部署

# 克隆项目
git clone https://github.com/PancrePal-xiaoyibao/PancrePal-xiaoyibao.git
cd ai-gateway

# 构建Docker镜像
docker build -t ai-gateway .

# FastGPT配置
FASTGPT_BASE_URL=https://your-fastgpt-instance.com
FASTGPT_API_KEY=your-api-key
FASTGPT_APP_ID=your-app-id

# Dify配置
DIFY_BASE_URL=https://your-dify-instance.com
DIFY_API_KEY=your-api-key

# Coze配置
COZE_API_TOKEN=your-api-token
COZE_BOT_ID=your-bot-id

# S3/MinIO配置（可选）
S3_ENDPOINT=https://your-s3-endpoint.com
S3_ACCESS_KEY=your-access-key
S3_SECRET_KEY=your-secret-key
S3_BUCKET=your-bucket-name
S3_REGION=your-region
S3_KEY_PREFIX=uploads
S3_ACL=public-read
S3_PUBLIC_BASE_URL=https://your-cdn-domain.com

# 运行容器
docker run -d \
  --name ai-gateway \
  -p 3000:3000 \
  --env-file .env \
  ai-gateway

services:
  app:
    image: ghcr.io/liueic/pancrepal-xiaoyibao:latest
    container_name: pancrepal-app
    restart: unless-stopped
    ports:
      - "8000:8000"
    environment:
      # 数据库连接（容器内指向 mongo 服务）
      MONGO_URI: ${MONGO_URI:-mongodb://mongo:27017}
      MONGO_DATABASE: ${MONGO_DATABASE:-ai-gateway}
      # 下列平台密钥建议在宿主机/CI 以环境变量注入
      # DIFY_BASE_URL: ${DIFY_BASE_URL}
      # DIFY_API_KEY: ${DIFY_API_KEY}
      # FASTGPT_BASE_URL: ${FASTGPT_BASE_URL}
      # FASTGPT_API_KEY: ${FASTGPT_API_KEY}
    depends_on:
      mongo:
        condition: service_healthy
    healthcheck:
      test: ["CMD", "wget", "-qO-", "http://127.0.0.1:8000/health"]
      interval: 30s
      timeout: 5s
      retries: 5
    networks:
      - app-net

  mongo:
    image: mongo:7
    container_name: pancrepal-mongo
    restart: unless-stopped
    ports:
      - "27017:27017"
    volumes:
      - mongo-data:/data/db
    healthcheck:
      test: ["CMD", "mongosh", "--quiet", "--eval", "db.adminCommand('ping').ok" ]
      interval: 30s
      timeout: 5s
      retries: 5
    networks:
      - app-net

volumes:
  mongo-data:

networks:
  app-net:

# 启动服务
docker compose up -d

# 查看日志
docker compose logs -f ai-gateway

# 停止服务
docker compose down

# 使用其他端口
docker run -d -p 8080:8000 --env-file .env pancrepal-app

# 检查服务状态
curl http://localhost:8000/health

# 预期响应
{
  "status": "healthy",
  "timestamp": "2024-01-15T10:30:00Z"
}

# 查看容器日志
docker logs pancrepal-app

# 实时查看日志
docker logs -f pancrepal-app

# 查看最近100行日志
docker logs --tail 100 pancrepal-app

# 查看容器资源使用情况
docker stats pancrepal-app

# 进入容器进行调试
docker exec -it pancrepal-app /bin/bash

# 拉取最新代码
git pull

# 重新构建镜像
docker build -t pancrepal-app .

# 停止旧容器
docker stop pancrepal-app

# 删除旧容器
docker rm pancrepal-app

# 启动新容器
docker run -d --name pancrepal-app -p 8080:8000 --env-file .env pancrepal-app

# 重新构建并启动
docker compose up -d --build

# 或者先停止再启动
docker compose down
docker-compose up -d --build

# 检查容器状态
docker ps -a

# 查看容器详细信息
docker inspect pancrepal-app

# 查看环境变量
docker exec pancrepal-app env

# 测试网络连接
docker exec pancrepal-app ping your-ai-platform.com