1.8 KiB
Dependency Policy
GeoIntel deliberately uses technologies matching the GeoAI Engineer profile. Dependencies must support the core goal: geospatial processing, remote sensing, AI inference, QA/QC, and professional frontend visualization.
Approved backend core
- FastAPI
- Uvicorn
- Pydantic
- SQLAlchemy
- Alembic
- GeoAlchemy2
- psycopg
- python-multipart
Approved GIS/remote-sensing
- GeoPandas
- Shapely
- PyProj
- Rasterio
- GDAL where available
- Fiona or pyogrio where needed
- NumPy
- OpenCV when needed for image processing
Docker GIS runtime
The backend Docker image may install the approved gis optional dependency
group so the deployed workbench has real raster/vector runtime capability:
- rasterio
- numpy
- pillow
- geopandas
- pyogrio
The Docker image may also install GDAL, GEOS and PROJ system packages required by those GIS libraries. This does not enable new product behavior by itself; it only allows existing raster/vector endpoints to run when requested.
AI dependencies remain separate in the ai optional dependency group and must
not be installed by the default Docker backend image unless an explicit AI image
or profile is introduced later.
Approved AI
- PyTorch
- Ultralytics
- Segment Anything only after detection foundation works
Approved frontend
- React
- TypeScript
- Vite
- MapLibre GL
- Deck.gl
- TanStack Query
- Zustand or React context for local UI state
- Recharts for charts
Add-dependency rule
Before adding a dependency:
- Explain why existing dependencies are insufficient.
- Add it to this document.
- Add setup notes if it has native/system requirements.
- Ensure Docker build still works.
Avoid in V1
- Heavy MLOps platforms.
- User auth frameworks.
- Full workflow orchestration stacks beyond simple queueing.
- Unnecessary UI component mega-libraries.