docker-compose.yml

services:
  frontend:
    build:
      context: ./frontend
      dockerfile: Dockerfile
    ports:
      - "3000:3000"
    environment:
      - NODE_ENV=production
      - NEXT_PUBLIC_BACKEND_URL=http://backend:5000
    env_file:
      - ./frontend/.env
    depends_on:
      - backend
    networks:
      - angelfive-network

  backend:
    build:
      context: ./backend
      dockerfile: Dockerfile
    ports:
      - "5000:5000"
    environment:
      - NODE_ENV=production
      - PORT=5000
      - FRONTEND_URL=http://localhost:3000,http://frontend:3000
      - ML_SERVICE_URL=http://ml-service:8000
      - REDIS_URL=redis://redis:6379
    env_file:
      - ./backend/.env
    depends_on:
      redis:
        condition: service_healthy
      ml-service:
        condition: service_started
    networks:
      - angelfive-network

  ml-service:
    build:
      context: ./ml-service
      dockerfile: Dockerfile
    ports:
      - "8000:8000"
    environment:
      - PORT=8000
    env_file:
      - ./ml-service/.env
    volumes:
      - ml_model_cache:/app/model_cache
    networks:
      - angelfive-network

  redis:
    image: redis:7-alpine
    ports:
      - "6379:6379"
    volumes:
      - redis_data:/data
    healthcheck:
      test: ["CMD", "redis-cli", "ping"]
      interval: 10s
      timeout: 5s
      retries: 5
    networks:
      - angelfive-network

networks:
  angelfive-network:
    driver: bridge

volumes:
  redis_data:
  ml_model_cache: