README.md

metadata

license: mit
sdk: gradio
colorFrom: yellow
colorTo: green
sdk_version: 6.0.2

Sundew Health Backend

Neurosymbolic, energy-aware ECG monitoring backend using FastAPI, PyTorch, and PostgreSQL.

Quickstart

1. Create a .env from .env.example and set DATABASE_URL.
2. Install dependencies (CPU PyTorch wheels): pip install -e . --extra-index-url https://download.pytorch.org/whl/cpu.
3. Run the API: uvicorn app.main:app --reload.

Database (PostgreSQL + Alembic)

• Set DATABASE_URL to your Postgres DSN (e.g., postgresql+asyncpg://user:pass@localhost:5432/sundew_health).
• Run migrations: alembic upgrade head.
• Create new migrations: alembic revision -m "message" --autogenerate.

Tests

Run pytest to execute the test suite.

Notes

• Gating uses sundew-algorithms (significance + hysteresis) ahead of model inference.
• Adaptive Sparse Training (adaptive-sparse-training) is installed; torch shims are applied to load it, but training still uses the simpler loop until AST wiring is added.