# docker-compose.yml — md-vector-db 本地开发与生产部署
version: "3.8"

services:
  md-vector-db:
    build:
      context: .
      dockerfile: Dockerfile
    image: md-vector-db:latest
    container_name: md-vector-db
    restart: unless-stopped
    ports:
      - "${MD_VECTOR_PORT:-8000}:8000"
    volumes:
      # 持久化 ChromaDB 数据
      - ./data:/app/data
      # 挂载配置文件
      - ./config.yaml:/app/config.yaml:ro
      # 挂载待入库文档目录
      - ${MD_VECTOR_DOCS_DIR:-./md_docs}:/app/md_docs:ro
    environment:
      - MD_VECTOR_CONFIG=/app/config.yaml
      - MD_VECTOR_DB_DATA_DIR=/app/data
      - MD_VECTOR_API_KEY=${MD_VECTOR_API_KEY:-}
      - EMBED_API_KEY=${EMBED_API_KEY:-}
      - CORS_ORIGINS=${CORS_ORIGINS:-http://localhost:3000}
      - MAX_REQUEST_BODY_SIZE=${MAX_REQUEST_BODY_SIZE:-10485760}
    env_file:
      - .env
    healthcheck:
      test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/api/v1/health')"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 60s

  # 可选：GPU 版本（需 nvidia-container-toolkit）
  md-vector-db-gpu:
    profiles: ["gpu"]
    build:
      context: .
      dockerfile: Dockerfile
    image: md-vector-db:latest
    container_name: md-vector-db-gpu
    restart: unless-stopped
    ports:
      - "${MD_VECTOR_PORT:-8000}:8000"
    volumes:
      - ./data:/app/data
      - ./config.yaml:/app/config.yaml:ro
      - ${MD_VECTOR_DOCS_DIR:-./md_docs}:/app/md_docs:ro
    environment:
      - MD_VECTOR_CONFIG=/app/config.yaml
      - MD_VECTOR_DB_DATA_DIR=/app/data
      - MD_VECTOR_API_KEY=${MD_VECTOR_API_KEY:-}
      - EMBED_API_KEY=${EMBED_API_KEY:-}
      - CORS_ORIGINS=${CORS_ORIGINS:-http://localhost:3000}
    env_file:
      - .env
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu]