the request will only work if the EntityType has no Features.)", + "type": "boolean" + } + }, + "id": "aiplatform.projects.locations.featurestores.entityTypes.delete", + "httpMethod": "DELETE", + "path": "v1beta1/{+name}" + } + } + }, + "operations": { + "methods": { + "cancel": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "httpMethod": "POST", + "path": "v1beta1/{+name}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/operations/[^/]+$", + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations/{operationsId}:cancel", + "id": "aiplatform.projects.locations.featurestores.operations.cancel", + "parameterOrder": [ + "name" + ] + }, + "get": { + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.featurestores.operations.get", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations/{operationsId}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/operations/[^/]+$", + "required": true, + "description": "The name of the operation resource.", + "type": "string", + "location": "path" + } + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}" + }, + "delete": { + "httpMethod": "DELETE", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations/{operationsId}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string", + "required": true, + "description": "The name of the operation resource to be deleted." + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "id": "aiplatform.projects.locations.featurestores.operations.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}" + }, + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "path": "v1beta1/{+name}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "pageSize": { + "format": "int32", + "type": "integer", + "description": "The standard list page size.", + "location": "query" + }, + "name": { + "location": "path", + "type": "string", + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", + "required": true + }, + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token." + } + }, + "httpMethod": "GET", + "id": "aiplatform.projects.locations.featurestores.operations.list", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations", + "parameterOrder": [ + "name" + ] + }, + "wait": { + "httpMethod": "POST", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "format": "google-duration", + "type": "string" + }, + "name": { + "type": "string", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on." + } + }, + "path": "v1beta1/{+name}:wait", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.featurestores.operations.wait", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations/{operationsId}:wait" + } + } + } + } + }, + "evaluationTasks": { + "resources": { + "operations": { + "methods": { + "wait": { + "path": "v1beta1/{+name}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationTasks/{evaluationTasksId}/operations/{operationsId}:wait", + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "id": "aiplatform.projects.locations.evaluationTasks.operations.wait", + "parameters": { + "name": { + "description": "The name of the operation resource to wait on.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/evaluationTasks/[^/]+/operations/[^/]+$", + "type": "string", + "location": "path" + }, + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "type": "string", + "location": "query" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "delete": { + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "DELETE", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationTasks/{evaluationTasksId}/operations/{operationsId}", + "parameters": { + "name": { + "location": "path", + "required": true, + "description": "The name of the operation resource to be deleted.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/evaluationTasks/[^/]+/operations/[^/]+$" + } + }, + "id": "aiplatform.projects.locations.evaluationTasks.operations.delete", + "path": "v1beta1/{+name}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." + }, + "list": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationTasks/{evaluationTasksId}/operations", + "parameters": { + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + }, + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + }, + "pageSize": { + "description": "The standard list page size.", + "location": "query", + "format": "int32", + "type": "integer" + }, + "name": { + "required": true, + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/evaluationTasks/[^/]+$", + "description": "The name of the operation's parent resource." + } + }, + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "id": "aiplatform.projects.locations.evaluationTasks.operations.list", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "path": "v1beta1/{+name}/operations", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "get": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "httpMethod": "GET", + "parameters": { + "name": { + "location": "path", + "type": "string", + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/evaluationTasks/[^/]+/operations/[^/]+$", + "required": true + } + }, + "id": "aiplatform.projects.locations.evaluationTasks.operations.get", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationTasks/{evaluationTasksId}/operations/{operationsId}" + } + } + } + } + }, + "dataLabelingJobs": { + "resources": { + "operations": { + "methods": { + "list": { + "parameters": { + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token." + }, + "pageSize": { + "type": "integer", + "description": "The standard list page size.", + "format": "int32", + "location": "query" + }, + "name": { + "type": "string", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+$", + "description": "The name of the operation's parent resource." + }, + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + } + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "httpMethod": "GET", + "path": "v1beta1/{+name}/operations", + "id": "aiplatform.projects.locations.dataLabelingJobs.operations.list", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations" + }, + "delete": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.dataLabelingJobs.operations.delete", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "httpMethod": "DELETE", + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be deleted.", + "type": "string" + } + }, + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "cancel": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "required": true, + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be cancelled." + } + }, + "path": "v1beta1/{+name}:cancel", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.dataLabelingJobs.operations.cancel", + "httpMethod": "POST" + }, + "get": { + "path": "v1beta1/{+name}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "id": "aiplatform.projects.locations.dataLabelingJobs.operations.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+/operations/[^/]+$", + "type": "string", + "required": true, + "description": "The name of the operation resource." + } + } + }, + "wait": { + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}:wait", + "id": "aiplatform.projects.locations.dataLabelingJobs.operations.wait", + "path": "v1beta1/{+name}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "timeout": { + "location": "query", + "type": "string", + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + }, + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "required": true, + "location": "path" + } + }, + "httpMethod": "POST" + } + } + } + }, + "methods": { + "get": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1DataLabelingJob" + }, + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "description": "Gets a DataLabelingJob.", + "id": "aiplatform.projects.locations.dataLabelingJobs.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}", + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+$", + "location": "path", + "description": "Required. The name of the DataLabelingJob. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}`" + } + } + }, + "list": { + "parameterOrder": [ + "parent" + ], + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs", + "id": "aiplatform.projects.locations.dataLabelingJobs.list", + "description": "Lists DataLabelingJobs in a Location.", + "parameters": { + "orderBy": { + "description": "A comma-separated list of fields to order by, sorted in ascending order by default. Use `desc` after a field name for descending.", + "location": "query", + "type": "string" + }, + "readMask": { + "description": "Mask specifying which fields to read. FieldMask represents a set of symbolic field paths. For example, the mask can be `paths: \"name\"`. The \"name\" here is a field in DataLabelingJob. If this field is not set, all fields of the DataLabelingJob are returned.", + "type": "string", + "location": "query", + "format": "google-fieldmask" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + }, + "filter": { + "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`", + "type": "string", + "location": "query" + }, + "parent": { + "description": "Required. The parent of the DataLabelingJob. Format: `projects/{project}/locations/{location}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true, + "location": "path" + }, + "pageSize": { + "location": "query", + "format": "int32", + "description": "The standard list page size.", + "type": "integer" + } + }, + "path": "v1beta1/{+parent}/dataLabelingJobs", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListDataLabelingJobsResponse" + } + }, + "delete": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.dataLabelingJobs.delete", + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "description": "Required. The name of the DataLabelingJob to be deleted. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}`", + "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+$", + "type": "string", + "required": true, + "location": "path" + } + }, + "description": "Deletes a DataLabelingJob.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}" + }, + "cancel": { + "path": "v1beta1/{+name}:cancel", + "id": "aiplatform.projects.locations.dataLabelingJobs.cancel", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}:cancel", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1CancelDataLabelingJobRequest" + }, + "description": "Cancels a DataLabelingJob. Success of cancellation is not guaranteed.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "httpMethod": "POST", + "parameters": { + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+$", + "description": "Required. The name of the DataLabelingJob. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}`", + "type": "string" + } + }, + "parameterOrder": [ + "name" + ] + }, + "create": { + "parameterOrder": [ + "parent" + ], + "httpMethod": "POST", + "parameters": { + "parent": { + "type": "string", + "required": true, + "location": "path", + "description": "Required. The parent of the DataLabelingJob. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "id": "aiplatform.projects.locations.dataLabelingJobs.create", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1DataLabelingJob" + }, + "path": "v1beta1/{+parent}/dataLabelingJobs", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1DataLabelingJob" + }, + "description": "Creates a DataLabelingJob." + } + } + }, + "publishers": { + "resources": { + "models": { + "methods": { + "streamRawPredict": { + "description": "Perform a streaming online prediction with an arbitrary HTTP payload.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "response": { + "$ref": "GoogleApiHttpBody" + }, + "id": "aiplatform.projects.locations.publishers.models.streamRawPredict", + "parameters": { + "endpoint": { + "type": "string", + "location": "path", + "required": true, + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$" + } + }, + "path": "v1beta1/{+endpoint}:streamRawPredict", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1StreamRawPredictRequest" + }, + "parameterOrder": [ + "endpoint" + ], + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:streamRawPredict" + }, + "getIamPolicy": { + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+resource}:getIamPolicy", + "id": "aiplatform.projects.locations.publishers.models.getIamPolicy", + "parameterOrder": [ + "resource" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:getIamPolicy", + "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", + "response": { + "$ref": "GoogleIamV1Policy" + }, + "parameters": { + "resource": { + "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", + "location": "path", + "type": "string", + "required": true, + "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field." + }, + "options.requestedPolicyVersion": { + "type": "integer", + "location": "query", + "format": "int32", + "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies)." + } + } + }, + "serverStreamingPredict": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1StreamingPredictRequest" + }, + "description": "Perform a server-side streaming online prediction request for Vertex LLM streaming.", + "parameterOrder": [ + "endpoint" + ], + "path": "v1beta1/{+endpoint}:serverStreamingPredict", + "id": "aiplatform.projects.locations.publishers.models.serverStreamingPredict", + "httpMethod": "POST", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1StreamingPredictResponse" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:serverStreamingPredict", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "parameters": { + "endpoint": { + "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", + "location": "path", + "required": true, + "type": "string", + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" + } + } + }, + "computeTokens": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:computeTokens", + "id": "aiplatform.projects.locations.publishers.models.computeTokens", + "parameters": { + "endpoint": { + "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", + "location": "path", + "type": "string", + "description": "Required. The name of the Endpoint requested to get lists of tokens and token ids.", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "endpoint" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ComputeTokensResponse" + }, + "httpMethod": "POST", + "description": "Return a list of tokens based on the input text.", + "path": "v1beta1/{+endpoint}:computeTokens", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ComputeTokensRequest" + } + }, + "predict": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1PredictResponse" + }, + "parameterOrder": [ + "endpoint" + ], + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:predict", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1PredictRequest" + }, + "path": "v1beta1/{+endpoint}:predict", + "description": "Perform an online prediction.", + "parameters": { + "endpoint": { + "required": true, + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$" + } + }, + "id": "aiplatform.projects.locations.publishers.models.predict" + }, + "countTokens": { + "path": "v1beta1/{+endpoint}:countTokens", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1CountTokensRequest" + }, + "parameterOrder": [ + "endpoint" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "description": "Perform a token counting.", + "parameters": { + "endpoint": { + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", + "description": "Required. The name of the Endpoint requested to perform token counting. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" + } + }, + "id": "aiplatform.projects.locations.publishers.models.countTokens", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1CountTokensResponse" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:countTokens", + "httpMethod": "POST" + }, + "streamGenerateContent": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponse" + }, + "id": "aiplatform.projects.locations.publishers.models.streamGenerateContent", + "parameters": { + "model": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", + "location": "path", + "type": "string", + "description": "Required. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "parameterOrder": [ + "model" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1GenerateContentRequest" + }, + "path": "v1beta1/{+model}:streamGenerateContent", + "description": "Generate content with multimodal inputs with streaming support.", + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:streamGenerateContent" + }, + "generateContent": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1GenerateContentRequest" + }, + "parameters": { + "model": { + "location": "path", + "required": true, + "description": "Required. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`", + "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", + "type": "string" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:generateContent", + "description": "Generate content with multimodal inputs.", + "path": "v1beta1/{+model}:generateContent", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ], + "httpMethod": "POST", + "id": "aiplatform.projects.locations.publishers.models.generateContent", + "parameterOrder": [ + "model" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponse" + } + }, + "rawPredict": { + "description": "Perform an online prediction with an arbitrary HTTP payload. The response includes the following HTTP headers: * `X-Vertex-AI-Endpoint-Id`: ID of the Endpoint that served this prediction. * `X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's DeployedModel that served this prediction.", + "response": { + "$ref": "GoogleApiHttpBody" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1RawPredictRequest" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:rawPredict", + "parameters": { + "endpoint": { + "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", + "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", + "type": "string", + "location": "path", + "required": true + } + }, + "path": "v1beta1/{+endpoint}:rawPredict", + "id": "aiplatform.projects.locations.publishers.models.rawPredict", + "parameterOrder": [ + "endpoint" + ], + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform", + "https://www.googleapis.com/auth/cloud-platform.read-only" + ] + } + } + } + } + }, + "extensionControllers": { + "resources": { + "operations": { + "methods": { + "wait": { + "id": "aiplatform.projects.locations.extensionControllers.operations.wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string", + "location": "query", + "format": "google-duration" + }, + "name": { + "required": true, + "description": "The name of the operation resource to wait on.", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/extensionControllers/[^/]+/operations/[^/]+$" + } + }, + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensionControllers/{extensionControllersId}/operations/{operationsId}:wait" + }, + "get": { + "httpMethod": "GET", + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.extensionControllers.operations.get", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensionControllers/{extensionControllersId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/extensionControllers/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource.", + "type": "string", + "required": true + } + } + }, + "cancel": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensionControllers/{extensionControllersId}/operations/{operationsId}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "id": "aiplatform.projects.locations.extensionControllers.operations.cancel", + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "parameters": { + "name": { + "type": "string", + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/extensionControllers/[^/]+/operations/[^/]+$", + "required": true + } + } + }, + "list": { + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.extensionControllers.operations.list", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}/operations", + "parameters": { + "name": { + "required": true, + "location": "path", + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/extensionControllers/[^/]+$", + "type": "string" + }, + "filter": { + "description": "The standard list filter.", + "location": "query", + "type": "string" + }, + "pageSize": { + "description": "The standard list page size.", + "format": "int32", + "type": "integer", + "location": "query" + }, + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + } + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensionControllers/{extensionControllersId}/operations" + }, + "delete": { + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "type": "string", + "required": true, + "location": "path", + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/extensionControllers/[^/]+/operations/[^/]+$" + } + }, + "httpMethod": "DELETE", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.extensionControllers.operations.delete", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensionControllers/{extensionControllersId}/operations/{operationsId}" + } + } + } + } + }, + "operations": { + "methods": { + "list": { + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "pageToken": { + "description": "The standard list page token.", + "location": "query", + "type": "string" + }, + "pageSize": { + "format": "int32", + "description": "The standard list page size.", + "location": "query", + "type": "integer" + }, + "name": { + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string", + "location": "path", + "required": true + }, + "filter": { + "description": "The standard list filter.", + "location": "query", + "type": "string" + } + }, + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "path": "v1beta1/{+name}/operations", + "httpMethod": "GET", + "id": "aiplatform.projects.locations.operations.list", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/operations" + }, + "get": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.operations.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/operations/[^/]+$", + "required": true, + "type": "string", + "description": "The name of the operation resource." + } + }, + "parameterOrder": [ + "name" + ] + }, + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.operations.delete", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "description": "The name of the operation resource to be deleted.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/operations/[^/]+$", + "required": true, + "location": "path" + } + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}" + }, + "wait": { + "parameters": { + "name": { + "type": "string", + "description": "The name of the operation resource to wait on.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/operations/[^/]+$", + "location": "path" + }, + "timeout": { + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string", + "location": "query" + } + }, + "path": "v1beta1/{+name}:wait", + "httpMethod": "POST", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.operations.wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." + }, + "cancel": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}:cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "type": "string" + } + }, + "path": "v1beta1/{+name}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "id": "aiplatform.projects.locations.operations.cancel", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST" + } + } + }, + "indexes": { + "resources": { + "operations": { + "methods": { + "list": { + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations", + "parameters": { + "pageToken": { + "location": "query", + "description": "The standard list page token.", + "type": "string" + }, + "pageSize": { + "description": "The standard list page size.", + "format": "int32", + "location": "query", + "type": "integer" + }, + "name": { + "location": "path", + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", + "required": true, + "type": "string" + }, + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.indexes.operations.list", + "path": "v1beta1/{+name}/operations", + "httpMethod": "GET" + }, + "get": { + "path": "v1beta1/{+name}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource.", + "required": true + } + }, + "id": "aiplatform.projects.locations.indexes.operations.get", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "wait": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "POST", + "parameters": { + "timeout": { + "type": "string", + "location": "query", + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "type": "string", + "location": "path", + "required": true + } + }, + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations/{operationsId}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.indexes.operations.wait", + "path": "v1beta1/{+name}:wait", + "parameterOrder": [ + "name" + ] + }, + "cancel": { + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "httpMethod": "POST", + "id": "aiplatform.projects.locations.indexes.operations.cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations/{operationsId}:cancel", + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+/operations/[^/]+$" + } + }, + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}:cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + } + }, + "delete": { + "httpMethod": "DELETE", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be deleted.", + "type": "string", + "required": true, + "location": "path" + } + }, + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.indexes.operations.delete", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations/{operationsId}" + } + } + } + }, + "methods": { + "get": { + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}", + "httpMethod": "GET", + "parameters": { + "name": { + "type": "string", + "description": "Required. The name of the Index resource. Format: `projects/{project}/locations/{location}/indexes/{index}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Index" + }, + "description": "Gets an Index.", + "id": "aiplatform.projects.locations.indexes.get", + "path": "v1beta1/{+name}" + }, + "upsertDatapoints": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1UpsertDatapointsRequest" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.indexes.upsertDatapoints", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1UpsertDatapointsResponse" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}:upsertDatapoints", + "parameters": { + "index": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", + "type": "string", + "location": "path", + "description": "Required. The name of the Index resource to be updated. Format: `projects/{project}/locations/{location}/indexes/{index}`" + } + }, + "parameterOrder": [ + "index" + ], + "httpMethod": "POST", + "path": "v1beta1/{+index}:upsertDatapoints", + "description": "Add/update Datapoints into an Index." + }, + "removeDatapoints": { + "id": "aiplatform.projects.locations.indexes.removeDatapoints", + "description": "Remove Datapoints from an Index.", + "parameterOrder": [ + "index" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1RemoveDatapointsResponse" + }, + "parameters": { + "index": { + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", + "description": "Required. The name of the Index resource to be updated. Format: `projects/{project}/locations/{location}/indexes/{index}`", + "required": true, + "location": "path", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}:removeDatapoints", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1RemoveDatapointsRequest" + }, + "httpMethod": "POST", + "path": "v1beta1/{+index}:removeDatapoints" + }, + "delete": { + "parameters": { + "name": { + "description": "Required. The name of the Index resource to be deleted. Format: `projects/{project}/locations/{location}/indexes/{index}`", + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", + "required": true, + "type": "string", + "location": "path" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}", + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "description": "Deletes an Index. An Index can only be deleted when all its DeployedIndexes had been undeployed.", + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.indexes.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "patch": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}", + "httpMethod": "PATCH", + "parameters": { + "updateMask": { + "location": "query", + "description": "The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask.", + "type": "string", + "format": "google-fieldmask" + }, + "name": { + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", + "description": "Output only. The resource name of the Index." + } + }, + "description": "Updates an Index.", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Index" + }, + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.indexes.patch" + }, + "create": { + "path": "v1beta1/{+parent}/indexes", + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes", + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "description": "Required. The resource name of the Location to create the Index in. Format: `projects/{project}/locations/{location}`", + "required": true, + "type": "string" + } + }, + "id": "aiplatform.projects.locations.indexes.create", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Creates an Index.", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Index" + }, + "parameterOrder": [ + "parent" + ] + }, + "list": { + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListIndexesResponse" + }, + "description": "Lists Indexes in a Location.", + "parameters": { + "readMask": { + "location": "query", + "type": "string", + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask" + }, + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter." + }, + "parent": { + "type": "string", + "description": "Required. The resource name of the Location from which to list the Indexes. Format: `projects/{project}/locations/{location}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path" + }, + "pageSize": { + "description": "The standard list page size.", + "format": "int32", + "type": "integer", + "location": "query" + }, + "pageToken": { + "type": "string", + "description": "The standard list page token. Typically obtained via ListIndexesResponse.next_page_token of the previous IndexService.ListIndexes call.", + "location": "query" + } + }, + "path": "v1beta1/{+parent}/indexes", + "id": "aiplatform.projects.locations.indexes.list", + "parameterOrder": [ + "parent" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes" + } + } + }, + "migratableResources": { + "resources": { + "operations": { + "methods": { + "get": { + "id": "aiplatform.projects.locations.migratableResources.operations.get", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations/{operationsId}", + "parameters": { + "name": { + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string", + "required": true + } + } + }, + "delete": { + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.migratableResources.operations.delete", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+/operations/[^/]+$", + "required": true, + "type": "string", + "description": "The name of the operation resource to be deleted.", + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations/{operationsId}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "httpMethod": "DELETE", + "path": "v1beta1/{+name}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." + }, + "cancel": { + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "path": "v1beta1/{+name}:cancel", + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "type": "string" + } + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "id": "aiplatform.projects.locations.migratableResources.operations.cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations/{operationsId}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "id": "aiplatform.projects.locations.migratableResources.operations.list", + "path": "v1beta1/{+name}/operations", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "parameters": { + "name": { + "description": "The name of the operation's parent resource.", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+$", + "location": "path" + }, + "pageSize": { + "type": "integer", + "location": "query", + "format": "int32", + "description": "The standard list page size." + }, + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + }, + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter." + } + }, + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations" + }, + "wait": { + "path": "v1beta1/{+name}:wait", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+/operations/[^/]+$", + "required": true, + "type": "string", + "description": "The name of the operation resource to wait on.", + "location": "path" + }, + "timeout": { + "format": "google-duration", + "location": "query", + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.migratableResources.operations.wait", + "parameterOrder": [ + "name" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations/{operationsId}:wait", + "httpMethod": "POST" + } + } + } + }, + "methods": { + "search": { + "description": "Searches all of the resources in automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com that can be migrated to Vertex AI's given location.", + "parameterOrder": [ + "parent" + ], + "path": "v1beta1/{+parent}/migratableResources:search", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/migratableResources:search", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1SearchMigratableResourcesResponse" + }, + "id": "aiplatform.projects.locations.migratableResources.search", + "parameters": { + "parent": { + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "description": "Required. The location that the migratable resources should be searched from. It's the Vertex AI location that the resources can be migrated to, not the resources' original location. Format: `projects/{project}/locations/{location}`" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1SearchMigratableResourcesRequest" + } + }, + "batchMigrate": { + "parameters": { + "parent": { + "description": "Required. The location of the migrated resource will live in. Format: `projects/{project}/locations/{location}`", + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+parent}/migratableResources:batchMigrate", + "id": "aiplatform.projects.locations.migratableResources.batchMigrate", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Batch migrates resources from ml.googleapis.com, automl.googleapis.com, and datalabeling.googleapis.com to Vertex AI.", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1BatchMigrateResourcesRequest" + }, + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/migratableResources:batchMigrate", + "parameterOrder": [ + "parent" + ] + } + } + }, + "featureGroups": { + "resources": { + "operations": { + "methods": { + "list": { + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "path": "v1beta1/{+name}/operations", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.featureGroups.operations.list", + "parameters": { + "pageSize": { + "location": "query", + "description": "The standard list page size.", + "format": "int32", + "type": "integer" + }, + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + }, + "name": { + "description": "The name of the operation's parent resource.", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", + "location": "path" + }, + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/operations" + }, + "delete": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/operations/{operationsId}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "httpMethod": "DELETE", + "parameters": { + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/operations/[^/]+$", + "type": "string", + "description": "The name of the operation resource to be deleted." + } + }, + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.featureGroups.operations.delete", + "response": { + "$ref": "GoogleProtobufEmpty" + } + }, + "wait": { + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.featureGroups.operations.wait", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/operations/{operationsId}:wait", + "path": "v1beta1/{+name}:wait", + "parameters": { + "name": { + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string", + "required": true + }, + "timeout": { + "type": "string", + "format": "google-duration", + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." + }, + "get": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.featureGroups.operations.get", + "parameters": { + "name": { + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource.", + "location": "path" + } + }, + "parameterOrder": [ + "name" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." + } + } + }, + "features": { + "resources": { + "operations": { + "methods": { + "get": { + "path": "v1beta1/{+name}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "description": "The name of the operation resource.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+/operations/[^/]+$", + "type": "string", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.featureGroups.features.operations.get", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "list": { + "path": "v1beta1/{+name}/operations", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}/operations", + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "parameters": { + "pageSize": { + "type": "integer", + "format": "int32", + "description": "The standard list page size.", + "location": "query" + }, + "filter": { + "description": "The standard list filter.", + "location": "query", + "type": "string" + }, + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+$", + "required": true, + "description": "The name of the operation's parent resource.", + "location": "path" + }, + "pageToken": { + "description": "The standard list page token.", + "location": "query", + "type": "string" + } + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "id": "aiplatform.projects.locations.featureGroups.features.operations.list" + }, + "delete": { + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.featureGroups.features.operations.delete", + "httpMethod": "DELETE", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+/operations/[^/]+$", + "type": "string", + "location": "path", + "description": "The name of the operation resource to be deleted.", + "required": true + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "wait": { + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}:wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "httpMethod": "POST", + "path": "v1beta1/{+name}:wait", + "parameters": { + "name": { + "location": "path", + "required": true, + "type": "string", + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+/operations/[^/]+$" + }, + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "format": "google-duration", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.featureGroups.features.operations.wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + } + } + } + }, + "methods": { + "create": { + "path": "v1beta1/{+parent}/features", + "parameters": { + "parent": { + "location": "path", + "required": true, + "description": "Required. The resource name of the EntityType or FeatureGroup to create a Feature. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$" + }, + "featureId": { + "location": "query", + "description": "Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.", + "type": "string" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "POST", + "description": "Creates a new Feature in a given FeatureGroup.", + "parameterOrder": [ + "parent" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Feature" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features", + "id": "aiplatform.projects.locations.featureGroups.features.create", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "delete": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Deletes a single Feature.", + "id": "aiplatform.projects.locations.featureGroups.features.delete", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}", + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+$", + "required": true, + "description": "Required. The name of the Features to be deleted. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}`" + } + }, + "httpMethod": "DELETE", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "get": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Feature" + }, + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.featureGroups.features.get", + "parameters": { + "name": { + "type": "string", + "description": "Required. The name of the Feature resource. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+$", + "location": "path" + } + }, + "description": "Gets details of a single Feature.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "httpMethod": "GET" + }, + "list": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListFeaturesResponse" + }, + "parameters": { + "latestStatsCount": { + "location": "query", + "type": "integer", + "description": "Only applicable for Vertex AI Feature Store (Legacy). If set, return the most recent ListFeaturesRequest.latest_stats_count of stats for each Feature in response. Valid value is [0, 10]. If number of stats exists \u003c ListFeaturesRequest.latest_stats_count, return all existing stats.", + "format": "int32" + }, + "orderBy": { + "location": "query", + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `feature_id` * `value_type` (Not supported for FeatureRegistry Feature) * `create_time` * `update_time`", + "type": "string" + }, + "pageToken": { + "description": "A page token, received from a previous FeaturestoreService.ListFeatures call or FeatureRegistryService.ListFeatures call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.ListFeatures or FeatureRegistryService.ListFeatures must match the call that provided the page token.", + "location": "query", + "type": "string" + }, + "filter": { + "description": "Lists the Features that match the filter expression. The following filters are supported: * `value_type`: Supports = and != comparisons. * `create_time`: Supports =, !=, \u003c, \u003e, \u003e=, and \u003c= comparisons. Values must be in RFC 3339 format. * `update_time`: Supports =, !=, \u003c, \u003e, \u003e=, and \u003c= comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality as well as key presence. Examples: * `value_type = DOUBLE` --\u003e Features whose type is DOUBLE. * `create_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\" OR update_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\"` --\u003e EntityTypes created or updated after 2020-01-31T15:30:00.000000Z. * `labels.active = yes AND labels.env = prod` --\u003e Features having both (active: yes) and (env: prod) labels. * `labels.env: *` --\u003e Any Feature which has a label with 'env' as the key.", + "type": "string", + "location": "query" + }, + "readMask": { + "type": "string", + "description": "Mask specifying which fields to read.", + "location": "query", + "format": "google-fieldmask" + }, + "pageSize": { + "format": "int32", + "description": "The maximum number of Features to return. The service may return fewer than this value. If unspecified, at most 1000 Features will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000.", + "location": "query", + "type": "integer" + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", + "location": "path", + "required": true, + "type": "string", + "description": "Required. The resource name of the Location to list Features. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features", + "description": "Lists Features in a given FeatureGroup.", + "path": "v1beta1/{+parent}/features", + "parameterOrder": [ + "parent" + ], + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.featureGroups.features.list" + }, + "patch": { + "parameters": { + "updateMask": { + "format": "google-fieldmask", + "type": "string", + "location": "query", + "description": "Field mask is used to specify the fields to be overwritten in the Features resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `description` * `labels` * `disable_monitoring` (Not supported for FeatureRegistryService Feature) * `point_of_contact` (Not supported for FeaturestoreService FeatureStore)" + }, + "name": { + "required": true, + "type": "string", + "description": "Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+$" + } + }, + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}", + "httpMethod": "PATCH", + "description": "Updates the parameters of a single Feature.", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.featureGroups.features.patch", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Feature" + } + } + } + } + }, + "methods": { + "list": { + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "path": "v1beta1/{+parent}/featureGroups", + "id": "aiplatform.projects.locations.featureGroups.list", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListFeatureGroupsResponse" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups", + "parameters": { + "orderBy": { + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported Fields: * `create_time` * `update_time`", + "type": "string", + "location": "query" + }, + "pageSize": { + "description": "The maximum number of FeatureGroups to return. The service may return fewer than this value. If unspecified, at most 100 FeatureGroups will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100.", + "format": "int32", + "location": "query", + "type": "integer" + }, + "parent": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "description": "Required. The resource name of the Location to list FeatureGroups. Format: `projects/{project}/locations/{location}`", + "type": "string" + }, + "filter": { + "type": "string", + "description": "Lists the FeatureGroups that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality and key presence. Examples: * `create_time \u003e \"2020-01-01\" OR update_time \u003e \"2020-01-01\"` FeatureGroups created or updated after 2020-01-01. * `labels.env = \"prod\"` FeatureGroups with label \"env\" set to \"prod\".", + "location": "query" + }, + "pageToken": { + "location": "query", + "description": "A page token, received from a previous FeatureGroupAdminService.ListFeatureGroups call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureGroupAdminService.ListFeatureGroups must match the call that provided the page token.", + "type": "string" + } + }, + "description": "Lists FeatureGroups in a given project and location." + }, + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "DELETE", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}", + "parameters": { + "force": { + "description": "If set to true, any Features under this FeatureGroup will also be deleted. (Otherwise, the request will only work if the FeatureGroup has no Features.)", + "location": "query", + "type": "boolean" + }, + "name": { + "type": "string", + "description": "Required. The name of the FeatureGroup to be deleted. Format: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$" + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.featureGroups.delete", + "description": "Deletes a single FeatureGroup.", + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "create": { + "parameters": { + "featureGroupId": { + "location": "query", + "type": "string", + "description": "Required. The ID to use for this FeatureGroup, which will become the final component of the FeatureGroup's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location." + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true, + "type": "string", + "location": "path", + "description": "Required. The resource name of the Location to create FeatureGroups. Format: `projects/{project}/locations/{location}`" + } + }, + "path": "v1beta1/{+parent}/featureGroups", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureGroup" + }, + "description": "Creates a new FeatureGroup in a given project and location.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "httpMethod": "POST", + "id": "aiplatform.projects.locations.featureGroups.create" + }, + "get": { + "parameters": { + "name": { + "description": "Required. The name of the FeatureGroup resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", + "required": true, + "location": "path", + "type": "string" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}", + "description": "Gets details of a single FeatureGroup.", + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureGroup" + }, + "httpMethod": "GET", + "id": "aiplatform.projects.locations.featureGroups.get" + }, + "patch": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "httpMethod": "PATCH", + "description": "Updates the parameters of a single FeatureGroup.", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureGroup" + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "updateMask": { + "format": "google-fieldmask", + "location": "query", + "description": "Field mask is used to specify the fields to be overwritten in the FeatureGroup resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `description` * `big_query` * `big_query.entity_id_columns`", + "type": "string" + }, + "name": { + "required": true, + "description": "Identifier. Name of the FeatureGroup. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.featureGroups.patch" + } + } + }, + "solvers": { + "resources": { + "operations": { + "methods": { + "get": { + "id": "aiplatform.projects.locations.solvers.operations.get", + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "required": true, + "type": "string", + "location": "path", + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/solvers/[^/]+/operations/[^/]+$" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/solvers/{solversId}/operations/{operationsId}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "GET" + }, + "delete": { + "id": "aiplatform.projects.locations.solvers.operations.delete", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/solvers/{solversId}/operations/{operationsId}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1beta1/{+name}", + "httpMethod": "DELETE", + "parameters": { + "name": { + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/solvers/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be deleted." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "parameters": { + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + }, + "name": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/solvers/[^/]+$", + "description": "The name of the operation's parent resource.", + "required": true + }, + "pageSize": { + "format": "int32", + "description": "The standard list page size.", + "location": "query", + "type": "integer" + }, + "filter": { + "type": "string", + "description": "The standard list filter.", + "location": "query" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "id": "aiplatform.projects.locations.solvers.operations.list", + "path": "v1beta1/{+name}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/solvers/{solversId}/operations", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET" + } + } + } + } + }, + "customJobs": { + "methods": { + "get": { + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+$", + "required": true, + "type": "string", + "description": "Required. The name of the CustomJob resource. Format: `projects/{project}/locations/{location}/customJobs/{custom_job}`" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}", + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1CustomJob" + }, + "description": "Gets a CustomJob.", + "httpMethod": "GET", + "id": "aiplatform.projects.locations.customJobs.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "cancel": { + "httpMethod": "POST", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.customJobs.cancel", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+$", + "required": true, + "description": "Required. The name of the CustomJob to cancel. Format: `projects/{project}/locations/{location}/customJobs/{custom_job}`", + "type": "string" + } + }, + "path": "v1beta1/{+name}:cancel", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}:cancel", + "description": "Cancels a CustomJob. Starts asynchronous cancellation on the CustomJob. The server makes a best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetCustomJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On successful cancellation, the CustomJob is not deleted; instead it becomes a job with a CustomJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and CustomJob.state is set to `CANCELLED`.", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1CancelCustomJobRequest" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "delete": { + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.customJobs.delete", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+$", + "required": true, + "description": "Required. The name of the CustomJob resource to be deleted. Format: `projects/{project}/locations/{location}/customJobs/{custom_job}`", + "type": "string" + } + }, + "description": "Deletes a CustomJob.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "create": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1CustomJob" + }, + "path": "v1beta1/{+parent}/customJobs", + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "type": "string", + "required": true, + "description": "Required. The resource name of the Location to create the CustomJob in. Format: `projects/{project}/locations/{location}`" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs", + "id": "aiplatform.projects.locations.customJobs.create", + "parameterOrder": [ + "parent" + ], + "description": "Creates a CustomJob. A created CustomJob right away will be attempted to be run.", + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1CustomJob" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListCustomJobsResponse" + }, + "parameterOrder": [ + "parent" + ], + "path": "v1beta1/{+parent}/customJobs", + "parameters": { + "filter": { + "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`", + "type": "string", + "location": "query" + }, + "parent": { + "type": "string", + "required": true, + "description": "Required. The resource name of the Location to list the CustomJobs from. Format: `projects/{project}/locations/{location}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$" + }, + "readMask": { + "location": "query", + "type": "string", + "format": "google-fieldmask", + "description": "Mask specifying which fields to read." + }, + "pageSize": { + "description": "The standard list page size.", + "type": "integer", + "format": "int32", + "location": "query" + }, + "pageToken": { + "location": "query", + "description": "The standard list page token. Typically obtained via ListCustomJobsResponse.next_page_token of the previous JobService.ListCustomJobs call.", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.customJobs.list", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs", + "description": "Lists CustomJobs in a Location.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + } + }, + "resources": { + "operations": { + "methods": { + "delete": { + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+/operations/[^/]+$", + "type": "string", + "location": "path", + "description": "The name of the operation resource to be deleted.", + "required": true + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations/{operationsId}", + "httpMethod": "DELETE", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "id": "aiplatform.projects.locations.customJobs.operations.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + } + }, + "wait": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations/{operationsId}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "timeout": { + "type": "string", + "location": "query", + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + }, + "name": { + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string", + "required": true + } + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "id": "aiplatform.projects.locations.customJobs.operations.wait", + "path": "v1beta1/{+name}:wait" + }, + "list": { + "path": "v1beta1/{+name}/operations", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.customJobs.operations.list", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations", + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "name": { + "description": "The name of the operation's parent resource.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+$", + "location": "path", + "type": "string" + }, + "pageSize": { + "format": "int32", + "location": "query", + "description": "The standard list page size.", + "type": "integer" + }, + "pageToken": { + "location": "query", + "description": "The standard list page token.", + "type": "string" + }, + "filter": { + "description": "The standard list filter.", + "location": "query", + "type": "string" + } + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." + }, + "cancel": { + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "httpMethod": "POST", + "id": "aiplatform.projects.locations.customJobs.operations.cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations/{operationsId}:cancel", + "parameters": { + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+/operations/[^/]+$", + "type": "string", + "description": "The name of the operation resource to be cancelled." + } + }, + "path": "v1beta1/{+name}:cancel" + }, + "get": { + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+/operations/[^/]+$", + "required": true, + "description": "The name of the operation resource.", + "location": "path" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations/{operationsId}", + "httpMethod": "GET", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "id": "aiplatform.projects.locations.customJobs.operations.get", + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}" + } + } + } + } + }, + "tuningJobs": { + "methods": { + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists TuningJobs in a Location.", + "path": "v1beta1/{+parent}/tuningJobs", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tuningJobs", + "id": "aiplatform.projects.locations.tuningJobs.list", + "httpMethod": "GET", + "parameters": { + "pageSize": { + "format": "int32", + "type": "integer", + "description": "Optional. The standard list page size.", + "location": "query" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "Optional. The standard list page token. Typically obtained via ListTuningJob.next_page_token of the previous GenAiTuningService.ListTuningJob][] call." + }, + "parent": { + "location": "path", + "required": true, + "description": "Required. The resource name of the Location to list the TuningJobs from. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string" + }, + "filter": { + "type": "string", + "location": "query", + "description": "Optional. The standard list filter." + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListTuningJobsResponse" + }, + "parameterOrder": [ + "parent" + ] + }, + "get": { + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tuningJobs/{tuningJobsId}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/tuningJobs/[^/]+$", + "location": "path", + "required": true, + "type": "string", + "description": "Required. The name of the TuningJob resource. Format: `projects/{project}/locations/{location}/tuningJobs/{tuning_job}`" + } + }, + "description": "Gets a TuningJob.", + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1TuningJob" + }, + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.tuningJobs.get" + }, + "create": { + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1TuningJob" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1TuningJob" + }, + "id": "aiplatform.projects.locations.tuningJobs.create", + "description": "Creates a TuningJob. A created TuningJob right away will be attempted to be run.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tuningJobs", + "path": "v1beta1/{+parent}/tuningJobs", + "parameterOrder": [ + "parent" + ], + "parameters": { + "parent": { + "required": true, + "type": "string", + "description": "Required. The resource name of the Location to create the TuningJob in. Format: `projects/{project}/locations/{location}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + } + }, + "cancel": { + "path": "v1beta1/{+name}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tuningJobs/{tuningJobsId}:cancel", + "parameterOrder": [ + "name" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1CancelTuningJobRequest" + }, + "description": "Cancels a TuningJob. Starts asynchronous cancellation on the TuningJob. The server makes a best effort to cancel the job, but success is not guaranteed. Clients can use GenAiTuningService.GetTuningJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On successful cancellation, the TuningJob is not deleted; instead it becomes a job with a TuningJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and TuningJob.state is set to `CANCELLED`.", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/tuningJobs/[^/]+$", + "location": "path", + "type": "string", + "required": true, + "description": "Required. The name of the TuningJob to cancel. Format: `projects/{project}/locations/{location}/tuningJobs/{tuning_job}`" + } + }, + "id": "aiplatform.projects.locations.tuningJobs.cancel" + } + } + }, + "indexEndpoints": { + "methods": { + "readIndexDatapoints": { + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:readIndexDatapoints", + "parameters": { + "indexEndpoint": { + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", + "location": "path", + "required": true, + "type": "string", + "description": "Required. The name of the index endpoint. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`" + } + }, + "path": "v1beta1/{+indexEndpoint}:readIndexDatapoints", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ReadIndexDatapointsRequest" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "indexEndpoint" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ReadIndexDatapointsResponse" + }, + "description": "Reads the datapoints/vectors of the given IDs. A maximum of 1000 datapoints can be retrieved in a batch.", + "id": "aiplatform.projects.locations.indexEndpoints.readIndexDatapoints" + }, + "mutateDeployedIndex": { + "description": "Update an existing DeployedIndex under an IndexEndpoint.", + "id": "aiplatform.projects.locations.indexEndpoints.mutateDeployedIndex", + "path": "v1beta1/{+indexEndpoint}:mutateDeployedIndex", + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1DeployedIndex" + }, + "parameters": { + "indexEndpoint": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", + "required": true, + "location": "path", + "description": "Required. The name of the IndexEndpoint resource into which to deploy an Index. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`" + } + }, + "parameterOrder": [ + "indexEndpoint" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:mutateDeployedIndex", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "create": { + "id": "aiplatform.projects.locations.indexEndpoints.create", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1IndexEndpoint" + }, + "parameterOrder": [ + "parent" + ], + "path": "v1beta1/{+parent}/indexEndpoints", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "parent": { + "location": "path", + "type": "string", + "description": "Required. The resource name of the Location to create the IndexEndpoint in. Format: `projects/{project}/locations/{location}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Creates an IndexEndpoint.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints", + "httpMethod": "POST" + }, + "delete": { + "parameters": { + "name": { + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", + "required": true, + "description": "Required. The name of the IndexEndpoint resource to be deleted. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`" + } + }, + "httpMethod": "DELETE", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.indexEndpoints.delete", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "description": "Deletes an IndexEndpoint.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}" + }, + "findNeighbors": { + "parameters": { + "indexEndpoint": { + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", + "description": "Required. The name of the index endpoint. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", + "location": "path" + } + }, + "parameterOrder": [ + "indexEndpoint" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "path": "v1beta1/{+indexEndpoint}:findNeighbors", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1FindNeighborsRequest" + }, + "description": "Finds the nearest neighbors of each vector within the request.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:findNeighbors", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1FindNeighborsResponse" + }, + "id": "aiplatform.projects.locations.indexEndpoints.findNeighbors" + }, + "list": { + "id": "aiplatform.projects.locations.indexEndpoints.list", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location from which to list the IndexEndpoints. Format: `projects/{project}/locations/{location}`", + "required": true, + "type": "string", + "location": "path" + }, + "pageSize": { + "location": "query", + "description": "Optional. The standard list page size.", + "format": "int32", + "type": "integer" + }, + "readMask": { + "location": "query", + "description": "Optional. Mask specifying which fields to read.", + "type": "string", + "format": "google-fieldmask" + }, + "filter": { + "location": "query", + "type": "string", + "description": "Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `index_endpoint` supports = and !=. `index_endpoint` represents the IndexEndpoint ID, ie. the last segment of the IndexEndpoint's resourcename. * `display_name` supports =, != and regex() (uses [re2](https://github.com/google/re2/wiki/Syntax) syntax) * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* or labels:key - key existence A key including a space must be quoted. `labels.\"a key\"`. Some examples: * `index_endpoint=\"1\"` * `display_name=\"myDisplayName\"` * `regex(display_name, \"^A\") -\u003e The display name starts with an A. * `labels.myKey=\"myValue\"`" + }, + "pageToken": { + "type": "string", + "description": "Optional. The standard list page token. Typically obtained via ListIndexEndpointsResponse.next_page_token of the previous IndexEndpointService.ListIndexEndpoints call.", + "location": "query" + } + }, + "parameterOrder": [ + "parent" + ], + "path": "v1beta1/{+parent}/indexEndpoints", + "httpMethod": "GET", + "description": "Lists IndexEndpoints in a Location.", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListIndexEndpointsResponse" + } + }, + "deployIndex": { + "parameterOrder": [ + "indexEndpoint" + ], + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:deployIndex", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1DeployIndexRequest" + }, + "path": "v1beta1/{+indexEndpoint}:deployIndex", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "indexEndpoint": { + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", + "description": "Required. The name of the IndexEndpoint resource into which to deploy an Index. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", + "required": true + } + }, + "id": "aiplatform.projects.locations.indexEndpoints.deployIndex", + "description": "Deploys an Index into this IndexEndpoint, creating a DeployedIndex within it. Only non-empty Indexes can be deployed.", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "patch": { + "httpMethod": "PATCH", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1IndexEndpoint" + }, + "id": "aiplatform.projects.locations.indexEndpoints.patch", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", + "location": "path", + "required": true, + "description": "Output only. The resource name of the IndexEndpoint.", + "type": "string" + }, + "updateMask": { + "description": "Required. The update mask applies to the resource. See google.protobuf.FieldMask.", + "location": "query", + "format": "google-fieldmask", + "type": "string" + } + }, + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1IndexEndpoint" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}", + "description": "Updates an IndexEndpoint." + }, + "undeployIndex": { + "path": "v1beta1/{+indexEndpoint}:undeployIndex", + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1UndeployIndexRequest" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:undeployIndex", + "parameterOrder": [ + "indexEndpoint" + ], + "description": "Undeploys an Index from an IndexEndpoint, removing a DeployedIndex from it, and freeing all resources it's using.", + "id": "aiplatform.projects.locations.indexEndpoints.undeployIndex", + "parameters": { + "indexEndpoint": { + "location": "path", + "type": "string", + "description": "Required. The name of the IndexEndpoint resource from which to undeploy an Index. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$" + } + } + }, + "get": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1IndexEndpoint" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}", + "id": "aiplatform.projects.locations.indexEndpoints.get", + "parameterOrder": [ + "name" + ], + "description": "Gets an IndexEndpoint.", + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", + "location": "path", + "description": "Required. The name of the IndexEndpoint resource. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "path": "v1beta1/{+name}" + } + }, + "resources": { + "operations": { + "methods": { + "wait": { + "httpMethod": "POST", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+/operations/[^/]+$", + "type": "string", + "required": true, + "location": "path", + "description": "The name of the operation resource to wait on." + }, + "timeout": { + "location": "query", + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration" + } + }, + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations/{operationsId}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.indexEndpoints.operations.wait", + "path": "v1beta1/{+name}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ] + }, + "list": { + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.indexEndpoints.operations.list", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "path": "v1beta1/{+name}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "pageSize": { + "location": "query", + "type": "integer", + "description": "The standard list page size.", + "format": "int32" + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token." + }, + "name": { + "description": "The name of the operation's parent resource.", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", + "required": true + }, + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter." + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations" + }, + "get": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations/{operationsId}", + "parameters": { + "name": { + "description": "The name of the operation resource.", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+/operations/[^/]+$", + "location": "path" + } + }, + "httpMethod": "GET", + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.indexEndpoints.operations.get" + }, + "delete": { + "id": "aiplatform.projects.locations.indexEndpoints.operations.delete", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations/{operationsId}", + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "httpMethod": "DELETE", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+/operations/[^/]+$", + "required": true, + "description": "The name of the operation resource to be deleted.", + "type": "string" + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "cancel": { + "path": "v1beta1/{+name}:cancel", + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "id": "aiplatform.projects.locations.indexEndpoints.operations.cancel", + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "type": "string", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+/operations/[^/]+$" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations/{operationsId}:cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + } + } + } + } + } + }, + "specialistPools": { + "methods": { + "delete": { + "httpMethod": "DELETE", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}", + "description": "Deletes a SpecialistPool as well as all Specialists in the pool.", + "id": "aiplatform.projects.locations.specialistPools.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+$", + "description": "Required. The resource name of the SpecialistPool to delete. Format: `projects/{project}/locations/{location}/specialistPools/{specialist_pool}`" + }, + "force": { + "description": "If set to true, any specialist managers in this SpecialistPool will also be deleted. (Otherwise, the request will only work if the SpecialistPool has no specialist managers.)", + "type": "boolean", + "location": "query" + } + }, + "parameterOrder": [ + "name" + ] + }, + "get": { + "id": "aiplatform.projects.locations.specialistPools.get", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1SpecialistPool" + }, + "httpMethod": "GET", + "description": "Gets a SpecialistPool.", + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "type": "string", + "location": "path", + "required": true, + "description": "Required. The name of the SpecialistPool resource. The form is `projects/{project}/locations/{location}/specialistPools/{specialist_pool}`.", + "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+$" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}" + }, + "create": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1SpecialistPool" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "parent": { + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The parent Project name for the new SpecialistPool. The form is `projects/{project}/locations/{location}`.", + "location": "path" + } + }, + "path": "v1beta1/{+parent}/specialistPools", + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.specialistPools.create", + "description": "Creates a SpecialistPool." + }, + "patch": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1SpecialistPool" + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "parameters": { + "updateMask": { + "type": "string", + "format": "google-fieldmask", + "description": "Required. The update mask applies to the resource.", + "location": "query" + }, + "name": { + "description": "Required. The resource name of the SpecialistPool.", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+$", + "type": "string" + } + }, + "path": "v1beta1/{+name}", + "description": "Updates a SpecialistPool.", + "id": "aiplatform.projects.locations.specialistPools.patch", + "httpMethod": "PATCH" + }, + "list": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListSpecialistPoolsResponse" + }, + "parameters": { + "readMask": { + "type": "string", + "format": "google-fieldmask", + "description": "Mask specifying which fields to read. FieldMask represents a set of", + "location": "query" + }, + "pageToken": { + "description": "The standard list page token. Typically obtained by ListSpecialistPoolsResponse.next_page_token of the previous SpecialistPoolService.ListSpecialistPools call. Return first page if empty.", + "location": "query", + "type": "string" + }, + "pageSize": { + "description": "The standard list page size.", + "type": "integer", + "location": "query", + "format": "int32" + }, + "parent": { + "location": "path", + "description": "Required. The name of the SpecialistPool's parent resource. Format: `projects/{project}/locations/{location}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true + } + }, + "httpMethod": "GET", + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+parent}/specialistPools", + "id": "aiplatform.projects.locations.specialistPools.list", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools", + "description": "Lists SpecialistPools in a Location." + } + }, + "resources": { + "operations": { + "methods": { + "get": { + "id": "aiplatform.projects.locations.specialistPools.operations.get", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations/{operationsId}", + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+/operations/[^/]+$", + "type": "string", + "required": true, + "location": "path" + } + } + }, + "cancel": { + "path": "v1beta1/{+name}:cancel", + "id": "aiplatform.projects.locations.specialistPools.operations.cancel", + "parameters": { + "name": { + "type": "string", + "required": true, + "description": "The name of the operation resource to be cancelled.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+/operations/[^/]+$" + } + }, + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations/{operationsId}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "httpMethod": "POST" + }, + "delete": { + "id": "aiplatform.projects.locations.specialistPools.operations.delete", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource to be deleted.", + "required": true, + "type": "string" + } + }, + "httpMethod": "DELETE", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." + }, + "wait": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "description": "The name of the operation resource to wait on.", + "type": "string" + }, + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "format": "google-duration", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.specialistPools.operations.wait", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations/{operationsId}:wait", + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "path": "v1beta1/{+name}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "path": "v1beta1/{+name}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations", + "parameters": { + "pageSize": { + "location": "query", + "format": "int32", + "description": "The standard list page size.", + "type": "integer" + }, + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+$", + "description": "The name of the operation's parent resource.", + "required": true, + "location": "path" + }, + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token." + } + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "id": "aiplatform.projects.locations.specialistPools.operations.list" + } + } + } + } + }, + "ragCorpora": { + "methods": { + "list": { + "path": "v1beta1/{+parent}/ragCorpora", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists RagCorpora in a Location.", + "parameterOrder": [ + "parent" + ], + "parameters": { + "pageToken": { + "location": "query", + "type": "string", + "description": "Optional. The standard list page token. Typically obtained via ListRagCorporaResponse.next_page_token of the previous VertexRagDataService.ListRagCorpora call." + }, + "pageSize": { + "location": "query", + "format": "int32", + "type": "integer", + "description": "Optional. The standard list page size." + }, + "parent": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location from which to list the RagCorpora. Format: `projects/{project}/locations/{location}`", + "location": "path", + "type": "string" + } + }, + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora", + "id": "aiplatform.projects.locations.ragCorpora.list", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListRagCorporaResponse" + } + }, + "get": { + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.ragCorpora.get", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1RagCorpus" + }, + "parameters": { + "name": { + "required": true, + "location": "path", + "description": "Required. The name of the RagCorpus resource. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", + "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", + "type": "string" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}", + "path": "v1beta1/{+name}", + "description": "Gets a RagCorpus.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "create": { + "parameters": { + "parent": { + "type": "string", + "description": "Required. The resource name of the Location to create the RagCorpus in. Format: `projects/{project}/locations/{location}`", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Creates a RagCorpus.", + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1RagCorpus" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora", + "path": "v1beta1/{+parent}/ragCorpora", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.ragCorpora.create" + }, + "delete": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "description": "Deletes a RagCorpus.", + "id": "aiplatform.projects.locations.ragCorpora.delete", + "httpMethod": "DELETE", + "parameters": { + "force": { + "description": "Optional. If set to true, any RagFiles in this RagCorpus will also be deleted. Otherwise, the request will only work if the RagCorpus has no RagFiles.", + "location": "query", + "type": "boolean" + }, + "name": { + "description": "Required. The name of the RagCorpus resource to be deleted. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", + "type": "string", + "location": "path" + } + }, + "path": "v1beta1/{+name}" + } + }, + "resources": { + "operations": { + "methods": { + "get": { + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/operations/{operationsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "required": true, + "description": "The name of the operation resource.", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/operations/[^/]+$" + } + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "id": "aiplatform.projects.locations.ragCorpora.operations.get", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "cancel": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "type": "string", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1beta1/{+name}:cancel", + "httpMethod": "POST", + "id": "aiplatform.projects.locations.ragCorpora.operations.cancel", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/operations/{operationsId}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`." + }, + "wait": { + "id": "aiplatform.projects.locations.ragCorpora.operations.wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+name}:wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "parameters": { + "timeout": { + "location": "query", + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string" + }, + "name": { + "type": "string", + "required": true, + "location": "path", + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/operations/[^/]+$" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/operations/{operationsId}:wait", + "httpMethod": "POST" + }, + "list": { + "parameterOrder": [ + "name" + ], + "parameters": { + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + }, + "pageSize": { + "type": "integer", + "location": "query", + "format": "int32", + "description": "The standard list page size." + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token." + }, + "name": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", + "description": "The name of the operation's parent resource.", + "required": true + } + }, + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "id": "aiplatform.projects.locations.ragCorpora.operations.list", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/operations", + "path": "v1beta1/{+name}/operations", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." + }, + "delete": { + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource to be deleted.", + "required": true, + "type": "string" + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.ragCorpora.operations.delete", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/operations/{operationsId}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "httpMethod": "DELETE" + } + } + }, + "ragFiles": { + "methods": { + "delete": { + "description": "Deletes a RagFile.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}", + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "type": "string", + "required": true, + "description": "Required. The name of the RagFile resource to be deleted. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}/ragFiles/{rag_file}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+$" + } + }, + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.ragCorpora.ragFiles.delete", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "list": { + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", + "type": "string", + "location": "path", + "required": true, + "description": "Required. The resource name of the RagCorpus from which to list the RagFiles. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "Optional. The standard list page token. Typically obtained via ListRagFilesResponse.next_page_token of the previous VertexRagDataService.ListRagFiles call." + }, + "pageSize": { + "format": "int32", + "location": "query", + "type": "integer", + "description": "Optional. The standard list page size." + } + }, + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.ragCorpora.ragFiles.list", + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists RagFiles in a RagCorpus.", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListRagFilesResponse" + }, + "path": "v1beta1/{+parent}/ragFiles" + }, + "import": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles:import", + "parameters": { + "parent": { + "location": "path", + "required": true, + "description": "Required. The name of the RagCorpus resource into which to import files. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$" + } + }, + "path": "v1beta1/{+parent}/ragFiles:import", + "parameterOrder": [ + "parent" + ], + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ImportRagFilesRequest" + }, + "id": "aiplatform.projects.locations.ragCorpora.ragFiles.import", + "description": "Import files from Google Cloud Storage or Google Drive into a RagCorpus." + }, + "get": { + "id": "aiplatform.projects.locations.ragCorpora.ragFiles.get", + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1RagFile" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+$", + "required": true, + "location": "path", + "description": "Required. The name of the RagFile resource. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}/ragFiles/{rag_file}`" + } + }, + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "description": "Gets a RagFile." + } + }, + "resources": { + "operations": { + "methods": { + "delete": { + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "httpMethod": "DELETE", + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.ragCorpora.ragFiles.operations.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "location": "path", + "description": "The name of the operation resource to be deleted.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", + "type": "string" + } + } + }, + "get": { + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameters": { + "name": { + "type": "string", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource." + } + }, + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.ragCorpora.ragFiles.operations.get", + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}" + }, + "list": { + "httpMethod": "GET", + "path": "v1beta1/{+name}/operations", + "id": "aiplatform.projects.locations.ragCorpora.ragFiles.operations.list", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "parameters": { + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + }, + "name": { + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+$", + "location": "path", + "required": true, + "type": "string" + }, + "filter": { + "type": "string", + "description": "The standard list filter.", + "location": "query" + }, + "pageSize": { + "location": "query", + "description": "The standard list page size.", + "format": "int32", + "type": "integer" + } + }, + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations" + }, + "cancel": { + "id": "aiplatform.projects.locations.ragCorpora.ragFiles.operations.cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}:cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "parameters": { + "name": { + "required": true, + "location": "path", + "type": "string", + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$" + } + } + }, + "wait": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}:wait", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.ragCorpora.ragFiles.operations.wait", + "httpMethod": "POST", + "path": "v1beta1/{+name}:wait", + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string", + "format": "google-duration", + "location": "query" + }, + "name": { + "description": "The name of the operation resource to wait on.", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", + "type": "string" + } + } + } + } + } + } + } + } + }, + "deploymentResourcePools": { + "resources": { + "operations": { + "methods": { + "wait": { + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.deploymentResourcePools.operations.wait", + "parameters": { + "name": { + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+/operations/[^/]+$", + "location": "path", + "required": true, + "type": "string" + }, + "timeout": { + "format": "google-duration", + "type": "string", + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + } + }, + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}:wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." + }, + "get": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "httpMethod": "GET", + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "type": "string", + "required": true, + "location": "path", + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+/operations/[^/]+$" + } + }, + "id": "aiplatform.projects.locations.deploymentResourcePools.operations.get" + }, + "delete": { + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "type": "string", + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+/operations/[^/]+$", + "required": true, + "location": "path" + } + }, + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.deploymentResourcePools.operations.delete", + "httpMethod": "DELETE" + }, + "cancel": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "parameters": { + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+/operations/[^/]+$", + "type": "string", + "description": "The name of the operation resource to be cancelled." + } + }, + "path": "v1beta1/{+name}:cancel", + "id": "aiplatform.projects.locations.deploymentResourcePools.operations.cancel", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}:cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + } + }, + "list": { + "id": "aiplatform.projects.locations.deploymentResourcePools.operations.list", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "path": "v1beta1/{+name}/operations", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter." + }, + "pageSize": { + "format": "int32", + "type": "integer", + "location": "query", + "description": "The standard list page size." + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + }, + "name": { + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$", + "location": "path", + "description": "The name of the operation's parent resource." + } + } + } + } + } + }, + "methods": { + "patch": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}", + "parameters": { + "updateMask": { + "description": "Required. The list of fields to update.", + "type": "string", + "location": "query", + "format": "google-fieldmask" + }, + "name": { + "location": "path", + "type": "string", + "description": "Immutable. The resource name of the DeploymentResourcePool. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", + "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$", + "required": true + } + }, + "id": "aiplatform.projects.locations.deploymentResourcePools.patch", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Update a DeploymentResourcePool.", + "httpMethod": "PATCH", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1DeploymentResourcePool" + }, + "path": "v1beta1/{+name}" + }, + "create": { + "httpMethod": "POST", + "path": "v1beta1/{+parent}/deploymentResourcePools", + "parameters": { + "parent": { + "location": "path", + "required": true, + "type": "string", + "description": "Required. The parent location resource where this DeploymentResourcePool will be created. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "description": "Create a DeploymentResourcePool.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1CreateDeploymentResourcePoolRequest" + }, + "id": "aiplatform.projects.locations.deploymentResourcePools.create" + }, + "list": { + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListDeploymentResourcePoolsResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.deploymentResourcePools.list", + "path": "v1beta1/{+parent}/deploymentResourcePools", + "description": "List DeploymentResourcePools in a location.", + "parameters": { + "pageSize": { + "type": "integer", + "location": "query", + "format": "int32", + "description": "The maximum number of DeploymentResourcePools to return. The service may return fewer than this value." + }, + "parent": { + "description": "Required. The parent Location which owns this collection of DeploymentResourcePools. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string", + "location": "path", + "required": true + }, + "pageToken": { + "location": "query", + "description": "A page token, received from a previous `ListDeploymentResourcePools` call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to `ListDeploymentResourcePools` must match the call that provided the page token.", + "type": "string" + } + }, + "parameterOrder": [ + "parent" + ] + }, + "delete": { + "parameters": { + "name": { + "type": "string", + "description": "Required. The name of the DeploymentResourcePool to delete. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$" + } + }, + "id": "aiplatform.projects.locations.deploymentResourcePools.delete", + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "httpMethod": "DELETE", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}", + "description": "Delete a DeploymentResourcePool." + }, + "queryDeployedModels": { + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}:queryDeployedModels", + "parameterOrder": [ + "deploymentResourcePool" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1QueryDeployedModelsResponse" + }, + "id": "aiplatform.projects.locations.deploymentResourcePools.queryDeployedModels", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "deploymentResourcePool": { + "type": "string", + "description": "Required. The name of the target DeploymentResourcePool to query. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", + "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$", + "required": true, + "location": "path" + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "A page token, received from a previous `QueryDeployedModels` call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to `QueryDeployedModels` must match the call that provided the page token." + }, + "pageSize": { + "description": "The maximum number of DeployedModels to return. The service may return fewer than this value.", + "type": "integer", + "format": "int32", + "location": "query" + } + }, + "description": "List DeployedModels that have been deployed on this DeploymentResourcePool.", + "path": "v1beta1/{+deploymentResourcePool}:queryDeployedModels" + }, + "get": { + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "description": "Get a DeploymentResourcePool.", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$", + "type": "string", + "description": "Required. The name of the DeploymentResourcePool to retrieve. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", + "required": true + } + }, + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.deploymentResourcePools.get", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1DeploymentResourcePool" + } + } + } + }, + "cachedContents": { + "methods": { + "delete": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/cachedContents/[^/]+$", + "location": "path", + "description": "Required. The resource name referring to the cached content" + } + }, + "parameterOrder": [ + "name" + ], + "description": "Deletes cached content", + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.cachedContents.delete", + "httpMethod": "DELETE", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/cachedContents/{cachedContentsId}" + }, + "list": { + "parameters": { + "pageToken": { + "location": "query", + "description": "Optional. A page token, received from a previous `ListCachedContents` call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to `ListCachedContents` must match the call that provided the page token.", + "type": "string" + }, + "pageSize": { + "type": "integer", + "format": "int32", + "location": "query", + "description": "Optional. The maximum number of cached contents to return. The service may return fewer than this value. If unspecified, some default (under maximum) number of items will be returned. The maximum value is 1000; values above 1000 will be coerced to 1000." + }, + "parent": { + "type": "string", + "location": "path", + "description": "Required. The parent, which owns this collection of cached contents.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "path": "v1beta1/{+parent}/cachedContents", + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListCachedContentsResponse" + }, + "parameterOrder": [ + "parent" + ], + "description": "Lists cached contents in a project", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/cachedContents", + "id": "aiplatform.projects.locations.cachedContents.list" + }, + "get": { + "parameters": { + "name": { + "type": "string", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/cachedContents/[^/]+$", + "description": "Required. The resource name referring to the cached content" + } + }, + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1CachedContent" + }, + "id": "aiplatform.projects.locations.cachedContents.get", + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/cachedContents/{cachedContentsId}", + "description": "Gets cached content configurations" + }, + "create": { + "httpMethod": "POST", + "parameters": { + "parent": { + "description": "Required. The parent resource where the cached content will be created", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string" + } + }, + "description": "Creates cached content, this call will initialize the cached content in the data storage, and users need to pay for the cache data storage.", + "id": "aiplatform.projects.locations.cachedContents.create", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1CachedContent" + }, + "path": "v1beta1/{+parent}/cachedContents", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1CachedContent" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/cachedContents" + }, + "patch": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/cachedContents/{cachedContentsId}", + "httpMethod": "PATCH", + "path": "v1beta1/{+name}", + "description": "Updates cached content configurations", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1CachedContent" + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.cachedContents.patch", + "parameters": { + "name": { + "type": "string", + "location": "path", + "description": "Immutable. Identifier. The server-generated resource name of the cached content Format: projects/{project}/locations/{location}/cachedContents/{cached_content}", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/cachedContents/[^/]+$" + }, + "updateMask": { + "type": "string", + "format": "google-fieldmask", + "description": "Required. The list of fields to update.", + "location": "query" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1CachedContent" + } + } + } + }, + "trainingPipelines": { + "resources": { + "operations": { + "methods": { + "cancel": { + "id": "aiplatform.projects.locations.trainingPipelines.operations.cancel", + "path": "v1beta1/{+name}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "required": true, + "type": "string", + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+/operations/[^/]+$" + } + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}:cancel" + }, + "get": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+/operations/[^/]+$", + "type": "string", + "location": "path", + "description": "The name of the operation resource.", + "required": true + } + }, + "id": "aiplatform.projects.locations.trainingPipelines.operations.get", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "path": "v1beta1/{+name}" + }, + "delete": { + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.trainingPipelines.operations.delete", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be deleted.", + "location": "path" + } + }, + "path": "v1beta1/{+name}" + }, + "wait": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+/operations/[^/]+$", + "type": "string", + "required": true, + "location": "path", + "description": "The name of the operation resource to wait on." + }, + "timeout": { + "location": "query", + "type": "string", + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.trainingPipelines.operations.wait", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}:wait", + "httpMethod": "POST", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+name}:wait" + }, + "list": { + "path": "v1beta1/{+name}/operations", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "id": "aiplatform.projects.locations.trainingPipelines.operations.list", + "parameters": { + "pageSize": { + "location": "query", + "description": "The standard list page size.", + "type": "integer", + "format": "int32" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + }, + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+$", + "type": "string", + "description": "The name of the operation's parent resource.", + "location": "path" + }, + "filter": { + "description": "The standard list filter.", + "location": "query", + "type": "string" + } + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations", + "httpMethod": "GET" + } + } + } + }, + "methods": { + "list": { + "parameters": { + "filter": { + "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `training_task_definition` `=`, `!=` comparisons, and `:` wildcard. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"PIPELINE_STATE_SUCCEEDED\" AND display_name:\"my_pipeline_*\"` * `state!=\"PIPELINE_STATE_FAILED\" OR display_name=\"my_pipeline\"` * `NOT display_name=\"my_pipeline\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `training_task_definition:\"*automl_text_classification*\"`", + "location": "query", + "type": "string" + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token. Typically obtained via ListTrainingPipelinesResponse.next_page_token of the previous PipelineService.ListTrainingPipelines call." + }, + "parent": { + "description": "Required. The resource name of the Location to list the TrainingPipelines from. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string", + "location": "path", + "required": true + }, + "readMask": { + "format": "google-fieldmask", + "description": "Mask specifying which fields to read.", + "type": "string", + "location": "query" + }, + "pageSize": { + "format": "int32", + "type": "integer", + "description": "The standard list page size.", + "location": "query" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.trainingPipelines.list", + "httpMethod": "GET", + "description": "Lists TrainingPipelines in a Location.", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListTrainingPipelinesResponse" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines", + "parameterOrder": [ + "parent" + ], + "path": "v1beta1/{+parent}/trainingPipelines" + }, + "delete": { + "httpMethod": "DELETE", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Deletes a TrainingPipeline.", + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.trainingPipelines.delete", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "location": "path", + "required": true, + "type": "string", + "description": "Required. The name of the TrainingPipeline resource to be deleted. Format: `projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}`", + "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+$" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}" + }, + "get": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}", + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1TrainingPipeline" + }, + "id": "aiplatform.projects.locations.trainingPipelines.get", + "description": "Gets a TrainingPipeline.", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+$", + "required": true, + "description": "Required. The name of the TrainingPipeline resource. Format: `projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}`", + "type": "string", + "location": "path" + } + }, + "httpMethod": "GET" + }, + "cancel": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1CancelTrainingPipelineRequest" + }, + "description": "Cancels a TrainingPipeline. Starts asynchronous cancellation on the TrainingPipeline. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use PipelineService.GetTrainingPipeline or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the TrainingPipeline is not deleted; instead it becomes a pipeline with a TrainingPipeline.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and TrainingPipeline.state is set to `CANCELLED`.", + "parameters": { + "name": { + "type": "string", + "required": true, + "description": "Required. The name of the TrainingPipeline to cancel. Format: `projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+$" + } + }, + "path": "v1beta1/{+name}:cancel", + "httpMethod": "POST", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.trainingPipelines.cancel", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ] + }, + "create": { + "description": "Creates a TrainingPipeline. A created TrainingPipeline right away will be attempted to be run.", + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines", + "id": "aiplatform.projects.locations.trainingPipelines.create", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+parent}/trainingPipelines", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1TrainingPipeline" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1TrainingPipeline" + }, + "parameters": { + "parent": { + "description": "Required. The resource name of the Location to create the TrainingPipeline in. Format: `projects/{project}/locations/{location}`", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string" + } + }, + "parameterOrder": [ + "parent" + ] + } + } + }, + "tensorboards": { + "methods": { + "delete": { + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.tensorboards.delete", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "description": "Required. The name of the Tensorboard to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", + "type": "string" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}", + "description": "Deletes a Tensorboard.", + "path": "v1beta1/{+name}" + }, + "get": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Tensorboard" + }, + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", + "required": true, + "description": "Required. The name of the Tensorboard resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", + "type": "string" + } + }, + "description": "Gets a Tensorboard.", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}", + "httpMethod": "GET", + "id": "aiplatform.projects.locations.tensorboards.get" + }, + "batchRead": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.tensorboards.batchRead", + "parameterOrder": [ + "tensorboard" + ], + "parameters": { + "timeSeries": { + "type": "string", + "location": "query", + "repeated": true, + "description": "Required. The resource names of the TensorboardTimeSeries to read data from. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`" + }, + "tensorboard": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", + "required": true, + "description": "Required. The resource name of the Tensorboard containing TensorboardTimeSeries to read data from. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`. The TensorboardTimeSeries referenced by time_series must be sub resources of this Tensorboard.", + "location": "path", + "type": "string" + } + }, + "httpMethod": "GET", + "path": "v1beta1/{+tensorboard}:batchRead", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}:batchRead", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1BatchReadTensorboardTimeSeriesDataResponse" + }, + "description": "Reads multiple TensorboardTimeSeries' data. The data point number limit is 1000 for scalars, 100 for tensors and blob references. If the number of data points stored is less than the limit, all data is returned. Otherwise, the number limit of data points is randomly selected from this time series and returned." + }, + "readSize": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}:readSize", + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ReadTensorboardSizeResponse" + }, + "id": "aiplatform.projects.locations.tensorboards.readSize", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+tensorboard}:readSize", + "description": "Returns the storage size for a given TensorBoard instance.", + "parameterOrder": [ + "tensorboard" + ], + "parameters": { + "tensorboard": { + "type": "string", + "description": "Required. The name of the Tensorboard resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", + "location": "path", + "required": true + } + } + }, + "readUsage": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "tensorboard": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", + "required": true, + "description": "Required. The name of the Tensorboard resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", + "location": "path" + } + }, + "parameterOrder": [ + "tensorboard" + ], + "id": "aiplatform.projects.locations.tensorboards.readUsage", + "httpMethod": "GET", + "path": "v1beta1/{+tensorboard}:readUsage", + "description": "Returns a list of monthly active users for a given TensorBoard instance.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}:readUsage", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponse" + } + }, + "list": { + "description": "Lists Tensorboards in a Location.", + "parameters": { + "orderBy": { + "location": "query", + "description": "Field to use to sort the list.", + "type": "string" + }, + "pageSize": { + "type": "integer", + "description": "The maximum number of Tensorboards to return. The service may return fewer than this value. If unspecified, at most 100 Tensorboards are returned. The maximum value is 100; values above 100 are coerced to 100.", + "location": "query", + "format": "int32" + }, + "pageToken": { + "description": "A page token, received from a previous TensorboardService.ListTensorboards call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboards must match the call that provided the page token.", + "location": "query", + "type": "string" + }, + "filter": { + "type": "string", + "location": "query", + "description": "Lists the Tensorboards that match the filter expression." + }, + "readMask": { + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask", + "type": "string", + "location": "query" + }, + "parent": { + "location": "path", + "description": "Required. The resource name of the Location to list Tensorboards. Format: `projects/{project}/locations/{location}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListTensorboardsResponse" + }, + "id": "aiplatform.projects.locations.tensorboards.list", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards", + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "path": "v1beta1/{+parent}/tensorboards" + }, + "create": { + "description": "Creates a Tensorboard.", + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards", + "parameters": { + "parent": { + "location": "path", + "type": "string", + "required": true, + "description": "Required. The resource name of the Location to create the Tensorboard in. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "httpMethod": "POST", + "id": "aiplatform.projects.locations.tensorboards.create", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Tensorboard" + }, + "path": "v1beta1/{+parent}/tensorboards" + }, + "patch": { + "id": "aiplatform.projects.locations.tensorboards.patch", + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "httpMethod": "PATCH", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Tensorboard" + }, + "description": "Updates a Tensorboard.", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", + "location": "path", + "required": true, + "type": "string", + "description": "Output only. Name of the Tensorboard. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`" + }, + "updateMask": { + "description": "Required. Field mask is used to specify the fields to be overwritten in the Tensorboard resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified.", + "location": "query", + "format": "google-fieldmask", + "type": "string" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}" + } + }, + "resources": { + "experiments": { + "methods": { + "write": { + "parameters": { + "tensorboardExperiment": { + "required": true, + "location": "path", + "type": "string", + "description": "Required. The resource name of the TensorboardExperiment to write data to. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1WriteTensorboardExperimentDataRequest" + }, + "parameterOrder": [ + "tensorboardExperiment" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}:write", + "path": "v1beta1/{+tensorboardExperiment}:write", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1WriteTensorboardExperimentDataResponse" + }, + "description": "Write time series data points of multiple TensorboardTimeSeries in multiple TensorboardRun's. If any data fail to be ingested, an error is returned.", + "id": "aiplatform.projects.locations.tensorboards.experiments.write", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "batchCreate": { + "path": "v1beta1/{+parent}:batchCreate", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1BatchCreateTensorboardTimeSeriesResponse" + }, + "description": "Batch create TensorboardTimeSeries that belong to a TensorboardExperiment.", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1BatchCreateTensorboardTimeSeriesRequest" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}:batchCreate", + "id": "aiplatform.projects.locations.tensorboards.experiments.batchCreate", + "parameterOrder": [ + "parent" + ], + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", + "type": "string", + "description": "Required. The resource name of the TensorboardExperiment to create the TensorboardTimeSeries in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}` The TensorboardRuns referenced by the parent fields in the CreateTensorboardTimeSeriesRequest messages must be sub resources of this TensorboardExperiment.", + "required": true, + "location": "path" + } + }, + "httpMethod": "POST" + }, + "list": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListTensorboardExperimentsResponse" + }, + "id": "aiplatform.projects.locations.tensorboards.experiments.list", + "path": "v1beta1/{+parent}/experiments", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "readMask": { + "format": "google-fieldmask", + "description": "Mask specifying which fields to read.", + "type": "string", + "location": "query" + }, + "orderBy": { + "location": "query", + "description": "Field to use to sort the list.", + "type": "string" + }, + "filter": { + "description": "Lists the TensorboardExperiments that match the filter expression.", + "type": "string", + "location": "query" + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", + "location": "path", + "type": "string", + "required": true, + "description": "Required. The resource name of the Tensorboard to list TensorboardExperiments. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`" + }, + "pageSize": { + "location": "query", + "format": "int32", + "type": "integer", + "description": "The maximum number of TensorboardExperiments to return. The service may return fewer than this value. If unspecified, at most 50 TensorboardExperiments are returned. The maximum value is 1000; values above 1000 are coerced to 1000." + }, + "pageToken": { + "description": "A page token, received from a previous TensorboardService.ListTensorboardExperiments call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboardExperiments must match the call that provided the page token.", + "location": "query", + "type": "string" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments", + "httpMethod": "GET", + "parameterOrder": [ + "parent" + ], + "description": "Lists TensorboardExperiments in a Location." + }, + "create": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments", + "parameters": { + "parent": { + "location": "path", + "required": true, + "description": "Required. The resource name of the Tensorboard to create the TensorboardExperiment in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", + "type": "string" + }, + "tensorboardExperimentId": { + "description": "Required. The ID to use for the Tensorboard experiment, which becomes the final component of the Tensorboard experiment's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`.", + "location": "query", + "type": "string" + } + }, + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardExperiment" + }, + "path": "v1beta1/{+parent}/experiments", + "parameterOrder": [ + "parent" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardExperiment" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Creates a TensorboardExperiment.", + "id": "aiplatform.projects.locations.tensorboards.experiments.create" + }, + "delete": { + "id": "aiplatform.projects.locations.tensorboards.experiments.delete", + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}", + "description": "Deletes a TensorboardExperiment.", + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", + "location": "path", + "required": true, + "description": "Required. The name of the TensorboardExperiment to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`" + } + } + }, + "patch": { + "parameters": { + "name": { + "required": true, + "description": "Output only. Name of the TensorboardExperiment. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$" + }, + "updateMask": { + "location": "query", + "type": "string", + "description": "Required. Field mask is used to specify the fields to be overwritten in the TensorboardExperiment resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified.", + "format": "google-fieldmask" + } + }, + "id": "aiplatform.projects.locations.tensorboards.experiments.patch", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardExperiment" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}", + "parameterOrder": [ + "name" + ], + "description": "Updates a TensorboardExperiment.", + "httpMethod": "PATCH", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardExperiment" + }, + "path": "v1beta1/{+name}" + }, + "get": { + "parameters": { + "name": { + "type": "string", + "location": "path", + "required": true, + "description": "Required. The name of the TensorboardExperiment resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardExperiment" + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.tensorboards.experiments.get", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}", + "description": "Gets a TensorboardExperiment.", + "httpMethod": "GET" + } + }, + "resources": { + "operations": { + "methods": { + "get": { + "id": "aiplatform.projects.locations.tensorboards.experiments.operations.get", + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource.", + "location": "path", + "required": true + } + }, + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "GET" + }, + "wait": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}:wait", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}:wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "description": "The name of the operation resource to wait on." + }, + "timeout": { + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "format": "google-duration" + } + }, + "id": "aiplatform.projects.locations.tensorboards.experiments.operations.wait", + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + }, + "pageSize": { + "type": "integer", + "location": "query", + "format": "int32", + "description": "The standard list page size." + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", + "location": "path", + "description": "The name of the operation's parent resource.", + "type": "string", + "required": true + } + }, + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.tensorboards.experiments.operations.list", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations", + "httpMethod": "GET", + "path": "v1beta1/{+name}/operations", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." + }, + "delete": { + "httpMethod": "DELETE", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}", + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "location": "path", + "required": true, + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.tensorboards.experiments.operations.delete" + }, + "cancel": { + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "id": "aiplatform.projects.locations.tensorboards.experiments.operations.cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}:cancel", + "path": "v1beta1/{+name}:cancel", + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string" + } + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`." + } + } + }, + "runs": { + "resources": { + "timeSeries": { + "methods": { + "delete": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}", + "description": "Deletes a TensorboardTimeSeries.", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", + "type": "string", + "description": "Required. The name of the TensorboardTimeSeries to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`", + "required": true, + "location": "path" + } + }, + "httpMethod": "DELETE", + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.delete", + "parameterOrder": [ + "name" + ] + }, + "read": { + "path": "v1beta1/{+tensorboardTimeSeries}:read", + "httpMethod": "GET", + "parameters": { + "filter": { + "type": "string", + "description": "Reads the TensorboardTimeSeries' data that match the filter expression.", + "location": "query" + }, + "maxDataPoints": { + "location": "query", + "format": "int32", + "description": "The maximum number of TensorboardTimeSeries' data to return. This value should be a positive integer. This value can be set to -1 to return all data.", + "type": "integer" + }, + "tensorboardTimeSeries": { + "location": "path", + "type": "string", + "required": true, + "description": "Required. The resource name of the TensorboardTimeSeries to read data from. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}:read", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ReadTensorboardTimeSeriesDataResponse" + }, + "description": "Reads a TensorboardTimeSeries' data. By default, if the number of data points stored is less than 1000, all data is returned. Otherwise, 1000 data points is randomly selected from this time series and returned. This value can be changed by changing max_data_points, which can't be greater than 10k.", + "parameterOrder": [ + "tensorboardTimeSeries" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.read" + }, + "get": { + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", + "required": true, + "description": "Required. The name of the TensorboardTimeSeries resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "description": "Gets a TensorboardTimeSeries.", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.get", + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardTimeSeries" + } + }, + "patch": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardTimeSeries" + }, + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.patch", + "httpMethod": "PATCH", + "parameters": { + "name": { + "type": "string", + "location": "path", + "description": "Output only. Name of the TensorboardTimeSeries.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$" + }, + "updateMask": { + "description": "Required. Field mask is used to specify the fields to be overwritten in the TensorboardTimeSeries resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified.", + "location": "query", + "format": "google-fieldmask", + "type": "string" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardTimeSeries" + }, + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}", + "description": "Updates a TensorboardTimeSeries." + }, + "exportTensorboardTimeSeries": { + "path": "v1beta1/{+tensorboardTimeSeries}:exportTensorboardTimeSeries", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ExportTensorboardTimeSeriesDataResponse" + }, + "description": "Exports a TensorboardTimeSeries' data. Data is returned in paginated responses.", + "httpMethod": "POST", + "parameterOrder": [ + "tensorboardTimeSeries" + ], + "parameters": { + "tensorboardTimeSeries": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", + "type": "string", + "description": "Required. The resource name of the TensorboardTimeSeries to export data from. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ExportTensorboardTimeSeriesDataRequest" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}:exportTensorboardTimeSeries", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.exportTensorboardTimeSeries" + }, + "readBlobData": { + "description": "Gets bytes of TensorboardBlobs. This is to allow reading blob data stored in consumer project's Cloud Storage bucket without users having to obtain Cloud Storage access permission.", + "parameters": { + "blobIds": { + "description": "IDs of the blobs to read.", + "location": "query", + "repeated": true, + "type": "string" + }, + "timeSeries": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", + "type": "string", + "description": "Required. The resource name of the TensorboardTimeSeries to list Blobs. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`", + "location": "path", + "required": true + } + }, + "path": "v1beta1/{+timeSeries}:readBlobData", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}:readBlobData", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.readBlobData", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "parameterOrder": [ + "timeSeries" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ReadTensorboardBlobDataResponse" + } + }, + "list": { + "parameters": { + "pageSize": { + "format": "int32", + "type": "integer", + "location": "query", + "description": "The maximum number of TensorboardTimeSeries to return. The service may return fewer than this value. If unspecified, at most 50 TensorboardTimeSeries are returned. The maximum value is 1000; values above 1000 are coerced to 1000." + }, + "parent": { + "location": "path", + "required": true, + "description": "Required. The resource name of the TensorboardRun to list TensorboardTimeSeries. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", + "type": "string" + }, + "orderBy": { + "location": "query", + "description": "Field to use to sort the list.", + "type": "string" + }, + "readMask": { + "format": "google-fieldmask", + "location": "query", + "description": "Mask specifying which fields to read.", + "type": "string" + }, + "filter": { + "location": "query", + "description": "Lists the TensorboardTimeSeries that match the filter expression.", + "type": "string" + }, + "pageToken": { + "description": "A page token, received from a previous TensorboardService.ListTensorboardTimeSeries call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboardTimeSeries must match the call that provided the page token.", + "type": "string", + "location": "query" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists TensorboardTimeSeries in a Location.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries", + "parameterOrder": [ + "parent" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListTensorboardTimeSeriesResponse" + }, + "httpMethod": "GET", + "path": "v1beta1/{+parent}/timeSeries", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.list" + }, + "create": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.create", + "path": "v1beta1/{+parent}/timeSeries", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardTimeSeries" + }, + "parameterOrder": [ + "parent" + ], + "description": "Creates a TensorboardTimeSeries.", + "parameters": { + "parent": { + "description": "Required. The resource name of the TensorboardRun to create the TensorboardTimeSeries in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", + "location": "path", + "required": true + }, + "tensorboardTimeSeriesId": { + "description": "Optional. The user specified unique ID to use for the TensorboardTimeSeries, which becomes the final component of the TensorboardTimeSeries's resource name. This value should match \"a-z0-9{0, 127}\"", + "location": "query", + "type": "string" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardTimeSeries" + } + } + }, + "resources": { + "operations": { + "methods": { + "get": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", + "required": true, + "type": "string", + "description": "The name of the operation resource.", + "location": "path" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}", + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.get", + "path": "v1beta1/{+name}" + }, + "list": { + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "parameters": { + "filter": { + "location": "query", + "description": "The standard list filter.", + "type": "string" + }, + "name": { + "required": true, + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", + "type": "string", + "location": "path" + }, + "pageSize": { + "type": "integer", + "location": "query", + "description": "The standard list page size.", + "format": "int32" + }, + "pageToken": { + "description": "The standard list page token.", + "location": "query", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.list", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations", + "path": "v1beta1/{+name}/operations" + }, + "delete": { + "httpMethod": "DELETE", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "location": "path", + "type": "string", + "required": true, + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$" + } + }, + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.delete", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}" + }, + "wait": { + "httpMethod": "POST", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "path": "v1beta1/{+name}:wait", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}:wait", + "parameters": { + "timeout": { + "type": "string", + "format": "google-duration", + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + }, + "name": { + "location": "path", + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", + "required": true, + "type": "string" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ] + }, + "cancel": { + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.cancel", + "httpMethod": "POST", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "path": "v1beta1/{+name}:cancel", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}:cancel" + } + } + } + } + }, + "operations": { + "methods": { + "get": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.get", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "httpMethod": "GET", + "parameters": { + "name": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource.", + "required": true + } + }, + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}", + "path": "v1beta1/{+name}" + }, + "wait": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "parameters": { + "timeout": { + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "type": "string" + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "type": "string", + "location": "path", + "required": true + } + }, + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.wait", + "parameterOrder": [ + "name" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}:wait", + "path": "v1beta1/{+name}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "list": { + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.list", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "path": "v1beta1/{+name}/operations", + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", + "required": true, + "location": "path", + "description": "The name of the operation's parent resource." + }, + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + }, + "pageSize": { + "location": "query", + "format": "int32", + "description": "The standard list page size.", + "type": "integer" + }, + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations" + }, + "cancel": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}:cancel", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", + "type": "string", + "location": "path" + } + }, + "httpMethod": "POST", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "path": "v1beta1/{+name}:cancel", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "delete": { + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.delete", + "httpMethod": "DELETE", + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}", + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", + "type": "string", + "description": "The name of the operation resource to be deleted.", + "location": "path" + } + } + } + } + } + }, + "methods": { + "patch": { + "parameterOrder": [ + "name" + ], + "httpMethod": "PATCH", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.patch", + "parameters": { + "name": { + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", + "description": "Output only. Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", + "location": "path" + }, + "updateMask": { + "description": "Required. Field mask is used to specify the fields to be overwritten in the TensorboardRun resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified.", + "type": "string", + "format": "google-fieldmask", + "location": "query" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardRun" + }, + "path": "v1beta1/{+name}", + "description": "Updates a TensorboardRun.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardRun" + } + }, + "get": { + "parameters": { + "name": { + "description": "Required. The name of the TensorboardRun resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$" + } + }, + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardRun" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets a TensorboardRun.", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.get", + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}", + "httpMethod": "GET" + }, + "list": { + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.list", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists TensorboardRuns in a Location.", + "parameters": { + "parent": { + "location": "path", + "description": "Required. The resource name of the TensorboardExperiment to list TensorboardRuns. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", + "required": true, + "type": "string" + }, + "filter": { + "location": "query", + "type": "string", + "description": "Lists the TensorboardRuns that match the filter expression." + }, + "orderBy": { + "location": "query", + "type": "string", + "description": "Field to use to sort the list." + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "A page token, received from a previous TensorboardService.ListTensorboardRuns call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboardRuns must match the call that provided the page token." + }, + "readMask": { + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask", + "location": "query", + "type": "string" + }, + "pageSize": { + "type": "integer", + "location": "query", + "format": "int32", + "description": "The maximum number of TensorboardRuns to return. The service may return fewer than this value. If unspecified, at most 50 TensorboardRuns are returned. The maximum value is 1000; values above 1000 are coerced to 1000." + } + }, + "path": "v1beta1/{+parent}/runs", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs", + "parameterOrder": [ + "parent" + ], + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListTensorboardRunsResponse" + } + }, + "batchCreate": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1BatchCreateTensorboardRunsResponse" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs:batchCreate", + "parameters": { + "parent": { + "type": "string", + "description": "Required. The resource name of the TensorboardExperiment to create the TensorboardRuns in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}` The parent field in the CreateTensorboardRunRequest messages must match this field.", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$" + } + }, + "httpMethod": "POST", + "description": "Batch create TensorboardRuns.", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1BatchCreateTensorboardRunsRequest" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+parent}/runs:batchCreate", + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.batchCreate" + }, + "delete": { + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", + "description": "Required. The name of the TensorboardRun to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", + "required": true, + "type": "string" + } + }, + "description": "Deletes a TensorboardRun.", + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.delete", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "DELETE", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}" + }, + "write": { + "description": "Write time series data points into multiple TensorboardTimeSeries under a TensorboardRun. If any data fail to be ingested, an error is returned.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1WriteTensorboardRunDataRequest" + }, + "httpMethod": "POST", + "parameters": { + "tensorboardRun": { + "type": "string", + "description": "Required. The resource name of the TensorboardRun to write data to. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", + "required": true + } + }, + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.write", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1WriteTensorboardRunDataResponse" + }, + "parameterOrder": [ + "tensorboardRun" + ], + "path": "v1beta1/{+tensorboardRun}:write", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}:write" + }, + "create": { + "description": "Creates a TensorboardRun.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "parameters": { + "tensorboardRunId": { + "location": "query", + "type": "string", + "description": "Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`." + }, + "parent": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", + "location": "path", + "type": "string", + "description": "Required. The resource name of the TensorboardExperiment to create the TensorboardRun in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardRun" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1TensorboardRun" + }, + "path": "v1beta1/{+parent}/runs", + "httpMethod": "POST", + "id": "aiplatform.projects.locations.tensorboards.experiments.runs.create" + } + } + } + } + }, + "operations": { + "methods": { + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.tensorboards.operations.delete", + "httpMethod": "DELETE", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations/{operationsId}", + "parameters": { + "name": { + "location": "path", + "required": true, + "description": "The name of the operation resource to be deleted.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/operations/[^/]+$" + } + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ] + }, + "wait": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations/{operationsId}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "POST", + "parameterOrder": [ + "name" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "path": "v1beta1/{+name}:wait", + "id": "aiplatform.projects.locations.tensorboards.operations.wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/operations/[^/]+$", + "type": "string", + "description": "The name of the operation resource to wait on.", + "required": true, + "location": "path" + }, + "timeout": { + "format": "google-duration", + "location": "query", + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + } + } + }, + "get": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations/{operationsId}", + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "location": "path", + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/operations/[^/]+$", + "type": "string", + "required": true + } + }, + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.tensorboards.operations.get" + }, + "cancel": { + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.tensorboards.operations.cancel", + "httpMethod": "POST", + "parameters": { + "name": { + "required": true, + "type": "string", + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/operations/[^/]+$", + "location": "path" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations/{operationsId}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1beta1/{+name}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "path": "v1beta1/{+name}/operations", + "parameterOrder": [ + "name" + ], + "parameters": { + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "pageToken": { + "description": "The standard list page token.", + "location": "query", + "type": "string" + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", + "location": "path", + "type": "string", + "description": "The name of the operation's parent resource.", + "required": true + }, + "pageSize": { + "description": "The standard list page size.", + "format": "int32", + "location": "query", + "type": "integer" + } + }, + "id": "aiplatform.projects.locations.tensorboards.operations.list", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + } + } + } + } + } + }, + "agents": { + "resources": { + "operations": { + "methods": { + "list": { + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/agents/[^/]+$", + "description": "The name of the operation's parent resource.", + "location": "path", + "type": "string", + "required": true + }, + "filter": { + "description": "The standard list filter.", + "location": "query", + "type": "string" + }, + "pageSize": { + "description": "The standard list page size.", + "type": "integer", + "format": "int32", + "location": "query" + }, + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + } + }, + "path": "v1beta1/{+name}/operations", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/agents/{agentsId}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "id": "aiplatform.projects.locations.agents.operations.list" + }, + "get": { + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/agents/{agentsId}/operations/{operationsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "GET", + "parameters": { + "name": { + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/agents/[^/]+/operations/[^/]+$", + "type": "string", + "description": "The name of the operation resource." + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.agents.operations.get", + "path": "v1beta1/{+name}" + }, + "cancel": { + "id": "aiplatform.projects.locations.agents.operations.cancel", + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/agents/[^/]+/operations/[^/]+$", + "required": true + } + }, + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/agents/{agentsId}/operations/{operationsId}:cancel", + "path": "v1beta1/{+name}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "httpMethod": "POST" + }, + "delete": { + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1beta1/{+name}", + "httpMethod": "DELETE", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/agents/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "type": "string", + "description": "The name of the operation resource to be deleted." + } + }, + "id": "aiplatform.projects.locations.agents.operations.delete", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/agents/{agentsId}/operations/{operationsId}" + }, + "wait": { + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}:wait", + "httpMethod": "POST", + "id": "aiplatform.projects.locations.agents.operations.wait", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/agents/{agentsId}/operations/{operationsId}:wait", + "parameters": { + "name": { + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/agents/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource to wait on." + }, + "timeout": { + "type": "string", + "format": "google-duration", + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + } + }, + "parameterOrder": [ + "name" + ] + } + } + } + } + }, + "datasets": { + "methods": { + "create": { + "parameterOrder": [ + "parent" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Dataset" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets", + "id": "aiplatform.projects.locations.datasets.create", + "description": "Creates a Dataset.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "parent": { + "type": "string", + "description": "Required. The resource name of the Location to create the Dataset in. Format: `projects/{project}/locations/{location}`", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "path": "v1beta1/{+parent}/datasets" + }, + "get": { + "description": "Gets a Dataset.", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Dataset" + }, + "parameters": { + "readMask": { + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask", + "location": "query", + "type": "string" + }, + "name": { + "description": "Required. The name of the Dataset resource.", + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}", + "id": "aiplatform.projects.locations.datasets.get" + }, + "export": { + "parameters": { + "name": { + "required": true, + "description": "Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+name}:export", + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ExportDataRequest" + }, + "description": "Exports data from a Dataset.", + "id": "aiplatform.projects.locations.datasets.export", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:export", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "patch": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "description": "Updates a Dataset.", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.datasets.patch", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Dataset" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}", + "parameters": { + "updateMask": { + "location": "query", + "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Updatable fields: * `display_name` * `description` * `labels`", + "format": "google-fieldmask", + "type": "string" + }, + "name": { + "required": true, + "description": "Output only. Identifier. The resource name of the Dataset.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", + "location": "path" + } + }, + "httpMethod": "PATCH", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Dataset" + } + }, + "import": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:import", + "description": "Imports data into a Dataset.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", + "description": "Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", + "required": true + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.datasets.import", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}:import", + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ImportDataRequest" + } + }, + "searchDataItems": { + "id": "aiplatform.projects.locations.datasets.searchDataItems", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:searchDataItems", + "parameterOrder": [ + "dataset" + ], + "path": "v1beta1/{+dataset}:searchDataItems", + "parameters": { + "orderByDataItem": { + "type": "string", + "location": "query", + "description": "A comma-separated list of data item fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending." + }, + "dataItemFilter": { + "description": "An expression for filtering the DataItem that will be returned. * `data_item_id` - for = or !=. * `labeled` - for = or !=. * `has_annotation(ANNOTATION_SPEC_ID)` - true only for DataItem that have at least one annotation with annotation_spec_id = `ANNOTATION_SPEC_ID` in the context of SavedQuery or DataLabelingJob. For example: * `data_item=1` * `has_annotation(5)`", + "location": "query", + "type": "string" + }, + "annotationsFilter": { + "deprecated": true, + "description": "An expression for filtering the Annotations that will be returned per DataItem. * `annotation_spec_id` - for = or !=.", + "type": "string", + "location": "query" + }, + "dataLabelingJob": { + "type": "string", + "location": "query", + "description": "The resource name of a DataLabelingJob. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}` If this field is set, all of the search will be done in the context of this DataLabelingJob." + }, + "annotationsLimit": { + "type": "integer", + "location": "query", + "description": "If set, only up to this many of Annotations will be returned per DataItemView. The maximum value is 1000. If not set, the maximum value will be used.", + "format": "int32" + }, + "orderBy": { + "location": "query", + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending.", + "deprecated": true, + "type": "string" + }, + "savedQuery": { + "deprecated": true, + "location": "query", + "description": "The resource name of a SavedQuery(annotation set in UI). Format: `projects/{project}/locations/{location}/datasets/{dataset}/savedQueries/{saved_query}` All of the search will be done in the context of this SavedQuery.", + "type": "string" + }, + "fieldMask": { + "type": "string", + "description": "Mask specifying which fields of DataItemView to read.", + "location": "query", + "format": "google-fieldmask" + }, + "orderByAnnotation.orderBy": { + "type": "string", + "location": "query", + "description": "A comma-separated list of annotation fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Must also specify saved_query." + }, + "pageToken": { + "description": "A token identifying a page of results for the server to return Typically obtained via SearchDataItemsResponse.next_page_token of the previous DatasetService.SearchDataItems call.", + "type": "string", + "location": "query" + }, + "annotationFilters": { + "description": "An expression that specifies what Annotations will be returned per DataItem. Annotations satisfied either of the conditions will be returned. * `annotation_spec_id` - for = or !=. Must specify `saved_query_id=` - saved query id that annotations should belong to.", + "type": "string", + "location": "query", + "repeated": true + }, + "orderByAnnotation.savedQuery": { + "type": "string", + "location": "query", + "description": "Required. Saved query of the Annotation. Only Annotations belong to this saved query will be considered for ordering." + }, + "pageSize": { + "format": "int32", + "location": "query", + "type": "integer", + "description": "Requested page size. Server may return fewer results than requested. Default and maximum page size is 100." + }, + "dataset": { + "type": "string", + "location": "path", + "required": true, + "description": "Required. The resource name of the Dataset from which to search DataItems. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$" + } + }, + "description": "Searches DataItems in a Dataset.", + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1SearchDataItemsResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "delete": { + "httpMethod": "DELETE", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a Dataset.", + "id": "aiplatform.projects.locations.datasets.delete", + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "location": "path", + "description": "Required. The resource name of the Dataset to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", + "required": true + } + }, + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "list": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListDatasetsResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+parent}/datasets", + "description": "Lists Datasets in a Location.", + "id": "aiplatform.projects.locations.datasets.list", + "parameters": { + "readMask": { + "location": "query", + "format": "google-fieldmask", + "description": "Mask specifying which fields to read.", + "type": "string" + }, + "pageSize": { + "description": "The standard list page size.", + "type": "integer", + "format": "int32", + "location": "query" + }, + "parent": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "required": true, + "description": "Required. The name of the Dataset's parent resource. Format: `projects/{project}/locations/{location}`" + }, + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + }, + "orderBy": { + "type": "string", + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time`", + "location": "query" + }, + "filter": { + "type": "string", + "location": "query", + "description": "An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `display_name`: supports = and != * `metadata_schema_uri`: supports = and != * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels.\"a key\"`. Some examples: * `displayName=\"myDisplayName\"` * `labels.myKey=\"myValue\"`" + } + }, + "httpMethod": "GET", + "parameterOrder": [ + "parent" + ] + } + }, + "resources": { + "annotationSpecs": { + "methods": { + "get": { + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1AnnotationSpec" + }, + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+$", + "required": true, + "description": "Required. The name of the AnnotationSpec resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}/annotationSpecs/{annotation_spec}`", + "type": "string" + }, + "readMask": { + "format": "google-fieldmask", + "location": "query", + "description": "Mask specifying which fields to read.", + "type": "string" + } + }, + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.datasets.annotationSpecs.get", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}", + "description": "Gets an AnnotationSpec.", + "parameterOrder": [ + "name" + ] + } + }, + "resources": { + "operations": { + "methods": { + "delete": { + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.delete", + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", + "required": true, + "description": "The name of the operation resource to be deleted.", + "type": "string", + "location": "path" + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "httpMethod": "DELETE", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}" + }, + "list": { + "parameters": { + "name": { + "required": true, + "description": "The name of the operation's parent resource.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+$", + "type": "string" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + }, + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "pageSize": { + "format": "int32", + "description": "The standard list page size.", + "location": "query", + "type": "integer" + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.list", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations", + "path": "v1beta1/{+name}/operations", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "get": { + "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.get", + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameters": { + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource.", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}" + }, + "cancel": { + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}:cancel", + "path": "v1beta1/{+name}:cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", + "location": "path" + } + }, + "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.cancel", + "parameterOrder": [ + "name" + ] + }, + "wait": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.wait", + "parameters": { + "timeout": { + "format": "google-duration", + "location": "query", + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "location": "path", + "type": "string", + "required": true + } + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}:wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "path": "v1beta1/{+name}:wait" + } + } + } + } + }, + "dataItems": { + "resources": { + "annotations": { + "resources": { + "operations": { + "methods": { + "get": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "GET", + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.get", + "parameters": { + "name": { + "description": "The name of the operation resource.", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", + "type": "string" + } + } + }, + "list": { + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "parameters": { + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "pageSize": { + "type": "integer", + "description": "The standard list page size.", + "format": "int32", + "location": "query" + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token." + }, + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+$", + "location": "path", + "type": "string", + "description": "The name of the operation's parent resource." + } + }, + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.list", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations", + "httpMethod": "GET", + "path": "v1beta1/{+name}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "delete": { + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", + "type": "string", + "location": "path", + "description": "The name of the operation resource to be deleted." + } + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}", + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ] + }, + "wait": { + "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.wait", + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on." + }, + "timeout": { + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "location": "query" + } + }, + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}:wait" + }, + "cancel": { + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.cancel", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "required": true, + "type": "string" + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "path": "v1beta1/{+name}:cancel" + } + } + } + }, + "methods": { + "list": { + "id": "aiplatform.projects.locations.datasets.dataItems.annotations.list", + "path": "v1beta1/{+parent}/annotations", + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "description": "Lists Annotations belongs to a dataitem", + "parameters": { + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + }, + "parent": { + "location": "path", + "description": "Required. The resource name of the DataItem to list Annotations from. Format: `projects/{project}/locations/{location}/datasets/{dataset}/dataItems/{data_item}`", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+$" + }, + "pageSize": { + "type": "integer", + "location": "query", + "format": "int32", + "description": "The standard list page size." + }, + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "readMask": { + "format": "google-fieldmask", + "location": "query", + "description": "Mask specifying which fields to read.", + "type": "string" + }, + "orderBy": { + "location": "query", + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending.", + "type": "string" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListAnnotationsResponse" + } + } + } + }, + "operations": { + "methods": { + "wait": { + "path": "v1beta1/{+name}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}:wait", + "httpMethod": "POST", + "id": "aiplatform.projects.locations.datasets.dataItems.operations.wait", + "parameters": { + "name": { + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string", + "required": true + }, + "timeout": { + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "location": "query" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "delete": { + "id": "aiplatform.projects.locations.datasets.dataItems.operations.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "httpMethod": "DELETE", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}", + "parameters": { + "name": { + "type": "string", + "location": "path", + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", + "required": true + } + }, + "parameterOrder": [ + "name" + ] + }, + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.datasets.dataItems.operations.list", + "path": "v1beta1/{+name}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "parameterOrder": [ + "name" + ], + "parameters": { + "pageToken": { + "location": "query", + "description": "The standard list page token.", + "type": "string" + }, + "filter": { + "description": "The standard list filter.", + "location": "query", + "type": "string" + }, + "name": { + "description": "The name of the operation's parent resource.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+$", + "required": true, + "location": "path" + }, + "pageSize": { + "location": "query", + "format": "int32", + "type": "integer", + "description": "The standard list page size." + } + }, + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations" + }, + "get": { + "path": "v1beta1/{+name}", + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string", + "description": "The name of the operation resource." + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.datasets.dataItems.operations.get", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "cancel": { + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "id": "aiplatform.projects.locations.datasets.dataItems.operations.cancel", + "path": "v1beta1/{+name}:cancel", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}:cancel", + "parameters": { + "name": { + "type": "string", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be cancelled." + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + } + } + } + } + }, + "methods": { + "list": { + "path": "v1beta1/{+parent}/dataItems", + "httpMethod": "GET", + "id": "aiplatform.projects.locations.datasets.dataItems.list", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems", + "parameters": { + "readMask": { + "description": "Mask specifying which fields to read.", + "type": "string", + "format": "google-fieldmask", + "location": "query" + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", + "location": "path", + "type": "string", + "description": "Required. The resource name of the Dataset to list DataItems from. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", + "required": true + }, + "pageSize": { + "format": "int32", + "type": "integer", + "description": "The standard list page size.", + "location": "query" + }, + "orderBy": { + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending.", + "location": "query", + "type": "string" + }, + "filter": { + "location": "query", + "description": "The standard list filter.", + "type": "string" + }, + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + } + }, + "description": "Lists DataItems in a Dataset.", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListDataItemsResponse" + }, + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + } + } + }, + "savedQueries": { + "methods": { + "delete": { + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.datasets.savedQueries.delete", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "description": "Required. The resource name of the SavedQuery to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/savedQueries/{saved_query}`", + "required": true, + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+$" + } + }, + "description": "Deletes a SavedQuery.", + "httpMethod": "DELETE" + }, + "list": { + "parameterOrder": [ + "parent" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListSavedQueriesResponse" + }, + "parameters": { + "pageSize": { + "description": "The standard list page size.", + "format": "int32", + "type": "integer", + "location": "query" + }, + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + }, + "readMask": { + "location": "query", + "type": "string", + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask" + }, + "filter": { + "location": "query", + "description": "The standard list filter.", + "type": "string" + }, + "orderBy": { + "type": "string", + "location": "query", + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending." + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", + "location": "path", + "required": true, + "type": "string", + "description": "Required. The resource name of the Dataset to list SavedQueries from. Format: `projects/{project}/locations/{location}/datasets/{dataset}`" + } + }, + "description": "Lists SavedQueries in a Dataset.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "path": "v1beta1/{+parent}/savedQueries", + "id": "aiplatform.projects.locations.datasets.savedQueries.list" + } + }, + "resources": { + "operations": { + "methods": { + "get": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource.", + "required": true, + "location": "path", + "type": "string" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "GET", + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.datasets.savedQueries.operations.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameterOrder": [ + "name" + ] + }, + "delete": { + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.datasets.savedQueries.operations.delete", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "parameters": { + "name": { + "description": "The name of the operation resource to be deleted.", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", + "required": true + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}" + }, + "list": { + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "id": "aiplatform.projects.locations.datasets.savedQueries.operations.list", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations", + "path": "v1beta1/{+name}/operations", + "parameters": { + "name": { + "description": "The name of the operation's parent resource.", + "type": "string", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+$" + }, + "pageSize": { + "type": "integer", + "description": "The standard list page size.", + "location": "query", + "format": "int32" + }, + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + } + }, + "httpMethod": "GET" + }, + "wait": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}:wait", + "parameters": { + "timeout": { + "format": "google-duration", + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string" + }, + "name": { + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.datasets.savedQueries.operations.wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}:wait" + }, + "cancel": { + "id": "aiplatform.projects.locations.datasets.savedQueries.operations.cancel", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}:cancel", + "path": "v1beta1/{+name}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be cancelled.", + "type": "string" + } + }, + "httpMethod": "POST", + "parameterOrder": [ + "name" + ] + } + } + } + } + }, + "datasetVersions": { + "methods": { + "get": { + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/datasetVersions/[^/]+$", + "description": "Required. The resource name of the Dataset version to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", + "location": "path", + "required": true + }, + "readMask": { + "format": "google-fieldmask", + "type": "string", + "location": "query", + "description": "Mask specifying which fields to read." + } + }, + "parameterOrder": [ + "name" + ], + "description": "Gets a Dataset version.", + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1DatasetVersion" + }, + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.datasets.datasetVersions.get" + }, + "list": { + "description": "Lists DatasetVersions in a Dataset.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+parent}/datasetVersions", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListDatasetVersionsResponse" + }, + "httpMethod": "GET", + "parameters": { + "filter": { + "type": "string", + "location": "query", + "description": "Optional. The standard list filter." + }, + "readMask": { + "description": "Optional. Mask specifying which fields to read.", + "location": "query", + "type": "string", + "format": "google-fieldmask" + }, + "pageSize": { + "format": "int32", + "location": "query", + "description": "Optional. The standard list page size.", + "type": "integer" + }, + "orderBy": { + "location": "query", + "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending.", + "type": "string" + }, + "pageToken": { + "description": "Optional. The standard list page token.", + "location": "query", + "type": "string" + }, + "parent": { + "description": "Required. The resource name of the Dataset to list DatasetVersions from. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", + "required": true, + "type": "string", + "location": "path" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions", + "id": "aiplatform.projects.locations.datasets.datasetVersions.list", + "parameterOrder": [ + "parent" + ] + }, + "delete": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Deletes a Dataset version.", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/datasetVersions/[^/]+$", + "description": "Required. The resource name of the Dataset version to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", + "type": "string", + "location": "path", + "required": true + } + }, + "httpMethod": "DELETE", + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.datasets.datasetVersions.delete" + }, + "patch": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1DatasetVersion" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}", + "id": "aiplatform.projects.locations.datasets.datasetVersions.patch", + "httpMethod": "PATCH", + "parameterOrder": [ + "name" + ], + "description": "Updates a DatasetVersion.", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/datasetVersions/[^/]+$", + "description": "Output only. Identifier. The resource name of the DatasetVersion.", + "type": "string", + "required": true + }, + "updateMask": { + "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Updatable fields: * `display_name`", + "type": "string", + "location": "query", + "format": "google-fieldmask" + } + }, + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1DatasetVersion" + } + }, + "create": { + "parameters": { + "parent": { + "required": true, + "description": "Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", + "type": "string" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions", + "path": "v1beta1/{+parent}/datasetVersions", + "id": "aiplatform.projects.locations.datasets.datasetVersions.create", + "parameterOrder": [ + "parent" + ], + "description": "Create a version from a Dataset.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1DatasetVersion" + } + }, + "restore": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}:restore", + "path": "v1beta1/{+name}:restore", + "parameterOrder": [ + "name" + ], + "description": "Restores a dataset version.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "GET", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/datasetVersions/[^/]+$", + "required": true, + "type": "string", + "description": "Required. The name of the DatasetVersion resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`" + } + }, + "id": "aiplatform.projects.locations.datasets.datasetVersions.restore" + } + } + }, + "operations": { + "methods": { + "get": { + "id": "aiplatform.projects.locations.datasets.operations.get", + "parameters": { + "name": { + "description": "The name of the operation resource.", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "httpMethod": "GET" + }, + "cancel": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/operations/[^/]+$", + "location": "path", + "required": true, + "description": "The name of the operation resource to be cancelled.", + "type": "string" + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.datasets.operations.cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations/{operationsId}:cancel", + "path": "v1beta1/{+name}:cancel", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`." + }, + "wait": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+name}:wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations/{operationsId}:wait", + "httpMethod": "POST", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "timeout": { + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "type": "string" + }, + "name": { + "description": "The name of the operation resource to wait on.", + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/operations/[^/]+$", + "required": true + } + }, + "id": "aiplatform.projects.locations.datasets.operations.wait" + }, + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.datasets.operations.list", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", + "required": true, + "location": "path", + "description": "The name of the operation's parent resource.", + "type": "string" + }, + "pageToken": { + "location": "query", + "description": "The standard list page token.", + "type": "string" + }, + "filter": { + "type": "string", + "description": "The standard list filter.", + "location": "query" + }, + "pageSize": { + "format": "int32", + "location": "query", + "description": "The standard list page size.", + "type": "integer" + } + }, + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations", + "path": "v1beta1/{+name}/operations", + "parameterOrder": [ + "name" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." + }, + "delete": { + "id": "aiplatform.projects.locations.datasets.operations.delete", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/operations/[^/]+$", + "location": "path", + "required": true, + "description": "The name of the operation resource to be deleted." + } + }, + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleProtobufEmpty" + } + } + } + } + } + }, + "modelDeploymentMonitoringJobs": { + "resources": { + "operations": { + "methods": { + "list": { + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "filter": { + "location": "query", + "description": "The standard list filter.", + "type": "string" + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token." + }, + "pageSize": { + "location": "query", + "type": "integer", + "format": "int32", + "description": "The standard list page size." + }, + "name": { + "description": "The name of the operation's parent resource.", + "required": true, + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$" + } + }, + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.list", + "path": "v1beta1/{+name}/operations", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." + }, + "cancel": { + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "httpMethod": "POST", + "parameters": { + "name": { + "location": "path", + "required": true, + "type": "string", + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$" + } + }, + "path": "v1beta1/{+name}:cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}:cancel" + }, + "get": { + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.get", + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "required": true, + "location": "path", + "type": "string", + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$" + } + }, + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "wait": { + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "type": "string", + "format": "google-duration" + }, + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "type": "string", + "required": true + } + }, + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}:wait", + "path": "v1beta1/{+name}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "httpMethod": "POST" + }, + "delete": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.delete", + "parameters": { + "name": { + "description": "The name of the operation resource to be deleted.", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "httpMethod": "DELETE", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ] + } + } + } + }, + "methods": { + "patch": { + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.patch", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob" + }, + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "httpMethod": "PATCH", + "description": "Updates a ModelDeploymentMonitoringJob.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "updateMask": { + "type": "string", + "location": "query", + "format": "google-fieldmask", + "description": "Required. The update mask is used to specify the fields to be overwritten in the ModelDeploymentMonitoringJob resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. For the objective config, the user can either provide the update mask for model_deployment_monitoring_objective_configs or any combination of its nested fields, such as: model_deployment_monitoring_objective_configs.objective_config.training_dataset. Updatable fields: * `display_name` * `model_deployment_monitoring_schedule_config` * `model_monitoring_alert_config` * `logging_sampling_strategy` * `labels` * `log_ttl` * `enable_monitoring_pipeline_logs` . and * `model_deployment_monitoring_objective_configs` . or * `model_deployment_monitoring_objective_configs.objective_config.training_dataset` * `model_deployment_monitoring_objective_configs.objective_config.training_prediction_skew_detection_config` * `model_deployment_monitoring_objective_configs.objective_config.prediction_drift_detection_config`" + }, + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", + "type": "string", + "location": "path", + "description": "Output only. Resource name of a ModelDeploymentMonitoringJob." + } + } + }, + "delete": { + "httpMethod": "DELETE", + "description": "Deletes a ModelDeploymentMonitoringJob.", + "parameters": { + "name": { + "type": "string", + "location": "path", + "required": true, + "description": "Required. The resource name of the model monitoring job to delete. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`", + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.delete" + }, + "create": { + "parameterOrder": [ + "parent" + ], + "httpMethod": "POST", + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.create", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob" + }, + "path": "v1beta1/{+parent}/modelDeploymentMonitoringJobs", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs", + "description": "Creates a ModelDeploymentMonitoringJob. It will run periodically on a configured interval.", + "parameters": { + "parent": { + "location": "path", + "description": "Required. The parent of the ModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}`", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "resume": { + "description": "Resumes a paused ModelDeploymentMonitoringJob. It will start to run from next scheduled time. A deleted ModelDeploymentMonitoringJob can't be resumed.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.resume", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", + "location": "path", + "description": "Required. The resource name of the ModelDeploymentMonitoringJob to resume. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`", + "required": true, + "type": "string" + } + }, + "path": "v1beta1/{+name}:resume", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ResumeModelDeploymentMonitoringJobRequest" + }, + "httpMethod": "POST", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}:resume" + }, + "list": { + "httpMethod": "GET", + "parameters": { + "readMask": { + "location": "query", + "format": "google-fieldmask", + "type": "string", + "description": "Mask specifying which fields to read" + }, + "pageSize": { + "description": "The standard list page size.", + "format": "int32", + "type": "integer", + "location": "query" + }, + "parent": { + "type": "string", + "required": true, + "description": "Required. The parent of the ModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + }, + "filter": { + "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`", + "location": "query", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+parent}/modelDeploymentMonitoringJobs", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs", + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.list", + "parameterOrder": [ + "parent" + ], + "description": "Lists ModelDeploymentMonitoringJobs in a Location.", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListModelDeploymentMonitoringJobsResponse" + } + }, + "searchModelDeploymentMonitoringStatsAnomalies": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}:searchModelDeploymentMonitoringStatsAnomalies", + "path": "v1beta1/{+modelDeploymentMonitoringJob}:searchModelDeploymentMonitoringStatsAnomalies", + "parameterOrder": [ + "modelDeploymentMonitoringJob" + ], + "parameters": { + "modelDeploymentMonitoringJob": { + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", + "location": "path", + "type": "string", + "description": "Required. ModelDeploymentMonitoring Job resource name. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesResponse" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesRequest" + }, + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.searchModelDeploymentMonitoringStatsAnomalies", + "description": "Searches Model Monitoring Statistics generated within a given time window." + }, + "get": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}", + "parameters": { + "name": { + "type": "string", + "location": "path", + "description": "Required. The resource name of the ModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`", + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.get", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "description": "Gets a ModelDeploymentMonitoringJob.", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob" + } + }, + "pause": { + "description": "Pauses a ModelDeploymentMonitoringJob. If the job is running, the server makes a best effort to cancel the job. Will mark ModelDeploymentMonitoringJob.state to 'PAUSED'.", + "parameters": { + "name": { + "type": "string", + "required": true, + "description": "Required. The resource name of the ModelDeploymentMonitoringJob to pause. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`", + "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", + "location": "path" + } + }, + "httpMethod": "POST", + "path": "v1beta1/{+name}:pause", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1PauseModelDeploymentMonitoringJobRequest" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}:pause", + "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.pause" + } + } + }, + "featureOnlineStores": { + "methods": { + "getIamPolicy": { + "httpMethod": "POST", + "id": "aiplatform.projects.locations.featureOnlineStores.getIamPolicy", + "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", + "parameterOrder": [ + "resource" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}:getIamPolicy", + "response": { + "$ref": "GoogleIamV1Policy" + }, + "parameters": { + "options.requestedPolicyVersion": { + "location": "query", + "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", + "format": "int32", + "type": "integer" + }, + "resource": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", + "required": true, + "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+resource}:getIamPolicy" + }, + "testIamPermissions": { + "parameterOrder": [ + "resource" + ], + "response": { + "$ref": "GoogleIamV1TestIamPermissionsResponse" + }, + "path": "v1beta1/{+resource}:testIamPermissions", + "httpMethod": "POST", + "id": "aiplatform.projects.locations.featureOnlineStores.testIamPermissions", + "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}:testIamPermissions", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "resource": { + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", + "location": "path", + "required": true, + "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "type": "string" + }, + "permissions": { + "location": "query", + "repeated": true, + "type": "string", + "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions)." + } + } + }, + "create": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStore" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.featureOnlineStores.create", + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores", + "description": "Creates a new FeatureOnlineStore in a given project and location.", + "parameters": { + "parent": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location to create FeatureOnlineStores. Format: `projects/{project}/locations/{location}`", + "type": "string", + "required": true + }, + "featureOnlineStoreId": { + "description": "Required. The ID to use for this FeatureOnlineStore, which will become the final component of the FeatureOnlineStore's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location.", + "type": "string", + "location": "query" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+parent}/featureOnlineStores" + }, + "delete": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}", + "description": "Deletes a single FeatureOnlineStore. The FeatureOnlineStore must not contain any FeatureViews.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", + "type": "string", + "description": "Required. The name of the FeatureOnlineStore to be deleted. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}`", + "location": "path" + }, + "force": { + "description": "If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted. (Otherwise, the request will only work if the FeatureOnlineStore has no FeatureViews.)", + "type": "boolean", + "location": "query" + } + }, + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.featureOnlineStores.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "get": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStore" + }, + "id": "aiplatform.projects.locations.featureOnlineStores.get", + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets details of a single FeatureOnlineStore.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}", + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", + "type": "string", + "location": "path", + "description": "Required. The name of the FeatureOnlineStore resource." + } + }, + "httpMethod": "GET" + }, + "patch": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}", + "httpMethod": "PATCH", + "id": "aiplatform.projects.locations.featureOnlineStores.patch", + "description": "Updates the parameters of a single FeatureOnlineStore.", + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "parameters": { + "updateMask": { + "location": "query", + "format": "google-fieldmask", + "type": "string", + "description": "Field mask is used to specify the fields to be overwritten in the FeatureOnlineStore resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `description` * `bigtable` * `bigtable.auto_scaling` * `bigtable.enable_multi_region_replica`" + }, + "name": { + "type": "string", + "description": "Identifier. Name of the FeatureOnlineStore. Format: `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", + "required": true + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStore" + } + }, + "setIamPolicy": { + "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", + "parameters": { + "resource": { + "location": "path", + "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", + "type": "string", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.featureOnlineStores.setIamPolicy", + "response": { + "$ref": "GoogleIamV1Policy" + }, + "path": "v1beta1/{+resource}:setIamPolicy", + "request": { + "$ref": "GoogleIamV1SetIamPolicyRequest" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}:setIamPolicy", + "httpMethod": "POST", + "parameterOrder": [ + "resource" + ] + }, + "list": { + "description": "Lists FeatureOnlineStores in a given project and location.", + "id": "aiplatform.projects.locations.featureOnlineStores.list", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+parent}/featureOnlineStores", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListFeatureOnlineStoresResponse" + }, + "parameters": { + "parent": { + "description": "Required. The resource name of the Location to list FeatureOnlineStores. Format: `projects/{project}/locations/{location}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "required": true + }, + "pageSize": { + "location": "query", + "type": "integer", + "description": "The maximum number of FeatureOnlineStores to return. The service may return fewer than this value. If unspecified, at most 100 FeatureOnlineStores will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100.", + "format": "int32" + }, + "pageToken": { + "description": "A page token, received from a previous FeatureOnlineStoreAdminService.ListFeatureOnlineStores call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureOnlineStoreAdminService.ListFeatureOnlineStores must match the call that provided the page token.", + "location": "query", + "type": "string" + }, + "filter": { + "description": "Lists the FeatureOnlineStores that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality and key presence. Examples: * `create_time \u003e \"2020-01-01\" OR update_time \u003e \"2020-01-01\"` FeatureOnlineStores created or updated after 2020-01-01. * `labels.env = \"prod\"` FeatureOnlineStores with label \"env\" set to \"prod\".", + "type": "string", + "location": "query" + }, + "orderBy": { + "type": "string", + "location": "query", + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported Fields: * `create_time` * `update_time`" + } + }, + "parameterOrder": [ + "parent" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores", + "httpMethod": "GET" + } + }, + "resources": { + "featureViews": { + "resources": { + "operations": { + "methods": { + "delete": { + "parameters": { + "name": { + "description": "The name of the operation resource to be deleted.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", + "location": "path", + "required": true + } + }, + "httpMethod": "DELETE", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.operations.delete", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ] + }, + "wait": { + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.operations.wait", + "httpMethod": "POST", + "parameters": { + "timeout": { + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "type": "string" + }, + "name": { + "type": "string", + "location": "path", + "required": true, + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$" + } + }, + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}:wait", + "path": "v1beta1/{+name}:wait" + }, + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "required": true, + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", + "description": "The name of the operation's parent resource." + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token." + }, + "pageSize": { + "description": "The standard list page size.", + "type": "integer", + "format": "int32", + "location": "query" + }, + "filter": { + "location": "query", + "description": "The standard list filter.", + "type": "string" + } + }, + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.operations.list", + "httpMethod": "GET", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations" + }, + "get": { + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}", + "httpMethod": "GET", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.operations.get", + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + } + } + }, + "featureViewSyncs": { + "methods": { + "list": { + "path": "v1beta1/{+parent}/featureViewSyncs", + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.featureViewSyncs.list", + "httpMethod": "GET", + "description": "Lists FeatureViewSyncs in a given FeatureView.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/featureViewSyncs", + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "parent": { + "required": true, + "description": "Required. The resource name of the FeatureView to list FeatureViewSyncs. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$" + }, + "pageToken": { + "location": "query", + "description": "A page token, received from a previous FeatureOnlineStoreAdminService.ListFeatureViewSyncs call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureOnlineStoreAdminService.ListFeatureViewSyncs must match the call that provided the page token.", + "type": "string" + }, + "orderBy": { + "location": "query", + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `create_time`", + "type": "string" + }, + "pageSize": { + "type": "integer", + "description": "The maximum number of FeatureViewSyncs to return. The service may return fewer than this value. If unspecified, at most 1000 FeatureViewSyncs will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000.", + "format": "int32", + "location": "query" + }, + "filter": { + "type": "string", + "description": "Lists the FeatureViewSyncs that match the filter expression. The following filters are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003e=`, and `\u003c=` comparisons. Values must be in RFC 3339 format. Examples: * `create_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\"` --\u003e FeatureViewSyncs created after 2020-01-31T15:30:00.000000Z.", + "location": "query" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListFeatureViewSyncsResponse" + } + }, + "get": { + "path": "v1beta1/{+name}", + "description": "Gets details of a single FeatureViewSync.", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureViewSync" + }, + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/featureViewSyncs/{featureViewSyncsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "location": "path", + "description": "Required. The name of the FeatureViewSync resource. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}/featureViewSyncs/{feature_view_sync}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+/featureViewSyncs/[^/]+$", + "required": true + } + }, + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.featureViewSyncs.get" + } + } + } + }, + "methods": { + "create": { + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "runSyncImmediately": { + "location": "query", + "description": "Immutable. If set to true, one on demand sync will be run immediately, regardless whether the FeatureView.sync_config is configured or not.", + "type": "boolean" + }, + "parent": { + "description": "Required. The resource name of the FeatureOnlineStore to create FeatureViews. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}`", + "required": true, + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$" + }, + "featureViewId": { + "location": "query", + "description": "Required. The ID to use for the FeatureView, which will become the final component of the FeatureView's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within a FeatureOnlineStore.", + "type": "string" + } + }, + "path": "v1beta1/{+parent}/featureViews", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Creates a new FeatureView in a given FeatureOnlineStore.", + "parameterOrder": [ + "parent" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureView" + }, + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.create" + }, + "setIamPolicy": { + "request": { + "$ref": "GoogleIamV1SetIamPolicyRequest" + }, + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.setIamPolicy", + "parameterOrder": [ + "resource" + ], + "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", + "path": "v1beta1/{+resource}:setIamPolicy", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "resource": { + "location": "path", + "type": "string", + "required": true, + "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$" + } + }, + "response": { + "$ref": "GoogleIamV1Policy" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:setIamPolicy", + "httpMethod": "POST" + }, + "sync": { + "path": "v1beta1/{+featureView}:sync", + "parameters": { + "featureView": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", + "description": "Required. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`", + "required": true, + "type": "string" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1SyncFeatureViewResponse" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:sync", + "parameterOrder": [ + "featureView" + ], + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.sync", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1SyncFeatureViewRequest" + }, + "description": "Triggers on-demand sync for the FeatureView." + }, + "get": { + "description": "Gets details of a single FeatureView.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}", + "path": "v1beta1/{+name}", + "httpMethod": "GET", + "parameters": { + "name": { + "required": true, + "type": "string", + "description": "Required. The name of the FeatureView resource. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", + "location": "path" + } + }, + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.get", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureView" + }, + "parameterOrder": [ + "name" + ] + }, + "patch": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1FeatureView" + }, + "description": "Updates the parameters of a single FeatureView.", + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.patch", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", + "required": true, + "description": "Identifier. Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`", + "location": "path" + }, + "updateMask": { + "description": "Field mask is used to specify the fields to be overwritten in the FeatureView resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `service_agent_type` * `big_query_source` * `big_query_source.uri` * `big_query_source.entity_id_columns` * `feature_registry_source` * `feature_registry_source.feature_groups` * `sync_config` * `sync_config.cron`", + "format": "google-fieldmask", + "type": "string", + "location": "query" + } + }, + "httpMethod": "PATCH" + }, + "fetchFeatureValues": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1FetchFeatureValuesRequest" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:fetchFeatureValues", + "httpMethod": "POST", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponse" + }, + "description": "Fetch feature values under a FeatureView.", + "path": "v1beta1/{+featureView}:fetchFeatureValues", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.fetchFeatureValues", + "parameterOrder": [ + "featureView" + ], + "parameters": { + "featureView": { + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", + "description": "Required. FeatureView resource format `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/{featureView}`", + "required": true, + "type": "string", + "location": "path" + } + } + }, + "delete": { + "parameters": { + "name": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", + "description": "Required. The name of the FeatureView to be deleted. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`", + "required": true + } + }, + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.delete", + "httpMethod": "DELETE", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}", + "path": "v1beta1/{+name}", + "description": "Deletes a single FeatureView.", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "list": { + "parameters": { + "parent": { + "description": "Required. The resource name of the FeatureOnlineStore to list FeatureViews. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}`", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", + "type": "string", + "location": "path", + "required": true + }, + "orderBy": { + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `feature_view_id` * `create_time` * `update_time`", + "location": "query", + "type": "string" + }, + "filter": { + "location": "query", + "description": "Lists the FeatureViews that match the filter expression. The following filters are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003e=`, and `\u003c=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003e=`, and `\u003c=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality as well as key presence. Examples: * `create_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\" OR update_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\"` --\u003e FeatureViews created or updated after 2020-01-31T15:30:00.000000Z. * `labels.active = yes AND labels.env = prod` --\u003e FeatureViews having both (active: yes) and (env: prod) labels. * `labels.env: *` --\u003e Any FeatureView which has a label with 'env' as the key.", + "type": "string" + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "A page token, received from a previous FeatureOnlineStoreAdminService.ListFeatureViews call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureOnlineStoreAdminService.ListFeatureViews must match the call that provided the page token." + }, + "pageSize": { + "type": "integer", + "format": "int32", + "location": "query", + "description": "The maximum number of FeatureViews to return. The service may return fewer than this value. If unspecified, at most 1000 FeatureViews will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists FeatureViews in a given FeatureOnlineStore.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews", + "httpMethod": "GET", + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.list", + "parameterOrder": [ + "parent" + ], + "path": "v1beta1/{+parent}/featureViews", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListFeatureViewsResponse" + } + }, + "getIamPolicy": { + "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.getIamPolicy", + "path": "v1beta1/{+resource}:getIamPolicy", + "parameterOrder": [ + "resource" + ], + "response": { + "$ref": "GoogleIamV1Policy" + }, + "parameters": { + "resource": { + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", + "type": "string", + "location": "path", + "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "required": true + }, + "options.requestedPolicyVersion": { + "type": "integer", + "location": "query", + "format": "int32", + "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies)." + } + }, + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:getIamPolicy" + }, + "streamingFetchFeatureValues": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1StreamingFetchFeatureValuesRequest" + }, + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.streamingFetchFeatureValues", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1StreamingFetchFeatureValuesResponse" + }, + "parameterOrder": [ + "featureView" + ], + "description": "Bidirectional streaming RPC to fetch feature values under a FeatureView. Requests may not have a one-to-one mapping to responses and responses may be returned out-of-order to reduce latency.", + "path": "v1beta1/{+featureView}:streamingFetchFeatureValues", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:streamingFetchFeatureValues", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "featureView": { + "type": "string", + "description": "Required. FeatureView resource format `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/{featureView}`", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", + "required": true + } + }, + "httpMethod": "POST" + }, + "searchNearestEntities": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1SearchNearestEntitiesResponse" + }, + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.searchNearestEntities", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Search the nearest entities under a FeatureView. Search only works for indexable feature view; if a feature view isn't indexable, returns Invalid argument response.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:searchNearestEntities", + "path": "v1beta1/{+featureView}:searchNearestEntities", + "parameterOrder": [ + "featureView" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1SearchNearestEntitiesRequest" + }, + "parameters": { + "featureView": { + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", + "type": "string", + "description": "Required. FeatureView resource format `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/{featureView}`" + } + } + }, + "testIamPermissions": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "resource" + ], + "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.testIamPermissions", + "parameters": { + "permissions": { + "type": "string", + "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", + "repeated": true, + "location": "query" + }, + "resource": { + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", + "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "required": true + } + }, + "response": { + "$ref": "GoogleIamV1TestIamPermissionsResponse" + }, + "path": "v1beta1/{+resource}:testIamPermissions", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:testIamPermissions", + "httpMethod": "POST", + "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning." + } + } + }, + "operations": { + "methods": { + "list": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/operations", + "parameters": { + "name": { + "type": "string", + "location": "path", + "required": true, + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$" + }, + "filter": { + "location": "query", + "description": "The standard list filter.", + "type": "string" + }, + "pageSize": { + "type": "integer", + "format": "int32", + "description": "The standard list page size.", + "location": "query" + }, + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + } + }, + "id": "aiplatform.projects.locations.featureOnlineStores.operations.list", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "httpMethod": "GET", + "path": "v1beta1/{+name}/operations" + }, + "delete": { + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.featureOnlineStores.operations.delete", + "parameters": { + "name": { + "required": true, + "location": "path", + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." + }, + "wait": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}:wait", + "path": "v1beta1/{+name}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string", + "description": "The name of the operation resource to wait on." + }, + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "format": "google-duration", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.featureOnlineStores.operations.wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "get": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.featureOnlineStores.operations.get", + "httpMethod": "GET", + "parameters": { + "name": { + "type": "string", + "location": "path", + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/operations/[^/]+$", + "required": true + } + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ] + } + } + } + } + }, + "models": { + "methods": { + "export": { + "description": "Exports a trained, exportable Model to a location specified by the user. A Model is considered to be exportable if it has at least one supported export format.", + "id": "aiplatform.projects.locations.models.export", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "parameters": { + "name": { + "required": true, + "location": "path", + "type": "string", + "description": "Required. The resource name of the Model to export. The resource name may contain version id or version alias to specify the version, if no version is specified, the default version will be exported.", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:export", + "path": "v1beta1/{+name}:export", + "parameterOrder": [ + "name" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ExportModelRequest" + } + }, + "patch": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "required": true, + "description": "The resource name of the Model.", + "location": "path", + "type": "string" + }, + "updateMask": { + "format": "google-fieldmask", + "location": "query", + "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask.", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Model" + }, + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.models.patch", + "httpMethod": "PATCH", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Model" + }, + "description": "Updates a Model." + }, + "setIamPolicy": { + "parameterOrder": [ + "resource" + ], + "httpMethod": "POST", + "id": "aiplatform.projects.locations.models.setIamPolicy", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:setIamPolicy", + "request": { + "$ref": "GoogleIamV1SetIamPolicyRequest" + }, + "response": { + "$ref": "GoogleIamV1Policy" + }, + "parameters": { + "resource": { + "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "type": "string", + "location": "path" + } + }, + "path": "v1beta1/{+resource}:setIamPolicy", + "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "id": "aiplatform.projects.locations.models.list", + "path": "v1beta1/{+parent}/models", + "parameterOrder": [ + "parent" + ], + "parameters": { + "parent": { + "required": true, + "description": "Required. The resource name of the Location to list the Models from. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string", + "location": "path" + }, + "filter": { + "type": "string", + "description": "An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `model` supports = and !=. `model` represents the Model ID, i.e. the last segment of the Model's resource name. * `display_name` supports = and != * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels.\"a key\"`. * `base_model_name` only supports = Some examples: * `model=1234` * `displayName=\"myDisplayName\"` * `labels.myKey=\"myValue\"` * `baseModelName=\"text-bison\"`", + "location": "query" + }, + "readMask": { + "description": "Mask specifying which fields to read.", + "location": "query", + "format": "google-fieldmask", + "type": "string" + }, + "pageSize": { + "location": "query", + "type": "integer", + "format": "int32", + "description": "The standard list page size." + }, + "pageToken": { + "description": "The standard list page token. Typically obtained via ListModelsResponse.next_page_token of the previous ModelService.ListModels call.", + "location": "query", + "type": "string" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListModelsResponse" + }, + "description": "Lists Models in a Location.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models", + "httpMethod": "GET" + }, + "upload": { + "parameterOrder": [ + "parent" + ], + "path": "v1beta1/{+parent}/models:upload", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1UploadModelRequest" + }, + "parameters": { + "parent": { + "type": "string", + "description": "Required. The resource name of the Location into which to upload the Model. Format: `projects/{project}/locations/{location}`", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Uploads a Model artifact into Vertex AI.", + "id": "aiplatform.projects.locations.models.upload", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models:upload", + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "updateExplanationDataset": { + "id": "aiplatform.projects.locations.models.updateExplanationDataset", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:updateExplanationDataset", + "description": "Incrementally update the dataset used for an examples model.", + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "model" + ], + "path": "v1beta1/{+model}:updateExplanationDataset", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1UpdateExplanationDatasetRequest" + }, + "parameters": { + "model": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "description": "Required. The resource name of the Model to update. Format: `projects/{project}/locations/{location}/models/{model}`", + "type": "string", + "required": true + } + } + }, + "testIamPermissions": { + "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", + "parameters": { + "permissions": { + "type": "string", + "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", + "repeated": true, + "location": "query" + }, + "resource": { + "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "location": "path" + } + }, + "parameterOrder": [ + "resource" + ], + "httpMethod": "POST", + "id": "aiplatform.projects.locations.models.testIamPermissions", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleIamV1TestIamPermissionsResponse" + }, + "path": "v1beta1/{+resource}:testIamPermissions", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:testIamPermissions" + }, + "listVersions": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListModelVersionsResponse" + }, + "path": "v1beta1/{+name}:listVersions", + "parameters": { + "readMask": { + "type": "string", + "format": "google-fieldmask", + "location": "query", + "description": "Mask specifying which fields to read." + }, + "orderBy": { + "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `create_time` * `update_time` Example: `update_time asc, create_time desc`.", + "type": "string", + "location": "query" + }, + "filter": { + "type": "string", + "location": "query", + "description": "An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels.\"a key\"`. Some examples: * `labels.myKey=\"myValue\"`" + }, + "pageToken": { + "description": "The standard list page token. Typically obtained via next_page_token of the previous ListModelVersions call.", + "location": "query", + "type": "string" + }, + "pageSize": { + "location": "query", + "description": "The standard list page size.", + "format": "int32", + "type": "integer" + }, + "name": { + "required": true, + "description": "Required. The name of the model to list versions for.", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$" + } + }, + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:listVersions", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "id": "aiplatform.projects.locations.models.listVersions", + "description": "Lists versions of the specified model." + }, + "get": { + "httpMethod": "GET", + "parameters": { + "name": { + "required": true, + "description": "Required. The name of the Model resource. Format: `projects/{project}/locations/{location}/models/{model}` In order to retrieve a specific version of the model, also provide the version ID or version alias. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` If no version ID or alias is specified, the \"default\" version will be returned. The \"default\" version alias is created for the first version of the model, and can be moved to other versions later on. There will be exactly one default version.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "location": "path" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}", + "description": "Gets a Model.", + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.models.get", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Model" + }, + "parameterOrder": [ + "name" + ] + }, + "delete": { + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE", + "parameters": { + "name": { + "location": "path", + "type": "string", + "description": "Required. The name of the Model resource to be deleted. Format: `projects/{project}/locations/{location}/models/{model}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$" + } + }, + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.models.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Deletes a Model. A model cannot be deleted if any Endpoint resource has a DeployedModel based on the model in its deployed_models field.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}" + }, + "getIamPolicy": { + "parameters": { + "resource": { + "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "location": "path", + "required": true, + "type": "string" + }, + "options.requestedPolicyVersion": { + "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", + "location": "query", + "type": "integer", + "format": "int32" + } + }, + "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:getIamPolicy", + "id": "aiplatform.projects.locations.models.getIamPolicy", + "parameterOrder": [ + "resource" + ], + "path": "v1beta1/{+resource}:getIamPolicy", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleIamV1Policy" + } + }, + "copy": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1CopyModelRequest" + }, + "id": "aiplatform.projects.locations.models.copy", + "parameters": { + "parent": { + "description": "Required. The resource name of the Location into which to copy the Model. Format: `projects/{project}/locations/{location}`", + "type": "string", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "path": "v1beta1/{+parent}/models:copy", + "parameterOrder": [ + "parent" + ], + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models:copy", + "description": "Copies an already existing Vertex AI Model into the specified Location. The source Model must exist in the same Project. When copying custom Models, the users themselves are responsible for Model.metadata content to be region-agnostic, as well as making sure that any resources (e.g. files) it depends on remain accessible." + }, + "deleteVersion": { + "description": "Deletes a Model version. Model version can only be deleted if there are no DeployedModels created from it. Deleting the only version in the Model is not allowed. Use DeleteModel for deleting the Model instead.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.models.deleteVersion", + "httpMethod": "DELETE", + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "required": true, + "location": "path", + "description": "Required. The name of the model version to be deleted, with a version ID explicitly included. Example: `projects/{project}/locations/{location}/models/{model}@1234`" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:deleteVersion", + "path": "v1beta1/{+name}:deleteVersion", + "parameterOrder": [ + "name" + ] + }, + "mergeVersionAliases": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1MergeVersionAliasesRequest" + }, + "parameterOrder": [ + "name" + ], + "description": "Merges a set of aliases for a Model version.", + "httpMethod": "POST", + "parameters": { + "name": { + "type": "string", + "description": "Required. The name of the model version to merge aliases, with a version ID explicitly included. Example: `projects/{project}/locations/{location}/models/{model}@1234`", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "location": "path", + "required": true + } + }, + "id": "aiplatform.projects.locations.models.mergeVersionAliases", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:mergeVersionAliases", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Model" + }, + "path": "v1beta1/{+name}:mergeVersionAliases" + } + }, + "resources": { + "operations": { + "methods": { + "list": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations", + "parameters": { + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + }, + "pageSize": { + "description": "The standard list page size.", + "type": "integer", + "format": "int32", + "location": "query" + }, + "name": { + "description": "The name of the operation's parent resource.", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "location": "path" + }, + "filter": { + "description": "The standard list filter.", + "location": "query", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.models.operations.list", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}/operations", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "httpMethod": "GET", + "parameterOrder": [ + "name" + ] + }, + "cancel": { + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}:cancel", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations/{operationsId}:cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.models.operations.cancel", + "parameters": { + "name": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be cancelled.", + "required": true + } + }, + "httpMethod": "POST" + }, + "delete": { + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be deleted.", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations/{operationsId}", + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.models.operations.delete" + }, + "wait": { + "id": "aiplatform.projects.locations.models.operations.wait", + "path": "v1beta1/{+name}:wait", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations/{operationsId}:wait", + "httpMethod": "POST", + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string", + "format": "google-duration", + "location": "query" + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/operations/[^/]+$", + "type": "string", + "location": "path", + "required": true, + "description": "The name of the operation resource to wait on." + } + }, + "parameterOrder": [ + "name" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "get": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations/{operationsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/operations/[^/]+$", + "required": true, + "description": "The name of the operation resource." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "id": "aiplatform.projects.locations.models.operations.get" + } + } + }, + "evaluations": { + "resources": { + "operations": { + "methods": { + "delete": { + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "httpMethod": "DELETE", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.models.evaluations.operations.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "description": "The name of the operation resource to be deleted.", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/operations/[^/]+$", + "location": "path" + } + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." + }, + "wait": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}:wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}:wait", + "parameters": { + "name": { + "type": "string", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on." + }, + "timeout": { + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "format": "google-duration" + } + }, + "id": "aiplatform.projects.locations.models.evaluations.operations.wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "path": "v1beta1/{+name}/operations", + "parameters": { + "pageSize": { + "description": "The standard list page size.", + "format": "int32", + "location": "query", + "type": "integer" + }, + "name": { + "description": "The name of the operation's parent resource.", + "required": true, + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+$" + }, + "filter": { + "type": "string", + "description": "The standard list filter.", + "location": "query" + }, + "pageToken": { + "description": "The standard list page token.", + "location": "query", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.models.evaluations.operations.list" + }, + "get": { + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}", + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "id": "aiplatform.projects.locations.models.evaluations.operations.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/operations/[^/]+$", + "location": "path", + "description": "The name of the operation resource.", + "required": true + } + }, + "httpMethod": "GET" + }, + "cancel": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.models.evaluations.operations.cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/operations/[^/]+$", + "type": "string" + } + }, + "path": "v1beta1/{+name}:cancel", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}:cancel", + "httpMethod": "POST", + "parameterOrder": [ + "name" + ] + } + } + }, + "slices": { + "methods": { + "batchImport": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsResponse" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsRequest" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+parent}:batchImport", + "parameters": { + "parent": { + "required": true, + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/slices/[^/]+$", + "description": "Required. The name of the parent ModelEvaluationSlice resource. Format: `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}/slices/{slice}`" + } + }, + "parameterOrder": [ + "parent" + ], + "httpMethod": "POST", + "id": "aiplatform.projects.locations.models.evaluations.slices.batchImport", + "description": "Imports a list of externally generated EvaluatedAnnotations.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/slices/{slicesId}:batchImport" + }, + "list": { + "parameterOrder": [ + "parent" + ], + "httpMethod": "GET", + "parameters": { + "filter": { + "description": "The standard list filter. * `slice.dimension` - for =.", + "location": "query", + "type": "string" + }, + "pageSize": { + "location": "query", + "format": "int32", + "description": "The standard list page size.", + "type": "integer" + }, + "parent": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+$", + "required": true, + "type": "string", + "description": "Required. The resource name of the ModelEvaluation to list the ModelEvaluationSlices from. Format: `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}`" + }, + "readMask": { + "location": "query", + "type": "string", + "description": "Mask specifying which fields to read.", + "format": "google-fieldmask" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token. Typically obtained via ListModelEvaluationSlicesResponse.next_page_token of the previous ModelService.ListModelEvaluationSlices call." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+parent}/slices", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/slices", + "description": "Lists ModelEvaluationSlices in a ModelEvaluation.", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListModelEvaluationSlicesResponse" + }, + "id": "aiplatform.projects.locations.models.evaluations.slices.list" + }, + "get": { + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/slices/{slicesId}", + "id": "aiplatform.projects.locations.models.evaluations.slices.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/slices/[^/]+$", + "type": "string", + "description": "Required. The name of the ModelEvaluationSlice resource. Format: `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}/slices/{slice}`", + "required": true + } + }, + "parameterOrder": [ + "name" + ], + "description": "Gets a ModelEvaluationSlice.", + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationSlice" + } + } + } + } + }, + "methods": { + "import": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations:import", + "parameters": { + "parent": { + "description": "Required. The name of the parent model resource. Format: `projects/{project}/locations/{location}/models/{model}`", + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "required": true + } + }, + "path": "v1beta1/{+parent}/evaluations:import", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ImportModelEvaluationRequest" + }, + "httpMethod": "POST", + "id": "aiplatform.projects.locations.models.evaluations.import", + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Imports an externally generated ModelEvaluation." + }, + "get": { + "id": "aiplatform.projects.locations.models.evaluations.get", + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}", + "parameters": { + "name": { + "description": "Required. The name of the ModelEvaluation resource. Format: `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}`", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+$", + "location": "path" + } + }, + "description": "Gets a ModelEvaluation.", + "httpMethod": "GET", + "parameterOrder": [ + "name" + ] + }, + "list": { + "parameters": { + "pageSize": { + "format": "int32", + "type": "integer", + "description": "The standard list page size.", + "location": "query" + }, + "readMask": { + "format": "google-fieldmask", + "type": "string", + "description": "Mask specifying which fields to read.", + "location": "query" + }, + "pageToken": { + "type": "string", + "description": "The standard list page token. Typically obtained via ListModelEvaluationsResponse.next_page_token of the previous ModelService.ListModelEvaluations call.", + "location": "query" + }, + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + }, + "parent": { + "location": "path", + "description": "Required. The resource name of the Model to list the ModelEvaluations from. Format: `projects/{project}/locations/{location}/models/{model}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", + "required": true + } + }, + "httpMethod": "GET", + "path": "v1beta1/{+parent}/evaluations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations", + "description": "Lists ModelEvaluations in a Model.", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListModelEvaluationsResponse" + }, + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.models.evaluations.list" + } + } + } + } + }, + "modelMonitors": { + "resources": { + "modelMonitoringJobs": { + "methods": { + "delete": { + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ], + "description": "Deletes a ModelMonitoringJob.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}/modelMonitoringJobs/{modelMonitoringJobsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.modelMonitors.modelMonitoringJobs.delete", + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+/modelMonitoringJobs/[^/]+$", + "location": "path", + "description": "Required. The resource name of the model monitoring job to delete. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}/modelMonitoringJobs/{model_monitoring_job}`" + } + } + }, + "create": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringJob" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}/modelMonitoringJobs", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringJob" + }, + "description": "Creates a ModelMonitoringJob.", + "parameters": { + "parent": { + "location": "path", + "required": true, + "description": "Required. The parent of the ModelMonitoringJob. Format: `projects/{project}/locations/{location}/modelMoniitors/{model_monitor}`", + "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+$", + "type": "string" + }, + "modelMonitoringJobId": { + "type": "string", + "location": "query", + "description": "Optional. The ID to use for the Model Monitoring Job, which will become the final component of the model monitoring job resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "id": "aiplatform.projects.locations.modelMonitors.modelMonitoringJobs.create", + "parameterOrder": [ + "parent" + ], + "path": "v1beta1/{+parent}/modelMonitoringJobs" + }, + "get": { + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "id": "aiplatform.projects.locations.modelMonitors.modelMonitoringJobs.get", + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringJob" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}/modelMonitoringJobs/{modelMonitoringJobsId}", + "description": "Gets a ModelMonitoringJob.", + "parameters": { + "name": { + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+/modelMonitoringJobs/[^/]+$", + "description": "Required. The resource name of the ModelMonitoringJob. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}/modelMonitoringJobs/{model_monitoring_job}`", + "required": true + } + } + }, + "list": { + "parameterOrder": [ + "parent" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}/modelMonitoringJobs", + "description": "Lists ModelMonitoringJobs. Callers may choose to read across multiple Monitors as per [AIP-159](https://google.aip.dev/159) by using '-' (the hyphen or dash character) as a wildcard character instead of modelMonitor id in the parent. Format `projects/{project_id}/locations/{location}/moodelMonitors/-/modelMonitoringJobs`", + "path": "v1beta1/{+parent}/modelMonitoringJobs", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "filter": { + "type": "string", + "description": "The standard list filter. More detail in [AIP-160](https://google.aip.dev/160).", + "location": "query" + }, + "parent": { + "location": "path", + "type": "string", + "description": "Required. The parent of the ModelMonitoringJob. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+$" + }, + "readMask": { + "format": "google-fieldmask", + "type": "string", + "description": "Mask specifying which fields to read", + "location": "query" + }, + "pageSize": { + "description": "The standard list page size.", + "location": "query", + "format": "int32", + "type": "integer" + }, + "pageToken": { + "description": "The standard list page token.", + "location": "query", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.modelMonitors.modelMonitoringJobs.list", + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListModelMonitoringJobsResponse" + } + } + } + }, + "operations": { + "methods": { + "get": { + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.modelMonitors.operations.get", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "description": "The name of the operation resource." + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}/operations/{operationsId}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "httpMethod": "GET", + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "path": "v1beta1/{+name}/operations", + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.modelMonitors.operations.list", + "parameters": { + "pageSize": { + "format": "int32", + "type": "integer", + "description": "The standard list page size.", + "location": "query" + }, + "name": { + "required": true, + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+$", + "description": "The name of the operation's parent resource." + }, + "filter": { + "description": "The standard list filter.", + "location": "query", + "type": "string" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + } + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}/operations" + }, + "wait": { + "parameters": { + "timeout": { + "location": "query", + "type": "string", + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + }, + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+/operations/[^/]+$", + "location": "path", + "required": true, + "description": "The name of the operation resource to wait on." + } + }, + "path": "v1beta1/{+name}:wait", + "id": "aiplatform.projects.locations.modelMonitors.operations.wait", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}/operations/{operationsId}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ] + }, + "delete": { + "id": "aiplatform.projects.locations.modelMonitors.operations.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "type": "string", + "description": "The name of the operation resource to be deleted.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+/operations/[^/]+$", + "location": "path" + } + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}/operations/{operationsId}", + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ] + }, + "cancel": { + "id": "aiplatform.projects.locations.modelMonitors.operations.cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "httpMethod": "POST", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1beta1/{+name}:cancel", + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+/operations/[^/]+$" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}/operations/{operationsId}:cancel" + } + } + } + }, + "methods": { + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a ModelMonitor.", + "parameters": { + "force": { + "location": "query", + "description": "Optional. Force delete the model monitor with schedules.", + "type": "boolean" + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+$", + "location": "path", + "type": "string", + "required": true, + "description": "Required. The name of the ModelMonitor resource to be deleted. Format: `projects/{project}/locations/{location}/modelMonitords/{model_monitor}`" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}", + "id": "aiplatform.projects.locations.modelMonitors.delete", + "path": "v1beta1/{+name}", + "httpMethod": "DELETE", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ] + }, + "get": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}", + "httpMethod": "GET", + "id": "aiplatform.projects.locations.modelMonitors.get", + "description": "Gets a ModelMonitor.", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitor" + }, + "parameters": { + "name": { + "description": "Required. The name of the ModelMonitor resource. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+$", + "type": "string" + } + }, + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}" + }, + "searchModelMonitoringAlerts": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}:searchModelMonitoringAlerts", + "description": "Returns the Model Monitoring alerts.", + "httpMethod": "POST", + "id": "aiplatform.projects.locations.modelMonitors.searchModelMonitoringAlerts", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1SearchModelMonitoringAlertsRequest" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+modelMonitor}:searchModelMonitoringAlerts", + "parameterOrder": [ + "modelMonitor" + ], + "parameters": { + "modelMonitor": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+$", + "required": true, + "description": "Required. ModelMonitor resource name. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`", + "location": "path" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1SearchModelMonitoringAlertsResponse" + } + }, + "searchModelMonitoringStats": { + "id": "aiplatform.projects.locations.modelMonitors.searchModelMonitoringStats", + "parameters": { + "modelMonitor": { + "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+$", + "type": "string", + "required": true, + "location": "path", + "description": "Required. ModelMonitor resource name. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsRequest" + }, + "description": "Searches Model Monitoring Stats generated within a given time window.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}:searchModelMonitoringStats", + "path": "v1beta1/{+modelMonitor}:searchModelMonitoringStats", + "parameterOrder": [ + "modelMonitor" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsResponse" + }, + "httpMethod": "POST" + }, + "create": { + "httpMethod": "POST", + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.modelMonitors.create", + "path": "v1beta1/{+parent}/modelMonitors", + "parameters": { + "modelMonitorId": { + "type": "string", + "description": "Optional. The ID to use for the Model Monitor, which will become the final component of the model monitor resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`.", + "location": "query" + }, + "parent": { + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "description": "Required. The resource name of the Location to create the ModelMonitor in. Format: `projects/{project}/locations/{location}`" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors", + "description": "Creates a ModelMonitor.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitor" + }, + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "patch": { + "parameters": { + "name": { + "description": "Immutable. Resource name of the ModelMonitor. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`.", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+$", + "type": "string" + }, + "updateMask": { + "format": "google-fieldmask", + "location": "query", + "type": "string", + "description": "Required. Mask specifying which fields to update." + } + }, + "path": "v1beta1/{+name}", + "httpMethod": "PATCH", + "parameterOrder": [ + "name" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ModelMonitor" + }, + "id": "aiplatform.projects.locations.modelMonitors.patch", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Updates a ModelMonitor.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "path": "v1beta1/{+parent}/modelMonitors", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListModelMonitorsResponse" + }, + "httpMethod": "GET", + "description": "Lists ModelMonitors in a Location.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "parameters": { + "parent": { + "location": "path", + "description": "Required. The resource name of the Location to list the ModelMonitors from. Format: `projects/{project}/locations/{location}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true + }, + "pageToken": { + "description": "The standard list page token.", + "location": "query", + "type": "string" + }, + "pageSize": { + "location": "query", + "description": "The standard list page size.", + "format": "int32", + "type": "integer" + }, + "readMask": { + "type": "string", + "format": "google-fieldmask", + "description": "Mask specifying which fields to read.", + "location": "query" + }, + "filter": { + "location": "query", + "description": "The standard list filter. More detail in [AIP-160](https://google.aip.dev/160).", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.modelMonitors.list" + } + } + }, + "exampleStores": { + "resources": { + "operations": { + "methods": { + "get": { + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores/{exampleStoresId}/operations/{operationsId}", + "path": "v1beta1/{+name}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.exampleStores.operations.get", + "httpMethod": "GET", + "parameters": { + "name": { + "type": "string", + "description": "The name of the operation resource.", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/exampleStores/[^/]+/operations/[^/]+$" + } + } + }, + "cancel": { + "id": "aiplatform.projects.locations.exampleStores.operations.cancel", + "parameterOrder": [ + "name" + ], + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores/{exampleStoresId}/operations/{operationsId}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/exampleStores/[^/]+/operations/[^/]+$", + "type": "string", + "description": "The name of the operation resource to be cancelled.", + "required": true, + "location": "path" + } + }, + "path": "v1beta1/{+name}:cancel", + "httpMethod": "POST" + }, + "list": { + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "path": "v1beta1/{+name}/operations", + "httpMethod": "GET", + "id": "aiplatform.projects.locations.exampleStores.operations.list", + "parameterOrder": [ + "name" + ], + "parameters": { + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + }, + "pageSize": { + "description": "The standard list page size.", + "format": "int32", + "location": "query", + "type": "integer" + }, + "name": { + "description": "The name of the operation's parent resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/exampleStores/[^/]+$", + "type": "string", + "required": true, + "location": "path" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores/{exampleStoresId}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + } + }, + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.exampleStores.operations.delete", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores/{exampleStoresId}/operations/{operationsId}", + "parameters": { + "name": { + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/exampleStores/[^/]+/operations/[^/]+$", + "location": "path", + "type": "string", + "required": true + } + } + }, + "wait": { + "parameters": { + "name": { + "description": "The name of the operation resource to wait on.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/exampleStores/[^/]+/operations/[^/]+$", + "type": "string", + "location": "path" + }, + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "location": "query", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.exampleStores.operations.wait", + "path": "v1beta1/{+name}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores/{exampleStoresId}/operations/{operationsId}:wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "parameterOrder": [ + "name" + ], + "httpMethod": "POST" + } + } + } + } + }, + "persistentResources": { + "methods": { + "reboot": { + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1RebootPersistentResourceRequest" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}:reboot", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", + "type": "string", + "description": "Required. The name of the PersistentResource resource. Format: `projects/{project_id_or_number}/locations/{location_id}/persistentResources/{persistent_resource_id}`", + "required": true + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "description": "Reboots a PersistentResource.", + "id": "aiplatform.projects.locations.persistentResources.reboot", + "path": "v1beta1/{+name}:reboot" + }, + "get": { + "id": "aiplatform.projects.locations.persistentResources.get", + "parameters": { + "name": { + "required": true, + "location": "path", + "description": "Required. The name of the PersistentResource resource. Format: `projects/{project_id_or_number}/locations/{location_id}/persistentResources/{persistent_resource_id}`", + "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", + "type": "string" + } + }, + "description": "Gets a PersistentResource.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1PersistentResource" + } + }, + "patch": { + "httpMethod": "PATCH", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1PersistentResource" + }, + "parameters": { + "updateMask": { + "location": "query", + "description": "Required. Specify the fields to be overwritten in the PersistentResource by the update method.", + "format": "google-fieldmask", + "type": "string" + }, + "name": { + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", + "location": "path", + "description": "Immutable. Resource name of a PersistentResource." + } + }, + "description": "Updates a PersistentResource.", + "id": "aiplatform.projects.locations.persistentResources.patch", + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}" + }, + "create": { + "httpMethod": "POST", + "description": "Creates a PersistentResource.", + "id": "aiplatform.projects.locations.persistentResources.create", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1PersistentResource" + }, + "parameters": { + "persistentResourceId": { + "type": "string", + "location": "query", + "description": "Required. The ID to use for the PersistentResource, which become the final component of the PersistentResource's resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`." + }, + "parent": { + "description": "Required. The resource name of the Location to create the PersistentResource in. Format: `projects/{project}/locations/{location}`", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path" + } + }, + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+parent}/persistentResources", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources" + }, + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "DELETE", + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}", + "description": "Deletes a PersistentResource.", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.persistentResources.delete", + "parameters": { + "name": { + "required": true, + "location": "path", + "description": "Required. The name of the PersistentResource to be deleted. Format: `projects/{project}/locations/{location}/persistentResources/{persistent_resource}`", + "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", + "type": "string" + } + } + }, + "list": { + "path": "v1beta1/{+parent}/persistentResources", + "parameters": { + "parent": { + "required": true, + "location": "path", + "description": "Required. The resource name of the Location to list the PersistentResources from. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string" + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "Optional. The standard list page token. Typically obtained via ListPersistentResourceResponse.next_page_token of the previous PersistentResourceService.ListPersistentResource call." + }, + "pageSize": { + "type": "integer", + "location": "query", + "format": "int32", + "description": "Optional. The standard list page size." + } + }, + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "description": "Lists PersistentResources in a Location.", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListPersistentResourcesResponse" + }, + "id": "aiplatform.projects.locations.persistentResources.list", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources" + } + }, + "resources": { + "operations": { + "methods": { + "delete": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "httpMethod": "DELETE", + "id": "aiplatform.projects.locations.persistentResources.operations.delete", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations/{operationsId}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+/operations/[^/]+$", + "location": "path", + "required": true, + "type": "string", + "description": "The name of the operation resource to be deleted." + } + } + }, + "get": { + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations/{operationsId}", + "httpMethod": "GET", + "id": "aiplatform.projects.locations.persistentResources.operations.get", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource.", + "location": "path", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." + }, + "cancel": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "required": true, + "location": "path", + "description": "The name of the operation resource to be cancelled.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+/operations/[^/]+$" + } + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations/{operationsId}:cancel", + "id": "aiplatform.projects.locations.persistentResources.operations.cancel", + "httpMethod": "POST", + "path": "v1beta1/{+name}:cancel" + }, + "list": { + "id": "aiplatform.projects.locations.persistentResources.operations.list", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations", + "httpMethod": "GET", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "path": "v1beta1/{+name}/operations", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + }, + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + }, + "name": { + "description": "The name of the operation's parent resource.", + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", + "required": true + }, + "pageSize": { + "location": "query", + "description": "The standard list page size.", + "type": "integer", + "format": "int32" + } + }, + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + } + }, + "wait": { + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations/{operationsId}:wait", + "path": "v1beta1/{+name}:wait", + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.persistentResources.operations.wait", + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "location": "query", + "type": "string" + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+/operations/[^/]+$", + "type": "string", + "required": true, + "description": "The name of the operation resource to wait on.", + "location": "path" + } + } + } + } + } + } + }, + "notebookExecutionJobs": { + "resources": { + "operations": { + "methods": { + "get": { + "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.get", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}", + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "type": "string", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource." + } + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "delete": { + "path": "v1beta1/{+name}", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be deleted.", + "type": "string", + "required": true, + "location": "path" + } + }, + "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}", + "response": { + "$ref": "GoogleProtobufEmpty" + } + }, + "wait": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}:wait", + "parameters": { + "timeout": { + "format": "google-duration", + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string" + }, + "name": { + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+/operations/[^/]+$", + "type": "string", + "location": "path", + "required": true + } + }, + "parameterOrder": [ + "name" + ], + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.wait", + "path": "v1beta1/{+name}:wait" + }, + "cancel": { + "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.cancel", + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+/operations/[^/]+$", + "location": "path" + } + }, + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}:cancel", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}:cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + } + }, + "list": { + "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.list", + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "parameters": { + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token." + }, + "name": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+$", + "description": "The name of the operation's parent resource.", + "required": true + }, + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + }, + "pageSize": { + "format": "int32", + "description": "The standard list page size.", + "type": "integer", + "location": "query" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations" + } + } + } + }, + "methods": { + "get": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1NotebookExecutionJob" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "parameters": { + "view": { + "description": "Optional. The NotebookExecutionJob view. Defaults to BASIC.", + "enum": [ + "NOTEBOOK_EXECUTION_JOB_VIEW_UNSPECIFIED", + "NOTEBOOK_EXECUTION_JOB_VIEW_BASIC", + "NOTEBOOK_EXECUTION_JOB_VIEW_FULL" + ], + "type": "string", + "enumDescriptions": [ + "When unspecified, the API defaults to the BASIC view.", + "Includes all fields except for direct notebook inputs.", + "Includes all fields." + ], + "location": "query" + }, + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+$", + "description": "Required. The name of the NotebookExecutionJob resource.", + "type": "string", + "location": "path" + } + }, + "description": "Gets a NotebookExecutionJob.", + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.notebookExecutionJobs.get", + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}" + }, + "delete": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}", + "id": "aiplatform.projects.locations.notebookExecutionJobs.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Deletes a NotebookExecutionJob.", + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+$", + "required": true, + "type": "string", + "description": "Required. The name of the NotebookExecutionJob resource to be deleted." + } + }, + "path": "v1beta1/{+name}", + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + } + }, + "create": { + "id": "aiplatform.projects.locations.notebookExecutionJobs.create", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs", + "path": "v1beta1/{+parent}/notebookExecutionJobs", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1NotebookExecutionJob" + }, + "description": "Creates a NotebookExecutionJob.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameterOrder": [ + "parent" + ], + "parameters": { + "parent": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string", + "location": "path", + "description": "Required. The resource name of the Location to create the NotebookExecutionJob. Format: `projects/{project}/locations/{location}`" + }, + "notebookExecutionJobId": { + "type": "string", + "location": "query", + "description": "Optional. User specified ID for the NotebookExecutionJob." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST" + }, + "generateAccessToken": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1GenerateAccessTokenResponse" + }, + "httpMethod": "POST", + "description": "Internal only: Called from Compute Engine instance to obtain EUC for owner Anonymous access: authenticates caller using VM identity JWT. Design doc: go/colab-on-vertex-euc-dd", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}:generateAccessToken", + "id": "aiplatform.projects.locations.notebookExecutionJobs.generateAccessToken", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1GenerateAccessTokenRequest" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}:generateAccessToken", + "parameters": { + "name": { + "type": "string", + "description": "Required. The name of the resource requesting the OAuth2 token. Format: `projects/{project}/locations/{location}/notebookRuntimes/{notebook_runtime}` `projects/{project}/locations/{location}/notebookExecutionJobs/{notebook_execution_job}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+$", + "location": "path" + } + } + }, + "list": { + "path": "v1beta1/{+parent}/notebookExecutionJobs", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.notebookExecutionJobs.list", + "parameterOrder": [ + "parent" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListNotebookExecutionJobsResponse" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs", + "description": "Lists NotebookExecutionJobs in a Location.", + "parameters": { + "orderBy": { + "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`.", + "type": "string", + "location": "query" + }, + "pageSize": { + "type": "integer", + "format": "int32", + "location": "query", + "description": "Optional. The standard list page size." + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location from which to list the NotebookExecutionJobs. Format: `projects/{project}/locations/{location}`", + "type": "string", + "required": true, + "location": "path" + }, + "view": { + "enumDescriptions": [ + "When unspecified, the API defaults to the BASIC view.", + "Includes all fields except for direct notebook inputs.", + "Includes all fields." + ], + "enum": [ + "NOTEBOOK_EXECUTION_JOB_VIEW_UNSPECIFIED", + "NOTEBOOK_EXECUTION_JOB_VIEW_BASIC", + "NOTEBOOK_EXECUTION_JOB_VIEW_FULL" + ], + "description": "Optional. The NotebookExecutionJob view. Defaults to BASIC.", + "type": "string", + "location": "query" + }, + "pageToken": { + "location": "query", + "description": "Optional. The standard list page token. Typically obtained via ListNotebookExecutionJobs.next_page_token of the previous NotebookService.ListNotebookExecutionJobs call.", + "type": "string" + }, + "filter": { + "location": "query", + "description": "Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `notebookExecutionJob` supports = and !=. `notebookExecutionJob` represents the NotebookExecutionJob ID. * `displayName` supports = and != and regex. * `schedule` supports = and != and regex. Some examples: * `notebookExecutionJob=\"123\"` * `notebookExecutionJob=\"my-execution-job\"` * `displayName=\"myDisplayName\"` and `displayName=~\"myDisplayNameRegex\"`", + "type": "string" + } + }, + "httpMethod": "GET" + }, + "reportEvent": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ReportExecutionEventResponse" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}:reportEvent", + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+$", + "type": "string", + "location": "path", + "description": "Required. The name of the NotebookExecutionJob resource. Format: `projects/{project}/locations/{location}/notebookExecutionJobs/{notebook_execution_jobs}`" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ReportExecutionEventRequest" + }, + "httpMethod": "POST", + "description": "", + "path": "v1beta1/{+name}:reportEvent", + "id": "aiplatform.projects.locations.notebookExecutionJobs.reportEvent" + } + } + }, + "studies": { + "resources": { + "operations": { + "methods": { + "get": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.studies.operations.get", + "path": "v1beta1/{+name}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource.", + "required": true, + "type": "string", + "location": "path" + } + }, + "httpMethod": "GET" + }, + "wait": { + "path": "v1beta1/{+name}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "id": "aiplatform.projects.locations.studies.operations.wait", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations/{operationsId}:wait", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "parameters": { + "name": { + "type": "string", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on." + }, + "timeout": { + "type": "string", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "format": "google-duration" + } + } + }, + "cancel": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/operations/[^/]+$", + "type": "string", + "required": true, + "location": "path", + "description": "The name of the operation resource to be cancelled." + } + }, + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations/{operationsId}:cancel", + "id": "aiplatform.projects.locations.studies.operations.cancel", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "httpMethod": "POST", + "path": "v1beta1/{+name}:cancel" + }, + "list": { + "path": "v1beta1/{+name}/operations", + "httpMethod": "GET", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameters": { + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token." + }, + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter." + }, + "name": { + "location": "path", + "required": true, + "description": "The name of the operation's parent resource.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$" + }, + "pageSize": { + "format": "int32", + "location": "query", + "type": "integer", + "description": "The standard list page size." + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.studies.operations.list" + }, + "delete": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "DELETE", + "parameters": { + "name": { + "required": true, + "description": "The name of the operation resource to be deleted.", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/operations/[^/]+$" + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.studies.operations.delete", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations/{operationsId}" + } + } + }, + "trials": { + "methods": { + "addTrialMeasurement": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Trial" + }, + "id": "aiplatform.projects.locations.studies.trials.addTrialMeasurement", + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1AddTrialMeasurementRequest" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}:addTrialMeasurement", + "parameterOrder": [ + "trialName" + ], + "path": "v1beta1/{+trialName}:addTrialMeasurement", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Adds a measurement of the objective metrics to a Trial. This measurement is assumed to have been taken before the Trial is complete.", + "parameters": { + "trialName": { + "type": "string", + "location": "path", + "description": "Required. The name of the trial to add measurement. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$" + } + } + }, + "listOptimalTrials": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1ListOptimalTrialsRequest" + }, + "parameterOrder": [ + "parent" + ], + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", + "required": true, + "description": "Required. The name of the Study that the optimal Trial belongs to.", + "type": "string", + "location": "path" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListOptimalTrialsResponse" + }, + "id": "aiplatform.projects.locations.studies.trials.listOptimalTrials", + "path": "v1beta1/{+parent}/trials:listOptimalTrials", + "httpMethod": "POST", + "description": "Lists the pareto-optimal Trials for multi-objective Study or the optimal Trials for single-objective Study. The definition of pareto-optimal can be checked in wiki page. https://en.wikipedia.org/wiki/Pareto_efficiency", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials:listOptimalTrials" + }, + "list": { + "path": "v1beta1/{+parent}/trials", + "parameters": { + "pageSize": { + "description": "Optional. The number of Trials to retrieve per \"page\" of results. If unspecified, the service will pick an appropriate default.", + "location": "query", + "format": "int32", + "type": "integer" + }, + "pageToken": { + "location": "query", + "description": "Optional. A page token to request the next page of results. If unspecified, there are no subsequent pages.", + "type": "string" + }, + "parent": { + "location": "path", + "required": true, + "description": "Required. The resource name of the Study to list the Trial from. Format: `projects/{project}/locations/{location}/studies/{study}`", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$" + } + }, + "description": "Lists the Trials associated with a Study.", + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials", + "parameterOrder": [ + "parent" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListTrialsResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.studies.trials.list" + }, + "create": { + "httpMethod": "POST", + "description": "Adds a user provided Trial to a Study.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials", + "parameterOrder": [ + "parent" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Trial" + }, + "id": "aiplatform.projects.locations.studies.trials.create", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Trial" + }, + "parameters": { + "parent": { + "location": "path", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", + "description": "Required. The resource name of the Study to create the Trial in. Format: `projects/{project}/locations/{location}/studies/{study}`", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+parent}/trials" + }, + "suggest": { + "id": "aiplatform.projects.locations.studies.trials.suggest", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1SuggestTrialsRequest" + }, + "parameterOrder": [ + "parent" + ], + "path": "v1beta1/{+parent}/trials:suggest", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials:suggest", + "httpMethod": "POST", + "description": "Adds one or more Trials to a Study, with parameter values suggested by Vertex AI Vizier. Returns a long-running operation associated with the generation of Trial suggestions. When this long-running operation succeeds, it will contain a SuggestTrialsResponse.", + "parameters": { + "parent": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", + "required": true, + "description": "Required. The project and location that the Study belongs to. Format: `projects/{project}/locations/{location}/studies/{study}`", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "delete": { + "parameters": { + "name": { + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", + "location": "path", + "required": true, + "description": "Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`" + } + }, + "id": "aiplatform.projects.locations.studies.trials.delete", + "description": "Deletes a Trial.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "httpMethod": "DELETE", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}" + }, + "get": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Trial" + }, + "id": "aiplatform.projects.locations.studies.trials.get", + "httpMethod": "GET", + "description": "Gets a Trial.", + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}", + "parameters": { + "name": { + "description": "Required. The name of the Trial resource. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$" + } + } + }, + "stop": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}:stop", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Trial" + }, + "parameters": { + "name": { + "description": "Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", + "type": "string" + } + }, + "id": "aiplatform.projects.locations.studies.trials.stop", + "httpMethod": "POST", + "description": "Stops a Trial.", + "parameterOrder": [ + "name" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1StopTrialRequest" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}:stop" + }, + "checkTrialEarlyStoppingState": { + "description": "Checks whether a Trial should stop or not. Returns a long-running operation. When the operation is successful, it will contain a CheckTrialEarlyStoppingStateResponse.", + "parameters": { + "trialName": { + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", + "location": "path", + "required": true, + "description": "Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", + "type": "string" + } + }, + "parameterOrder": [ + "trialName" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateRequest" + }, + "id": "aiplatform.projects.locations.studies.trials.checkTrialEarlyStoppingState", + "httpMethod": "POST", + "path": "v1beta1/{+trialName}:checkTrialEarlyStoppingState", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}:checkTrialEarlyStoppingState" + }, + "complete": { + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Trial" + }, + "id": "aiplatform.projects.locations.studies.trials.complete", + "parameters": { + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", + "type": "string", + "description": "Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`" + } + }, + "description": "Marks a Trial as complete.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}:complete", + "path": "v1beta1/{+name}:complete", + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1CompleteTrialRequest" + } + } + }, + "resources": { + "operations": { + "methods": { + "list": { + "path": "v1beta1/{+name}/operations", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.studies.trials.operations.list", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "parameters": { + "pageSize": { + "location": "query", + "format": "int32", + "type": "integer", + "description": "The standard list page size." + }, + "name": { + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", + "description": "The name of the operation's parent resource.", + "location": "path" + }, + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter." + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "The standard list page token." + } + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." + }, + "get": { + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}", + "parameters": { + "name": { + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+/operations/[^/]+$", + "required": true, + "type": "string", + "location": "path" + } + }, + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.studies.trials.operations.get" + }, + "wait": { + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "id": "aiplatform.projects.locations.studies.trials.operations.wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+name}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}:wait", + "parameters": { + "name": { + "required": true, + "location": "path", + "description": "The name of the operation resource to wait on.", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+/operations/[^/]+$", + "type": "string" + }, + "timeout": { + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "type": "string", + "location": "query" + } + } + }, + "delete": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.studies.trials.operations.delete", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "httpMethod": "DELETE", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "location": "path", + "description": "The name of the operation resource to be deleted.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+/operations/[^/]+$", + "required": true + } + }, + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleProtobufEmpty" + } + }, + "cancel": { + "path": "v1beta1/{+name}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "id": "aiplatform.projects.locations.studies.trials.operations.cancel", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameters": { + "name": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be cancelled.", + "type": "string", + "required": true + } + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}:cancel", + "parameterOrder": [ + "name" + ] + } + } + } + } + } + }, + "methods": { + "delete": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", + "description": "Required. The name of the Study resource to be deleted. Format: `projects/{project}/locations/{location}/studies/{study}`", + "type": "string", + "location": "path", + "required": true + } + }, + "description": "Deletes a Study.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.studies.delete", + "httpMethod": "DELETE" + }, + "list": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies", + "parameters": { + "parent": { + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path", + "description": "Required. The resource name of the Location to list the Study from. Format: `projects/{project}/locations/{location}`" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "Optional. A page token to request the next page of results. If unspecified, there are no subsequent pages." + }, + "pageSize": { + "location": "query", + "description": "Optional. The maximum number of studies to return per \"page\" of results. If unspecified, service will pick an appropriate default.", + "format": "int32", + "type": "integer" + } + }, + "path": "v1beta1/{+parent}/studies", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListStudiesResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.studies.list", + "parameterOrder": [ + "parent" + ], + "httpMethod": "GET", + "description": "Lists all the studies in a region for an associated project." + }, + "lookup": { + "path": "v1beta1/{+parent}/studies:lookup", + "id": "aiplatform.projects.locations.studies.lookup", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1LookupStudyRequest" + }, + "httpMethod": "POST", + "parameters": { + "parent": { + "description": "Required. The resource name of the Location to get the Study from. Format: `projects/{project}/locations/{location}`", + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies:lookup", + "parameterOrder": [ + "parent" + ], + "description": "Looks a study up using the user-defined display_name field instead of the fully qualified resource name.", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Study" + } + }, + "create": { + "description": "Creates a Study. A resource name will be generated after creation of the Study.", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Study" + }, + "id": "aiplatform.projects.locations.studies.create", + "path": "v1beta1/{+parent}/studies", + "parameters": { + "parent": { + "description": "Required. The resource name of the Location to create the CustomJob in. Format: `projects/{project}/locations/{location}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string", + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "parameterOrder": [ + "parent" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Study" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies" + }, + "get": { + "id": "aiplatform.projects.locations.studies.get", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Study" + }, + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", + "description": "Required. The name of the Study resource. Format: `projects/{project}/locations/{location}/studies/{study}`", + "required": true, + "type": "string", + "location": "path" + } + }, + "httpMethod": "GET", + "description": "Gets a Study by name.", + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ] + } + } + }, + "batchPredictionJobs": { + "methods": { + "get": { + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJob" + }, + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets a BatchPredictionJob", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/batchPredictionJobs/[^/]+$", + "location": "path", + "type": "string", + "required": true, + "description": "Required. The name of the BatchPredictionJob resource. Format: `projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job}`" + } + }, + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.batchPredictionJobs.get", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs/{batchPredictionJobsId}" + }, + "cancel": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Cancels a BatchPredictionJob. Starts asynchronous cancellation on the BatchPredictionJob. The server makes the best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetBatchPredictionJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On a successful cancellation, the BatchPredictionJob is not deleted;instead its BatchPredictionJob.state is set to `CANCELLED`. Any files already outputted by the job are not deleted.", + "path": "v1beta1/{+name}:cancel", + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs/{batchPredictionJobsId}:cancel", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1CancelBatchPredictionJobRequest" + }, + "id": "aiplatform.projects.locations.batchPredictionJobs.cancel", + "parameters": { + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/batchPredictionJobs/[^/]+$", + "description": "Required. The name of the BatchPredictionJob to cancel. Format: `projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job}`", + "type": "string" + } + } + }, + "delete": { + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.batchPredictionJobs.delete", + "path": "v1beta1/{+name}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs/{batchPredictionJobsId}", + "httpMethod": "DELETE", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/batchPredictionJobs/[^/]+$", + "required": true, + "location": "path", + "type": "string", + "description": "Required. The name of the BatchPredictionJob resource to be deleted. Format: `projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job}`" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Deletes a BatchPredictionJob. Can only be called on jobs that already finished." + }, + "create": { + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJob" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJob" + }, + "path": "v1beta1/{+parent}/batchPredictionJobs", + "parameters": { + "parent": { + "location": "path", + "type": "string", + "description": "Required. The resource name of the Location to create the BatchPredictionJob in. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true + } + }, + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.batchPredictionJobs.create", + "description": "Creates a BatchPredictionJob. A BatchPredictionJob once created will right away be attempted to start." + }, + "list": { + "httpMethod": "GET", + "path": "v1beta1/{+parent}/batchPredictionJobs", + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.batchPredictionJobs.list", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListBatchPredictionJobsResponse" + }, + "description": "Lists BatchPredictionJobs in a Location.", + "parameters": { + "readMask": { + "format": "google-fieldmask", + "description": "Mask specifying which fields to read.", + "type": "string", + "location": "query" + }, + "filter": { + "type": "string", + "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `model_display_name` supports `=`, `!=` comparisons. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`", + "location": "query" + }, + "parent": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "type": "string", + "required": true, + "description": "Required. The resource name of the Location to list the BatchPredictionJobs from. Format: `projects/{project}/locations/{location}`" + }, + "pageSize": { + "description": "The standard list page size.", + "location": "query", + "type": "integer", + "format": "int32" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token. Typically obtained via ListBatchPredictionJobsResponse.next_page_token of the previous JobService.ListBatchPredictionJobs call." + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + } + } + }, + "metadataStores": { + "methods": { + "create": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1MetadataStore" + }, + "parameters": { + "parent": { + "description": "Required. The resource name of the Location where the MetadataStore should be created. Format: `projects/{project}/locations/{location}/`", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "location": "path" + }, + "metadataStoreId": { + "location": "query", + "description": "The {metadatastore} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` If not provided, the MetadataStore's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all MetadataStores in the parent Location. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting MetadataStore.)", + "type": "string" + } + }, + "description": "Initializes a MetadataStore, including allocation of resources.", + "path": "v1beta1/{+parent}/metadataStores", + "httpMethod": "POST", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.metadataStores.create" + }, + "list": { + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.metadataStores.list", + "description": "Lists MetadataStores for a Location.", + "path": "v1beta1/{+parent}/metadataStores", + "parameters": { + "pageSize": { + "format": "int32", + "description": "The maximum number of Metadata Stores to return. The service may return fewer. Must be in range 1-1000, inclusive. Defaults to 100.", + "type": "integer", + "location": "query" + }, + "pageToken": { + "description": "A page token, received from a previous MetadataService.ListMetadataStores call. Provide this to retrieve the subsequent page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with INVALID_ARGUMENT error.)", + "location": "query", + "type": "string" + }, + "parent": { + "required": true, + "location": "path", + "type": "string", + "description": "Required. The Location whose MetadataStores should be listed. Format: `projects/{project}/locations/{location}`", + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListMetadataStoresResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores" + }, + "get": { + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}", + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "location": "path", + "type": "string", + "description": "Required. The resource name of the MetadataStore to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`" + } + }, + "id": "aiplatform.projects.locations.metadataStores.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1MetadataStore" + }, + "path": "v1beta1/{+name}", + "description": "Retrieves a specific MetadataStore." + }, + "delete": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}", + "id": "aiplatform.projects.locations.metadataStores.delete", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "force": { + "type": "boolean", + "description": "Deprecated: Field is no longer supported.", + "location": "query", + "deprecated": true + }, + "name": { + "location": "path", + "type": "string", + "description": "Required. The resource name of the MetadataStore to delete. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$" + } + }, + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ], + "description": "Deletes a single MetadataStore and all its child resources (Artifacts, Executions, and Contexts).", + "path": "v1beta1/{+name}" + } + }, + "resources": { + "operations": { + "methods": { + "list": { + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "parameters": { + "filter": { + "type": "string", + "location": "query", + "description": "The standard list filter." + }, + "pageSize": { + "description": "The standard list page size.", + "format": "int32", + "location": "query", + "type": "integer" + }, + "pageToken": { + "location": "query", + "type": "string", + "description": "The standard list page token." + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "type": "string", + "location": "path", + "required": true, + "description": "The name of the operation's parent resource." + } + }, + "id": "aiplatform.projects.locations.metadataStores.operations.list", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "path": "v1beta1/{+name}/operations", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations" + }, + "cancel": { + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.metadataStores.operations.cancel", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations/{operationsId}:cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "httpMethod": "POST", + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/operations/[^/]+$", + "type": "string", + "location": "path" + } + }, + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "path": "v1beta1/{+name}:cancel" + }, + "get": { + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "path": "v1beta1/{+name}", + "httpMethod": "GET", + "parameters": { + "name": { + "description": "The name of the operation resource.", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/operations/[^/]+$", + "location": "path" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.metadataStores.operations.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "wait": { + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+name}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "parameters": { + "timeout": { + "format": "google-duration", + "type": "string", + "location": "query", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "type": "string", + "location": "path", + "required": true + } + }, + "id": "aiplatform.projects.locations.metadataStores.operations.wait", + "httpMethod": "POST", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations/{operationsId}:wait" + }, + "delete": { + "parameters": { + "name": { + "type": "string", + "location": "path", + "description": "The name of the operation resource to be deleted.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/operations/[^/]+$" + } + }, + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "parameterOrder": [ + "name" + ], + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.metadataStores.operations.delete", + "httpMethod": "DELETE", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations/{operationsId}" + } + } + }, + "contexts": { + "methods": { + "create": { + "parameterOrder": [ + "parent" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Context" + }, + "parameters": { + "contextId": { + "location": "query", + "type": "string", + "description": "The {context} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`. If not provided, the Context's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Contexts in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Context.)" + }, + "parent": { + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "type": "string", + "description": "Required. The resource name of the MetadataStore where the Context should be created. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`" + } + }, + "httpMethod": "POST", + "id": "aiplatform.projects.locations.metadataStores.contexts.create", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Context" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Creates a Context associated with a MetadataStore.", + "path": "v1beta1/{+parent}/contexts" + }, + "get": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Context" + }, + "id": "aiplatform.projects.locations.metadataStores.contexts.get", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", + "location": "path", + "description": "Required. The resource name of the Context to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", + "type": "string" + } + }, + "description": "Retrieves a specific Context.", + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}", + "path": "v1beta1/{+name}" + }, + "delete": { + "path": "v1beta1/{+name}", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Deletes a stored Context.", + "id": "aiplatform.projects.locations.metadataStores.contexts.delete", + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "force": { + "description": "The force deletion semantics is still undefined. Users should not use this field.", + "type": "boolean", + "location": "query" + }, + "etag": { + "type": "string", + "location": "query", + "description": "Optional. The etag of the Context to delete. If this is provided, it must match the server's etag. Otherwise, the request will fail with a FAILED_PRECONDITION." + }, + "name": { + "description": "Required. The resource name of the Context to delete. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", + "type": "string", + "location": "path", + "required": true + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}" + }, + "queryContextLineageSubgraph": { + "path": "v1beta1/{+context}:queryContextLineageSubgraph", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}:queryContextLineageSubgraph", + "description": "Retrieves Artifacts and Executions within the specified Context, connected by Event edges and returned as a LineageSubgraph.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "context": { + "required": true, + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", + "description": "Required. The resource name of the Context whose Artifacts and Executions should be retrieved as a LineageSubgraph. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}` The request may error with FAILED_PRECONDITION if the number of Artifacts, the number of Executions, or the number of Events that would be returned for the Context exceeds 1000." + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1LineageSubgraph" + }, + "id": "aiplatform.projects.locations.metadataStores.contexts.queryContextLineageSubgraph", + "httpMethod": "GET", + "parameterOrder": [ + "context" + ] + }, + "addContextArtifactsAndExecutions": { + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.metadataStores.contexts.addContextArtifactsAndExecutions", + "path": "v1beta1/{+context}:addContextArtifactsAndExecutions", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1AddContextArtifactsAndExecutionsRequest" + }, + "parameterOrder": [ + "context" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}:addContextArtifactsAndExecutions", + "parameters": { + "context": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", + "type": "string", + "description": "Required. The resource name of the Context that the Artifacts and Executions belong to. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", + "required": true + } + }, + "description": "Adds a set of Artifacts and Executions to a Context. If any of the Artifacts or Executions have already been added to a Context, they are simply skipped.", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1AddContextArtifactsAndExecutionsResponse" + } + }, + "removeContextChildren": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1RemoveContextChildrenRequest" + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1RemoveContextChildrenResponse" + }, + "id": "aiplatform.projects.locations.metadataStores.contexts.removeContextChildren", + "path": "v1beta1/{+context}:removeContextChildren", + "httpMethod": "POST", + "parameters": { + "context": { + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", + "location": "path", + "description": "Required. The resource name of the parent Context. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", + "type": "string", + "required": true + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}:removeContextChildren", + "description": "Remove a set of children contexts from a parent Context. If any of the child Contexts were NOT added to the parent Context, they are simply skipped.", + "parameterOrder": [ + "context" + ] + }, + "patch": { + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.metadataStores.contexts.patch", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Context" + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Context" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}", + "description": "Updates a stored Context.", + "httpMethod": "PATCH", + "parameters": { + "name": { + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", + "type": "string", + "description": "Immutable. The resource name of the Context." + }, + "updateMask": { + "type": "string", + "description": "Optional. A FieldMask indicating which fields should be updated.", + "location": "query", + "format": "google-fieldmask" + }, + "allowMissing": { + "type": "boolean", + "location": "query", + "description": "If set to true, and the Context is not found, a new Context is created." + } + }, + "parameterOrder": [ + "name" + ] + }, + "list": { + "httpMethod": "GET", + "parameterOrder": [ + "parent" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts", + "description": "Lists Contexts on the MetadataStore.", + "parameters": { + "pageToken": { + "type": "string", + "description": "A page token, received from a previous MetadataService.ListContexts call. Provide this to retrieve the subsequent page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with INVALID_ARGUMENT error.)", + "location": "query" + }, + "pageSize": { + "format": "int32", + "type": "integer", + "description": "The maximum number of Contexts to return. The service may return fewer. Must be in range 1-1000, inclusive. Defaults to 100.", + "location": "query" + }, + "filter": { + "type": "string", + "location": "query", + "description": "Filter specifying the boolean condition for the Contexts to satisfy in order to be part of the result set. The syntax to define filter query is based on https://google.aip.dev/160. Following are the supported set of filters: * **Attribute filtering**: For example: `display_name = \"test\"`. Supported fields include: `name`, `display_name`, `schema_title`, `create_time`, and `update_time`. Time fields, such as `create_time` and `update_time`, require values specified in RFC-3339 format. For example: `create_time = \"2020-11-19T11:30:00-04:00\"`. * **Metadata field**: To filter on metadata fields use traversal operation as follows: `metadata..`. For example: `metadata.field_1.number_value = 10.0`. In case the field name contains special characters (such as colon), one can embed it inside double quote. For example: `metadata.\"field:1\".number_value = 10.0` * **Parent Child filtering**: To filter Contexts based on parent-child relationship use the HAS operator as follows: ``` parent_contexts: \"projects//locations//metadataStores//contexts/\" child_contexts: \"projects//locations//metadataStores//contexts/\" ``` Each of the above supported filters can be combined together using logical operators (`AND` & `OR`). Maximum nested expression depth allowed is 5. For example: `display_name = \"test\" AND metadata.field1.bool_value = true`." + }, + "orderBy": { + "description": "How the list of messages is ordered. Specify the values to order by and an ordering operation. The default sorting order is ascending. To specify descending order for a field, users append a \" desc\" suffix; for example: \"foo desc, bar\". Subfields are specified with a `.` character, such as foo.bar. see https://google.aip.dev/132#ordering for more details.", + "location": "query", + "type": "string" + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "description": "Required. The MetadataStore whose Contexts should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", + "required": true, + "type": "string", + "location": "path" + } + }, + "path": "v1beta1/{+parent}/contexts", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListContextsResponse" + }, + "id": "aiplatform.projects.locations.metadataStores.contexts.list" + }, + "purge": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "parent": { + "type": "string", + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "description": "Required. The metadata store to purge Contexts from. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Purges Contexts.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts:purge", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1PurgeContextsRequest" + }, + "path": "v1beta1/{+parent}/contexts:purge", + "id": "aiplatform.projects.locations.metadataStores.contexts.purge", + "parameterOrder": [ + "parent" + ], + "httpMethod": "POST" + }, + "addContextChildren": { + "description": "Adds a set of Contexts as children to a parent Context. If any of the child Contexts have already been added to the parent Context, they are simply skipped. If this call would create a cycle or cause any Context to have more than 10 parents, the request will fail with an INVALID_ARGUMENT error.", + "parameterOrder": [ + "context" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1AddContextChildrenResponse" + }, + "path": "v1beta1/{+context}:addContextChildren", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}:addContextChildren", + "id": "aiplatform.projects.locations.metadataStores.contexts.addContextChildren", + "parameters": { + "context": { + "location": "path", + "description": "Required. The resource name of the parent Context. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", + "required": true, + "type": "string" + } + }, + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1AddContextChildrenRequest" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + } + }, + "resources": { + "operations": { + "methods": { + "list": { + "httpMethod": "GET", + "parameters": { + "name": { + "type": "string", + "required": true, + "description": "The name of the operation's parent resource.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$" + }, + "filter": { + "location": "query", + "type": "string", + "description": "The standard list filter." + }, + "pageSize": { + "format": "int32", + "location": "query", + "type": "integer", + "description": "The standard list page size." + }, + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + } + }, + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}/operations", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "id": "aiplatform.projects.locations.metadataStores.contexts.operations.list", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "wait": { + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "format": "google-duration", + "location": "query", + "type": "string" + }, + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to wait on.", + "type": "string" + } + }, + "httpMethod": "POST", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.metadataStores.contexts.operations.wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+name}:wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." + }, + "delete": { + "httpMethod": "DELETE", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}", + "id": "aiplatform.projects.locations.metadataStores.contexts.operations.delete", + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "type": "string", + "description": "The name of the operation resource to be deleted.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", + "location": "path" + } + }, + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "cancel": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}:cancel", + "path": "v1beta1/{+name}:cancel", + "parameterOrder": [ + "name" + ], + "httpMethod": "POST", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "id": "aiplatform.projects.locations.metadataStores.contexts.operations.cancel", + "parameters": { + "name": { + "type": "string", + "description": "The name of the operation resource to be cancelled.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", + "location": "path" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleProtobufEmpty" + } + }, + "get": { + "id": "aiplatform.projects.locations.metadataStores.contexts.operations.get", + "path": "v1beta1/{+name}", + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}", + "parameters": { + "name": { + "location": "path", + "required": true, + "description": "The name of the operation resource.", + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." + } + } + } + } + }, + "metadataSchemas": { + "methods": { + "create": { + "parameterOrder": [ + "parent" + ], + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Creates a MetadataSchema.", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1MetadataSchema" + }, + "path": "v1beta1/{+parent}/metadataSchemas", + "id": "aiplatform.projects.locations.metadataStores.metadataSchemas.create", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1MetadataSchema" + }, + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "description": "Required. The resource name of the MetadataStore where the MetadataSchema should be created. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", + "required": true, + "type": "string", + "location": "path" + }, + "metadataSchemaId": { + "location": "query", + "type": "string", + "description": "The {metadata_schema} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/metadataSchemas/{metadataschema}` If not provided, the MetadataStore's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all MetadataSchemas in the parent Location. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting MetadataSchema.)" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/metadataSchemas" + }, + "get": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/metadataSchemas/{metadataSchemasId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1MetadataSchema" + }, + "parameters": { + "name": { + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/metadataSchemas/[^/]+$", + "type": "string", + "description": "Required. The resource name of the MetadataSchema to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/metadataSchemas/{metadataschema}`" + } + }, + "description": "Retrieves a specific MetadataSchema.", + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.metadataStores.metadataSchemas.get", + "path": "v1beta1/{+name}" + }, + "list": { + "parameters": { + "filter": { + "location": "query", + "type": "string", + "description": "A query to filter available MetadataSchemas for matching results." + }, + "parent": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "description": "Required. The MetadataStore whose MetadataSchemas should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", + "type": "string", + "location": "path" + }, + "pageToken": { + "type": "string", + "location": "query", + "description": "A page token, received from a previous MetadataService.ListMetadataSchemas call. Provide this to retrieve the next page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with INVALID_ARGUMENT error.)" + }, + "pageSize": { + "location": "query", + "description": "The maximum number of MetadataSchemas to return. The service may return fewer. Must be in range 1-1000, inclusive. Defaults to 100.", + "type": "integer", + "format": "int32" + } + }, + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListMetadataSchemasResponse" + }, + "description": "Lists MetadataSchemas.", + "id": "aiplatform.projects.locations.metadataStores.metadataSchemas.list", + "path": "v1beta1/{+parent}/metadataSchemas", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/metadataSchemas", + "parameterOrder": [ + "parent" + ] + } + } + }, + "executions": { + "resources": { + "operations": { + "methods": { + "get": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "httpMethod": "GET", + "parameters": { + "name": { + "type": "string", + "required": true, + "location": "path", + "description": "The name of the operation resource.", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$" + } + }, + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.metadataStores.executions.operations.get", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}", + "path": "v1beta1/{+name}", + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." + }, + "delete": { + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.metadataStores.executions.operations.delete", + "parameters": { + "name": { + "type": "string", + "description": "The name of the operation resource to be deleted.", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", + "location": "path", + "required": true + } + }, + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "httpMethod": "DELETE", + "path": "v1beta1/{+name}", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "cancel": { + "parameters": { + "name": { + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", + "description": "The name of the operation resource to be cancelled." + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}:cancel", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.metadataStores.executions.operations.cancel", + "httpMethod": "POST", + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}:cancel" + }, + "wait": { + "httpMethod": "POST", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.metadataStores.executions.operations.wait", + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "parameters": { + "timeout": { + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", + "location": "query", + "format": "google-duration", + "type": "string" + }, + "name": { + "type": "string", + "description": "The name of the operation resource to wait on.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", + "location": "path" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}:wait", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+name}:wait", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "list": { + "path": "v1beta1/{+name}/operations", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "name" + ], + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations", + "id": "aiplatform.projects.locations.metadataStores.executions.operations.list", + "parameters": { + "name": { + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", + "location": "path", + "description": "The name of the operation's parent resource." + }, + "pageToken": { + "type": "string", + "description": "The standard list page token.", + "location": "query" + }, + "pageSize": { + "format": "int32", + "type": "integer", + "location": "query", + "description": "The standard list page size." + }, + "filter": { + "type": "string", + "description": "The standard list filter.", + "location": "query" + } + }, + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + } + } + } + } + }, + "methods": { + "addExecutionEvents": { + "id": "aiplatform.projects.locations.metadataStores.executions.addExecutionEvents", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1AddExecutionEventsResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}:addExecutionEvents", + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1AddExecutionEventsRequest" + }, + "path": "v1beta1/{+execution}:addExecutionEvents", + "parameterOrder": [ + "execution" + ], + "parameters": { + "execution": { + "description": "Required. The resource name of the Execution that the Events connect Artifacts with. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`", + "type": "string", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$" + } + }, + "description": "Adds Events to the specified Execution. An Event indicates whether an Artifact was used as an input or output for an Execution. If an Event already exists between the Execution and the Artifact, the Event is skipped." + }, + "patch": { + "id": "aiplatform.projects.locations.metadataStores.executions.patch", + "path": "v1beta1/{+name}", + "httpMethod": "PATCH", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Execution" + }, + "description": "Updates a stored Execution.", + "parameterOrder": [ + "name" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", + "type": "string", + "description": "Output only. The resource name of the Execution.", + "required": true, + "location": "path" + }, + "allowMissing": { + "type": "boolean", + "location": "query", + "description": "If set to true, and the Execution is not found, a new Execution is created." + }, + "updateMask": { + "description": "Optional. A FieldMask indicating which fields should be updated.", + "format": "google-fieldmask", + "location": "query", + "type": "string" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Execution" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "delete": { + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "description": "Deletes an Execution.", + "parameters": { + "etag": { + "location": "query", + "type": "string", + "description": "Optional. The etag of the Execution to delete. If this is provided, it must match the server's etag. Otherwise, the request will fail with a FAILED_PRECONDITION." + }, + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", + "location": "path", + "type": "string", + "description": "Required. The resource name of the Execution to delete. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`" + } + }, + "parameterOrder": [ + "name" + ], + "httpMethod": "DELETE", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}", + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.metadataStores.executions.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "queryExecutionInputsAndOutputs": { + "path": "v1beta1/{+execution}:queryExecutionInputsAndOutputs", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}:queryExecutionInputsAndOutputs", + "httpMethod": "GET", + "parameters": { + "execution": { + "location": "path", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", + "type": "string", + "description": "Required. The resource name of the Execution whose input and output Artifacts should be retrieved as a LineageSubgraph. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`" + } + }, + "response": { + "$ref": "GoogleCloudAiplatformV1beta1LineageSubgraph" + }, + "parameterOrder": [ + "execution" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Obtains the set of input and output Artifacts for this Execution, in the form of LineageSubgraph that also contains the Execution and connecting Events.", + "id": "aiplatform.projects.locations.metadataStores.executions.queryExecutionInputsAndOutputs" + }, + "purge": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions:purge", + "httpMethod": "POST", + "parameterOrder": [ + "parent" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "parent": { + "type": "string", + "description": "Required. The metadata store to purge Executions from. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "required": true, + "location": "path" + } + }, + "path": "v1beta1/{+parent}/executions:purge", + "description": "Purges Executions.", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1PurgeExecutionsRequest" + }, + "id": "aiplatform.projects.locations.metadataStores.executions.purge" + }, + "list": { + "description": "Lists Executions in the MetadataStore.", + "path": "v1beta1/{+parent}/executions", + "parameters": { + "parent": { + "location": "path", + "required": true, + "type": "string", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "description": "Required. The MetadataStore whose Executions should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`" + }, + "pageSize": { + "location": "query", + "description": "The maximum number of Executions to return. The service may return fewer. Must be in range 1-1000, inclusive. Defaults to 100.", + "format": "int32", + "type": "integer" + }, + "pageToken": { + "location": "query", + "description": "A page token, received from a previous MetadataService.ListExecutions call. Provide this to retrieve the subsequent page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with an INVALID_ARGUMENT error.)", + "type": "string" + }, + "filter": { + "location": "query", + "description": "Filter specifying the boolean condition for the Executions to satisfy in order to be part of the result set. The syntax to define filter query is based on https://google.aip.dev/160. Following are the supported set of filters: * **Attribute filtering**: For example: `display_name = \"test\"`. Supported fields include: `name`, `display_name`, `state`, `schema_title`, `create_time`, and `update_time`. Time fields, such as `create_time` and `update_time`, require values specified in RFC-3339 format. For example: `create_time = \"2020-11-19T11:30:00-04:00\"`. * **Metadata field**: To filter on metadata fields use traversal operation as follows: `metadata..` For example: `metadata.field_1.number_value = 10.0` In case the field name contains special characters (such as colon), one can embed it inside double quote. For example: `metadata.\"field:1\".number_value = 10.0` * **Context based filtering**: To filter Executions based on the contexts to which they belong use the function operator with the full resource name: `in_context()`. For example: `in_context(\"projects//locations//metadataStores//contexts/\")` Each of the above supported filters can be combined together using logical operators (`AND` & `OR`). Maximum nested expression depth allowed is 5. For example: `display_name = \"test\" AND metadata.field1.bool_value = true`.", + "type": "string" + }, + "orderBy": { + "description": "How the list of messages is ordered. Specify the values to order by and an ordering operation. The default sorting order is ascending. To specify descending order for a field, users append a \" desc\" suffix; for example: \"foo desc, bar\". Subfields are specified with a `.` character, such as foo.bar. see https://google.aip.dev/132#ordering for more details.", + "location": "query", + "type": "string" + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListExecutionsResponse" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "parent" + ], + "id": "aiplatform.projects.locations.metadataStores.executions.list", + "httpMethod": "GET" + }, + "create": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.metadataStores.executions.create", + "description": "Creates an Execution associated with a MetadataStore.", + "parameterOrder": [ + "parent" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Execution" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Execution" + }, + "parameters": { + "executionId": { + "description": "The {execution} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}` If not provided, the Execution's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Executions in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Execution.)", + "location": "query", + "type": "string" + }, + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "location": "path", + "type": "string", + "required": true, + "description": "Required. The resource name of the MetadataStore where the Execution should be created. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`" + } + }, + "httpMethod": "POST", + "path": "v1beta1/{+parent}/executions", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions" + }, + "get": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Execution" + }, + "description": "Retrieves a specific Execution.", + "id": "aiplatform.projects.locations.metadataStores.executions.get", + "httpMethod": "GET", + "path": "v1beta1/{+name}", + "parameters": { + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", + "location": "path", + "description": "Required. The resource name of the Execution to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`", + "type": "string" + } + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}", + "parameterOrder": [ + "name" + ] + } + } + }, + "artifacts": { + "methods": { + "list": { + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.metadataStores.artifacts.list", + "parameters": { + "filter": { + "type": "string", + "location": "query", + "description": "Filter specifying the boolean condition for the Artifacts to satisfy in order to be part of the result set. The syntax to define filter query is based on https://google.aip.dev/160. The supported set of filters include the following: * **Attribute filtering**: For example: `display_name = \"test\"`. Supported fields include: `name`, `display_name`, `uri`, `state`, `schema_title`, `create_time`, and `update_time`. Time fields, such as `create_time` and `update_time`, require values specified in RFC-3339 format. For example: `create_time = \"2020-11-19T11:30:00-04:00\"` * **Metadata field**: To filter on metadata fields use traversal operation as follows: `metadata..`. For example: `metadata.field_1.number_value = 10.0` In case the field name contains special characters (such as colon), one can embed it inside double quote. For example: `metadata.\"field:1\".number_value = 10.0` * **Context based filtering**: To filter Artifacts based on the contexts to which they belong, use the function operator with the full resource name `in_context()`. For example: `in_context(\"projects//locations//metadataStores//contexts/\")` Each of the above supported filter types can be combined together using logical operators (`AND` & `OR`). Maximum nested expression depth allowed is 5. For example: `display_name = \"test\" AND metadata.field1.bool_value = true`." + }, + "orderBy": { + "type": "string", + "description": "How the list of messages is ordered. Specify the values to order by and an ordering operation. The default sorting order is ascending. To specify descending order for a field, users append a \" desc\" suffix; for example: \"foo desc, bar\". Subfields are specified with a `.` character, such as foo.bar. see https://google.aip.dev/132#ordering for more details.", + "location": "query" + }, + "pageSize": { + "type": "integer", + "format": "int32", + "description": "The maximum number of Artifacts to return. The service may return fewer. Must be in range 1-1000, inclusive. Defaults to 100.", + "location": "query" + }, + "parent": { + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "description": "Required. The MetadataStore whose Artifacts should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", + "type": "string", + "required": true + }, + "pageToken": { + "location": "query", + "description": "A page token, received from a previous MetadataService.ListArtifacts call. Provide this to retrieve the subsequent page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with INVALID_ARGUMENT error.)", + "type": "string" + } + }, + "parameterOrder": [ + "parent" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts", + "path": "v1beta1/{+parent}/artifacts", + "description": "Lists Artifacts in the MetadataStore.", + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1ListArtifactsResponse" + } + }, + "queryArtifactLineageSubgraph": { + "id": "aiplatform.projects.locations.metadataStores.artifacts.queryArtifactLineageSubgraph", + "description": "Retrieves lineage of an Artifact represented through Artifacts and Executions connected by Event edges and returned as a LineageSubgraph.", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}:queryArtifactLineageSubgraph", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudAiplatformV1beta1LineageSubgraph" + }, + "path": "v1beta1/{+artifact}:queryArtifactLineageSubgraph", + "httpMethod": "GET", + "parameterOrder": [ + "artifact" + ], + "parameters": { + "artifact": { + "required": true, + "description": "Required. The resource name of the Artifact whose Lineage needs to be retrieved as a LineageSubgraph. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}` The request may error with FAILED_PRECONDITION if the number of Artifacts, the number of Executions, or the number of Events that would be returned for the Context exceeds 1000.", + "type": "string", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$" + }, + "filter": { + "location": "query", + "description": "Filter specifying the boolean condition for the Artifacts to satisfy in order to be part of the Lineage Subgraph. The syntax to define filter query is based on https://google.aip.dev/160. The supported set of filters include the following: * **Attribute filtering**: For example: `display_name = \"test\"` Supported fields include: `name`, `display_name`, `uri`, `state`, `schema_title`, `create_time`, and `update_time`. Time fields, such as `create_time` and `update_time`, require values specified in RFC-3339 format. For example: `create_time = \"2020-11-19T11:30:00-04:00\"` * **Metadata field**: To filter on metadata fields use traversal operation as follows: `metadata..`. For example: `metadata.field_1.number_value = 10.0` In case the field name contains special characters (such as colon), one can embed it inside double quote. For example: `metadata.\"field:1\".number_value = 10.0` Each of the above supported filter types can be combined together using logical operators (`AND` & `OR`). Maximum nested expression depth allowed is 5. For example: `display_name = \"test\" AND metadata.field1.bool_value = true`.", + "type": "string" + }, + "maxHops": { + "description": "Specifies the size of the lineage graph in terms of number of hops from the specified artifact. Negative Value: INVALID_ARGUMENT error is returned 0: Only input artifact is returned. No value: Transitive closure is performed to return the complete graph.", + "type": "integer", + "format": "int32", + "location": "query" + } + } + }, + "get": { + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Artifact" + }, + "parameterOrder": [ + "name" + ], + "description": "Retrieves a specific Artifact.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "type": "string", + "location": "path", + "required": true, + "description": "Required. The resource name of the Artifact to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$" + } + }, + "path": "v1beta1/{+name}", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}", + "id": "aiplatform.projects.locations.metadataStores.artifacts.get" + }, + "create": { + "id": "aiplatform.projects.locations.metadataStores.artifacts.create", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Artifact" + }, + "parameterOrder": [ + "parent" + ], + "parameters": { + "parent": { + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", + "required": true, + "description": "Required. The resource name of the MetadataStore where the Artifact should be created. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", + "location": "path", + "type": "string" + }, + "artifactId": { + "description": "The {artifact} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}` If not provided, the Artifact's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Artifacts in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Artifact.)", + "location": "query", + "type": "string" + } + }, + "path": "v1beta1/{+parent}/artifacts", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts", + "httpMethod": "POST", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Artifact" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Creates an Artifact associated with a MetadataStore." + }, + "purge": { + "httpMethod": "POST", + "description": "Purges Artifacts.", + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.metadataStores.artifacts.purge", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts:purge", + "parameterOrder": [ + "parent" + ], + "parameters": { + "parent": { + "location": "path", + "type": "string", + "description": "Required. The metadata store to purge Artifacts from. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$" + } + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1PurgeArtifactsRequest" + }, + "path": "v1beta1/{+parent}/artifacts:purge", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ] + }, + "patch": { + "response": { + "$ref": "GoogleCloudAiplatformV1beta1Artifact" + }, + "request": { + "$ref": "GoogleCloudAiplatformV1beta1Artifact" + }, + "httpMethod": "PATCH", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Updates a stored Artifact.", + "parameters": { + "updateMask": { + "location": "query", + "format": "google-fieldmask", + "type": "string", + "description": "Optional. A FieldMask indicating which fields should be updated." + }, + "allowMissing": { + "description": "If set to true, and the Artifact is not found, a new Artifact is created.", + "location": "query", + "type": "boolean" + }, + "name": { + "description": "Output only. The resource name of the Artifact.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$", + "type": "string", + "location": "path" + } + }, + "id": "aiplatform.projects.locations.metadataStores.artifacts.patch", + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}" + }, + "delete": { + "parameters": { + "etag": { + "location": "query", + "type": "string", + "description": "Optional. The etag of the Artifact to delete. If this is provided, it must match the server's etag. Otherwise, the request will fail with a FAILED_PRECONDITION." + }, + "name": { + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$", + "location": "path", + "description": "Required. The resource name of the Artifact to delete. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`", + "type": "string" + } + }, + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "id": "aiplatform.projects.locations.metadataStores.artifacts.delete", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}", + "httpMethod": "DELETE", + "parameterOrder": [ + "name" + ], + "path": "v1beta1/{+name}", + "description": "Deletes an Artifact." + } + }, + "resources": { + "operations": { + "methods": { + "cancel": { + "parameterOrder": [ + "name" + ], + "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.", + "path": "v1beta1/{+name}:cancel", + "httpMethod": "POST", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.cancel", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameters": { + "name": { + "description": "The name of the operation resource to be cancelled.", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", + "type": "string", + "location": "path", + "required": true + } + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}:cancel" + }, + "delete": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.delete", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", + "location": "path", + "required": true, + "description": "The name of the operation resource to be deleted.", + "type": "string" + } + }, + "httpMethod": "DELETE", + "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", + "response": { + "$ref": "GoogleProtobufEmpty" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}" + }, + "wait": { + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}:wait", + "parameters": { + "timeout": { + "type": "string", + "location": "query", + "format": "google-duration", + "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." + }, + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", + "required": true, + "description": "The name of the operation resource to wait on.", + "type": "string", + "location": "path" + } + }, + "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", + "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.wait", + "parameterOrder": [ + "name" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "path": "v1beta1/{+name}:wait", + "httpMethod": "POST" + }, + "list": { + "path": "v1beta1/{+name}/operations", + "httpMethod": "GET", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.list", + "response": { + "$ref": "GoogleLongrunningListOperationsResponse" + }, + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations", + "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", + "parameterOrder": [ + "name" + ], + "parameters": { + "pageToken": { + "description": "The standard list page token.", + "type": "string", + "location": "query" + }, + "pageSize": { + "location": "query", + "description": "The standard list page size.", + "format": "int32", + "type": "integer" + }, + "name": { + "description": "The name of the operation's parent resource.", + "location": "path", + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$", + "type": "string", + "required": true + }, + "filter": { + "description": "The standard list filter.", + "type": "string", + "location": "query" + } + } + }, + "get": { + "parameterOrder": [ + "name" + ], + "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleLongrunningOperation" + }, + "path": "v1beta1/{+name}", + "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.get", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}", + "httpMethod": "GET", + "parameters": { + "name": { + "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", + "required": true, + "location": "path", + "description": "The name of the operation resource.", + "type": "string" + } + } + } + } + } + } + } + } + } + }, + "methods": { + "retrieveContexts": { + "request": { + "$ref": "GoogleCloudAiplatformV1beta1RetrieveContextsRequest" + }, + "httpMethod": "POST", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "id": "aiplatform.projects.locations.retrieveContexts", + "description": "Retrieves relevant contexts for a query.", + "parameters": { + "parent": { + "type": "string", + "location": "path", + "description": "Required. The resource name of the Location from which to retrieve RagContexts. The users must have permission to make a call in the project. Format: `projects/{project}/locations/{location}`.", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$" + } + }, + "parameterOrder": [ + "parent" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}:retrieveContexts", + "path": "v1beta1/{+parent}:retrieveContexts", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1RetrieveContextsResponse" + } + }, + "list": { + "id": "aiplatform.projects.locations.list", + "parameters": { + "pageSize": { + "type": "integer", + "format": "int32", + "description": "The maximum number of results to return. If not set, the service selects a default.", + "location": "query" + }, + "filter": { + "location": "query", + "type": "string", + "description": "A filter to narrow down results to a preferred subset. The filtering language accepts strings like `\"displayName=tokyo\"`, and is documented in more detail in [AIP-160](https://google.aip.dev/160)." + }, + "pageToken": { + "type": "string", + "description": "A page token received from the `next_page_token` field in the response. Send that page token to receive the subsequent page.", + "location": "query" + }, + "name": { + "location": "path", + "description": "The resource that owns the locations collection, if applicable.", + "type": "string", + "pattern": "^projects/[^/]+$", + "required": true + } + }, + "description": "Lists information about the supported locations for this service.", + "httpMethod": "GET", + "parameterOrder": [ + "name" + ], + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudLocationListLocationsResponse" + }, + "path": "v1beta1/{+name}/locations", + "flatPath": "v1beta1/projects/{projectsId}/locations" + }, + "get": { + "httpMethod": "GET", + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}", + "parameterOrder": [ + "name" + ], + "id": "aiplatform.projects.locations.get", + "parameters": { + "name": { + "location": "path", + "description": "Resource name for the location.", + "pattern": "^projects/[^/]+/locations/[^/]+$", + "required": true, + "type": "string" + } + }, + "description": "Gets information about a location.", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "response": { + "$ref": "GoogleCloudLocationLocation" + }, + "path": "v1beta1/{+name}" + }, + "evaluateInstances": { + "description": "Evaluates instances based on a given metric.", + "httpMethod": "POST", + "id": "aiplatform.projects.locations.evaluateInstances", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1EvaluateInstancesResponse" + }, + "parameters": { + "location": { + "location": "path", + "type": "string", + "required": true, + "pattern": "^projects/[^/]+/locations/[^/]+$", + "description": "Required. The resource name of the Location to evaluate the instances. Format: `projects/{project}/locations/{location}`" + } + }, + "path": "v1beta1/{+location}:evaluateInstances", + "request": { + "$ref": "GoogleCloudAiplatformV1beta1EvaluateInstancesRequest" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "parameterOrder": [ + "location" + ], + "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}:evaluateInstances" + } + } + } + }, + "methods": { + "getCacheConfig": { + "flatPath": "v1beta1/projects/{projectsId}/cacheConfig", + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Gets a GenAI cache config.", + "path": "v1beta1/{+name}", + "httpMethod": "GET", + "response": { + "$ref": "GoogleCloudAiplatformV1beta1CacheConfig" + }, + "parameterOrder": [ + "name" + ], + "parameters": { + "name": { + "description": "Required. Name of the cache config. Format: - `projects/{project}/cacheConfig`.", + "type": "string", + "required": true, + "location": "path", + "pattern": "^projects/[^/]+/cacheConfig$" + } + }, + "id": "aiplatform.projects.getCacheConfig" + }, + "updateCacheConfig": { + "parameters": { + "name": { + "pattern": "^projects/[^/]+/cacheConfig$", + "type": "string", + "description": "Identifier. Name of the cache config. Format: - `projects/{project}/cacheConfig`.", + "location": "path", + "required": true + } + }, + "path": "v1beta1/{+name}", + "httpMethod": "PATCH", + "id": "aiplatform.projects.updateCacheConfig", + "flatPath": "v1beta1/projects/{projectsId}/cacheConfig", + "parameterOrder": [ + "name" + ], + "request": { + "$ref": "GoogleCloudAiplatformV1beta1CacheConfig" + }, + "scopes": [ + "https://www.googleapis.com/auth/cloud-platform" + ], + "description": "Updates a cache config.", + "response": { + "$ref": "GoogleLongrunningOperation" + } + } + } + } + }, + "batchPath": "batch", + "basePath": "", + "description": "Train high-quality custom machine learning models with minimal machine learning expertise and effort.", + "rootUrl": "https://aiplatform.googleapis.com/", + "ownerName": "Google", + "version_module": true, + "auth": { + "oauth2": { + "scopes": { + "https://www.googleapis.com/auth/cloud-platform": { + "description": "See, edit, configure, and delete your Google Cloud data and see the email address for your Google Account." + }, + "https://www.googleapis.com/auth/cloud-platform.read-only": { + "description": "View your data across Google Cloud services and see the email address of your Google Account" + } + } + } + }, + "mtlsRootUrl": "https://aiplatform.mtls.googleapis.com/", + "endpoints": [ + { + "description": "Locational Endpoint", + "endpointUrl": "https://africa-south1-aiplatform.googleapis.com/", + "location": "africa-south1" + }, + { + "location": "asia-east1", + "description": "Locational Endpoint", + "endpointUrl": "https://asia-east1-aiplatform.googleapis.com/" + }, + { + "endpointUrl": "https://asia-east2-aiplatform.googleapis.com/", + "location": "asia-east2", + "description": "Locational Endpoint" + }, + { + "location": "asia-northeast1", + "description": "Locational Endpoint", + "endpointUrl": "https://asia-northeast1-aiplatform.googleapis.com/" + }, + { + "description": "Locational Endpoint", + "endpointUrl": "https://asia-northeast2-aiplatform.googleapis.com/", + "location": "asia-northeast2" + }, + { + "location": "asia-northeast3", + "description": "Locational Endpoint", + "endpointUrl": "https://asia-northeast3-aiplatform.googleapis.com/" + }, + { + "description": "Locational Endpoint", + "endpointUrl": "https://asia-south1-aiplatform.googleapis.com/", + "location": "asia-south1" + }, + { + "location": "asia-southeast1", + "endpointUrl": "https://asia-southeast1-aiplatform.googleapis.com/", + "description": "Locational Endpoint" + }, + { + "description": "Locational Endpoint", + "endpointUrl": "https://asia-southeast2-aiplatform.googleapis.com/", + "location": "asia-southeast2" + }, + { + "endpointUrl": "https://australia-southeast1-aiplatform.googleapis.com/", + "location": "australia-southeast1", + "description": "Locational Endpoint" + }, + { + "description": "Locational Endpoint", + "endpointUrl": "https://australia-southeast2-aiplatform.googleapis.com/", + "location": "australia-southeast2" + }, + { + "location": "europe-central2", + "description": "Locational Endpoint", + "endpointUrl": "https://europe-central2-aiplatform.googleapis.com/" + }, + { + "endpointUrl": "https://europe-north1-aiplatform.googleapis.com/", + "description": "Locational Endpoint", + "location": "europe-north1" + }, + { + "description": "Locational Endpoint", + "endpointUrl": "https://europe-southwest1-aiplatform.googleapis.com/", + "location": "europe-southwest1" + }, + { + "description": "Locational Endpoint", + "endpointUrl": "https://europe-west1-aiplatform.googleapis.com/", + "location": "europe-west1" + }, + { + "description": "Locational Endpoint", + "endpointUrl": "https://europe-west2-aiplatform.googleapis.com/", + "location": "europe-west2" + }, + { + "location": "europe-west3", + "description": "Locational Endpoint", + "endpointUrl": "https://europe-west3-aiplatform.googleapis.com/" + }, + { + "location": "europe-west4", + "endpointUrl": "https://europe-west4-aiplatform.googleapis.com/", + "description": "Locational Endpoint" + }, + { + "description": "Locational Endpoint", + "endpointUrl": "https://europe-west6-aiplatform.googleapis.com/", + "location": "europe-west6" + }, + { + "location": "europe-west8", + "endpointUrl": "https://europe-west8-aiplatform.googleapis.com/", + "description": "Locational Endpoint" + }, + { + "location": "europe-west9", + "endpointUrl": "https://europe-west9-aiplatform.googleapis.com/", + "description": "Locational Endpoint" + }, + { + "location": "europe-west12", + "description": "Locational Endpoint", + "endpointUrl": "https://europe-west12-aiplatform.googleapis.com/" + }, + { + "location": "me-central1", + "description": "Locational Endpoint", + "endpointUrl": "https://me-central1-aiplatform.googleapis.com/" + }, + { + "location": "me-central2", + "endpointUrl": "https://me-central2-aiplatform.googleapis.com/", + "description": "Locational Endpoint" + }, + { + "location": "me-west1", + "description": "Locational Endpoint", + "endpointUrl": "https://me-west1-aiplatform.googleapis.com/" + }, + { + "endpointUrl": "https://northamerica-northeast1-aiplatform.googleapis.com/", + "location": "northamerica-northeast1", + "description": "Locational Endpoint" + }, + { + "location": "northamerica-northeast2", + "description": "Locational Endpoint", + "endpointUrl": "https://northamerica-northeast2-aiplatform.googleapis.com/" + }, + { + "location": "southamerica-east1", + "endpointUrl": "https://southamerica-east1-aiplatform.googleapis.com/", + "description": "Locational Endpoint" + }, + { + "endpointUrl": "https://southamerica-west1-aiplatform.googleapis.com/", + "description": "Locational Endpoint", + "location": "southamerica-west1" + }, + { + "endpointUrl": "https://us-central1-aiplatform.googleapis.com/", + "description": "Locational Endpoint", + "location": "us-central1" + }, + { + "location": "us-central2", + "description": "Locational Endpoint", + "endpointUrl": "https://us-central2-aiplatform.googleapis.com/" + }, + { + "location": "us-east1", + "description": "Locational Endpoint", + "endpointUrl": "https://us-east1-aiplatform.googleapis.com/" + }, + { + "location": "us-east4", + "description": "Locational Endpoint", + "endpointUrl": "https://us-east4-aiplatform.googleapis.com/" + }, + { + "description": "Locational Endpoint", + "location": "us-south1", + "endpointUrl": "https://us-south1-aiplatform.googleapis.com/" + }, + { + "location": "us-west1", + "description": "Locational Endpoint", + "endpointUrl": "https://us-west1-aiplatform.googleapis.com/" + }, + { + "location": "us-west2", + "endpointUrl": "https://us-west2-aiplatform.googleapis.com/", + "description": "Locational Endpoint" + }, + { + "endpointUrl": "https://us-west3-aiplatform.googleapis.com/", + "description": "Locational Endpoint", + "location": "us-west3" + }, + { + "endpointUrl": "https://us-west4-aiplatform.googleapis.com/", + "description": "Locational Endpoint", + "location": "us-west4" + }, + { + "endpointUrl": "https://us-east5-aiplatform.googleapis.com/", + "location": "us-east5", + "description": "Locational Endpoint" + } + ], + "title": "Vertex AI API" +} diff --git a/etc/api/api-list.yaml b/etc/api/api-list.yaml index eb1e743cf2..5eadfd8f66 100644 --- a/etc/api/api-list.yaml +++ b/etc/api/api-list.yaml @@ -32,6 +32,9 @@ api: - v2 adsensehost: - v4.1 + aiplatform: + - v1 + - v1beta1 alertcenter: - v1beta1 analytics: