name: fida-python-prod

services:
  server:
    container_name: "FiDA_${SERVE_ENV}_Server"
    build:
      context: .
      dockerfile: Dockerfile
    working_dir: /app
    volumes:
      - ./:/app
      - ./.env:/app/.env
      - /etc/localtime:/etc/localtime:ro
    ports:
      - "${SERVE_PORT}:80"
    environment:
      - SERVE_ENV=${SERVE_ENV}
    restart: unless-stopped

  # ==================== Celery Worker（单个 Worker 同时处理两个任务） ====================
  celery_worker:
    container_name: "FiDA_${SERVE_ENV}_CeleryWorker"
    build:
      context: .
      dockerfile: Dockerfile
    working_dir: /app
    command: >
      celery -A src.server.canvas_generate_3D.celery_app worker
      -n celery_worker@%h
      -Q img_to_3d_queue,three_d_to_3views_queue
      --concurrency=1
      --prefetch-multiplier=1
      --max-tasks-per-child=1
      --loglevel=INFO
    volumes:
      - ./:/app
      - ./.env:/app/.env
      - /etc/localtime:/etc/localtime:ro
    environment:
      - SERVE_ENV=${SERVE_ENV}
    depends_on:
      - server
    restart: unless-stopped

  # ==================== 可选：RabbitMQ（如果你想把 RabbitMQ 也纳入 docker-compose 管理） ====================
  # rabbitmq:
  #   image: rabbitmq:3.13-management
  #   container_name: "FiDA_${SERVE_ENV}_RabbitMQ"
  #   ports:
  #     - "5672:5672"
  #     - "15672:15672"
  #   environment:
  #     RABBITMQ_DEFAULT_USER: guest
  #     RABBITMQ_DEFAULT_PASS: guest
  #   volumes:
  #     - rabbitmq_data:/var/lib/rabbitmq
  #   restart: unless-stopped

# volumes:
#   rabbitmq_data: