greenproof-ml / requirements.txt
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Generate advice automatically when a check-in is scored
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# Pinned loosely — Hugging Face Spaces rebuilds on push and a surprise major
# version on pitch week is not a risk worth taking for a few KB of convenience.
fastapi>=0.115,<1
uvicorn[standard]>=0.32,<1
pydantic>=2.9,<3
# onnxruntime, NOT torch. Torch pulls ~2 GB and would make cold starts on the
# free Spaces tier unusable. Torch stays a dev-only dependency for the spike.
onnxruntime>=1.19,<2
huggingface_hub>=0.26,<1
numpy>=1.26,<3
pillow>=10.4,<12
# contrib, not plain opencv — cv2.aruco lives in contrib and the ArUco marker is
# how a photo becomes a measurement in millimetres.
opencv-contrib-python-headless>=4.10,<5
supabase>=2.9,<3
httpx>=0.27,<1
# Advisory layer only: species identification and care advice for the planter.
# NOT on the scoring path - pipeline.py never imports the advisor, so a slow or
# failed API call cannot affect a verdict.
#
# TWO PROVIDERS, picked at runtime from whichever key is set. Gemini is the
# default because its free tier costs nothing; Anthropic stays available because
# free tiers have closed under this project three times already and a second
# provider is the cheapest insurance against a fourth.
google-genai>=1.0
anthropic>=0.40