xiangsx/aigateway repository overview

客户端 → AI Gateway → AI服务
            ↓
       Logstash → Elasticsearch → Kibana

# 克隆项目
git clone <repository-url>
cd aigateway

# 编译
go build -o aigateway

# 运行
./aigateway

proxy:
  target_url: "http://localhost:3001"

logging:
  level: "info"
  output: "both"  # console, file, logstash, both
  logstash:
    enabled: true
    host: "192.168.0.142"
    port: 28779

# 启动ELK Stack
docker-compose -f docker-compose-elk.yml up -d

# 检查服务状态
docker-compose -f docker-compose-elk.yml ps

# 服务器配置
server:
  host: "0.0.0.0"
  port: 8082
  read_timeout: "30s"
  write_timeout: "30s"

# 代理配置
proxy:
  target_url: "http://localhost:3001"
  request_timeout: "30s"
  keep_alive: true

# 监控配置
monitor:
  enabled: true
  detailed_logs: true
  filter_rules:
    - name: "special_token"
      parameter: "token"
      type: "prefix"
      value: "special_"
      action: "save_to_file"

# 日志配置
logging:
  level: "info"
  output: "both"
  format: "json"
  
  # Logstash集成
  logstash:
    enabled: true
    host: "192.168.0.142"
    port: 28779
    protocol: "tcp"
    buffer_size: 1000
    
  # 详细请求日志
  request_logging:
    enabled: true
    include_headers: true
    include_body: true
    include_response: true
    max_body_size: 10240
    sensitive_headers:
      - "authorization"
      - "x-api-key"

{
  "timestamp": "2025-01-09T12:00:00Z",
  "level": "info",
  "service": "aigateway",
  "module": "proxy",
  "message": "POST /auto/v1/chat/completions 200",
  "trace_id": "abc123",
  "data": {
    "type": "request_log",
    "request": {
      "id": "abc123",
      "method": "POST",
      "path": "/auto/v1/chat/completions",
      "client_ip": "192.168.1.100",
      "duration": "1.5s",
      "body_size": 256
    },
    "response": {
      "status_code": 200,
      "is_stream": true,
      "stream_chunks": 15,
      "stream_bytes": 1457
    }
  }
}

input {
  tcp {
    port => 28779
    codec => json_lines
    type => "aigateway"
  }
}

filter {
  # 解析时间戳
  date {
    match => [ "timestamp", "ISO8601" ]
    target => "@timestamp"
  }
  
  # 按日志类型分类处理
  if [data][type] == "request_log" {
    mutate {
      add_field => { "log_category" => "request" }
      add_field => { "request_method" => "%{[data][request][method]}" }
      add_field => { "response_status" => "%{[data][response][status_code]}" }
    }
  }
}

output {
  elasticsearch {
    hosts => ["http://elasticsearch:9200"]
    # 按天分片，按类型分索引
    index => "aigateway-%{log_category}-%{+YYYY.MM.dd}"
  }
}

# 查看所有流式请求
data.response.is_stream:true

# 查看错误请求
response_status:>=400

# 查看特定时间段的请求
@timestamp:[2025-01-09T00:00:00 TO 2025-01-09T23:59:59]

# 查看慢请求 (>1秒)
duration_ms:>1000

curl http://localhost:8082/health

curl http://localhost:8082/metrics

# 访问: http://localhost:8083
# 用户名: admin
# 密码: admin123

go build -o aigateway

# 创建测试后端
python3 test-stream.py

# 测试流式请求
curl -X POST http://localhost:8082/auto/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"messages":[{"role":"user","content":"Hello"}],"stream":true}' \
  --no-buffer

# 查看实时日志
tail -f logs/aigateway.log

# 检查Logstash连接
nc -zv 192.168.0.142 28779