docker-compose.gpu.yml

services:
  backend:
    container_name: bilinote-backend
    build:
      context: .
      dockerfile: backend/Dockerfile.gpu
      args:
        # 国内拉不到 docker.io 时设置 BASE_REGISTRY；注意所选镜像需要支持 nvidia/cuda 命名空间
        BASE_REGISTRY: ${BASE_REGISTRY:-docker.io}
        APT_MIRROR: ${APT_MIRROR:-mirrors.tuna.tsinghua.edu.cn}
        PIP_INDEX: ${PIP_INDEX:-https://pypi.tuna.tsinghua.edu.cn/simple}
    env_file:
      - .env
    environment:
      - BACKEND_PORT=${BACKEND_PORT}
      - BACKEND_HOST=${BACKEND_HOST}
    volumes:
      # 同 docker-compose.yml：./backend 绑到 /app，DB / 转写器配置 / 截图 / 上传都持久化
      - ./backend:/app
    expose:
      - "${BACKEND_PORT}"  # 不再对外暴露，用于 nginx 内部通信
    # 用 unless-stopped 避免短暂崩溃把容器永久打死后再也读不到 .env 修改
    restart: unless-stopped
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:${BACKEND_PORT}/api/sys_health"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 30s   # GPU 镜像首次加载 CUDA 比 CPU 慢，给久一点
    # GPU 部署默认跑较大模型，把内存限制提到 8g 避免 host OOM
    mem_limit: 8g
    deploy:
      resources:
        reservations:
          devices:
            - driver: "nvidia"
              count: "all"
              capabilities: ["gpu"]

  frontend:
    container_name: bilinote-frontend
    build:
      context: .
      dockerfile: BillNote_frontend/Dockerfile
      args:
        BASE_REGISTRY: ${BASE_REGISTRY:-docker.io}
    env_file:
      - .env
    expose:
      - "80"  # 不暴露给宿主机，只供 nginx 访问
    restart: unless-stopped
    mem_limit: 512m

  nginx:
    container_name: bilinote-nginx
    image: nginx:1.25-alpine
    ports:
      - "${APP_PORT}:80"
    volumes:
      - ./nginx/default.conf:/etc/nginx/conf.d/default.conf
    depends_on:
      backend:
        condition: service_healthy
      frontend:
        condition: service_started
    restart: unless-stopped
    mem_limit: 256m