Add 3 new data-driven insight cards (daily cases, district risk
comparison, weather impact) with real parquet data. Fix season
card to use current date instead of data date. Expand to 11 cards.
Add POST /api/chat endpoint proxying to ai.2890.ltd with JWT auth.
Create ChatBot frontend component with collapsible chat panel,
message bubbles, and auto-scroll. Chat API key stored in .env only.
Clean up duplicate typing imports in insights.py, export cachedPost.
Context: Build a spatial risk assessment system correlating air quality
data with children's respiratory disease incidence across Wuhan.
Approach: FastAPI backend serving PostGIS spatial queries, React
frontend with Deck.gl maps, and a PyTorch SpatialTemporalGCN pipeline
for multi-day (1d/3d/7d) risk prediction.
Changes:
- backend/ — FastAPI API with auth (JWT), alerts, risk analysis,
geocoded case data, grid statistics, and report endpoints
- frontend/ — React dashboard with interactive risk maps, alert
monitoring, district comparison charts, and timeline player
- models/ — SpatialTemporalGCN model with trained weights and ONNX
export for inference
- scripts/ — ETL pipeline for weather + medical data, grid generation,
feature engineering, training, and daily inference
- deploy/ — Docker Compose configs for backend, frontend, and MLflow
- docs/ — API docs, deployment guide, user guide, and code review
Impact: Enables spatial risk visualization, alert monitoring, and
ML-driven health risk forecasting for environmental health teams.
