docker-compose.yml

version: '3.8'

services:
  api:
    build: .
    container_name: cbsl-forecaster-api
    ports:
      - "8000:8000"
    restart: unless-stopped
    environment:
      - MLFLOW_TRACKING_URI=${MLFLOW_TRACKING_URI:-file:./mlruns}
      - DAGSHUB_USER_TOKEN=${DAGSHUB_USER_TOKEN:-}
    volumes:
      # Map data and mlruns so the API can access new data/models without rebuilding
      - ./data:/app/data
      - ./mlruns:/app/mlruns

  dashboard:
    build: .
    container_name: cbsl-forecaster-dashboard
    command: streamlit run src/models/dashboard.py --server.port 8501 --server.address 0.0.0.0
    ports:
      - "8501:8501"
    environment:
      - API_URL=http://api:8000
    depends_on:
      - api
    restart: unless-stopped
    volumes:
      # Map data so the dashboard can access the parsed CSVs
      - ./data:/app/data