Cleanup

api/pyproject.toml

@@ -26,7 +26,12 @@ requires = ["hatchling"]
 build-backend = "hatchling.build"
 
 [tool.uv]
-dev-dependencies = ["app", "mypy>=1.15.0", "pytest>=8.3.4", "ruff>=0.9.6"]
+dev-dependencies = [
+    "app",
+ "mypy>=1.15.0",
+ "pytest>=8.3.4",
+ "ruff>=0.9.6",
+]
 
 [tool.uv.sources]
 app = { workspace = true }

api/src/app/config/config.py

@@ -11,6 +11,7 @@ class Settings(BaseSettings):
     """Global configuration for the application."""
 
     model_config = SettingsConfigDict(env_file=".env")
+
     auth_token: str
     tiff_path: str
     grid_tiles_path: str
@@ -21,4 +22,4 @@ class Settings(BaseSettings):
 @lru_cache
 def get_settings() -> Settings:
     """Return the global configuration."""
-    return Settings()
+    return Settings()  # type: ignore

api/src/app/main.py

@@ -25,16 +25,18 @@ def path_params(raster_filename: Annotated[str, Query(description="Raster filena
 
 # Use ORJSONResponse to handle serialization of NaN values. Normal Json fails to serialize NaN values.
 app = FastAPI(title="Amazonia360 API", default_response_class=ORJSONResponse)
+
 app.add_middleware(CORSMiddleware, allow_origins=["*"], allow_methods=["*"], allow_headers=["*"])
 
 tiler_routes = ZonalTilerFactory(path_dependency=path_params)
 
 app.include_router(tiler_routes.router, tags=["Raster"], dependencies=[Depends(verify_token)])
 app.include_router(grid_router, prefix="/grid", tags=["Grid"], dependencies=[Depends(verify_token)])
-app.include_router(ai_router, prefix="/ai", tags=["LLMs"], dependencies=[Depends(verify_token)])
-
+app.include_router(ai_router, prefix="/ai", tags=["Text Generation"], dependencies=[Depends(verify_token)])
 add_exception_handlers(app, DEFAULT_STATUS_CODES)
 
+_ = get_settings()  # load settings at startup to check for issues
+
 
 @app.get("/tifs", tags=["Raster"], dependencies=[Depends(verify_token)])
 async def list_files():

api/src/app/openai_service.py

@@ -1,11 +1,11 @@
 import json
 
-from openai import OpenAI
+from openai import OpenAI, OpenAIError
 
 from app.config.config import get_settings
 
 
-def generate_description(context_data: dict, description_type: str, language: str) -> dict[str, str] | str:
+def generate_description(context_data: dict, description_type: str, language: str) -> str:
     """
     Generate a description using OpenAI's Chat Completions API based on context data, a
     description type, and the desired language.
@@ -50,24 +50,16 @@ def generate_description(context_data: dict, description_type: str, language: st
     # Initialize the OpenAI client
     client = OpenAI(api_key=get_settings().openai_token.get_secret_value())
 
-    try:
-        # Make the API call
-        completion = client.chat.completions.create(
-            model="gpt-4o",
-            messages=[system_message, user_message],
-            max_tokens=1024,
-            temperature=0.7,
-        )
-    except Exception as e:
-        # Handle API errors
-        return {"error": f"API request failed: {str(e)}"}
+    # Make the API call
+    completion = client.chat.completions.create(
+        model="gpt-4o",
+        messages=[system_message, user_message],  # type: ignore
+        max_tokens=1024,
+        temperature=0.7,
+    )
 
     # Extract and validate the response content
     if not completion or not completion.choices[0] or not completion.choices[0].message.content:
-        return {"error": "API response was empty or invalid."}
-
+        raise OpenAIError("OpenAI API response was empty or invalid")
     description = completion.choices[0].message.content.strip()
-    if not description:
-        return {"error": "Description generation failed."}
-
     return description

api/src/app/routers/text_generation.py

@@ -14,10 +14,14 @@ class Context(BaseModel):
     description_type: Literal["Short", "Normal", "Long"] = "Normal"
 
 
+class DescritionResponse(BaseModel):
+    description: str
+
+
 @router.post("/")
 def generate_description_text(
     context: Context,
-):
+) -> DescritionResponse:
     """Generate a description based on context data and audience profile."""
     description = generate_description(context.data, context.description_type, context.language)
-    return {"description": description}
+    return DescritionResponse(description=description)

api/tests/conftest.py

@@ -1,5 +1,6 @@
 import json
 import os
+from collections.abc import Generator
 from pathlib import Path
 
 import numpy as np
@@ -81,7 +82,7 @@ def geojson() -> str:
 
 
 @pytest.fixture()
-def grid_dataset(setup_data_folder) -> str:
+def grid_dataset(setup_data_folder) -> Generator[str]:
     """Create an empty binary file to be used as grid dataset stub
     for a level 0 tile. like:
            data
@@ -146,7 +147,7 @@ def tif_file(setup_data_folder):
     The bbox is BoundingBox(left=0.0, bottom=7.0, right=3.0, top=10.0)
     """
     data = np.array([[0, 1, 0], [1, 9, 1], [0, 1, 0]])
-    transform = rasterio.transform.from_origin(0, 10, 1, 1)
+    transform = rasterio.transform.from_origin(0, 10, 1, 1)  # pyright: ignore
     with rasterio.open(
         f"{get_settings().tiff_path}/raster.tif",
         "w",