docker-compose.yml

# 默认配置 - 使用预构建的Docker镜像
# 使用方式: ./run_compose.sh remote
#
# 镜像会从 GitHub Container Registry (ghcr.io) 自动拉取
# 如果需要本地构建镜像（开发环境），请注释掉 image 行，取消注释 build 部分
#
# 数据库配置:
# - 默认使用 PostgreSQL（生产环境推荐）
# - 如需使用 SQLite（本地开发），请设置环境变量 DATABASE_TYPE=sqlite 并注释掉 postgres 服务

services:
  # PostgreSQL 数据库服务（生产环境默认启用）
  postgres:
    image: ${DOCKER_POSTGRES_IMAGE:-postgres:16-alpine}
    container_name: wharttest-postgres
    environment:
      POSTGRES_USER: ${POSTGRES_USER:-postgres}
      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-postgres}
      POSTGRES_DB: ${POSTGRES_DB:-wharttest}
    ports:
      - "8919:5432"
    volumes:
      - postgres-data:/var/lib/postgresql/data
    networks:
      - wharttest-network
    restart: unless-stopped
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U ${POSTGRES_USER:-postgres}"]
      interval: 10s
      timeout: 5s
      retries: 5

  # Redis 服务 - Celery的broker和backend
  redis:
    image: ${DOCKER_REDIS_IMAGE:-redis:7-alpine}
    container_name: wharttest-redis
    ports:
      - "8911:6379"
    volumes:
      - redis-data:/data
    networks:
      - wharttest-network
    restart: unless-stopped
    healthcheck:
      test: [ "CMD", "redis-cli", "ping" ]
      interval: 10s
      timeout: 5s
      retries: 5
    command: redis-server --appendonly yes

  # 后端 Django 服务（包含Celery Worker和Beat）
  backend:
    image: ${DOCKER_BACKEND_IMAGE:-ghcr.io/mgdaaslab/wharttest-backend:latest}
    # 如果需要本地构建，注释掉上面的image行，取消注释下面的build部分
    # build:
    #   context: ./WHartTest_Django
    #   dockerfile: Dockerfile
    container_name: wharttest-backend
    # 启动逻辑已移至 Dockerfile 的 ENTRYPOINT 和 supervisord.conf
    ports:
      - "8912:8000"
    volumes:
      - ./data:/app/data
      - backend-static:/app/static
      - ./WHartTest_Skills:/app/bundled_skills:ro
    environment:
      # 数据库配置
      # 默认使用 PostgreSQL（生产环境推荐）
      # 如需使用 SQLite（本地开发），请设置 DATABASE_TYPE=sqlite
      - DATABASE_TYPE=${DATABASE_TYPE:-postgres}
      # SQLite 配置（DATABASE_TYPE=sqlite 时使用）
      - DATABASE_PATH=${DATABASE_PATH:-/app/data/db.sqlite3}
      # PostgreSQL 配置（DATABASE_TYPE=postgres 时使用）
      - POSTGRES_HOST=${POSTGRES_HOST:-postgres}
      - POSTGRES_PORT=${POSTGRES_PORT:-5432}
      - POSTGRES_DB=${POSTGRES_DB:-wharttest}
      - POSTGRES_USER=${POSTGRES_USER:-postgres}
      - POSTGRES_PASSWORD=${POSTGRES_PASSWORD:-postgres}
      # 其他配置
      - MEDIA_ROOT=${MEDIA_ROOT:-/app/data/media}
      - LANGGRAPH_CHECKPOINT_SQLITE_PATH=${LANGGRAPH_CHECKPOINT_SQLITE_PATH:-/app/data/chat_history.sqlite}
      - DJANGO_DEBUG=True
      - DJANGO_SECRET_KEY=${DJANGO_SECRET_KEY:-django-insecure-change-this-in-production}
      - DJANGO_ALLOWED_HOSTS=${DJANGO_ALLOWED_HOSTS:-*}
      - DJANGO_CORS_ALLOWED_ORIGINS=http://localhost:3000,http://localhost:5173,http://localhost:80
      - DJANGO_ADMIN_USERNAME=${DJANGO_ADMIN_USERNAME:-admin}
      - DJANGO_ADMIN_EMAIL=${DJANGO_ADMIN_EMAIL:-admin@example.com}
      - DJANGO_ADMIN_PASSWORD=${DJANGO_ADMIN_PASSWORD:-admin123456}
      # Celery配置
      - CELERY_BROKER_URL=redis://redis:6379/0
      - CELERY_RESULT_BACKEND=redis://redis:6379/0
      # Qdrant向量数据库
      - QDRANT_URL=http://qdrant:6333
      # 内部API基础URL - 使用localhost因为在同一容器
      - DJANGO_BASE_URL=http://localhost:8000
      - WEIXIN_PLUGIN_HOST_URL=http://weixin-plugin-host:3001
      - HF_ENDPOINT=${DOCKER_HF_ENDPOINT:-https://huggingface.co}
    depends_on:
      postgres:
        condition: service_healthy
      redis:
        condition: service_healthy
      qdrant:
        condition: service_started
      weixin-plugin-host:
        condition: service_started
    networks:
      - wharttest-network
    restart: unless-stopped
    healthcheck:
      test: [ "CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/api/')" ]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 40s

  weixin-plugin-host:
    build:
      context: ./WHartTest_WeixinPluginHost
      dockerfile: Dockerfile
      args:
        NODE_BASE_IMAGE: ${DOCKER_NODE_22_BASE_IMAGE:-node:22-alpine}
        NPM_REGISTRY: ${DOCKER_NPM_REGISTRY:-https://registry.npmjs.org}
    container_name: wharttest-weixin-plugin-host
    ports:
      - "8922:3001"
    volumes:
      - ./data:/app/data
    environment:
      - PORT=3001
      - HOST=0.0.0.0
      # weixin-plugin-host 回调后端的地址
      # Docker 全量部署：后端容器服务名为 backend，使用 Docker 内部网络直连
      - WHARTTEST_BACKEND_URL=http://backend:8000
      - WHARTTEST_API_KEY=${WHARTTEST_API_KEY:-wharttest-default-mcp-key-2025}
      - WHARTTEST_SHARED_DATA_DIR=/app/data
      - OPENCLAW_STATE_DIR=/app/data/openclaw-state
      - OPENCLAW_CONFIG=/app/data/openclaw-state/openclaw.json
    networks:
      - wharttest-network
    restart: unless-stopped
    healthcheck:
      test: [ "CMD", "wget", "--quiet", "--tries=1", "--spider", "http://localhost:3001/health" ]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 20s

  # 前端 Vue 服务
  frontend:
    image: ${DOCKER_FRONTEND_IMAGE:-ghcr.io/mgdaaslab/wharttest-frontend:latest}
    # 如果需要本地构建，注释掉上面的image行，取消注释下面的build部分
    # build:
    #   context: ./WHartTest_Vue
    #   dockerfile: Dockerfile
    container_name: wharttest-frontend
    ports:
      - "8913:80"
    depends_on:
      - backend
    networks:
      - wharttest-network
    restart: unless-stopped
    healthcheck:
      test: [ "CMD", "wget", "--quiet", "--tries=1", "--spider", "http://localhost/" ]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 20s

  # MCP 服务（独立容器）
  mcp:
    image: ${DOCKER_MCP_IMAGE:-ghcr.io/mgdaaslab/wharttest-mcp:latest}
    # 如果需要本地构建，注释掉上面的image行，取消注释下面的build部分
    # build:
    #   context: ./WHartTest_MCP
    #   dockerfile: Dockerfile
    container_name: wharttest-mcp
    user: root
    environment:
      # WHartTest Tools 配置
      - WHARTTEST_BACKEND_URL=${WHARTTEST_BACKEND_URL:-http://backend:8000}
      # 使用系统自动生成的默认API Key，生产环境请在.env中覆盖
      - WHARTTEST_API_KEY=${WHARTTEST_API_KEY:-wharttest-default-mcp-key-2025}
      # MS MCP API 配置（可选）
      - MS_API_HOST=${MS_API_HOST:-http://ms.example.com}
      - MS_ACCESS_KEY=${MS_ACCESS_KEY:-your_16byte_key1}
      - MS_SECRET_KEY=${MS_SECRET_KEY:-your_16byte_key2}
    ports:
      - "8914:8006" # WHartTest_tools 服务端口
      - "8915:8007" # ms_mcp_api 服务端口
    volumes:
      - ./data/playwright-screenshots:/tmp/playwright-output # 使用本地目录挂载
    depends_on:
      - backend
    networks:
      - wharttest-network
    restart: unless-stopped
    healthcheck:
      test: [ "CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8006/')" ]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 30s

  # Playwright MCP 服务（官方Docker镜像）
  playwright-mcp:
    image: ${DOCKER_PLAYWRIGHT_MCP_IMAGE:-mcr.microsoft.com/playwright/mcp}
    container_name: wharttest-playwright-mcp
    user: root # 以 root 用户运行,确保有权限写入挂载目录
    entrypoint: [ "node", "/app/cli.js" ]
    command: [ "--no-sandbox", "--host", "0.0.0.0", "--allowed-hosts", "*", "--config", "/app/playwright-mcp-config.json" ]
    ports:
      - "8916:8931"
    volumes:
      - ./data/playwright-screenshots:/tmp/playwright-output # 使用本地目录挂载
      - ./WHartTest_MCP/playwright-mcp-config.json:/app/playwright-mcp-config.json:ro # 挂载配置文件
    networks:
      - wharttest-network
    restart: unless-stopped
    healthcheck:
      test: [ "CMD", "node", "-e", "require('http').get('http://localhost:8931/mcp', res => process.exit(res.statusCode ? 0 : 1)).on('error', () => process.exit(1))" ]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 20s

  # Qdrant 向量数据库服务
  qdrant:
    image: ${DOCKER_QDRANT_IMAGE:-qdrant/qdrant:latest}
    container_name: wharttest-qdrant
    ports:
      - "8918:6333"  # REST API
    volumes:
      - qdrant-data:/qdrant/storage
    networks:
      - wharttest-network
    restart: unless-stopped
    deploy:
      resources:
        limits:
          memory: 2G

  # Xinference 模型推理服务（Embedding + Reranker）
  # xinference:
  #   image: xprobe/xinference:latest-cpu
  #   container_name: wharttest-xinference
  #   ports:
  #     - "8917:9997"
  #   volumes:
  #     - xinference-data:/root/.xinference
  #     - xinference-cache:/root/.cache/huggingface
  #   environment:
  #     - HF_ENDPOINT=https://hf-mirror.com
  #   networks:
  #     - wharttest-network
  #   restart: unless-stopped
  #   command: xinference-local -H 0.0.0.0
  #   healthcheck:
  #     test: ["CMD", "curl", "-f", "http://localhost:9997/"]
  #     interval: 30s
  #     timeout: 10s
  #     retries: 3
  #     start_period: 60s
  #   deploy:
  #     resources:
  #       limits:
  #         memory: 4G
    # 启动后需要部署模型:
    # Embedding 模型
# curl -X POST "http://localhost:8917/v1/models" \
#   -H "Content-Type: application/json" \
#   -d '{"model_name": "bge-m3", "model_type": "embedding", "model_uid": "bge-m3"}'

# # Reranker 模型
# curl -X POST "http://localhost:8917/v1/models" \
#   -H "Content-Type: application/json" \
#   -d '{"model_name": "bge-reranker-v2-m3", "model_type": "rerank", "model_uid": "bge-reranker-v2-m3"}'

networks:
  wharttest-network:
    driver: bridge

volumes:
  backend-static:
  redis-data:
  celery-beat-schedule:
  xinference-data:
  xinference-cache:
  qdrant-data:
  postgres-data:  # PostgreSQL 数据存储（启用 postgres 服务时使用）
    # db.sqlite3 和 media 改用本地目录挂载，不再需要 named volume
    # playwright-screenshots 改用本地目录挂载，不再需要 named volume