Akiba So
fc468464b2
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.
52 lines
1.3 KiB
YAML
52 lines
1.3 KiB
YAML
version: '3.8'
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services:
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mlflow:
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image: ghcr.io/mlflow/mlflow:latest
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container_name: wuhan_mlflow
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ports:
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- "5000:5000"
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environment:
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- MLFLOW_TRACKING_URI=postgresql://postgres:postgres@postgis:5432/mlflow
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- AWS_ACCESS_KEY_ID=${AWS_ACCESS_KEY_ID:-minio}
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- AWS_SECRET_ACCESS_KEY=${AWS_SECRET_ACCESS_KEY:-minio123}
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- AWS_DEFAULT_REGION=us-east-1
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- MLFLOW_S3_ENDPOINT_URL=http://minio:9000
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volumes:
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- mlflow_artifacts:/mlflow/artifacts
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depends_on:
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postgis:
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condition: service_healthy
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command: >
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mlflow server
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--backend-store-uri postgresql://postgres:postgres@postgis:5432/mlflow
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--default-artifact-root s3://mlflow/
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--host 0.0.0.0
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--port 5000
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healthcheck:
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test: ["CMD", "curl", "-f", "http://localhost:5000/"]
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interval: 30s
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timeout: 10s
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retries: 3
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postgis:
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image: postgis/postgis:15-3.3
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container_name: wuhan_postgis
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environment:
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- POSTGRES_DB=mlflow
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- POSTGRES_USER=postgres
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- POSTGRES_PASSWORD=postgres
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ports:
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- "5432:5432"
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volumes:
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- postgis_data:/var/lib/postgresql/data
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healthcheck:
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test: ["CMD-SHELL", "pg_isready -U postgres"]
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interval: 10s
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timeout: 5s
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retries: 5
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volumes:
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mlflow_artifacts:
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postgis_data:
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