Cleanup for v1.0.8 (#483)

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "ontogpt"
-version = "1.0.7"
+version = "1.0.8"
 description = "OntoGPT"
 authors = ["Chris Mungall <[email protected]>", "J. Harry Caufield <[email protected]>"]
 license = "BSD-3"

src/ontogpt/evaluation/resolver.py

@@ -6,8 +6,8 @@
 
 from ontogpt.evaluation.ctd.eval_ctd import EvalCTD
 from ontogpt.evaluation.ctd.eval_ctd_ner import EvalCTDNER
-from ontogpt.evaluation.maxo.eval_maxo import EvalMAXO
 from ontogpt.evaluation.evaluation_engine import SPIRESEvaluationEngine
+from ontogpt.evaluation.maxo.eval_maxo import EvalMAXO
 
 resolver = ClassResolver([EvalCTD, EvalCTDNER, EvalMAXO], base=SPIRESEvaluationEngine)
 

src/ontogpt/utils/clinical_cases.py

@@ -1,4 +1,14 @@
-"""Utilities for working with clinical case reports."""
+"""Utilities for working with clinical case reports.
+
+The prompt in get_kanjee_prompt() is that used by
+the following citation:
+    Kanjee Z, Crowe B, Rodman A. Accuracy of a
+    generative artificial intelligence model in
+    a complex diagnostic challenge. JAMA.
+    2023 Jul 3;330(1):78–80.
+    http://dx.doi.org/10.1001/jama.2023.8288
+    PMCID: PMC10273128
+"""
 
 def get_kanjee_prompt() -> str:
     """Prompt from Kanjee et al. 2023."""

src/ontogpt/webapp/main.py

@@ -1,4 +1,33 @@
-"""Webapp main function."""
+"""OntoGPT Webapp main function.
+
+This module sets up a FastAPI web application for
+the OntoGPT project. It includes routes for handling
+GET and POST requests, and integrates with components
+such as SPIRESEngine and HTMLExporter to process and
+display data.
+
+Classes:
+    Query: A Pydantic model representing the structure
+    of the form data.
+
+Functions:
+    get_engine(datamodel: str, llm_model: str) -> SPIRESEngine:
+        Retrieves or initializes a SPIRESEngine instance for
+        the given datamodel and LLM model.
+
+    read_root(request: Request) -> TemplateResponse:
+        Handles GET requests to the root URL,
+        rendering the form.html template.
+
+    form_post(request: Request, datamodel: str = Form(...),
+        text: str = Form(...), llm_model: str = Form(...))
+        -> TemplateResponse:
+        Handles POST requests to the root URL, processing
+        the form data and rendering the results.html template.
+
+    start():
+        Launches the FastAPI application using Uvicorn.
+"""
 
 from io import StringIO
 from pathlib import Path