commit fb6c4d5

Author: Jacopo Chevallard <[email protected]>
Date:   Wed Oct 9 12:06:23 2024 +0200

    feat: starting reorganizing modules for simpler maintenance and readability

examples/chatbot/README.md

@@ -8,12 +8,12 @@ This example demonstrates how to create a simple chatbot using Quivr and Chainli
 
 ## Installation
 
-1. Clone the repository or navigate to the `core/examples/chatbot` directory.
+1. Clone the repository or navigate to the `backend/core/examples/chatbot` directory.
 
 2. Install the required dependencies:
 
    ```
-   pip install -r requirements.lock
+   pip install -r requirements.txt
    ```
 
 ## Running the Chatbot

examples/chatbot/requirements.txt

@@ -0,0 +1,2 @@
+quivr-core[base]==0.0.8
+chainlit==1.1.306

examples/pdf_document_from_yaml.py

@@ -5,7 +5,7 @@
 
 import dotenv
 from quivr_core import Brain
-from quivr_core.config import AssistantConfig
+from quivr_core.rag.entities.config import AssistantConfig
 from rich.traceback import install as rich_install
 
 ConsoleOutputHandler = logging.StreamHandler()

examples/pdf_parsing_tika.py

@@ -1,7 +1,7 @@
 from langchain_core.embeddings import DeterministicFakeEmbedding
 from langchain_core.language_models import FakeListChatModel
 from quivr_core import Brain
-from quivr_core.config import LLMEndpointConfig
+from quivr_core.rag.entities.config import LLMEndpointConfig
 from quivr_core.llm.llm_endpoint import LLMEndpoint
 from rich.console import Console
 from rich.panel import Panel

examples/simple_question.py

@@ -0,0 +1,20 @@
+import tempfile
+
+from quivr_core import Brain
+from quivr_core.rag.quivr_rag_langgraph import QuivrQARAGLangGraph
+
+
+if __name__ == "__main__":
+    with tempfile.NamedTemporaryFile(mode="w", suffix=".txt") as temp_file:
+        temp_file.write("Gold is a liquid of blue-like colour.")
+        temp_file.flush()
+
+        brain = Brain.from_files(
+            name="test_brain",
+            file_paths=[temp_file.name],
+        )
+
+        answer = brain.ask(
+            "what is gold? asnwer in french", rag_pipeline=QuivrQARAGLangGraph
+        )
+        print("answer QuivrQARAGLangGraph :", answer.answer)

examples/simple_question_streaming.py

@@ -4,7 +4,7 @@
 from dotenv import load_dotenv
 from quivr_core import Brain
 from quivr_core.quivr_rag import QuivrQARAG
-from quivr_core.quivr_rag_langgraph import QuivrQARAGLangGraph
+from quivr_core.rag.quivr_rag_langgraph import QuivrQARAGLangGraph
 
 
 async def main():