README.md

🌿 Sundew Diabetes Watch (Hugging Face Space: Docker + Streamlit)

Mission: Low-cost, energy-aware diabetes risk monitoring for everyone — especially communities across Africa. This app uses the Sundew selective-activation algorithm to run heavier models only when needed, saving compute and making always-on monitoring practical on affordable hardware.

How it works

• Upload a CSV with columns: timestamp, glucose_mgdl, carbs_g, insulin_units, steps, hr (optional extras allowed).
• A lightweight risk score runs on each event.
• Sundew decides when to open the gate and run a heavier model for near-term risk.
• You control the target activation rate to meet power/latency budgets.

Disclaimer: Research prototype. Not medical advice.

Developing locally

python -m venv .venv && source .venv/bin/activate  # Windows: .venv\Scripts\activate
pip install -r requirements.txt
streamlit run app.py

Deploying as a Hugging Face Space (Docker)

• Create a new Docker Space and push these files.
• The Dockerfile exposes port 7860 and launches streamlit run app.py.