services:
  ray-head:
    build:
      context: .
      dockerfile: Dockerfile_ray
    platform: linux/amd64
    container_name: ray-head
    hostname: ray-head
    ports:
      - "8265:8265" # Ray Dashboard
      - "10001:10001" # Ray Client Server
      - "6379:6379" # Redis port for Ray GCS
    command: >
      ray start --head  --dashboard-host=0.0.0.0  --dashboard-port=8265 --port=6379 --redis-password="" --object-manager-port=8076 --node-manager-port=8077 --min-worker-port=10002 --max-worker-port=19999 --block
    env_file:
      - .env
    networks:
      - ray-network
    restart: unless-stopped
    deploy:
      resources:
        limits:
          memory: 8G
        reservations:
          memory: 8G

  ray-worker:
    build:
      context: .
      dockerfile: Dockerfile_ray
    platform: linux/amd64
    container_name: ray-worker
    hostname: ray-worker
    depends_on:
      - ray-head
    command: >
      ray start  --address=ray-head:6379 --object-manager-port=8076 --node-manager-port=8077 --min-worker-port=10002 --max-worker-port=19999 --block
    env_file:
      - .env
    networks:
      - ray-network
    restart: unless-stopped
    deploy:
      resources:
        limits:
          memory: 4G
        reservations:
          memory: 4G

  aworld-web-server:
    build:
      context: .
      dockerfile: Dockerfile_ray
    platform: linux/amd64
    container_name: aworld-api-server
    hostname: aworld-api-server
    depends_on:
      - ray-head
    command: aworld web --port 8000
    env_file:
      - .env
    networks:
      - ray-network
    restart: unless-stopped
    deploy:
      resources:
        limits:
          memory: 4G
        reservations:
          memory: 4G

networks:
  ray-network:
    driver: bridge

volumes:
  workspace:
    driver: local