video-flow/docker-compose.yml

version: '3.8'

# Video Flow - Docker Compose 配置
# 支持水平扩展的视频处理服务

services:
  # ============================================================
  # Redis - 消息队列和缓存
  # ============================================================
  redis:
    image: redis:7-alpine
    ports:
      - "6379:6379"
    volumes:
      - redis_data:/data
    command: redis-server --appendonly yes
    healthcheck:
      test: ["CMD", "redis-cli", "ping"]
      interval: 10s
      timeout: 5s
      retries: 5
    restart: unless-stopped

  # ============================================================
  # FastAPI Backend - API 服务
  # ============================================================
  api:
    build:
      context: .
      dockerfile: Dockerfile
    ports:
      - "8000:8000"
    volumes:
      - ./modules:/app/modules:ro
      - ./api:/app/api:ro
      - ./config.py:/app/config.py:ro
      - ./assets:/app/assets
      - ./output:/app/output
      - ./temp:/app/temp
      - ./video_flow.db:/app/video_flow.db
      # 方案A：通过 Unix Socket 连接宿主机 Postgres（不暴露 5432）
      - /var/run/postgresql:/var/run/postgresql
      # 复用 8502（/root/video-flow）生成的历史素材
      - /root/video-flow/temp:/legacy/temp:ro
      - /root/video-flow/output:/legacy/output:ro
    environment:
      - REDIS_URL=redis://redis:6379/0
      - PYTHONUNBUFFERED=1
      # 8503 读写 8502 的 Postgres（从 .env 注入，避免写死密码）
      - DB_CONNECTION_STRING=${VIDEO_FLOW_DB_CONNECTION_STRING}
    depends_on:
      redis:
        condition: service_healthy
    command: uvicorn api.main:app --host 0.0.0.0 --port 8000
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:8000/api/health"]
      interval: 30s
      timeout: 10s
      retries: 3
    restart: unless-stopped

  # ============================================================
  # Celery Worker - 视频处理 Worker
  # 可以通过 docker-compose scale worker=N 水平扩展
  # ============================================================
  worker:
    build:
      context: .
      dockerfile: Dockerfile
    volumes:
      - ./modules:/app/modules:ro
      - ./api:/app/api:ro
      - ./config.py:/app/config.py:ro
      - ./bin:/app/bin:ro
      - ./assets:/app/assets
      - ./output:/app/output
      - ./temp:/app/temp
      - ./video_flow.db:/app/video_flow.db
      - /var/run/postgresql:/var/run/postgresql
      - /root/video-flow/temp:/legacy/temp:ro
      - /root/video-flow/output:/legacy/output:ro
    environment:
      - REDIS_URL=redis://redis:6379/0
      - PYTHONUNBUFFERED=1
      - C_FORCE_ROOT=1
      - DB_CONNECTION_STRING=${VIDEO_FLOW_DB_CONNECTION_STRING}
    depends_on:
      redis:
        condition: service_healthy
    command: celery -A api.celery_app worker --loglevel=info --concurrency=2 -Q default,video,audio
    restart: unless-stopped
    deploy:
      # 生产环境可以增加副本数
      replicas: 1
      resources:
        limits:
          cpus: '2'
          memory: 4G

  # ============================================================
  # React Frontend - 前端服务 (生产环境)
  # ============================================================
  web:
    build:
      context: ./web
      dockerfile: Dockerfile
    ports:
      - "3000:80"
    depends_on:
      - api
    restart: unless-stopped

  # ============================================================
  # Streamlit - 原有调试界面 (保留在 8503)
  # 连接到 8502 的数据目录，复用历史素材
  # ============================================================
  streamlit:
    build:
      context: .
      dockerfile: Dockerfile
    ports:
      # 默认对外保持 8502（兼容历史入口）；容器内仍运行在 8503
      - "${STREAMLIT_PORT:-8502}:8503"
    volumes:
      - ./app.py:/app/app.py:ro
      - ./modules:/app/modules:ro
      - ./config.py:/app/config.py:ro
      - ./assets:/app/assets
      - ./output:/app/output
      # 挂载 8502 服务的 temp 目录，复用历史项目数据
      - /opt/gloda-factory/temp:/app/temp
      - ./video_flow.db:/app/video_flow.db
      - /var/run/postgresql:/var/run/postgresql
      - /root/video-flow/temp:/legacy/temp:ro
      - /root/video-flow/output:/legacy/output:ro
    environment:
      - PYTHONUNBUFFERED=1
      - DB_CONNECTION_STRING=${VIDEO_FLOW_DB_CONNECTION_STRING}
      - WEB_BASE_URL=${WEB_BASE_URL}
    command: streamlit run app.py --server.port 8503 --server.address 0.0.0.0
    restart: unless-stopped

volumes:
  redis_data:

networks:
  default:
    name: video-flow-network