93 lines
2.7 KiB
Markdown
93 lines
2.7 KiB
Markdown
# Dependency Policy
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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.
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## Approved backend core
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- FastAPI
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- Uvicorn
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- Pydantic
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- SQLAlchemy
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- Alembic
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- GeoAlchemy2
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- psycopg
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- python-multipart
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- RDFLib for standards-compliant parsing of bounded official RDF/DCAT source
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catalogues. It is pure Python and does not fetch provider distributions.
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## Approved GIS/remote-sensing
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- GeoPandas
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- Shapely
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- PyProj
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- Rasterio
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- GDAL where available
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- Fiona or pyogrio where needed
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- NumPy
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- OpenCV when needed for image processing
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## Docker GIS runtime
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The backend Docker image may install the approved `gis` optional dependency
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group so the deployed workbench has real raster/vector runtime capability:
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- rasterio
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- numpy
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- pillow
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- geopandas
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- pyogrio
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The Docker image may also install GDAL, GEOS and PROJ system packages required
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by those GIS libraries. This does not enable new product behavior by itself; it
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only allows existing raster/vector endpoints to run when requested.
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AI dependencies remain separate in the `ai` optional dependency group and must
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not be installed by the default Docker backend image unless an explicit AI image
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or profile is introduced later.
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The opt-in Unraid all-in-one AI build is NVIDIA-GPU-oriented. It installs the
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pinned PyTorch/torchvision pair from the CUDA 13.0 wheel index before installing
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the `ai` extra. The production runtime exposes the NVIDIA device, selects
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`YOLO_DEVICE=cuda:0` and sets `YOLO_REQUIRE_CUDA=true`, so missing CUDA fails
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closed instead of silently falling back to CPU. The index and versions remain
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explicit Docker build arguments and require live driver/runtime validation on
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Tower before release promotion.
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Docker dependency metadata is copied before application source. Backend source
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changes therefore reuse the dependency layer while changes to `pyproject.toml`
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still invalidate it correctly. Runtime GIS and YOLO import/preflight smokes run
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after the complete backend source is copied.
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## Approved AI
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- PyTorch
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- Ultralytics
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- Segment Anything only after detection foundation works
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## Approved frontend
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- React
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- TypeScript
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- Vite
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- MapLibre GL
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- Deck.gl
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- TanStack Query
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- Zustand or React context for local UI state
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- Recharts for charts
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## Add-dependency rule
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Before adding a dependency:
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1. Explain why existing dependencies are insufficient.
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2. Add it to this document.
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3. Add setup notes if it has native/system requirements.
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4. Ensure Docker build still works.
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## Avoid in V1
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- Heavy MLOps platforms.
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- User auth frameworks.
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- Full workflow orchestration stacks beyond simple queueing.
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- Unnecessary UI component mega-libraries.
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