更新A2A
This commit is contained in:
zhanggangyong
@@ -0,0 +1,16 @@
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"""
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A2A LiteLLM Agent Package
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"""
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from .agent import LiteLLMAgent
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from .config import get_config, LiteLLMConfig, AgentConfig, A2AConfig
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from .a2a_server import A2AAgentServer, create_app
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__all__ = [
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"LiteLLMAgent",
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"get_config",
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"LiteLLMConfig",
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"AgentConfig",
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"A2AConfig",
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"A2AAgentServer",
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"create_app"
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]
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@@ -0,0 +1,43 @@
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# A2A LiteLLM Agent Dockerfile
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FROM python:3.11-slim
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WORKDIR /app
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# 安装系统依赖
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RUN apt-get update && apt-get install -y --no-install-recommends \
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gcc \
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curl \
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&& rm -rf /var/lib/apt/lists/*
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# 复制依赖文件
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COPY agents/a2a_litellm_agent/requirements.txt .
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# 安装Python依赖
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RUN pip install --no-cache-dir -r requirements.txt requests
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# 复制 common 模块（回调工具）
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COPY common/agent_callback_utils.py /app/common/
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RUN touch /app/common/__init__.py
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# 复制应用代码
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COPY agents/a2a_litellm_agent/*.py /app/
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# 设置环境变量
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ENV SERVICE_HOST=0.0.0.0
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ENV SERVICE_PORT=8080
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ENV POD_NAME=a2a-litellm-agent
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ENV TEMPLATE_TYPE=a2a_litellm_agent
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ENV PYTHONUNBUFFERED=1
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# 回调配置
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ENV AGENT_CALLBACK_URL=http://mcp-server.taiji-ai.svc.cluster.local:8002/api/v1/billing/agent-callback
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# 健康检查
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HEALTHCHECK --interval=30s --timeout=10s --start-period=30s --retries=3 \
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CMD python3 -c "import urllib.request; urllib.request.urlopen('http://localhost:8080/health').read()" || exit 1
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# 暴露端口
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EXPOSE 8080
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# 启动命令
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CMD ["python", "main.py"]
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@@ -0,0 +1,539 @@
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"""
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A2A协议兼容的Agent服务
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实现Google Agent2Agent协议规范
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支持从请求传入 API key，也支持从环境变量获取
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"""
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import asyncio
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import json
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import uuid
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import os
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from typing import Optional, Dict, Any, AsyncGenerator
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from datetime import datetime
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from contextlib import asynccontextmanager
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from fastapi import FastAPI, HTTPException, Request, Response
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from fastapi.responses import StreamingResponse, JSONResponse
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from fastapi.middleware.cors import CORSMiddleware
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from pydantic import BaseModel, Field
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import structlog
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from agent import LiteLLMAgent
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from config import get_config, AgentConfig, A2AConfig
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# 配置日志
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logger = structlog.get_logger()
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# 环境变量配置
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SERVICE_HOST = os.getenv("SERVICE_HOST", "0.0.0.0")
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SERVICE_PORT = int(os.getenv("SERVICE_PORT", "8080"))
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POD_NAME = os.getenv("POD_NAME", "a2a-litellm-agent")
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TEMPLATE_TYPE = os.getenv("TEMPLATE_TYPE", "a2a_litellm_agent")
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# ============== A2A 协议数据模型 ==============
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class A2APart(BaseModel):
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"""A2A消息部分"""
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kind: str = "text"
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text: Optional[str] = None
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data: Optional[Dict[str, Any]] = None
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mime_type: Optional[str] = None
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class A2AMessage(BaseModel):
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"""A2A消息"""
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role: str
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parts: list[A2APart]
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messageId: str = Field(default_factory=lambda: uuid.uuid4().hex)
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class A2AMessageSendParams(BaseModel):
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"""A2A发送消息参数"""
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message: A2AMessage
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configuration: Optional[Dict[str, Any]] = None
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api_key: Optional[str] = Field(None, description="LiteLLM API密钥（可选，优先使用，否则从环境变量获取）")
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model: Optional[str] = Field(None, description="模型名称（可选，优先使用，否则从环境变量获取）")
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class A2ARequest(BaseModel):
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"""A2A JSON-RPC请求"""
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jsonrpc: str = "2.0"
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id: str
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method: str
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params: Optional[Dict[str, Any]] = None
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class A2AArtifact(BaseModel):
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"""A2A响应工件"""
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artifactId: str = Field(default_factory=lambda: uuid.uuid4().hex)
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name: str = "response"
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parts: list[A2APart]
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class A2ATaskStatus(BaseModel):
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"""A2A任务状态"""
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state: str # submitted, working, input-required, completed, failed, canceled
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timestamp: str = Field(default_factory=lambda: datetime.utcnow().isoformat() + "Z")
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message: Optional[str] = None
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class A2ATask(BaseModel):
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"""A2A任务"""
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kind: str = "task"
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id: str = Field(default_factory=lambda: uuid.uuid4().hex)
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contextId: str = Field(default_factory=lambda: uuid.uuid4().hex)
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status: A2ATaskStatus
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artifacts: Optional[list[A2AArtifact]] = None
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class A2AResponse(BaseModel):
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"""A2A JSON-RPC响应"""
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jsonrpc: str = "2.0"
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id: str
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result: Optional[A2ATask] = None
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error: Optional[Dict[str, Any]] = None
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class A2AStreamEvent(BaseModel):
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"""A2A流式事件"""
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kind: str
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taskId: str
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contextId: str
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data: Optional[Dict[str, Any]] = None
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# ============== Agent Card ==============
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class AgentSkill(BaseModel):
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"""Agent技能"""
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id: str
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name: str
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description: str
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inputSchema: Optional[Dict[str, Any]] = None
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outputSchema: Optional[Dict[str, Any]] = None
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class AgentCapabilities(BaseModel):
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"""Agent能力"""
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text: bool = True
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streaming: bool = True
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push_notifications: bool = False
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forms: bool = False
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files: bool = False
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class AgentCard(BaseModel):
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"""A2A Agent Card - 描述Agent能力"""
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name: str
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description: str
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version: str
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url: str
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capabilities: AgentCapabilities
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skills: list[AgentSkill]
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authentication: Optional[Dict[str, Any]] = None
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# ============== A2A Server ==============
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class A2AAgentServer:
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"""A2A协议Agent服务器"""
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def __init__(
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self,
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api_key: Optional[str] = None,
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model: Optional[str] = None
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):
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"""
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初始化A2A Agent服务器
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Args:
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api_key: LiteLLM API密钥（可选，优先使用，否则从环境变量获取）
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model: 模型名称（可选，优先使用，否则从环境变量获取）
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"""
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# 获取配置
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self.llm_config, self.agent_config, self.a2a_config = get_config(api_key, model)
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# 创建Agent（使用默认配置）
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self.default_agent = LiteLLMAgent(
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litellm_config=self.llm_config,
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agent_config=self.agent_config
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)
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# 任务存储
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self.tasks: Dict[str, A2ATask] = {}
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# 创建FastAPI应用
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self.app = self._create_app()
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def _create_app(self) -> FastAPI:
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"""创建FastAPI应用"""
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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logger.info("A2A Agent服务启动", agent_name=self.agent_config.name)
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yield
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await self.default_agent.close()
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logger.info("A2A Agent服务关闭")
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app = FastAPI(
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title=f"{self.agent_config.name} - A2A Agent",
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description=self.agent_config.description,
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version=self.agent_config.version,
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lifespan=lifespan
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)
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# CORS中间件
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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# 注册路由
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self._register_routes(app)
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return app
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def _get_agent(self, api_key: Optional[str] = None, model: Optional[str] = None) -> LiteLLMAgent:
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"""
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获取Agent实例
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如果提供了api_key或model，创建新的Agent实例
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否则使用默认Agent
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"""
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if api_key or model:
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# 创建新的配置和Agent
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llm_config, agent_config, _ = get_config(api_key, model)
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return LiteLLMAgent(litellm_config=llm_config, agent_config=agent_config)
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return self.default_agent
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def _register_routes(self, app: FastAPI):
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"""注册A2A协议路由"""
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@app.get("/")
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async def root():
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"""服务根路径"""
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return {
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"name": self.agent_config.name,
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"version": self.agent_config.version,
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"protocol": "A2A",
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"status": "running",
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"pod_name": POD_NAME,
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"template_type": TEMPLATE_TYPE
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}
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@app.get("/health")
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async def health_check():
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"""健康检查"""
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return {
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"status": "healthy",
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"pod_name": POD_NAME,
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"template_type": TEMPLATE_TYPE,
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"configured": self.llm_config.api_key is not None,
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"timestamp": datetime.utcnow().isoformat()
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}
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@app.get("/.well-known/agent.json")
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async def get_agent_card(request: Request):
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"""获取Agent Card (A2A发现协议)"""
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base_url = str(request.base_url).rstrip("/")
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card = AgentCard(
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name=self.agent_config.name,
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description=self.agent_config.description,
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version=self.agent_config.version,
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url=base_url,
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capabilities=AgentCapabilities(
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text=True,
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streaming=self.agent_config.enable_streaming,
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push_notifications=False
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),
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skills=[
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AgentSkill(
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id="general-assistant",
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name="通用助手",
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description="回答问题、提供建议、协助完成各种任务"
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),
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AgentSkill(
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id="code-helper",
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name="代码助手",
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description="编写、解释和调试代码"
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)
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]
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)
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return card.model_dump()
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@app.post("/message/send")
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async def send_message(request: Request):
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"""A2A message/send 端点"""
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body = await request.json()
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# 解析JSON-RPC请求
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try:
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rpc_request = A2ARequest(**body)
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except Exception as e:
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return JSONResponse({
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"jsonrpc": "2.0",
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"id": body.get("id", "unknown"),
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"error": {
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"code": -32600,
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"message": f"Invalid Request: {str(e)}"
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}
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})
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# 处理 message/send 方法
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if rpc_request.method == "message/send":
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return await self._handle_message_send(rpc_request)
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elif rpc_request.method == "message/stream":
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return await self._handle_message_stream(rpc_request)
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else:
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return JSONResponse({
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"jsonrpc": "2.0",
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"id": rpc_request.id,
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"error": {
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"code": -32601,
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"message": f"Method not found: {rpc_request.method}"
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}
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})
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@app.post("/message/stream")
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async def stream_message(request: Request):
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"""A2A message/stream 端点 (SSE流式响应)"""
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body = await request.json()
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try:
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rpc_request = A2ARequest(**body)
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except Exception as e:
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return JSONResponse({
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"jsonrpc": "2.0",
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"id": body.get("id", "unknown"),
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"error": {
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"code": -32600,
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"message": f"Invalid Request: {str(e)}"
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}
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})
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return await self._handle_message_stream(rpc_request)
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@app.get("/tasks/{task_id}")
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async def get_task(task_id: str):
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"""获取任务状态"""
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if task_id not in self.tasks:
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raise HTTPException(status_code=404, detail="Task not found")
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return self.tasks[task_id].model_dump()
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async def _handle_message_send(self, request: A2ARequest) -> JSONResponse:
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"""处理 message/send 请求"""
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params = request.params or {}
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message_data = params.get("message", {})
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# 提取API key和model（如果提供）
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api_key = params.get("api_key") or os.getenv("LITELLM_API_KEY")
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model = params.get("model") or os.getenv("MODEL_NAME") or os.getenv("LITELLM_MODEL")
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# 提取用户消息文本
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user_text = ""
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parts = message_data.get("parts", [])
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for part in parts:
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if part.get("kind") == "text":
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user_text += part.get("text", "")
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if not user_text:
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return JSONResponse({
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"jsonrpc": "2.0",
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"id": request.id,
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"error": {
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"code": -32602,
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"message": "Invalid params: no text content found"
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}
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})
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# 创建任务
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task_id = uuid.uuid4().hex
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context_id = params.get("contextId", uuid.uuid4().hex)
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task = A2ATask(
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id=task_id,
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contextId=context_id,
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status=A2ATaskStatus(state="working")
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)
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self.tasks[task_id] = task
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try:
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# 获取Agent实例（如果提供了api_key或model，使用新的实例）
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agent = self._get_agent(api_key, model)
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# 调用Agent获取响应
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logger.info("处理消息", task_id=task_id, message_preview=user_text[:50])
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response_text = await agent.chat(
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message=user_text,
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conversation_id=context_id
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)
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# 如果创建了新Agent，关闭它
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if api_key or model:
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await agent.close()
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# 更新任务状态
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task.status = A2ATaskStatus(state="completed")
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task.artifacts = [
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A2AArtifact(
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name="response",
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parts=[A2APart(kind="text", text=response_text)]
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)
|
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]
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self.tasks[task_id] = task
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return JSONResponse({
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"jsonrpc": "2.0",
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"id": request.id,
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"result": task.model_dump()
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})
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except Exception as e:
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logger.error("处理消息失败", error=str(e))
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task.status = A2ATaskStatus(state="failed", message=str(e))
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self.tasks[task_id] = task
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return JSONResponse({
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"jsonrpc": "2.0",
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"id": request.id,
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"error": {
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"code": -32000,
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"message": f"Agent error: {str(e)}"
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||||
}
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||||
})
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async def _handle_message_stream(self, request: A2ARequest) -> StreamingResponse:
|
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"""处理 message/stream 请求 (SSE)"""
|
||||
params = request.params or {}
|
||||
message_data = params.get("message", {})
|
||||
|
||||
# 提取API key和model（如果提供）
|
||||
api_key = params.get("api_key") or os.getenv("LITELLM_API_KEY")
|
||||
model = params.get("model") or os.getenv("MODEL_NAME") or os.getenv("LITELLM_MODEL")
|
||||
|
||||
# 提取用户消息
|
||||
user_text = ""
|
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parts = message_data.get("parts", [])
|
||||
for part in parts:
|
||||
if part.get("kind") == "text":
|
||||
user_text += part.get("text", "")
|
||||
|
||||
task_id = uuid.uuid4().hex
|
||||
context_id = params.get("contextId", uuid.uuid4().hex)
|
||||
|
||||
async def event_generator() -> AsyncGenerator[str, None]:
|
||||
"""生成SSE事件流"""
|
||||
agent = None
|
||||
try:
|
||||
# 获取Agent实例
|
||||
agent = self._get_agent(api_key, model)
|
||||
|
||||
# 发送任务开始事件
|
||||
start_event = {
|
||||
"kind": "task-start",
|
||||
"taskId": task_id,
|
||||
"contextId": context_id
|
||||
}
|
||||
yield f"data: {json.dumps(start_event)}\n\n"
|
||||
|
||||
# 获取流式响应
|
||||
stream = await agent.chat(
|
||||
message=user_text,
|
||||
conversation_id=context_id,
|
||||
stream=True
|
||||
)
|
||||
|
||||
full_response = ""
|
||||
async for chunk in stream:
|
||||
full_response += chunk
|
||||
# 发送文本增量事件
|
||||
delta_event = {
|
||||
"kind": "artifact-delta",
|
||||
"taskId": task_id,
|
||||
"contextId": context_id,
|
||||
"data": {
|
||||
"kind": "text",
|
||||
"text": chunk
|
||||
}
|
||||
}
|
||||
yield f"data: {json.dumps(delta_event)}\n\n"
|
||||
|
||||
# 发送完成事件
|
||||
complete_event = {
|
||||
"kind": "task-complete",
|
||||
"taskId": task_id,
|
||||
"contextId": context_id,
|
||||
"data": {
|
||||
"status": "completed",
|
||||
"artifacts": [{
|
||||
"name": "response",
|
||||
"parts": [{"kind": "text", "text": full_response}]
|
||||
}]
|
||||
}
|
||||
}
|
||||
yield f"data: {json.dumps(complete_event)}\n\n"
|
||||
|
||||
except Exception as e:
|
||||
# 发送错误事件
|
||||
error_event = {
|
||||
"kind": "task-error",
|
||||
"taskId": task_id,
|
||||
"contextId": context_id,
|
||||
"data": {
|
||||
"error": str(e)
|
||||
}
|
||||
}
|
||||
yield f"data: {json.dumps(error_event)}\n\n"
|
||||
finally:
|
||||
# 如果创建了新Agent，关闭它
|
||||
if agent and (api_key or model):
|
||||
await agent.close()
|
||||
|
||||
return StreamingResponse(
|
||||
event_generator(),
|
||||
media_type="text/event-stream",
|
||||
headers={
|
||||
"Cache-Control": "no-cache",
|
||||
"Connection": "keep-alive",
|
||||
"X-Accel-Buffering": "no"
|
||||
}
|
||||
)
|
||||
|
||||
def run(self, host: Optional[str] = None, port: Optional[int] = None):
|
||||
"""运行服务器"""
|
||||
import uvicorn
|
||||
|
||||
host = host or self.agent_config.host
|
||||
port = port or self.agent_config.port
|
||||
|
||||
logger.info(f"启动A2A Agent服务", host=host, port=port)
|
||||
uvicorn.run(self.app, host=host, port=port)
|
||||
|
||||
|
||||
def create_app(api_key: Optional[str] = None, model: Optional[str] = None) -> FastAPI:
|
||||
"""
|
||||
创建FastAPI应用（用于uvicorn启动）
|
||||
|
||||
使用方式:
|
||||
uvicorn a2a_server:app --host 0.0.0.0 --port 8080
|
||||
|
||||
或设置环境变量后:
|
||||
export LITELLM_API_KEY="your-key"
|
||||
export MODEL_NAME="your-model"
|
||||
uvicorn a2a_server:app --host 0.0.0.0 --port 8080
|
||||
"""
|
||||
server = A2AAgentServer(api_key=api_key, model=model)
|
||||
return server.app
|
||||
|
||||
|
||||
# uvicorn 启动入口
|
||||
# 环境变量: LITELLM_API_KEY, MODEL_NAME (或 LITELLM_MODEL)
|
||||
app = create_app()
|
||||
@@ -0,0 +1,282 @@
|
||||
"""
|
||||
LiteLLM Agent 核心模块
|
||||
|
||||
基于LiteLLM框架的Agent实现，支持A2A协议
|
||||
"""
|
||||
import asyncio
|
||||
import json
|
||||
import uuid
|
||||
from typing import AsyncGenerator, Optional, Dict, Any, List
|
||||
from dataclasses import dataclass, field
|
||||
from datetime import datetime
|
||||
|
||||
import httpx
|
||||
import structlog
|
||||
|
||||
from config import LiteLLMConfig, AgentConfig, get_config
|
||||
|
||||
# 配置日志
|
||||
logger = structlog.get_logger()
|
||||
|
||||
|
||||
@dataclass
|
||||
class Message:
|
||||
"""消息数据结构"""
|
||||
role: str # user, assistant, system
|
||||
content: str
|
||||
message_id: str = field(default_factory=lambda: uuid.uuid4().hex)
|
||||
timestamp: datetime = field(default_factory=datetime.now)
|
||||
metadata: Dict[str, Any] = field(default_factory=dict)
|
||||
|
||||
|
||||
@dataclass
|
||||
class Conversation:
|
||||
"""对话上下文"""
|
||||
conversation_id: str = field(default_factory=lambda: uuid.uuid4().hex)
|
||||
messages: List[Message] = field(default_factory=list)
|
||||
created_at: datetime = field(default_factory=datetime.now)
|
||||
|
||||
def add_message(self, role: str, content: str) -> Message:
|
||||
"""添加消息到对话"""
|
||||
msg = Message(role=role, content=content)
|
||||
self.messages.append(msg)
|
||||
return msg
|
||||
|
||||
def to_openai_format(self) -> List[Dict[str, str]]:
|
||||
"""转换为OpenAI格式的消息列表"""
|
||||
return [{"role": m.role, "content": m.content} for m in self.messages]
|
||||
|
||||
|
||||
class LiteLLMAgent:
|
||||
"""
|
||||
基于LiteLLM的Agent实现
|
||||
|
||||
支持功能:
|
||||
- 多轮对话
|
||||
- 流式响应
|
||||
- 工具调用
|
||||
- A2A协议兼容
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
api_key: Optional[str] = None,
|
||||
model: Optional[str] = None,
|
||||
litellm_config: Optional[LiteLLMConfig] = None,
|
||||
agent_config: Optional[AgentConfig] = None
|
||||
):
|
||||
"""
|
||||
初始化Agent
|
||||
|
||||
Args:
|
||||
api_key: LiteLLM API密钥（可选，优先使用，否则从环境变量获取）
|
||||
model: 模型名称（可选，优先使用，否则从环境变量获取）
|
||||
litellm_config: LiteLLM配置对象
|
||||
agent_config: Agent配置对象
|
||||
"""
|
||||
if litellm_config:
|
||||
self.llm_config = litellm_config
|
||||
else:
|
||||
self.llm_config = LiteLLMConfig(api_key=api_key, model=model)
|
||||
|
||||
if agent_config:
|
||||
self.agent_config = agent_config
|
||||
else:
|
||||
self.agent_config = AgentConfig()
|
||||
|
||||
# 验证配置
|
||||
self.llm_config.validate()
|
||||
|
||||
# HTTP客户端
|
||||
self._client: Optional[httpx.AsyncClient] = None
|
||||
|
||||
# 对话管理
|
||||
self.conversations: Dict[str, Conversation] = {}
|
||||
|
||||
# 工具注册
|
||||
self.tools: Dict[str, callable] = {}
|
||||
|
||||
logger.info(
|
||||
"Agent初始化完成",
|
||||
agent_name=self.agent_config.name,
|
||||
model=self.llm_config.model,
|
||||
base_url=self.llm_config.base_url
|
||||
)
|
||||
|
||||
async def _get_client(self) -> httpx.AsyncClient:
|
||||
"""获取或创建HTTP客户端"""
|
||||
if self._client is None or self._client.is_closed:
|
||||
self._client = httpx.AsyncClient(
|
||||
timeout=httpx.Timeout(self.llm_config.timeout),
|
||||
headers={
|
||||
"Authorization": f"Bearer {self.llm_config.api_key}",
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
)
|
||||
return self._client
|
||||
|
||||
async def close(self):
|
||||
"""关闭资源"""
|
||||
if self._client and not self._client.is_closed:
|
||||
await self._client.aclose()
|
||||
|
||||
def register_tool(self, name: str, func: callable, description: str = ""):
|
||||
"""注册工具函数"""
|
||||
self.tools[name] = {
|
||||
"function": func,
|
||||
"description": description
|
||||
}
|
||||
logger.info(f"注册工具: {name}")
|
||||
|
||||
def get_or_create_conversation(self, conversation_id: Optional[str] = None) -> Conversation:
|
||||
"""获取或创建对话"""
|
||||
if conversation_id and conversation_id in self.conversations:
|
||||
return self.conversations[conversation_id]
|
||||
|
||||
conv = Conversation(conversation_id=conversation_id or uuid.uuid4().hex)
|
||||
# 添加系统提示
|
||||
conv.add_message("system", self.agent_config.system_prompt)
|
||||
self.conversations[conv.conversation_id] = conv
|
||||
return conv
|
||||
|
||||
async def chat(
|
||||
self,
|
||||
message: str,
|
||||
conversation_id: Optional[str] = None,
|
||||
stream: bool = False
|
||||
) -> str | AsyncGenerator[str, None]:
|
||||
"""
|
||||
发送消息并获取回复
|
||||
|
||||
Args:
|
||||
message: 用户消息
|
||||
conversation_id: 对话ID（用于多轮对话）
|
||||
stream: 是否流式响应
|
||||
|
||||
Returns:
|
||||
如果stream=False，返回完整回复字符串
|
||||
如果stream=True，返回异步生成器
|
||||
"""
|
||||
# 获取对话上下文
|
||||
conversation = self.get_or_create_conversation(conversation_id)
|
||||
conversation.add_message("user", message)
|
||||
|
||||
if stream:
|
||||
return self._stream_chat(conversation)
|
||||
else:
|
||||
return await self._simple_chat(conversation)
|
||||
|
||||
async def _simple_chat(self, conversation: Conversation) -> str:
|
||||
"""非流式对话"""
|
||||
client = await self._get_client()
|
||||
|
||||
request_body = {
|
||||
"model": self.llm_config.model,
|
||||
"messages": conversation.to_openai_format(),
|
||||
"temperature": self.llm_config.temperature,
|
||||
"max_tokens": self.llm_config.max_tokens
|
||||
}
|
||||
|
||||
logger.debug("发送请求", endpoint=self.llm_config.chat_endpoint)
|
||||
|
||||
try:
|
||||
response = await client.post(
|
||||
self.llm_config.chat_endpoint,
|
||||
json=request_body
|
||||
)
|
||||
response.raise_for_status()
|
||||
|
||||
result = response.json()
|
||||
assistant_message = result["choices"][0]["message"]["content"]
|
||||
|
||||
# 保存助手回复到对话
|
||||
conversation.add_message("assistant", assistant_message)
|
||||
|
||||
logger.info("收到回复", length=len(assistant_message))
|
||||
return assistant_message
|
||||
|
||||
except httpx.HTTPStatusError as e:
|
||||
logger.error("HTTP错误", status_code=e.response.status_code, detail=e.response.text)
|
||||
raise
|
||||
except Exception as e:
|
||||
logger.error("请求失败", error=str(e))
|
||||
raise
|
||||
|
||||
async def _stream_chat(self, conversation: Conversation) -> AsyncGenerator[str, None]:
|
||||
"""流式对话"""
|
||||
client = await self._get_client()
|
||||
|
||||
request_body = {
|
||||
"model": self.llm_config.model,
|
||||
"messages": conversation.to_openai_format(),
|
||||
"temperature": self.llm_config.temperature,
|
||||
"max_tokens": self.llm_config.max_tokens,
|
||||
"stream": True
|
||||
}
|
||||
|
||||
full_response = ""
|
||||
|
||||
try:
|
||||
async with client.stream(
|
||||
"POST",
|
||||
self.llm_config.chat_endpoint,
|
||||
json=request_body
|
||||
) as response:
|
||||
response.raise_for_status()
|
||||
|
||||
async for line in response.aiter_lines():
|
||||
if line.startswith("data: "):
|
||||
data = line[6:]
|
||||
if data == "[DONE]":
|
||||
break
|
||||
|
||||
try:
|
||||
chunk = json.loads(data)
|
||||
delta = chunk.get("choices", [{}])[0].get("delta", {})
|
||||
content = delta.get("content", "")
|
||||
if content:
|
||||
full_response += content
|
||||
yield content
|
||||
except json.JSONDecodeError:
|
||||
continue
|
||||
|
||||
# 保存完整回复到对话
|
||||
conversation.add_message("assistant", full_response)
|
||||
|
||||
except Exception as e:
|
||||
logger.error("流式请求失败", error=str(e))
|
||||
raise
|
||||
|
||||
async def invoke_tool(self, tool_name: str, **kwargs) -> Any:
|
||||
"""调用注册的工具"""
|
||||
if tool_name not in self.tools:
|
||||
raise ValueError(f"未找到工具: {tool_name}")
|
||||
|
||||
tool = self.tools[tool_name]
|
||||
func = tool["function"]
|
||||
|
||||
logger.info(f"调用工具: {tool_name}", kwargs=kwargs)
|
||||
|
||||
if asyncio.iscoroutinefunction(func):
|
||||
return await func(**kwargs)
|
||||
else:
|
||||
return func(**kwargs)
|
||||
|
||||
|
||||
# 示例工具函数
|
||||
def tool_get_current_time() -> str:
|
||||
"""获取当前时间"""
|
||||
return datetime.now().strftime("%Y-%m-%d %H:%M:%S")
|
||||
|
||||
|
||||
def tool_calculate(expression: str) -> str:
|
||||
"""计算数学表达式"""
|
||||
try:
|
||||
# 安全的数学计算
|
||||
allowed_chars = set("0123456789+-*/.() ")
|
||||
if not all(c in allowed_chars for c in expression):
|
||||
return "错误: 不支持的字符"
|
||||
result = eval(expression)
|
||||
return str(result)
|
||||
except Exception as e:
|
||||
return f"计算错误: {str(e)}"
|
||||
@@ -0,0 +1,145 @@
|
||||
"""
|
||||
LiteLLM Agent 配置模块
|
||||
|
||||
支持用户传入密钥和模型名称，同时支持从环境变量获取
|
||||
"""
|
||||
import os
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Optional
|
||||
from dotenv import load_dotenv
|
||||
|
||||
# 加载环境变量
|
||||
load_dotenv()
|
||||
|
||||
|
||||
@dataclass
|
||||
class LiteLLMConfig:
|
||||
"""LiteLLM 配置"""
|
||||
# 基础URL - 用户提供的LiteLLM服务地址
|
||||
base_url: str = "https://litellm.graystone-fb459c5d.southeastasia.azurecontainerapps.io"
|
||||
|
||||
# 完整的chat completions端点
|
||||
chat_endpoint: str = field(init=False)
|
||||
|
||||
# API密钥 - 优先使用传入的，否则从环境变量获取
|
||||
api_key: Optional[str] = None
|
||||
|
||||
# 模型名称 - 优先使用传入的，否则从环境变量获取
|
||||
model: Optional[str] = None
|
||||
|
||||
# 请求超时时间(秒)
|
||||
timeout: int = 120
|
||||
|
||||
# 最大重试次数
|
||||
max_retries: int = 3
|
||||
|
||||
# 温度参数
|
||||
temperature: float = 0.7
|
||||
|
||||
# 最大token数
|
||||
max_tokens: int = 4096
|
||||
|
||||
def __post_init__(self):
|
||||
self.chat_endpoint = f"{self.base_url}/chat/completions"
|
||||
|
||||
# 从环境变量读取（如果未直接提供）
|
||||
if self.api_key is None:
|
||||
self.api_key = os.getenv("LITELLM_API_KEY")
|
||||
if self.model is None:
|
||||
self.model = os.getenv("MODEL_NAME") or os.getenv("LITELLM_MODEL", "gpt-4")
|
||||
|
||||
def validate(self) -> bool:
|
||||
"""验证配置是否完整"""
|
||||
if not self.api_key:
|
||||
raise ValueError("API密钥未设置! 请设置 LITELLM_API_KEY 环境变量或直接传入 api_key")
|
||||
if not self.model:
|
||||
raise ValueError("模型名称未设置! 请设置 MODEL_NAME 环境变量或直接传入 model")
|
||||
return True
|
||||
|
||||
|
||||
@dataclass
|
||||
class AgentConfig:
|
||||
"""Agent 配置"""
|
||||
# Agent名称
|
||||
name: str = "xiaohei-agent"
|
||||
|
||||
# Agent描述
|
||||
description: str = "一个基于LiteLLM的智能Agent，支持A2A协议"
|
||||
|
||||
# Agent版本
|
||||
version: str = "1.0.0"
|
||||
|
||||
# 服务端口
|
||||
port: int = 8080
|
||||
|
||||
# 服务主机
|
||||
host: str = "0.0.0.0"
|
||||
|
||||
# 是否启用流式响应
|
||||
enable_streaming: bool = True
|
||||
|
||||
# 系统提示词
|
||||
system_prompt: str = """你是小黑Agent，一个智能助手。
|
||||
你可以帮助用户完成各种任务，包括：
|
||||
|
||||
- 回答问题
|
||||
|
||||
- 代码编写和解释
|
||||
|
||||
- 文档分析
|
||||
|
||||
- 任务规划
|
||||
|
||||
请用中文回答用户的问题，保持友好和专业。"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class A2AConfig:
|
||||
"""A2A协议配置"""
|
||||
# A2A协议版本
|
||||
protocol_version: str = "1.0"
|
||||
|
||||
# Agent Card配置
|
||||
agent_card: dict = field(default_factory=lambda: {
|
||||
"name": "xiaohei-agent",
|
||||
"description": "基于LiteLLM的智能Agent，支持A2A协议通信",
|
||||
"version": "1.0.0",
|
||||
"capabilities": {
|
||||
"text": True,
|
||||
"streaming": True,
|
||||
"push_notifications": False
|
||||
},
|
||||
"skills": [
|
||||
{
|
||||
"id": "general-assistant",
|
||||
"name": "通用助手",
|
||||
"description": "回答问题、提供建议、协助任务"
|
||||
},
|
||||
{
|
||||
"id": "code-helper",
|
||||
"name": "代码助手",
|
||||
"description": "编写、解释和调试代码"
|
||||
}
|
||||
]
|
||||
})
|
||||
|
||||
|
||||
def get_config(
|
||||
api_key: Optional[str] = None,
|
||||
model: Optional[str] = None
|
||||
) -> tuple[LiteLLMConfig, AgentConfig, A2AConfig]:
|
||||
"""
|
||||
获取完整配置
|
||||
|
||||
Args:
|
||||
api_key: LiteLLM API密钥（可选，优先使用，否则从环境变量获取）
|
||||
model: 模型名称（可选，优先使用，否则从环境变量获取）
|
||||
|
||||
Returns:
|
||||
(LiteLLMConfig, AgentConfig, A2AConfig) 配置元组
|
||||
"""
|
||||
litellm_config = LiteLLMConfig(api_key=api_key, model=model)
|
||||
agent_config = AgentConfig()
|
||||
a2a_config = A2AConfig()
|
||||
|
||||
return litellm_config, agent_config, a2a_config
|
||||
@@ -0,0 +1,43 @@
|
||||
"""
|
||||
A2A LiteLLM Agent 主入口
|
||||
支持从环境变量或请求传入 API key
|
||||
"""
|
||||
import os
|
||||
import uvicorn
|
||||
from a2a_server import create_app
|
||||
|
||||
# 环境变量配置
|
||||
SERVICE_HOST = os.getenv("SERVICE_HOST", "0.0.0.0")
|
||||
SERVICE_PORT = int(os.getenv("SERVICE_PORT", "8080"))
|
||||
POD_NAME = os.getenv("POD_NAME", "a2a-litellm-agent")
|
||||
TEMPLATE_TYPE = os.getenv("TEMPLATE_TYPE", "a2a_litellm_agent")
|
||||
|
||||
# 从环境变量获取默认配置（可选）
|
||||
default_api_key = os.getenv("LITELLM_API_KEY")
|
||||
default_model = os.getenv("MODEL_NAME") or os.getenv("LITELLM_MODEL")
|
||||
|
||||
# 创建应用
|
||||
app = create_app(api_key=default_api_key, model=default_model)
|
||||
|
||||
|
||||
def main():
|
||||
"""主函数"""
|
||||
print(f"🚀 启动 A2A LiteLLM Agent")
|
||||
print(f" - Pod名称: {POD_NAME}")
|
||||
print(f" - 模板类型: {TEMPLATE_TYPE}")
|
||||
print(f" - 服务地址: http://{SERVICE_HOST}:{SERVICE_PORT}")
|
||||
if default_api_key:
|
||||
print(f" - 已配置默认 API key（可通过请求覆盖）")
|
||||
else:
|
||||
print(f" - 未配置默认 API key，需在请求中传入")
|
||||
|
||||
uvicorn.run(
|
||||
app,
|
||||
host=SERVICE_HOST,
|
||||
port=SERVICE_PORT,
|
||||
log_level="info"
|
||||
)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,7 @@
|
||||
# LiteLLM Agent API服务依赖
|
||||
httpx>=0.27.0
|
||||
fastapi>=0.115.0
|
||||
uvicorn[standard]>=0.32.0
|
||||
pydantic>=2.0.0
|
||||
python-dotenv>=1.0.0
|
||||
structlog>=24.0.0
|
||||
@@ -0,0 +1,36 @@
|
||||
FROM python:3.11-slim
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
# 安装系统依赖
|
||||
RUN apt-get update && apt-get install -y \
|
||||
curl \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
|
||||
# 安装Python依赖
|
||||
RUN pip install --no-cache-dir \
|
||||
fastapi==0.109.0 \
|
||||
uvicorn[standard]==0.27.0 \
|
||||
pydantic==2.5.3 \
|
||||
langchain==0.1.0 \
|
||||
langchain-community==0.0.10 \
|
||||
litellm==1.17.0 \
|
||||
azure-storage-blob==12.19.0 \
|
||||
azure-identity==1.15.0
|
||||
|
||||
# 复制agent代码和共享工具
|
||||
COPY agents/azure_blob_agent/azure_blob_agent.py .
|
||||
COPY common/agent_callback_utils.py /app/common/
|
||||
COPY common/api_key_utils.py /app/common/
|
||||
|
||||
# 设置环境变量
|
||||
ENV PYTHONUNBUFFERED=1
|
||||
ENV SERVICE_HOST=0.0.0.0
|
||||
ENV SERVICE_PORT=8080
|
||||
|
||||
# 健康检查 - 使用Python避免僵尸进程
|
||||
HEALTHCHECK --interval=30s --timeout=10s --start-period=40s --retries=3 \
|
||||
CMD python3 -c "import urllib.request; urllib.request.urlopen('http://localhost:8080/health').read()" || exit 1
|
||||
|
||||
# 运行agent (直接使用Python，避免shell)
|
||||
CMD ["python3", "-u", "azure_blob_agent.py"]
|
||||
@@ -0,0 +1,536 @@
|
||||
"""
|
||||
Azure Blob Storage AI Agent - 使用LangChain + LiteLLM实现
|
||||
通过HTTP API接收连接字符串，并提供智能文件操作功能
|
||||
"""
|
||||
import os
|
||||
import logging
|
||||
import time
|
||||
from typing import Optional, Dict, Any, List
|
||||
from datetime import datetime
|
||||
from fastapi import FastAPI, HTTPException
|
||||
from pydantic import BaseModel, Field
|
||||
from azure.storage.blob import BlobServiceClient, ContainerClient
|
||||
from langchain.agents import Tool, AgentExecutor, create_react_agent
|
||||
from langchain.prompts import PromptTemplate
|
||||
from langchain_community.chat_models import ChatLiteLLM
|
||||
import uvicorn
|
||||
from agent_callback_utils import AgentCallbackHandler, CallbackContextManager
|
||||
|
||||
# 配置日志
|
||||
logging.basicConfig(
|
||||
level=logging.INFO,
|
||||
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
|
||||
)
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# 环境变量配置
|
||||
SERVICE_HOST = os.getenv("SERVICE_HOST", "0.0.0.0")
|
||||
SERVICE_PORT = int(os.getenv("SERVICE_PORT", "8080"))
|
||||
POD_NAME = os.getenv("POD_NAME", "azure-blob-agent")
|
||||
TEMPLATE_TYPE = os.getenv("TEMPLATE_TYPE", "azure_blob_agent")
|
||||
|
||||
# LiteLLM配置（从环境变量获取）
|
||||
LITELLM_API_BASE = os.getenv("LITELLM_API_BASE", "http://localhost:4000")
|
||||
MODEL_NAME = os.getenv("MODEL_NAME") or os.getenv("LITELLM_MODEL", "gpt-3.5-turbo")
|
||||
|
||||
# Azure Storage 连接字符串（从环境变量获取）
|
||||
AZURE_STORAGE_CONNECTION_STRING = os.getenv("AZURE_STORAGE_CONNECTION_STRING", "")
|
||||
|
||||
# 全局变量
|
||||
blob_service_client: Optional[BlobServiceClient] = None
|
||||
connection_string: Optional[str] = None
|
||||
callback_handler: Optional[AgentCallbackHandler] = None
|
||||
|
||||
# FastAPI应用
|
||||
app = FastAPI(
|
||||
title="Azure Blob Storage AI Agent",
|
||||
description="智能Azure Blob存储管理代理",
|
||||
version="1.0.0"
|
||||
)
|
||||
|
||||
|
||||
# ==================== 请求/响应模型 ====================
|
||||
|
||||
class ConnectRequest(BaseModel):
|
||||
"""连接请求"""
|
||||
connection_string: str = Field(..., description="Azure Storage连接字符串")
|
||||
|
||||
|
||||
class QueryRequest(BaseModel):
|
||||
"""查询请求"""
|
||||
query: str = Field(..., description="自然语言查询或操作指令")
|
||||
litellm_api_key: str = Field(..., description="LiteLLM API密钥")
|
||||
user_id: Optional[str] = Field(None, description="用户ID（用于计费回调）")
|
||||
container_name: Optional[str] = Field(None, description="指定容器名称")
|
||||
|
||||
|
||||
class HealthResponse(BaseModel):
|
||||
"""健康检查响应"""
|
||||
status: str
|
||||
connected: bool
|
||||
connection_info: Optional[Dict] = None
|
||||
|
||||
|
||||
# ==================== Azure Blob Storage 工具函数 ====================
|
||||
|
||||
def list_containers_tool() -> str:
|
||||
"""列出所有容器"""
|
||||
global blob_service_client
|
||||
|
||||
if not blob_service_client:
|
||||
return "错误: 未连接到Azure Blob Storage"
|
||||
|
||||
try:
|
||||
containers = blob_service_client.list_containers()
|
||||
container_list = []
|
||||
for container in containers:
|
||||
container_list.append({
|
||||
"name": container.name,
|
||||
"last_modified": str(container.last_modified)
|
||||
})
|
||||
|
||||
if not container_list:
|
||||
return "当前没有容器"
|
||||
|
||||
result = "容器列表:\n"
|
||||
for i, c in enumerate(container_list, 1):
|
||||
result += f"{i}. {c['name']} (最后修改: {c['last_modified']})\n"
|
||||
|
||||
return result
|
||||
except Exception as e:
|
||||
logger.error(f"列出容器失败: {str(e)}")
|
||||
return f"错误: {str(e)}"
|
||||
|
||||
|
||||
def list_blobs_in_container(container_name: str) -> str:
|
||||
"""列出指定容器中的所有blob"""
|
||||
global blob_service_client
|
||||
|
||||
if not blob_service_client:
|
||||
return "错误: 未连接到Azure Blob Storage"
|
||||
|
||||
try:
|
||||
container_client = blob_service_client.get_container_client(container_name)
|
||||
blobs = container_client.list_blobs()
|
||||
|
||||
blob_list = []
|
||||
for blob in blobs:
|
||||
blob_list.append({
|
||||
"name": blob.name,
|
||||
"size": blob.size,
|
||||
"content_type": blob.content_settings.content_type if blob.content_settings else "unknown",
|
||||
"last_modified": str(blob.last_modified)
|
||||
})
|
||||
|
||||
if not blob_list:
|
||||
return f"容器 '{container_name}' 中没有文件"
|
||||
|
||||
result = f"容器 '{container_name}' 中的文件列表:\n"
|
||||
total_size = 0
|
||||
for i, b in enumerate(blob_list, 1):
|
||||
size_mb = b['size'] / (1024 * 1024)
|
||||
result += f"{i}. {b['name']} ({size_mb:.2f}MB, {b['content_type']})\n"
|
||||
total_size += b['size']
|
||||
|
||||
result += f"\n总计: {len(blob_list)} 个文件, {total_size / (1024 * 1024):.2f}MB"
|
||||
|
||||
return result
|
||||
except Exception as e:
|
||||
logger.error(f"列出blob失败: {str(e)}")
|
||||
return f"错误: {str(e)}"
|
||||
|
||||
|
||||
def get_blob_info(container_name: str, blob_name: str) -> str:
|
||||
"""获取blob的详细信息"""
|
||||
global blob_service_client
|
||||
|
||||
if not blob_service_client:
|
||||
return "错误: 未连接到Azure Blob Storage"
|
||||
|
||||
try:
|
||||
blob_client = blob_service_client.get_blob_client(container_name, blob_name)
|
||||
properties = blob_client.get_blob_properties()
|
||||
|
||||
info = f"文件信息: {blob_name}\n"
|
||||
info += f"- 容器: {container_name}\n"
|
||||
info += f"- 大小: {properties.size / (1024 * 1024):.2f}MB\n"
|
||||
info += f"- 类型: {properties.content_settings.content_type if properties.content_settings else 'unknown'}\n"
|
||||
info += f"- 创建时间: {properties.creation_time}\n"
|
||||
info += f"- 最后修改: {properties.last_modified}\n"
|
||||
info += f"- ETag: {properties.etag}\n"
|
||||
|
||||
if properties.metadata:
|
||||
info += f"- 元数据: {properties.metadata}\n"
|
||||
|
||||
return info
|
||||
except Exception as e:
|
||||
logger.error(f"获取blob信息失败: {str(e)}")
|
||||
return f"错误: {str(e)}"
|
||||
|
||||
|
||||
def search_blobs(container_name: str, keyword: str) -> str:
|
||||
"""在容器中搜索包含关键字的blob"""
|
||||
global blob_service_client
|
||||
|
||||
if not blob_service_client:
|
||||
return "错误: 未连接到Azure Blob Storage"
|
||||
|
||||
try:
|
||||
container_client = blob_service_client.get_container_client(container_name)
|
||||
blobs = container_client.list_blobs()
|
||||
|
||||
matched_blobs = []
|
||||
for blob in blobs:
|
||||
if keyword.lower() in blob.name.lower():
|
||||
matched_blobs.append({
|
||||
"name": blob.name,
|
||||
"size": blob.size,
|
||||
"last_modified": str(blob.last_modified)
|
||||
})
|
||||
|
||||
if not matched_blobs:
|
||||
return f"在容器 '{container_name}' 中没有找到包含 '{keyword}' 的文件"
|
||||
|
||||
result = f"搜索结果 (关键字: '{keyword}'):\n"
|
||||
for i, b in enumerate(matched_blobs, 1):
|
||||
result += f"{i}. {b['name']} ({b['size'] / 1024:.2f}KB)\n"
|
||||
|
||||
return result
|
||||
except Exception as e:
|
||||
logger.error(f"搜索blob失败: {str(e)}")
|
||||
return f"错误: {str(e)}"
|
||||
|
||||
|
||||
def get_storage_stats() -> str:
|
||||
"""获取存储统计信息"""
|
||||
global blob_service_client
|
||||
|
||||
if not blob_service_client:
|
||||
return "错误: 未连接到Azure Blob Storage"
|
||||
|
||||
try:
|
||||
containers = list(blob_service_client.list_containers())
|
||||
total_containers = len(containers)
|
||||
total_blobs = 0
|
||||
total_size = 0
|
||||
|
||||
container_stats = []
|
||||
for container in containers:
|
||||
container_client = blob_service_client.get_container_client(container.name)
|
||||
blobs = list(container_client.list_blobs())
|
||||
blob_count = len(blobs)
|
||||
container_size = sum(blob.size for blob in blobs)
|
||||
|
||||
total_blobs += blob_count
|
||||
total_size += container_size
|
||||
|
||||
container_stats.append({
|
||||
"name": container.name,
|
||||
"blobs": blob_count,
|
||||
"size_mb": container_size / (1024 * 1024)
|
||||
})
|
||||
|
||||
result = "存储统计信息:\n"
|
||||
result += f"- 总容器数: {total_containers}\n"
|
||||
result += f"- 总文件数: {total_blobs}\n"
|
||||
result += f"- 总大小: {total_size / (1024 * 1024):.2f}MB\n\n"
|
||||
|
||||
if container_stats:
|
||||
result += "各容器详情:\n"
|
||||
for stat in container_stats:
|
||||
result += f" • {stat['name']}: {stat['blobs']} 个文件, {stat['size_mb']:.2f}MB\n"
|
||||
|
||||
return result
|
||||
except Exception as e:
|
||||
logger.error(f"获取统计信息失败: {str(e)}")
|
||||
return f"错误: {str(e)}"
|
||||
|
||||
|
||||
# ==================== 创建LangChain Agent ====================
|
||||
|
||||
def create_blob_agent(litellm_api_key: str) -> Optional[AgentExecutor]:
|
||||
"""创建Azure Blob Storage Agent"""
|
||||
global blob_service_client
|
||||
|
||||
if not blob_service_client:
|
||||
logger.warning("尚未连接到Azure Blob Storage")
|
||||
return None
|
||||
|
||||
# 初始化LiteLLM
|
||||
try:
|
||||
llm = ChatLiteLLM(
|
||||
model=MODEL_NAME,
|
||||
api_base=LITELLM_API_BASE,
|
||||
api_key=litellm_api_key,
|
||||
temperature=0
|
||||
)
|
||||
logger.info(f"✅ LiteLLM初始化成功: {MODEL_NAME} @ {LITELLM_API_BASE}")
|
||||
except Exception as e:
|
||||
logger.error(f"❌ LiteLLM初始化失败: {str(e)}")
|
||||
return None
|
||||
|
||||
# 定义工具
|
||||
tools = [
|
||||
Tool(
|
||||
name="list_containers",
|
||||
func=list_containers_tool,
|
||||
description="列出所有Azure Blob Storage容器。当用户询问'有哪些容器'、'显示容器列表'时使用此工具。"
|
||||
),
|
||||
Tool(
|
||||
name="list_blobs",
|
||||
func=lambda input_str: list_blobs_in_container(input_str),
|
||||
description="列出指定容器中的所有文件。输入参数是容器名称。当用户询问'容器X中有什么文件'、'列出XXX容器的文件'时使用此工具。"
|
||||
),
|
||||
Tool(
|
||||
name="get_blob_info",
|
||||
func=lambda input_str: get_blob_info(*input_str.split(",")),
|
||||
description="获取特定文件的详细信息。输入格式: '容器名,文件名'。当用户询问'文件XXX的详细信息'、'XXX文件的属性'时使用此工具。"
|
||||
),
|
||||
Tool(
|
||||
name="search_blobs",
|
||||
func=lambda input_str: search_blobs(*input_str.split(",", 1)),
|
||||
description="在容器中搜索文件。输入格式: '容器名,关键字'。当用户询问'搜索包含XXX的文件'、'查找XXX'时使用此工具。"
|
||||
),
|
||||
Tool(
|
||||
name="get_storage_stats",
|
||||
func=get_storage_stats,
|
||||
description="获取存储的统计信息，包括容器数量、文件数量、总大小等。当用户询问'存储统计'、'有多少文件'、'占用多少空间'时使用此工具。"
|
||||
),
|
||||
]
|
||||
|
||||
# 定义Agent Prompt
|
||||
template = """你是一个Azure Blob Storage管理助手。你可以帮助用户管理和查询Azure存储中的文件。
|
||||
|
||||
可用工具:
|
||||
{tools}
|
||||
|
||||
工具名称: {tool_names}
|
||||
|
||||
回答问题时请使用以下格式:
|
||||
|
||||
Question: 用户的输入问题
|
||||
Thought: 你应该思考如何回答这个问题
|
||||
Action: 要使用的工具名称，必须是以下之一: [{tool_names}]
|
||||
Action Input: 传递给工具的输入
|
||||
Observation: 工具返回的结果
|
||||
... (这个 Thought/Action/Action Input/Observation 可以重复N次)
|
||||
Thought: 我现在知道最终答案了
|
||||
Final Answer: 对用户问题的最终回答
|
||||
|
||||
重要提示:
|
||||
- 如果用户只是说"列出容器"或"显示容器"，使用 list_containers 工具
|
||||
- 如果用户说"显示XXX容器的文件"，使用 list_blobs 工具，传入容器名
|
||||
- 搜索时需要同时提供容器名和关键字
|
||||
- 获取文件信息时需要提供容器名和文件名，用逗号分隔
|
||||
- 始终用中文回答
|
||||
|
||||
开始!
|
||||
|
||||
Question: {input}
|
||||
Thought: {agent_scratchpad}"""
|
||||
|
||||
prompt = PromptTemplate(
|
||||
template=template,
|
||||
input_variables=["input", "agent_scratchpad"],
|
||||
partial_variables={
|
||||
"tools": "\n".join([f"- {tool.name}: {tool.description}" for tool in tools]),
|
||||
"tool_names": ", ".join([tool.name for tool in tools])
|
||||
}
|
||||
)
|
||||
|
||||
# 创建Agent
|
||||
agent = create_react_agent(llm, tools, prompt)
|
||||
|
||||
# 创建Agent执行器
|
||||
agent_executor = AgentExecutor(
|
||||
agent=agent,
|
||||
tools=tools,
|
||||
verbose=True,
|
||||
handle_parsing_errors=True,
|
||||
max_iterations=5
|
||||
)
|
||||
|
||||
logger.info("✅ Azure Blob Storage Agent创建成功")
|
||||
return agent_executor
|
||||
|
||||
|
||||
# ==================== API端点 ====================
|
||||
|
||||
@app.get("/health", response_model=HealthResponse)
|
||||
async def health_check():
|
||||
"""健康检查"""
|
||||
global blob_service_client, connection_string
|
||||
|
||||
connected = blob_service_client is not None
|
||||
|
||||
connection_info = None
|
||||
if connected:
|
||||
try:
|
||||
# 获取账户信息
|
||||
account_info = blob_service_client.get_account_information()
|
||||
connection_info = {
|
||||
"account_kind": account_info.get('account_kind', 'unknown'),
|
||||
"sku_name": account_info.get('sku_name', 'unknown'),
|
||||
"connected_at": str(datetime.now())
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"获取账户信息失败: {str(e)}")
|
||||
|
||||
return HealthResponse(
|
||||
status="healthy" if connected else "not_connected",
|
||||
connected=connected,
|
||||
connection_info=connection_info
|
||||
)
|
||||
|
||||
|
||||
@app.post("/connect")
|
||||
async def connect_to_storage(request: ConnectRequest):
|
||||
"""连接到Azure Blob Storage"""
|
||||
global blob_service_client, connection_string
|
||||
|
||||
try:
|
||||
# 创建BlobServiceClient
|
||||
blob_service_client = BlobServiceClient.from_connection_string(
|
||||
request.connection_string
|
||||
)
|
||||
|
||||
# 测试连接
|
||||
account_info = blob_service_client.get_account_information()
|
||||
|
||||
connection_string = request.connection_string
|
||||
|
||||
logger.info(f"✅ 成功连接到Azure Blob Storage")
|
||||
|
||||
return {
|
||||
"status": "connected",
|
||||
"message": "成功连接到Azure Blob Storage",
|
||||
"account_info": {
|
||||
"account_kind": account_info.get('account_kind'),
|
||||
"sku_name": account_info.get('sku_name')
|
||||
}
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"❌ 连接失败: {str(e)}")
|
||||
blob_service_client = None
|
||||
connection_string = None
|
||||
raise HTTPException(status_code=400, detail=f"连接失败: {str(e)}")
|
||||
|
||||
|
||||
@app.post("/query")
|
||||
async def query_storage(request: QueryRequest):
|
||||
"""使用自然语言查询存储"""
|
||||
global blob_service_client, callback_handler
|
||||
|
||||
if not blob_service_client:
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail="未连接到Azure Blob Storage，请先调用 /connect"
|
||||
)
|
||||
|
||||
# 初始化回调处理器
|
||||
if not callback_handler:
|
||||
callback_handler = AgentCallbackHandler()
|
||||
|
||||
# 使用上下文管理器自动处理回调
|
||||
with CallbackContextManager(
|
||||
handler=callback_handler,
|
||||
user_id=request.user_id,
|
||||
request_id=f"blob-{int(time.time())}"
|
||||
) as ctx:
|
||||
try:
|
||||
ctx.add_tool("azure_blob_storage")
|
||||
|
||||
# 创建Agent
|
||||
agent = create_blob_agent(request.litellm_api_key)
|
||||
|
||||
if not agent:
|
||||
raise HTTPException(status_code=500, detail="Agent创建失败")
|
||||
|
||||
# 执行查询
|
||||
logger.info(f"收到查询: {request.query}")
|
||||
result = agent.invoke({"input": request.query})
|
||||
|
||||
return {
|
||||
"status": "success",
|
||||
"query": request.query,
|
||||
"answer": result.get("output", "无法生成答案"),
|
||||
"intermediate_steps": str(result.get("intermediate_steps", []))
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"查询执行失败: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail=f"查询失败: {str(e)}")
|
||||
|
||||
|
||||
@app.get("/")
|
||||
async def root():
|
||||
"""根端点"""
|
||||
return {
|
||||
"service": "Azure Blob Storage AI Agent",
|
||||
"version": "1.0.0",
|
||||
"pod_name": POD_NAME,
|
||||
"template": TEMPLATE_TYPE,
|
||||
"connected": blob_service_client is not None,
|
||||
"endpoints": {
|
||||
"health": "/health",
|
||||
"connect": "POST /connect",
|
||||
"query": "POST /query"
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
# ==================== 主函数 ====================
|
||||
|
||||
def init_storage_connection():
|
||||
"""启动时初始化存储连接"""
|
||||
global blob_service_client, connection_string
|
||||
|
||||
if AZURE_STORAGE_CONNECTION_STRING:
|
||||
try:
|
||||
logger.info("检测到环境变量中的连接字符串，尝试连接...")
|
||||
blob_service_client = BlobServiceClient.from_connection_string(
|
||||
AZURE_STORAGE_CONNECTION_STRING
|
||||
)
|
||||
|
||||
# 测试连接
|
||||
account_info = blob_service_client.get_account_information()
|
||||
connection_string = AZURE_STORAGE_CONNECTION_STRING
|
||||
|
||||
logger.info(f"✅ 成功连接到Azure Blob Storage")
|
||||
logger.info(f" - Account Kind: {account_info.get('account_kind')}")
|
||||
logger.info(f" - SKU: {account_info.get('sku_name')}")
|
||||
except Exception as e:
|
||||
logger.error(f"❌ 启动时连接失败: {str(e)}")
|
||||
logger.info("💡 提示: 可以稍后通过 /connect API 手动连接")
|
||||
blob_service_client = None
|
||||
connection_string = None
|
||||
else:
|
||||
logger.info("💡 未设置 AZURE_STORAGE_CONNECTION_STRING，需通过 /connect API 手动连接")
|
||||
|
||||
|
||||
def main():
|
||||
"""启动服务"""
|
||||
global callback_handler
|
||||
|
||||
logger.info(f"🚀 启动 Azure Blob Storage AI Agent")
|
||||
logger.info(f" - Pod名称: {POD_NAME}")
|
||||
logger.info(f" - 模板类型: {TEMPLATE_TYPE}")
|
||||
logger.info(f" - LiteLLM: {MODEL_NAME} @ {LITELLM_API_BASE}")
|
||||
logger.info(f" - 服务地址: http://{SERVICE_HOST}:{SERVICE_PORT}")
|
||||
logger.info(f" ℹ️ API key 将从请求中获取")
|
||||
|
||||
# 初始化存储连接
|
||||
init_storage_connection()
|
||||
|
||||
# 初始化回调处理器
|
||||
callback_handler = AgentCallbackHandler()
|
||||
|
||||
uvicorn.run(
|
||||
app,
|
||||
host=SERVICE_HOST,
|
||||
port=SERVICE_PORT,
|
||||
log_level="info"
|
||||
)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,29 @@
|
||||
# Azure Blob Agent - A2A 版本 Dockerfile
|
||||
FROM python:3.11-slim
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
# 安装系统依赖
|
||||
RUN apt-get update && apt-get install -y \
|
||||
gcc \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
|
||||
# 复制requirements文件
|
||||
COPY common/requirements_a2a.txt /app/
|
||||
|
||||
# 安装Python依赖
|
||||
RUN pip install --no-cache-dir -r requirements_a2a.txt
|
||||
|
||||
# 复制应用代码和共享工具
|
||||
COPY agents/azure_blob_agent_a2a/azure_blob_agent_a2a.py /app/
|
||||
COPY common/api_key_utils.py /app/common/
|
||||
|
||||
# 暴露端口
|
||||
EXPOSE 8080
|
||||
|
||||
# 健康检查
|
||||
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
|
||||
CMD python -c "import requests; requests.get('http://localhost:8080/health', timeout=5)"
|
||||
|
||||
# 启动应用
|
||||
CMD ["python", "azure_blob_agent_a2a.py"]
|
||||
@@ -0,0 +1,663 @@
|
||||
"""
|
||||
Azure Blob Storage AI Agent - A2A (Agent-to-Agent) 版本
|
||||
支持 Agent 之间的协作和通信
|
||||
"""
|
||||
import os
|
||||
import logging
|
||||
import json
|
||||
import httpx
|
||||
from typing import Optional, Dict, Any, List
|
||||
from datetime import datetime
|
||||
from fastapi import FastAPI, HTTPException, Header
|
||||
from pydantic import BaseModel, Field
|
||||
from azure.storage.blob import BlobServiceClient, ContainerClient
|
||||
import uvicorn
|
||||
from api_key_utils import get_api_key
|
||||
|
||||
# 配置日志
|
||||
logging.basicConfig(
|
||||
level=logging.INFO,
|
||||
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
|
||||
)
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# 环境变量配置
|
||||
SERVICE_HOST = os.getenv("SERVICE_HOST", "0.0.0.0")
|
||||
SERVICE_PORT = int(os.getenv("SERVICE_PORT", "8080"))
|
||||
POD_NAME = os.getenv("POD_NAME", "azure-blob-agent-a2a")
|
||||
TEMPLATE_TYPE = os.getenv("TEMPLATE_TYPE", "azure_blob_agent_a2a")
|
||||
AGENT_FRAMEWORK = os.getenv("AGENT_FRAMEWORK", "a2a")
|
||||
|
||||
# 工具配置
|
||||
TOOLS_CONFIG = json.loads(os.getenv("TOOLS_CONFIG", "{}"))
|
||||
TOOL_ENDPOINT = os.getenv("TOOL_ENDPOINT", "")
|
||||
TOOL_API_KEY = os.getenv("TOOL_API_KEY", "")
|
||||
|
||||
# 模型配置
|
||||
MODEL_PROVIDER = os.getenv("MODEL_PROVIDER", "openai")
|
||||
MODEL_NAME = os.getenv("MODEL_NAME", "gpt-4")
|
||||
MODEL_API_KEY = os.getenv("MODEL_API_KEY", "")
|
||||
MODEL_ENDPOINT = os.getenv("MODEL_ENDPOINT", "https://api.openai.com/v1")
|
||||
|
||||
# 存储配置
|
||||
AZURE_STORAGE_CONNECTION_STRING = os.getenv("AZURE_STORAGE_CONNECTION_STRING", "")
|
||||
STORAGE_ACCOUNT_NAME = os.getenv("STORAGE_ACCOUNT_NAME", "")
|
||||
|
||||
# 用户标识
|
||||
USER_ID = os.getenv("USER_ID", "")
|
||||
TENANT_ID = os.getenv("TENANT_ID", "")
|
||||
NAMESPACE = os.getenv("NAMESPACE", "ai-agents")
|
||||
|
||||
# A2A Agent 配置
|
||||
AGENT_ID = os.getenv("AGENT_ID", POD_NAME)
|
||||
AGENT_ROLE = os.getenv("AGENT_ROLE", "storage_manager")
|
||||
AGENT_CAPABILITIES = json.loads(os.getenv("AGENT_CAPABILITIES", '["blob_storage", "file_operations"]'))
|
||||
|
||||
# 全局存储客户端
|
||||
blob_service_client: Optional[BlobServiceClient] = None
|
||||
connection_string: Optional[str] = None
|
||||
|
||||
# A2A Agent 注册表 (其他可协作的 Agent)
|
||||
registered_agents: Dict[str, Dict] = {}
|
||||
|
||||
# FastAPI应用
|
||||
app = FastAPI(
|
||||
title="Azure Blob Storage AI Agent (A2A)",
|
||||
description="支持 Agent-to-Agent 协作的智能 Azure Blob 存储管理代理",
|
||||
version="1.0.0"
|
||||
)
|
||||
|
||||
|
||||
# ==================== 请求/响应模型 ====================
|
||||
|
||||
class ConnectRequest(BaseModel):
|
||||
"""连接请求"""
|
||||
connection_string: str = Field(..., description="Azure Storage连接字符串")
|
||||
|
||||
|
||||
class A2AMessage(BaseModel):
|
||||
"""A2A 消息格式"""
|
||||
message_id: str = Field(..., description="消息ID")
|
||||
from_agent: str = Field(..., description="发送者 Agent ID")
|
||||
to_agent: str = Field(..., description="接收者 Agent ID")
|
||||
message_type: str = Field(..., description="消息类型: request/response/notification")
|
||||
action: str = Field(..., description="请求的动作")
|
||||
parameters: Dict[str, Any] = Field(default_factory=dict, description="参数")
|
||||
context: Optional[Dict] = Field(default_factory=dict, description="上下文")
|
||||
timestamp: Optional[str] = None
|
||||
model_api_key: Optional[str] = Field(None, description="模型 API 密钥（可选，优先使用，否则从环境变量获取）")
|
||||
|
||||
|
||||
class A2AQueryRequest(BaseModel):
|
||||
"""A2A 查询请求"""
|
||||
query: str = Field(..., description="自然语言查询")
|
||||
container_name: Optional[str] = None
|
||||
requester_agent: Optional[str] = Field(None, description="请求者 Agent ID")
|
||||
context: Optional[Dict] = Field(default_factory=dict)
|
||||
model_api_key: Optional[str] = Field(None, description="模型 API 密钥（可选，优先使用，否则从环境变量获取）")
|
||||
|
||||
|
||||
class A2ARegisterRequest(BaseModel):
|
||||
"""A2A Agent 注册请求"""
|
||||
agent_id: str
|
||||
agent_role: str
|
||||
capabilities: List[str]
|
||||
endpoint: str
|
||||
|
||||
|
||||
class HealthResponse(BaseModel):
|
||||
"""健康检查响应"""
|
||||
status: str
|
||||
connected: bool
|
||||
framework: str
|
||||
agent_id: str
|
||||
agent_role: str
|
||||
capabilities: List[str]
|
||||
user_id: Optional[str] = None
|
||||
namespace: Optional[str] = None
|
||||
registered_agents_count: int = 0
|
||||
connection_info: Optional[Dict] = None
|
||||
|
||||
|
||||
# ==================== A2A 操作处理器 ====================
|
||||
|
||||
class A2AActionHandler:
|
||||
"""A2A 动作处理器"""
|
||||
|
||||
@staticmethod
|
||||
async def handle_list_containers(parameters: Dict) -> Dict:
|
||||
"""处理列出容器请求"""
|
||||
global blob_service_client
|
||||
|
||||
if not blob_service_client:
|
||||
return {"error": "未连接到 Azure Blob Storage"}
|
||||
|
||||
try:
|
||||
containers = blob_service_client.list_containers()
|
||||
container_list = []
|
||||
for container in containers:
|
||||
container_list.append({
|
||||
"name": container.name,
|
||||
"last_modified": str(container.last_modified)
|
||||
})
|
||||
|
||||
return {
|
||||
"success": True,
|
||||
"containers": container_list,
|
||||
"count": len(container_list)
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"列出容器失败: {str(e)}")
|
||||
return {"error": str(e)}
|
||||
|
||||
@staticmethod
|
||||
async def handle_list_blobs(parameters: Dict) -> Dict:
|
||||
"""处理列出 blob 请求"""
|
||||
global blob_service_client
|
||||
|
||||
if not blob_service_client:
|
||||
return {"error": "未连接到 Azure Blob Storage"}
|
||||
|
||||
container_name = parameters.get("container_name")
|
||||
if not container_name:
|
||||
return {"error": "缺少参数: container_name"}
|
||||
|
||||
try:
|
||||
container_client = blob_service_client.get_container_client(container_name)
|
||||
blobs = container_client.list_blobs()
|
||||
|
||||
blob_list = []
|
||||
total_size = 0
|
||||
for blob in blobs:
|
||||
blob_info = {
|
||||
"name": blob.name,
|
||||
"size": blob.size,
|
||||
"size_mb": round(blob.size / (1024 * 1024), 2),
|
||||
"content_type": blob.content_settings.content_type if blob.content_settings else "unknown",
|
||||
"last_modified": str(blob.last_modified)
|
||||
}
|
||||
blob_list.append(blob_info)
|
||||
total_size += blob.size
|
||||
|
||||
return {
|
||||
"success": True,
|
||||
"container": container_name,
|
||||
"blobs": blob_list,
|
||||
"count": len(blob_list),
|
||||
"total_size_mb": round(total_size / (1024 * 1024), 2)
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"列出 blob 失败: {str(e)}")
|
||||
return {"error": str(e)}
|
||||
|
||||
@staticmethod
|
||||
async def handle_get_blob_info(parameters: Dict) -> Dict:
|
||||
"""处理获取 blob 信息请求"""
|
||||
global blob_service_client
|
||||
|
||||
if not blob_service_client:
|
||||
return {"error": "未连接到 Azure Blob Storage"}
|
||||
|
||||
container_name = parameters.get("container_name")
|
||||
blob_name = parameters.get("blob_name")
|
||||
|
||||
if not container_name or not blob_name:
|
||||
return {"error": "缺少参数: container_name 或 blob_name"}
|
||||
|
||||
try:
|
||||
blob_client = blob_service_client.get_blob_client(container_name, blob_name)
|
||||
properties = blob_client.get_blob_properties()
|
||||
|
||||
return {
|
||||
"success": True,
|
||||
"blob_name": blob_name,
|
||||
"container": container_name,
|
||||
"size": properties.size,
|
||||
"size_mb": round(properties.size / (1024 * 1024), 2),
|
||||
"content_type": properties.content_settings.content_type if properties.content_settings else "unknown",
|
||||
"creation_time": str(properties.creation_time),
|
||||
"last_modified": str(properties.last_modified),
|
||||
"etag": properties.etag,
|
||||
"metadata": properties.metadata if properties.metadata else {}
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"获取 blob 信息失败: {str(e)}")
|
||||
return {"error": str(e)}
|
||||
|
||||
@staticmethod
|
||||
async def handle_search_blobs(parameters: Dict) -> Dict:
|
||||
"""处理搜索 blob 请求"""
|
||||
global blob_service_client
|
||||
|
||||
if not blob_service_client:
|
||||
return {"error": "未连接到 Azure Blob Storage"}
|
||||
|
||||
container_name = parameters.get("container_name")
|
||||
keyword = parameters.get("keyword")
|
||||
|
||||
if not container_name or not keyword:
|
||||
return {"error": "缺少参数: container_name 或 keyword"}
|
||||
|
||||
try:
|
||||
container_client = blob_service_client.get_container_client(container_name)
|
||||
blobs = container_client.list_blobs()
|
||||
|
||||
matched_blobs = []
|
||||
for blob in blobs:
|
||||
if keyword.lower() in blob.name.lower():
|
||||
matched_blobs.append({
|
||||
"name": blob.name,
|
||||
"size": blob.size,
|
||||
"size_kb": round(blob.size / 1024, 2),
|
||||
"last_modified": str(blob.last_modified)
|
||||
})
|
||||
|
||||
return {
|
||||
"success": True,
|
||||
"container": container_name,
|
||||
"keyword": keyword,
|
||||
"results": matched_blobs,
|
||||
"count": len(matched_blobs)
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"搜索 blob 失败: {str(e)}")
|
||||
return {"error": str(e)}
|
||||
|
||||
@staticmethod
|
||||
async def handle_get_stats(parameters: Dict) -> Dict:
|
||||
"""处理获取统计信息请求"""
|
||||
global blob_service_client
|
||||
|
||||
if not blob_service_client:
|
||||
return {"error": "未连接到 Azure Blob Storage"}
|
||||
|
||||
try:
|
||||
containers = list(blob_service_client.list_containers())
|
||||
total_containers = len(containers)
|
||||
total_blobs = 0
|
||||
total_size = 0
|
||||
|
||||
container_stats = []
|
||||
for container in containers:
|
||||
container_client = blob_service_client.get_container_client(container.name)
|
||||
blobs = list(container_client.list_blobs())
|
||||
blob_count = len(blobs)
|
||||
container_size = sum(blob.size for blob in blobs)
|
||||
|
||||
total_blobs += blob_count
|
||||
total_size += container_size
|
||||
|
||||
container_stats.append({
|
||||
"name": container.name,
|
||||
"blobs": blob_count,
|
||||
"size_mb": round(container_size / (1024 * 1024), 2)
|
||||
})
|
||||
|
||||
return {
|
||||
"success": True,
|
||||
"total_containers": total_containers,
|
||||
"total_blobs": total_blobs,
|
||||
"total_size_mb": round(total_size / (1024 * 1024), 2),
|
||||
"container_stats": container_stats
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"获取统计信息失败: {str(e)}")
|
||||
return {"error": str(e)}
|
||||
|
||||
|
||||
# 动作路由表
|
||||
ACTION_HANDLERS = {
|
||||
"list_containers": A2AActionHandler.handle_list_containers,
|
||||
"list_blobs": A2AActionHandler.handle_list_blobs,
|
||||
"get_blob_info": A2AActionHandler.handle_get_blob_info,
|
||||
"search_blobs": A2AActionHandler.handle_search_blobs,
|
||||
"get_stats": A2AActionHandler.handle_get_stats,
|
||||
}
|
||||
|
||||
|
||||
# ==================== API 端点 ====================
|
||||
|
||||
@app.get("/health", response_model=HealthResponse)
|
||||
async def health_check():
|
||||
"""健康检查"""
|
||||
global blob_service_client, connection_string
|
||||
|
||||
connected = blob_service_client is not None
|
||||
|
||||
connection_info = None
|
||||
if connected:
|
||||
try:
|
||||
account_info = blob_service_client.get_account_information()
|
||||
connection_info = {
|
||||
"account_kind": account_info.get('account_kind', 'unknown'),
|
||||
"sku_name": account_info.get('sku_name', 'unknown'),
|
||||
"connected_at": str(datetime.now())
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"获取账户信息失败: {str(e)}")
|
||||
|
||||
return HealthResponse(
|
||||
status="healthy" if connected else "not_connected",
|
||||
connected=connected,
|
||||
framework=AGENT_FRAMEWORK,
|
||||
agent_id=AGENT_ID,
|
||||
agent_role=AGENT_ROLE,
|
||||
capabilities=AGENT_CAPABILITIES,
|
||||
user_id=USER_ID,
|
||||
namespace=NAMESPACE,
|
||||
registered_agents_count=len(registered_agents),
|
||||
connection_info=connection_info
|
||||
)
|
||||
|
||||
|
||||
@app.post("/connect")
|
||||
async def connect_to_storage(request: ConnectRequest):
|
||||
"""连接到 Azure Blob Storage"""
|
||||
global blob_service_client, connection_string
|
||||
|
||||
try:
|
||||
blob_service_client = BlobServiceClient.from_connection_string(
|
||||
request.connection_string
|
||||
)
|
||||
|
||||
account_info = blob_service_client.get_account_information()
|
||||
connection_string = request.connection_string
|
||||
|
||||
logger.info(f"✅ 成功连接到 Azure Blob Storage (Agent: {AGENT_ID}, User: {USER_ID})")
|
||||
|
||||
return {
|
||||
"status": "connected",
|
||||
"message": "成功连接到 Azure Blob Storage",
|
||||
"framework": AGENT_FRAMEWORK,
|
||||
"agent_id": AGENT_ID,
|
||||
"user_id": USER_ID,
|
||||
"account_info": {
|
||||
"account_kind": account_info.get('account_kind'),
|
||||
"sku_name": account_info.get('sku_name')
|
||||
}
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"❌ 连接失败: {str(e)}")
|
||||
blob_service_client = None
|
||||
connection_string = None
|
||||
raise HTTPException(status_code=400, detail=f"连接失败: {str(e)}")
|
||||
|
||||
|
||||
@app.get("/a2a/capabilities")
|
||||
async def get_capabilities():
|
||||
"""获取 Agent 能力"""
|
||||
return {
|
||||
"agent_id": AGENT_ID,
|
||||
"agent_role": AGENT_ROLE,
|
||||
"capabilities": AGENT_CAPABILITIES,
|
||||
"supported_actions": list(ACTION_HANDLERS.keys()),
|
||||
"framework": AGENT_FRAMEWORK
|
||||
}
|
||||
|
||||
|
||||
@app.post("/a2a/register")
|
||||
async def register_agent(request: A2ARegisterRequest):
|
||||
"""注册其他 Agent"""
|
||||
global registered_agents
|
||||
|
||||
registered_agents[request.agent_id] = {
|
||||
"agent_id": request.agent_id,
|
||||
"agent_role": request.agent_role,
|
||||
"capabilities": request.capabilities,
|
||||
"endpoint": request.endpoint,
|
||||
"registered_at": str(datetime.now())
|
||||
}
|
||||
|
||||
logger.info(f"✅ Agent '{request.agent_id}' 注册成功")
|
||||
|
||||
return {
|
||||
"status": "registered",
|
||||
"agent_id": request.agent_id,
|
||||
"message": f"Agent '{request.agent_id}' 已注册"
|
||||
}
|
||||
|
||||
|
||||
@app.get("/a2a/agents")
|
||||
async def list_registered_agents():
|
||||
"""列出已注册的 Agent"""
|
||||
return {
|
||||
"agents": list(registered_agents.values()),
|
||||
"count": len(registered_agents)
|
||||
}
|
||||
|
||||
|
||||
@app.post("/a2a/message")
|
||||
async def handle_a2a_message(message: A2AMessage):
|
||||
"""处理 A2A 消息"""
|
||||
if not blob_service_client:
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail="未连接到 Azure Blob Storage，请先调用 /connect"
|
||||
)
|
||||
|
||||
# 获取 API key（优先使用请求传入的，否则从环境变量获取）
|
||||
api_key = get_api_key(message.model_api_key, "MODEL_API_KEY", MODEL_API_KEY)
|
||||
|
||||
# 验证消息目标
|
||||
if message.to_agent != AGENT_ID:
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail=f"消息目标不匹配: 期望 {AGENT_ID}, 收到 {message.to_agent}"
|
||||
)
|
||||
|
||||
# 处理消息
|
||||
if message.message_type == "request":
|
||||
action = message.action
|
||||
|
||||
if action not in ACTION_HANDLERS:
|
||||
return {
|
||||
"message_id": message.message_id,
|
||||
"status": "error",
|
||||
"error": f"不支持的动作: {action}",
|
||||
"supported_actions": list(ACTION_HANDLERS.keys())
|
||||
}
|
||||
|
||||
try:
|
||||
handler = ACTION_HANDLERS[action]
|
||||
result = await handler(message.parameters)
|
||||
|
||||
return {
|
||||
"message_id": message.message_id,
|
||||
"from_agent": AGENT_ID,
|
||||
"to_agent": message.from_agent,
|
||||
"message_type": "response",
|
||||
"action": action,
|
||||
"result": result,
|
||||
"timestamp": str(datetime.now()),
|
||||
"api_key_used": "request" if message.model_api_key else ("env" if MODEL_API_KEY else "none")
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"处理 A2A 消息失败: {str(e)}")
|
||||
return {
|
||||
"message_id": message.message_id,
|
||||
"status": "error",
|
||||
"error": str(e)
|
||||
}
|
||||
|
||||
return {
|
||||
"message_id": message.message_id,
|
||||
"status": "info",
|
||||
"message": f"收到消息类型: {message.message_type}"
|
||||
}
|
||||
|
||||
|
||||
@app.post("/query")
|
||||
async def query_storage(request: A2AQueryRequest):
|
||||
"""查询存储（支持 A2A 上下文）"""
|
||||
if not blob_service_client:
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail="未连接到 Azure Blob Storage，请先调用 /connect"
|
||||
)
|
||||
|
||||
# 获取 API key（优先使用请求传入的，否则从环境变量获取）
|
||||
api_key = get_api_key(request.model_api_key, "MODEL_API_KEY", MODEL_API_KEY)
|
||||
|
||||
try:
|
||||
query = request.query.lower()
|
||||
result = None
|
||||
action_used = None
|
||||
|
||||
# 简单的规则匹配
|
||||
if "容器" in query and ("列出" in query or "显示" in query or "有哪些" in query):
|
||||
result = await A2AActionHandler.handle_list_containers({})
|
||||
action_used = "list_containers"
|
||||
elif "统计" in query or "有多少" in query or "占用" in query:
|
||||
result = await A2AActionHandler.handle_get_stats({})
|
||||
action_used = "get_stats"
|
||||
elif request.container_name:
|
||||
if "文件" in query or "blob" in query.lower():
|
||||
result = await A2AActionHandler.handle_list_blobs({"container_name": request.container_name})
|
||||
action_used = "list_blobs"
|
||||
|
||||
return {
|
||||
"status": "success" if result else "info",
|
||||
"query": request.query,
|
||||
"action": action_used,
|
||||
"result": result,
|
||||
"agent_id": AGENT_ID,
|
||||
"requester": request.requester_agent,
|
||||
"framework": AGENT_FRAMEWORK,
|
||||
"api_key_used": "request" if request.model_api_key else ("env" if MODEL_API_KEY else "none")
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"查询执行失败: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail=f"查询失败: {str(e)}")
|
||||
|
||||
|
||||
@app.post("/a2a/collaborate")
|
||||
async def collaborate_with_agent(
|
||||
target_agent_id: str,
|
||||
action: str,
|
||||
parameters: Dict[str, Any]
|
||||
):
|
||||
"""与其他 Agent 协作"""
|
||||
if target_agent_id not in registered_agents:
|
||||
raise HTTPException(
|
||||
status_code=404,
|
||||
detail=f"Agent '{target_agent_id}' 未注册"
|
||||
)
|
||||
|
||||
target_agent = registered_agents[target_agent_id]
|
||||
|
||||
# 创建 A2A 消息
|
||||
message = A2AMessage(
|
||||
message_id=f"{AGENT_ID}_{datetime.now().timestamp()}",
|
||||
from_agent=AGENT_ID,
|
||||
to_agent=target_agent_id,
|
||||
message_type="request",
|
||||
action=action,
|
||||
parameters=parameters,
|
||||
timestamp=str(datetime.now())
|
||||
)
|
||||
|
||||
try:
|
||||
# 发送请求到目标 Agent
|
||||
async with httpx.AsyncClient() as client:
|
||||
response = await client.post(
|
||||
f"{target_agent['endpoint']}/a2a/message",
|
||||
json=message.dict(),
|
||||
timeout=30.0
|
||||
)
|
||||
response.raise_for_status()
|
||||
|
||||
return {
|
||||
"status": "success",
|
||||
"target_agent": target_agent_id,
|
||||
"action": action,
|
||||
"response": response.json()
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"协作失败: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail=f"协作失败: {str(e)}")
|
||||
|
||||
|
||||
@app.get("/")
|
||||
async def root():
|
||||
"""根端点"""
|
||||
return {
|
||||
"service": "Azure Blob Storage AI Agent",
|
||||
"version": "1.0.0",
|
||||
"framework": AGENT_FRAMEWORK,
|
||||
"agent_id": AGENT_ID,
|
||||
"agent_role": AGENT_ROLE,
|
||||
"capabilities": AGENT_CAPABILITIES,
|
||||
"pod_name": POD_NAME,
|
||||
"template": TEMPLATE_TYPE,
|
||||
"user_id": USER_ID,
|
||||
"namespace": NAMESPACE,
|
||||
"connected": blob_service_client is not None,
|
||||
"registered_agents": len(registered_agents),
|
||||
"endpoints": {
|
||||
"health": "/health",
|
||||
"connect": "POST /connect",
|
||||
"capabilities": "GET /a2a/capabilities",
|
||||
"register_agent": "POST /a2a/register",
|
||||
"list_agents": "GET /a2a/agents",
|
||||
"handle_message": "POST /a2a/message",
|
||||
"collaborate": "POST /a2a/collaborate",
|
||||
"query": "POST /query"
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
# ==================== 主函数 ====================
|
||||
|
||||
def init_storage_connection():
|
||||
"""启动时初始化存储连接"""
|
||||
global blob_service_client, connection_string
|
||||
|
||||
if AZURE_STORAGE_CONNECTION_STRING:
|
||||
try:
|
||||
logger.info("检测到环境变量中的连接字符串，尝试连接...")
|
||||
blob_service_client = BlobServiceClient.from_connection_string(
|
||||
AZURE_STORAGE_CONNECTION_STRING
|
||||
)
|
||||
|
||||
account_info = blob_service_client.get_account_information()
|
||||
connection_string = AZURE_STORAGE_CONNECTION_STRING
|
||||
|
||||
logger.info(f"✅ 成功连接到 Azure Blob Storage")
|
||||
logger.info(f" - Account Kind: {account_info.get('account_kind')}")
|
||||
logger.info(f" - SKU: {account_info.get('sku_name')}")
|
||||
except Exception as e:
|
||||
logger.error(f"❌ 启动时连接失败: {str(e)}")
|
||||
logger.info("💡 提示: 可以稍后通过 /connect API 手动连接")
|
||||
blob_service_client = None
|
||||
connection_string = None
|
||||
else:
|
||||
logger.info("💡 未设置 AZURE_STORAGE_CONNECTION_STRING，需通过 /connect API 手动连接")
|
||||
|
||||
|
||||
def main():
|
||||
"""启动服务"""
|
||||
logger.info(f"🚀 启动 Azure Blob Storage AI Agent (A2A)")
|
||||
logger.info(f" - Framework: {AGENT_FRAMEWORK}")
|
||||
logger.info(f" - Agent ID: {AGENT_ID}")
|
||||
logger.info(f" - Agent Role: {AGENT_ROLE}")
|
||||
logger.info(f" - Capabilities: {AGENT_CAPABILITIES}")
|
||||
logger.info(f" - Pod名称: {POD_NAME}")
|
||||
logger.info(f" - 模板类型: {TEMPLATE_TYPE}")
|
||||
logger.info(f" - User ID: {USER_ID}")
|
||||
logger.info(f" - Namespace: {NAMESPACE}")
|
||||
logger.info(f" - 模型: {MODEL_NAME} @ {MODEL_PROVIDER}")
|
||||
logger.info(f" - 服务地址: http://{SERVICE_HOST}:{SERVICE_PORT}")
|
||||
|
||||
# 初始化存储连接
|
||||
init_storage_connection()
|
||||
|
||||
uvicorn.run(
|
||||
app,
|
||||
host=SERVICE_HOST,
|
||||
port=SERVICE_PORT,
|
||||
log_level="info"
|
||||
)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,28 @@
|
||||
# Azure Blob Agent - MCP 版本 Dockerfile
|
||||
FROM python:3.11-slim
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
# 安装系统依赖
|
||||
RUN apt-get update && apt-get install -y \
|
||||
gcc \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
|
||||
# 复制requirements文件
|
||||
COPY common/requirements_mcp.txt /app/
|
||||
|
||||
# 安装Python依赖
|
||||
RUN pip install --no-cache-dir -r requirements_mcp.txt
|
||||
|
||||
# 复制应用代码
|
||||
COPY agents/azure_blob_agent_mcp/azure_blob_agent_mcp.py /app/
|
||||
|
||||
# 暴露端口
|
||||
EXPOSE 8080
|
||||
|
||||
# 健康检查
|
||||
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
|
||||
CMD python -c "import requests; requests.get('http://localhost:8080/health', timeout=5)"
|
||||
|
||||
# 启动应用
|
||||
CMD ["python", "azure_blob_agent_mcp.py"]
|
||||
@@ -0,0 +1,622 @@
|
||||
"""
|
||||
Azure Blob Storage AI Agent - MCP (Model Context Protocol) 版本
|
||||
使用 MCP 协议实现智能文件操作功能
|
||||
"""
|
||||
import os
|
||||
import logging
|
||||
import json
|
||||
from typing import Optional, Dict, Any, List
|
||||
from datetime import datetime
|
||||
from fastapi import FastAPI, HTTPException
|
||||
from pydantic import BaseModel, Field
|
||||
from azure.storage.blob import BlobServiceClient, ContainerClient
|
||||
import uvicorn
|
||||
import asyncio
|
||||
|
||||
# 配置日志
|
||||
logging.basicConfig(
|
||||
level=logging.INFO,
|
||||
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
|
||||
)
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# 环境变量配置
|
||||
SERVICE_HOST = os.getenv("SERVICE_HOST", "0.0.0.0")
|
||||
SERVICE_PORT = int(os.getenv("SERVICE_PORT", "8080"))
|
||||
POD_NAME = os.getenv("POD_NAME", "azure-blob-agent-mcp")
|
||||
TEMPLATE_TYPE = os.getenv("TEMPLATE_TYPE", "azure_blob_agent_mcp")
|
||||
AGENT_FRAMEWORK = os.getenv("AGENT_FRAMEWORK", "mcp")
|
||||
|
||||
# 工具配置 (从环境变量传入的 JSON)
|
||||
TOOLS_CONFIG = json.loads(os.getenv("TOOLS_CONFIG", "{}"))
|
||||
TOOL_ENDPOINT = os.getenv("TOOL_ENDPOINT", "")
|
||||
TOOL_API_KEY = os.getenv("TOOL_API_KEY", "")
|
||||
|
||||
# 模型配置
|
||||
MODEL_PROVIDER = os.getenv("MODEL_PROVIDER", "openai")
|
||||
MODEL_NAME = os.getenv("MODEL_NAME", "gpt-4")
|
||||
MODEL_API_KEY = os.getenv("MODEL_API_KEY", "")
|
||||
MODEL_ENDPOINT = os.getenv("MODEL_ENDPOINT", "https://api.openai.com/v1")
|
||||
|
||||
# 存储配置
|
||||
AZURE_STORAGE_CONNECTION_STRING = os.getenv("AZURE_STORAGE_CONNECTION_STRING", "")
|
||||
STORAGE_ACCOUNT_NAME = os.getenv("STORAGE_ACCOUNT_NAME", "")
|
||||
|
||||
# 用户标识
|
||||
USER_ID = os.getenv("USER_ID", "")
|
||||
TENANT_ID = os.getenv("TENANT_ID", "")
|
||||
NAMESPACE = os.getenv("NAMESPACE", "ai-agents")
|
||||
|
||||
# 全局存储客户端
|
||||
blob_service_client: Optional[BlobServiceClient] = None
|
||||
connection_string: Optional[str] = None
|
||||
|
||||
# MCP 工具注册表
|
||||
mcp_tools: Dict[str, Any] = {}
|
||||
|
||||
# FastAPI应用
|
||||
app = FastAPI(
|
||||
title="Azure Blob Storage AI Agent (MCP)",
|
||||
description="基于 MCP 协议的智能 Azure Blob 存储管理代理",
|
||||
version="1.0.0"
|
||||
)
|
||||
|
||||
|
||||
# ==================== 请求/响应模型 ====================
|
||||
|
||||
class ConnectRequest(BaseModel):
|
||||
"""连接请求"""
|
||||
connection_string: str = Field(..., description="Azure Storage连接字符串")
|
||||
|
||||
|
||||
class MCPToolRequest(BaseModel):
|
||||
"""MCP 工具调用请求"""
|
||||
tool_name: str = Field(..., description="工具名称")
|
||||
parameters: Dict[str, Any] = Field(default_factory=dict, description="工具参数")
|
||||
|
||||
|
||||
class MCPQueryRequest(BaseModel):
|
||||
"""MCP 查询请求"""
|
||||
query: str = Field(..., description="自然语言查询或操作指令")
|
||||
container_name: Optional[str] = Field(None, description="指定容器名称")
|
||||
context: Optional[Dict] = Field(default_factory=dict, description="上下文信息")
|
||||
|
||||
|
||||
class HealthResponse(BaseModel):
|
||||
"""健康检查响应"""
|
||||
status: str
|
||||
connected: bool
|
||||
framework: str
|
||||
user_id: Optional[str] = None
|
||||
namespace: Optional[str] = None
|
||||
connection_info: Optional[Dict] = None
|
||||
|
||||
|
||||
# ==================== MCP 工具定义 ====================
|
||||
|
||||
class MCPTool:
|
||||
"""MCP 工具基类"""
|
||||
|
||||
def __init__(self, name: str, description: str, parameters_schema: Dict):
|
||||
self.name = name
|
||||
self.description = description
|
||||
self.parameters_schema = parameters_schema
|
||||
|
||||
async def execute(self, parameters: Dict[str, Any]) -> Dict[str, Any]:
|
||||
"""执行工具"""
|
||||
raise NotImplementedError
|
||||
|
||||
def to_mcp_spec(self) -> Dict:
|
||||
"""转换为 MCP 工具规范"""
|
||||
return {
|
||||
"name": self.name,
|
||||
"description": self.description,
|
||||
"inputSchema": {
|
||||
"type": "object",
|
||||
"properties": self.parameters_schema,
|
||||
"required": list(self.parameters_schema.keys())
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
class ListContainersTool(MCPTool):
|
||||
"""列出所有容器工具"""
|
||||
|
||||
def __init__(self):
|
||||
super().__init__(
|
||||
name="list_containers",
|
||||
description="列出 Azure Blob Storage 中的所有容器",
|
||||
parameters_schema={}
|
||||
)
|
||||
|
||||
async def execute(self, parameters: Dict[str, Any]) -> Dict[str, Any]:
|
||||
global blob_service_client
|
||||
|
||||
if not blob_service_client:
|
||||
return {"error": "未连接到 Azure Blob Storage"}
|
||||
|
||||
try:
|
||||
containers = blob_service_client.list_containers()
|
||||
container_list = []
|
||||
for container in containers:
|
||||
container_list.append({
|
||||
"name": container.name,
|
||||
"last_modified": str(container.last_modified)
|
||||
})
|
||||
|
||||
return {
|
||||
"success": True,
|
||||
"containers": container_list,
|
||||
"count": len(container_list)
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"列出容器失败: {str(e)}")
|
||||
return {"error": str(e)}
|
||||
|
||||
|
||||
class ListBlobsTool(MCPTool):
|
||||
"""列出容器中的 blob 工具"""
|
||||
|
||||
def __init__(self):
|
||||
super().__init__(
|
||||
name="list_blobs",
|
||||
description="列出指定容器中的所有文件",
|
||||
parameters_schema={
|
||||
"container_name": {
|
||||
"type": "string",
|
||||
"description": "容器名称"
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
async def execute(self, parameters: Dict[str, Any]) -> Dict[str, Any]:
|
||||
global blob_service_client
|
||||
|
||||
if not blob_service_client:
|
||||
return {"error": "未连接到 Azure Blob Storage"}
|
||||
|
||||
container_name = parameters.get("container_name")
|
||||
if not container_name:
|
||||
return {"error": "缺少参数: container_name"}
|
||||
|
||||
try:
|
||||
container_client = blob_service_client.get_container_client(container_name)
|
||||
blobs = container_client.list_blobs()
|
||||
|
||||
blob_list = []
|
||||
total_size = 0
|
||||
for blob in blobs:
|
||||
blob_info = {
|
||||
"name": blob.name,
|
||||
"size": blob.size,
|
||||
"size_mb": round(blob.size / (1024 * 1024), 2),
|
||||
"content_type": blob.content_settings.content_type if blob.content_settings else "unknown",
|
||||
"last_modified": str(blob.last_modified)
|
||||
}
|
||||
blob_list.append(blob_info)
|
||||
total_size += blob.size
|
||||
|
||||
return {
|
||||
"success": True,
|
||||
"container": container_name,
|
||||
"blobs": blob_list,
|
||||
"count": len(blob_list),
|
||||
"total_size_mb": round(total_size / (1024 * 1024), 2)
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"列出 blob 失败: {str(e)}")
|
||||
return {"error": str(e)}
|
||||
|
||||
|
||||
class GetBlobInfoTool(MCPTool):
|
||||
"""获取 blob 信息工具"""
|
||||
|
||||
def __init__(self):
|
||||
super().__init__(
|
||||
name="get_blob_info",
|
||||
description="获取特定文件的详细信息",
|
||||
parameters_schema={
|
||||
"container_name": {
|
||||
"type": "string",
|
||||
"description": "容器名称"
|
||||
},
|
||||
"blob_name": {
|
||||
"type": "string",
|
||||
"description": "文件名称"
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
async def execute(self, parameters: Dict[str, Any]) -> Dict[str, Any]:
|
||||
global blob_service_client
|
||||
|
||||
if not blob_service_client:
|
||||
return {"error": "未连接到 Azure Blob Storage"}
|
||||
|
||||
container_name = parameters.get("container_name")
|
||||
blob_name = parameters.get("blob_name")
|
||||
|
||||
if not container_name or not blob_name:
|
||||
return {"error": "缺少参数: container_name 或 blob_name"}
|
||||
|
||||
try:
|
||||
blob_client = blob_service_client.get_blob_client(container_name, blob_name)
|
||||
properties = blob_client.get_blob_properties()
|
||||
|
||||
return {
|
||||
"success": True,
|
||||
"blob_name": blob_name,
|
||||
"container": container_name,
|
||||
"size": properties.size,
|
||||
"size_mb": round(properties.size / (1024 * 1024), 2),
|
||||
"content_type": properties.content_settings.content_type if properties.content_settings else "unknown",
|
||||
"creation_time": str(properties.creation_time),
|
||||
"last_modified": str(properties.last_modified),
|
||||
"etag": properties.etag,
|
||||
"metadata": properties.metadata if properties.metadata else {}
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"获取 blob 信息失败: {str(e)}")
|
||||
return {"error": str(e)}
|
||||
|
||||
|
||||
class SearchBlobsTool(MCPTool):
|
||||
"""搜索 blob 工具"""
|
||||
|
||||
def __init__(self):
|
||||
super().__init__(
|
||||
name="search_blobs",
|
||||
description="在容器中搜索包含关键字的文件",
|
||||
parameters_schema={
|
||||
"container_name": {
|
||||
"type": "string",
|
||||
"description": "容器名称"
|
||||
},
|
||||
"keyword": {
|
||||
"type": "string",
|
||||
"description": "搜索关键字"
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
async def execute(self, parameters: Dict[str, Any]) -> Dict[str, Any]:
|
||||
global blob_service_client
|
||||
|
||||
if not blob_service_client:
|
||||
return {"error": "未连接到 Azure Blob Storage"}
|
||||
|
||||
container_name = parameters.get("container_name")
|
||||
keyword = parameters.get("keyword")
|
||||
|
||||
if not container_name or not keyword:
|
||||
return {"error": "缺少参数: container_name 或 keyword"}
|
||||
|
||||
try:
|
||||
container_client = blob_service_client.get_container_client(container_name)
|
||||
blobs = container_client.list_blobs()
|
||||
|
||||
matched_blobs = []
|
||||
for blob in blobs:
|
||||
if keyword.lower() in blob.name.lower():
|
||||
matched_blobs.append({
|
||||
"name": blob.name,
|
||||
"size": blob.size,
|
||||
"size_kb": round(blob.size / 1024, 2),
|
||||
"last_modified": str(blob.last_modified)
|
||||
})
|
||||
|
||||
return {
|
||||
"success": True,
|
||||
"container": container_name,
|
||||
"keyword": keyword,
|
||||
"results": matched_blobs,
|
||||
"count": len(matched_blobs)
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"搜索 blob 失败: {str(e)}")
|
||||
return {"error": str(e)}
|
||||
|
||||
|
||||
class GetStorageStatsTool(MCPTool):
|
||||
"""获取存储统计工具"""
|
||||
|
||||
def __init__(self):
|
||||
super().__init__(
|
||||
name="get_storage_stats",
|
||||
description="获取存储的统计信息，包括容器数量、文件数量、总大小等",
|
||||
parameters_schema={}
|
||||
)
|
||||
|
||||
async def execute(self, parameters: Dict[str, Any]) -> Dict[str, Any]:
|
||||
global blob_service_client
|
||||
|
||||
if not blob_service_client:
|
||||
return {"error": "未连接到 Azure Blob Storage"}
|
||||
|
||||
try:
|
||||
containers = list(blob_service_client.list_containers())
|
||||
total_containers = len(containers)
|
||||
total_blobs = 0
|
||||
total_size = 0
|
||||
|
||||
container_stats = []
|
||||
for container in containers:
|
||||
container_client = blob_service_client.get_container_client(container.name)
|
||||
blobs = list(container_client.list_blobs())
|
||||
blob_count = len(blobs)
|
||||
container_size = sum(blob.size for blob in blobs)
|
||||
|
||||
total_blobs += blob_count
|
||||
total_size += container_size
|
||||
|
||||
container_stats.append({
|
||||
"name": container.name,
|
||||
"blobs": blob_count,
|
||||
"size_mb": round(container_size / (1024 * 1024), 2)
|
||||
})
|
||||
|
||||
return {
|
||||
"success": True,
|
||||
"total_containers": total_containers,
|
||||
"total_blobs": total_blobs,
|
||||
"total_size_mb": round(total_size / (1024 * 1024), 2),
|
||||
"container_stats": container_stats
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"获取统计信息失败: {str(e)}")
|
||||
return {"error": str(e)}
|
||||
|
||||
|
||||
# ==================== MCP 工具注册 ====================
|
||||
|
||||
def register_tools():
|
||||
"""注册所有 MCP 工具"""
|
||||
global mcp_tools
|
||||
|
||||
tools = [
|
||||
ListContainersTool(),
|
||||
ListBlobsTool(),
|
||||
GetBlobInfoTool(),
|
||||
SearchBlobsTool(),
|
||||
GetStorageStatsTool()
|
||||
]
|
||||
|
||||
for tool in tools:
|
||||
mcp_tools[tool.name] = tool
|
||||
|
||||
logger.info(f"✅ 注册了 {len(mcp_tools)} 个 MCP 工具")
|
||||
|
||||
|
||||
# ==================== API 端点 ====================
|
||||
|
||||
@app.get("/health", response_model=HealthResponse)
|
||||
async def health_check():
|
||||
"""健康检查"""
|
||||
global blob_service_client, connection_string
|
||||
|
||||
connected = blob_service_client is not None
|
||||
|
||||
connection_info = None
|
||||
if connected:
|
||||
try:
|
||||
account_info = blob_service_client.get_account_information()
|
||||
connection_info = {
|
||||
"account_kind": account_info.get('account_kind', 'unknown'),
|
||||
"sku_name": account_info.get('sku_name', 'unknown'),
|
||||
"connected_at": str(datetime.now())
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"获取账户信息失败: {str(e)}")
|
||||
|
||||
return HealthResponse(
|
||||
status="healthy" if connected else "not_connected",
|
||||
connected=connected,
|
||||
framework=AGENT_FRAMEWORK,
|
||||
user_id=USER_ID,
|
||||
namespace=NAMESPACE,
|
||||
connection_info=connection_info
|
||||
)
|
||||
|
||||
|
||||
@app.post("/connect")
|
||||
async def connect_to_storage(request: ConnectRequest):
|
||||
"""连接到 Azure Blob Storage"""
|
||||
global blob_service_client, connection_string
|
||||
|
||||
try:
|
||||
blob_service_client = BlobServiceClient.from_connection_string(
|
||||
request.connection_string
|
||||
)
|
||||
|
||||
account_info = blob_service_client.get_account_information()
|
||||
connection_string = request.connection_string
|
||||
|
||||
logger.info(f"✅ 成功连接到 Azure Blob Storage (User: {USER_ID})")
|
||||
|
||||
return {
|
||||
"status": "connected",
|
||||
"message": "成功连接到 Azure Blob Storage",
|
||||
"framework": AGENT_FRAMEWORK,
|
||||
"user_id": USER_ID,
|
||||
"account_info": {
|
||||
"account_kind": account_info.get('account_kind'),
|
||||
"sku_name": account_info.get('sku_name')
|
||||
}
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"❌ 连接失败: {str(e)}")
|
||||
blob_service_client = None
|
||||
connection_string = None
|
||||
raise HTTPException(status_code=400, detail=f"连接失败: {str(e)}")
|
||||
|
||||
|
||||
@app.get("/mcp/tools")
|
||||
async def list_mcp_tools():
|
||||
"""列出所有可用的 MCP 工具"""
|
||||
if not blob_service_client:
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail="未连接到 Azure Blob Storage，请先调用 /connect"
|
||||
)
|
||||
|
||||
tools_spec = [tool.to_mcp_spec() for tool in mcp_tools.values()]
|
||||
|
||||
return {
|
||||
"tools": tools_spec,
|
||||
"count": len(tools_spec),
|
||||
"framework": AGENT_FRAMEWORK
|
||||
}
|
||||
|
||||
|
||||
@app.post("/mcp/call")
|
||||
async def call_mcp_tool(request: MCPToolRequest):
|
||||
"""调用 MCP 工具"""
|
||||
if not blob_service_client:
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail="未连接到 Azure Blob Storage，请先调用 /connect"
|
||||
)
|
||||
|
||||
tool_name = request.tool_name
|
||||
if tool_name not in mcp_tools:
|
||||
raise HTTPException(
|
||||
status_code=404,
|
||||
detail=f"工具 '{tool_name}' 不存在"
|
||||
)
|
||||
|
||||
try:
|
||||
tool = mcp_tools[tool_name]
|
||||
result = await tool.execute(request.parameters)
|
||||
|
||||
return {
|
||||
"tool": tool_name,
|
||||
"result": result,
|
||||
"timestamp": str(datetime.now())
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"工具调用失败: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail=f"工具调用失败: {str(e)}")
|
||||
|
||||
|
||||
@app.post("/query")
|
||||
async def query_storage(request: MCPQueryRequest):
|
||||
"""使用自然语言查询存储 (简化版 - 实际应集成 LLM)"""
|
||||
if not blob_service_client:
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail="未连接到 Azure Blob Storage，请先调用 /connect"
|
||||
)
|
||||
|
||||
try:
|
||||
query = request.query.lower()
|
||||
result = None
|
||||
|
||||
# 简单的规则匹配 (实际应使用 LLM 进行意图识别)
|
||||
if "容器" in query and ("列出" in query or "显示" in query or "有哪些" in query):
|
||||
tool = mcp_tools["list_containers"]
|
||||
result = await tool.execute({})
|
||||
elif "统计" in query or "有多少" in query or "占用" in query:
|
||||
tool = mcp_tools["get_storage_stats"]
|
||||
result = await tool.execute({})
|
||||
elif request.container_name:
|
||||
if "文件" in query or "blob" in query.lower():
|
||||
tool = mcp_tools["list_blobs"]
|
||||
result = await tool.execute({"container_name": request.container_name})
|
||||
|
||||
if result:
|
||||
return {
|
||||
"status": "success",
|
||||
"query": request.query,
|
||||
"result": result,
|
||||
"framework": AGENT_FRAMEWORK
|
||||
}
|
||||
else:
|
||||
return {
|
||||
"status": "info",
|
||||
"query": request.query,
|
||||
"message": "未能匹配到合适的工具，请使用 /mcp/tools 查看可用工具",
|
||||
"available_tools": list(mcp_tools.keys())
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"查询执行失败: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail=f"查询失败: {str(e)}")
|
||||
|
||||
|
||||
@app.get("/")
|
||||
async def root():
|
||||
"""根端点"""
|
||||
return {
|
||||
"service": "Azure Blob Storage AI Agent",
|
||||
"version": "1.0.0",
|
||||
"framework": AGENT_FRAMEWORK,
|
||||
"pod_name": POD_NAME,
|
||||
"template": TEMPLATE_TYPE,
|
||||
"user_id": USER_ID,
|
||||
"namespace": NAMESPACE,
|
||||
"connected": blob_service_client is not None,
|
||||
"tools_count": len(mcp_tools),
|
||||
"endpoints": {
|
||||
"health": "/health",
|
||||
"connect": "POST /connect",
|
||||
"list_tools": "GET /mcp/tools",
|
||||
"call_tool": "POST /mcp/call",
|
||||
"query": "POST /query"
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
# ==================== 主函数 ====================
|
||||
|
||||
def init_storage_connection():
|
||||
"""启动时初始化存储连接"""
|
||||
global blob_service_client, connection_string
|
||||
|
||||
if AZURE_STORAGE_CONNECTION_STRING:
|
||||
try:
|
||||
logger.info("检测到环境变量中的连接字符串，尝试连接...")
|
||||
blob_service_client = BlobServiceClient.from_connection_string(
|
||||
AZURE_STORAGE_CONNECTION_STRING
|
||||
)
|
||||
|
||||
account_info = blob_service_client.get_account_information()
|
||||
connection_string = AZURE_STORAGE_CONNECTION_STRING
|
||||
|
||||
logger.info(f"✅ 成功连接到 Azure Blob Storage")
|
||||
logger.info(f" - Account Kind: {account_info.get('account_kind')}")
|
||||
logger.info(f" - SKU: {account_info.get('sku_name')}")
|
||||
except Exception as e:
|
||||
logger.error(f"❌ 启动时连接失败: {str(e)}")
|
||||
logger.info("💡 提示: 可以稍后通过 /connect API 手动连接")
|
||||
blob_service_client = None
|
||||
connection_string = None
|
||||
else:
|
||||
logger.info("💡 未设置 AZURE_STORAGE_CONNECTION_STRING，需通过 /connect API 手动连接")
|
||||
|
||||
|
||||
def main():
|
||||
"""启动服务"""
|
||||
logger.info(f"🚀 启动 Azure Blob Storage AI Agent (MCP)")
|
||||
logger.info(f" - Framework: {AGENT_FRAMEWORK}")
|
||||
logger.info(f" - Pod名称: {POD_NAME}")
|
||||
logger.info(f" - 模板类型: {TEMPLATE_TYPE}")
|
||||
logger.info(f" - User ID: {USER_ID}")
|
||||
logger.info(f" - Namespace: {NAMESPACE}")
|
||||
logger.info(f" - 模型: {MODEL_NAME} @ {MODEL_PROVIDER}")
|
||||
logger.info(f" - 服务地址: http://{SERVICE_HOST}:{SERVICE_PORT}")
|
||||
|
||||
# 注册 MCP 工具
|
||||
register_tools()
|
||||
|
||||
# 初始化存储连接
|
||||
init_storage_connection()
|
||||
|
||||
uvicorn.run(
|
||||
app,
|
||||
host=SERVICE_HOST,
|
||||
port=SERVICE_PORT,
|
||||
log_level="info"
|
||||
)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,38 @@
|
||||
FROM python:3.11-slim
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
# 安装系统依赖
|
||||
RUN apt-get update && apt-get install -y \
|
||||
curl \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
|
||||
# 安装 Python 依赖
|
||||
RUN pip install --no-cache-dir \
|
||||
fastapi==0.109.0 \
|
||||
uvicorn[standard]==0.27.0 \
|
||||
pydantic==2.5.3 \
|
||||
requests>=2.31.0
|
||||
|
||||
# 复制 common 模块（回调工具）
|
||||
COPY common/agent_callback_utils.py /app/common/
|
||||
RUN touch /app/common/__init__.py
|
||||
|
||||
# 复制应用代码
|
||||
COPY agents/echo_agent/echo_agent.py /app/
|
||||
|
||||
# 环境变量
|
||||
ENV PYTHONUNBUFFERED=1
|
||||
ENV SERVICE_HOST=0.0.0.0
|
||||
ENV SERVICE_PORT=8000
|
||||
|
||||
# 回调配置
|
||||
ENV AGENT_CALLBACK_URL=http://mcp-server:8002/api/v1/billing/agent-callback
|
||||
|
||||
# 健康检查
|
||||
HEALTHCHECK --interval=30s --timeout=10s --start-period=10s --retries=3 \
|
||||
CMD python3 -c "import urllib.request; urllib.request.urlopen('http://localhost:8000/health').read()" || exit 1
|
||||
|
||||
EXPOSE 8000
|
||||
|
||||
CMD ["python3", "-u", "echo_agent.py"]
|
||||
@@ -0,0 +1,185 @@
|
||||
"""
|
||||
Echo Agent - 简单的回显测试代理
|
||||
用于测试 Agent Manager 的部署功能
|
||||
"""
|
||||
import os
|
||||
import sys
|
||||
import logging
|
||||
from datetime import datetime
|
||||
from typing import Optional, Any
|
||||
|
||||
from fastapi import FastAPI
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
from pydantic import BaseModel, Field
|
||||
import uvicorn
|
||||
|
||||
# 添加 common 模块路径
|
||||
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
|
||||
|
||||
# 导入回调工具
|
||||
try:
|
||||
from common.agent_callback_utils import AgentCallbackHandler, CallbackContextManager
|
||||
CALLBACK_ENABLED = True
|
||||
except ImportError:
|
||||
CALLBACK_ENABLED = False
|
||||
AgentCallbackHandler = None
|
||||
CallbackContextManager = None
|
||||
|
||||
# 配置日志
|
||||
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# 环境变量
|
||||
SERVICE_HOST = os.getenv("SERVICE_HOST", "0.0.0.0")
|
||||
SERVICE_PORT = int(os.getenv("SERVICE_PORT", "8000"))
|
||||
POD_NAME = os.getenv("POD_NAME", "echo-agent")
|
||||
USER_ID = os.getenv("USER_ID", "")
|
||||
|
||||
# FastAPI 应用
|
||||
app = FastAPI(
|
||||
title="Echo Agent",
|
||||
description="简单的回显测试代理，用于验证 Agent Manager 部署功能",
|
||||
version="1.0.0"
|
||||
)
|
||||
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
allow_origins=["*"],
|
||||
allow_credentials=True,
|
||||
allow_methods=["*"],
|
||||
allow_headers=["*"],
|
||||
)
|
||||
|
||||
# 回调处理器
|
||||
callback_handler: Optional[AgentCallbackHandler] = None
|
||||
|
||||
|
||||
# ==================== 请求/响应模型 ====================
|
||||
|
||||
class EchoRequest(BaseModel):
|
||||
"""回显请求"""
|
||||
message: str = Field(..., description="要回显的消息")
|
||||
user_id: Optional[str] = Field(None, description="用户ID（用于计费回调）")
|
||||
metadata: Optional[dict] = Field(None, description="附加元数据")
|
||||
|
||||
|
||||
class EchoResponse(BaseModel):
|
||||
"""回显响应"""
|
||||
message: str
|
||||
echo: str
|
||||
pod_name: str
|
||||
metadata: Optional[dict] = None
|
||||
timestamp: str
|
||||
|
||||
|
||||
class HealthResponse(BaseModel):
|
||||
"""健康检查响应"""
|
||||
status: str
|
||||
pod_name: str
|
||||
version: str
|
||||
callback_enabled: bool
|
||||
timestamp: str
|
||||
|
||||
|
||||
# ==================== 生命周期 ====================
|
||||
|
||||
@app.on_event("startup")
|
||||
async def startup_event():
|
||||
"""应用启动时初始化回调处理器"""
|
||||
global callback_handler
|
||||
|
||||
if CALLBACK_ENABLED:
|
||||
callback_handler = AgentCallbackHandler(
|
||||
agent_name=POD_NAME,
|
||||
user_id=USER_ID
|
||||
)
|
||||
logger.info(f"回调处理器已初始化: callback_url={callback_handler.callback_url}")
|
||||
else:
|
||||
logger.warning("回调模块未加载，计费回调功能不可用")
|
||||
|
||||
|
||||
# ==================== API 端点 ====================
|
||||
|
||||
@app.get("/health", response_model=HealthResponse)
|
||||
@app.get("/", response_model=HealthResponse)
|
||||
async def health_check():
|
||||
"""健康检查"""
|
||||
return HealthResponse(
|
||||
status="healthy",
|
||||
pod_name=POD_NAME,
|
||||
version="1.0.0",
|
||||
callback_enabled=CALLBACK_ENABLED,
|
||||
timestamp=datetime.utcnow().isoformat()
|
||||
)
|
||||
|
||||
|
||||
@app.post("/echo", response_model=EchoResponse)
|
||||
async def echo(request: EchoRequest):
|
||||
"""回显消息"""
|
||||
logger.info(f"Echo: {request.message}")
|
||||
|
||||
# 使用回调上下文管理器
|
||||
if CALLBACK_ENABLED and callback_handler and request.user_id:
|
||||
with CallbackContextManager(
|
||||
handler=callback_handler,
|
||||
user_id=request.user_id,
|
||||
request_id=f"echo-{int(datetime.utcnow().timestamp())}"
|
||||
) as ctx:
|
||||
ctx.add_tool("echo")
|
||||
|
||||
response = EchoResponse(
|
||||
message=request.message,
|
||||
echo=f"[Echo from {POD_NAME}] {request.message}",
|
||||
pod_name=POD_NAME,
|
||||
metadata=request.metadata,
|
||||
timestamp=datetime.utcnow().isoformat()
|
||||
)
|
||||
else:
|
||||
response = EchoResponse(
|
||||
message=request.message,
|
||||
echo=f"[Echo from {POD_NAME}] {request.message}",
|
||||
pod_name=POD_NAME,
|
||||
metadata=request.metadata,
|
||||
timestamp=datetime.utcnow().isoformat()
|
||||
)
|
||||
|
||||
return response
|
||||
|
||||
|
||||
@app.get("/echo")
|
||||
async def echo_get(message: str = "Hello", user_id: Optional[str] = None):
|
||||
"""GET 方式回显"""
|
||||
return await echo(EchoRequest(message=message, user_id=user_id))
|
||||
|
||||
|
||||
@app.get("/info")
|
||||
async def get_info():
|
||||
"""获取 Agent 信息"""
|
||||
return {
|
||||
"agent_name": "Echo Agent",
|
||||
"pod_name": POD_NAME,
|
||||
"version": "1.0.0",
|
||||
"callback_enabled": CALLBACK_ENABLED,
|
||||
"callback_url": callback_handler.callback_url if callback_handler else None,
|
||||
"capabilities": ["echo", "health_check"],
|
||||
"environment": {
|
||||
"SERVICE_HOST": SERVICE_HOST,
|
||||
"SERVICE_PORT": SERVICE_PORT
|
||||
},
|
||||
"timestamp": datetime.utcnow().isoformat()
|
||||
}
|
||||
|
||||
|
||||
# ==================== 主入口 ====================
|
||||
|
||||
def main():
|
||||
"""主函数"""
|
||||
logger.info(f"启动 Echo Agent - {POD_NAME}")
|
||||
logger.info(f"服务地址: {SERVICE_HOST}:{SERVICE_PORT}")
|
||||
logger.info(f"回调功能: {'已启用' if CALLBACK_ENABLED else '未启用'}")
|
||||
|
||||
uvicorn.run(app, host=SERVICE_HOST, port=SERVICE_PORT, log_level="info")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,42 @@
|
||||
FROM python:3.11-slim
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
# 安装系统依赖
|
||||
RUN apt-get update && apt-get install -y \
|
||||
curl \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
|
||||
# 安装 Python 依赖
|
||||
RUN pip install --no-cache-dir \
|
||||
fastapi==0.109.0 \
|
||||
uvicorn[standard]==0.27.0 \
|
||||
pydantic==2.5.3 \
|
||||
requests>=2.31.0 \
|
||||
aiohttp>=3.9.0
|
||||
|
||||
# 复制 common 模块（回调工具）
|
||||
COPY common/agent_callback_utils.py /app/common/
|
||||
RUN touch /app/common/__init__.py
|
||||
|
||||
# 复制应用代码
|
||||
COPY agents/jina_search_agent/jina_search_agent.py /app/
|
||||
|
||||
# 环境变量
|
||||
ENV PYTHONUNBUFFERED=1
|
||||
ENV SERVICE_HOST=0.0.0.0
|
||||
ENV SERVICE_PORT=8080
|
||||
|
||||
# 默认 Jina API Key (硬编码)
|
||||
ENV JINA_API_KEY=jina_e26dc30420a44a1e859216528065b203TkMRmsoz-FgMDQC5FZX9jr5oF2CI
|
||||
|
||||
# 回调配置
|
||||
ENV AGENT_CALLBACK_URL=http://mcp-server:8002/api/v1/billing/agent-callback
|
||||
|
||||
# 健康检查
|
||||
HEALTHCHECK --interval=30s --timeout=10s --start-period=20s --retries=3 \
|
||||
CMD python3 -c "import urllib.request; urllib.request.urlopen('http://localhost:8080/health').read()" || exit 1
|
||||
|
||||
EXPOSE 8080
|
||||
|
||||
CMD ["python3", "-u", "jina_search_agent.py"]
|
||||
@@ -0,0 +1,320 @@
|
||||
"""
|
||||
Jina Search Agent - 使用 Jina Reader API 提取网页内容
|
||||
"""
|
||||
import os
|
||||
import sys
|
||||
import logging
|
||||
import aiohttp
|
||||
from typing import Optional, List
|
||||
from datetime import datetime
|
||||
|
||||
from fastapi import FastAPI, HTTPException, Query
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
from pydantic import BaseModel, Field
|
||||
import uvicorn
|
||||
|
||||
# 添加 common 模块路径
|
||||
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
|
||||
|
||||
# 导入回调工具
|
||||
try:
|
||||
from common.agent_callback_utils import AgentCallbackHandler, CallbackContextManager
|
||||
CALLBACK_ENABLED = True
|
||||
except ImportError:
|
||||
CALLBACK_ENABLED = False
|
||||
AgentCallbackHandler = None
|
||||
CallbackContextManager = None
|
||||
|
||||
# 配置日志
|
||||
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# 环境变量
|
||||
SERVICE_HOST = os.getenv("SERVICE_HOST", "0.0.0.0")
|
||||
SERVICE_PORT = int(os.getenv("SERVICE_PORT", "8080"))
|
||||
POD_NAME = os.getenv("POD_NAME", "jina-search-agent")
|
||||
USER_ID = os.getenv("USER_ID", "")
|
||||
JINA_API_KEY = os.getenv("JINA_API_KEY", "")
|
||||
|
||||
# Jina Reader API
|
||||
JINA_READER_URL = "https://r.jina.ai/"
|
||||
|
||||
# FastAPI 应用
|
||||
app = FastAPI(
|
||||
title="Jina Search Agent",
|
||||
description="使用 Jina Reader API 提取网页内容",
|
||||
version="1.0.0"
|
||||
)
|
||||
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
allow_origins=["*"],
|
||||
allow_credentials=True,
|
||||
allow_methods=["*"],
|
||||
allow_headers=["*"],
|
||||
)
|
||||
|
||||
# 回调处理器
|
||||
callback_handler: Optional[AgentCallbackHandler] = None
|
||||
|
||||
|
||||
# ==================== 请求/响应模型 ====================
|
||||
|
||||
class SearchRequest(BaseModel):
|
||||
"""搜索/提取请求"""
|
||||
url: str = Field(..., description="要提取内容的 URL")
|
||||
user_id: Optional[str] = Field(None, description="用户ID（用于计费回调）")
|
||||
jina_api_key: Optional[str] = Field(None, description="Jina API 密钥（可选，覆盖环境变量）")
|
||||
|
||||
|
||||
class SearchResponse(BaseModel):
|
||||
"""搜索/提取响应"""
|
||||
url: str
|
||||
title: Optional[str] = None
|
||||
content: str
|
||||
timestamp: str
|
||||
|
||||
|
||||
class BatchSearchRequest(BaseModel):
|
||||
"""批量搜索请求"""
|
||||
urls: List[str] = Field(..., description="要提取内容的 URL 列表")
|
||||
user_id: Optional[str] = Field(None, description="用户ID（用于计费回调）")
|
||||
jina_api_key: Optional[str] = Field(None, description="Jina API 密钥（可选）")
|
||||
|
||||
|
||||
class BatchSearchResponse(BaseModel):
|
||||
"""批量搜索响应"""
|
||||
results: List[SearchResponse]
|
||||
success_count: int
|
||||
failed_count: int
|
||||
timestamp: str
|
||||
|
||||
|
||||
class HealthResponse(BaseModel):
|
||||
"""健康检查响应"""
|
||||
status: str
|
||||
pod_name: str
|
||||
jina_api_configured: bool
|
||||
callback_enabled: bool
|
||||
timestamp: str
|
||||
|
||||
|
||||
# ==================== 生命周期 ====================
|
||||
|
||||
@app.on_event("startup")
|
||||
async def startup_event():
|
||||
"""应用启动时初始化回调处理器"""
|
||||
global callback_handler
|
||||
|
||||
if CALLBACK_ENABLED:
|
||||
callback_handler = AgentCallbackHandler(
|
||||
agent_name=POD_NAME,
|
||||
user_id=USER_ID
|
||||
)
|
||||
logger.info(f"回调处理器已初始化: callback_url={callback_handler.callback_url}")
|
||||
else:
|
||||
logger.warning("回调模块未加载，计费回调功能不可用")
|
||||
|
||||
|
||||
# ==================== 辅助函数 ====================
|
||||
|
||||
async def fetch_url_content(url: str, api_key: str) -> dict:
|
||||
"""使用 Jina Reader API 提取 URL 内容"""
|
||||
headers = {
|
||||
"Authorization": f"Bearer {api_key}",
|
||||
"Accept": "application/json"
|
||||
}
|
||||
|
||||
jina_url = f"{JINA_READER_URL}{url}"
|
||||
|
||||
try:
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(jina_url, headers=headers, timeout=30) as response:
|
||||
if response.status == 200:
|
||||
text = await response.text()
|
||||
return {
|
||||
"success": True,
|
||||
"url": url,
|
||||
"content": text,
|
||||
"title": None # Jina Reader 返回的是纯文本
|
||||
}
|
||||
else:
|
||||
error_text = await response.text()
|
||||
logger.warning(f"Jina Reader 请求失败 [{response.status}]: {url}")
|
||||
return {
|
||||
"success": False,
|
||||
"url": url,
|
||||
"error": f"HTTP {response.status}: {error_text[:200]}"
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"提取内容失败: {url} - {e}")
|
||||
return {
|
||||
"success": False,
|
||||
"url": url,
|
||||
"error": str(e)
|
||||
}
|
||||
|
||||
|
||||
# ==================== API 端点 ====================
|
||||
|
||||
@app.get("/health", response_model=HealthResponse)
|
||||
@app.get("/", response_model=HealthResponse)
|
||||
async def health_check():
|
||||
"""健康检查"""
|
||||
return HealthResponse(
|
||||
status="healthy",
|
||||
pod_name=POD_NAME,
|
||||
jina_api_configured=bool(JINA_API_KEY),
|
||||
callback_enabled=CALLBACK_ENABLED,
|
||||
timestamp=datetime.utcnow().isoformat()
|
||||
)
|
||||
|
||||
|
||||
@app.post("/search", response_model=SearchResponse)
|
||||
@app.post("/fetch", response_model=SearchResponse)
|
||||
async def fetch_content(request: SearchRequest):
|
||||
"""提取单个 URL 的内容"""
|
||||
api_key = request.jina_api_key or JINA_API_KEY
|
||||
|
||||
if not api_key:
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail="Jina API key 未设置。请在请求中传入 jina_api_key 或设置环境变量 JINA_API_KEY"
|
||||
)
|
||||
|
||||
# 使用回调上下文管理器
|
||||
if CALLBACK_ENABLED and callback_handler and request.user_id:
|
||||
with CallbackContextManager(
|
||||
handler=callback_handler,
|
||||
user_id=request.user_id,
|
||||
request_id=f"jina-fetch-{int(datetime.utcnow().timestamp())}"
|
||||
) as ctx:
|
||||
ctx.add_tool("jina_reader")
|
||||
ctx.add_tool("web_content_extraction")
|
||||
|
||||
result = await fetch_url_content(request.url, api_key)
|
||||
|
||||
if not result["success"]:
|
||||
raise HTTPException(
|
||||
status_code=500,
|
||||
detail=f"提取内容失败: {result.get('error', '未知错误')}"
|
||||
)
|
||||
|
||||
return SearchResponse(
|
||||
url=result["url"],
|
||||
title=result.get("title"),
|
||||
content=result["content"],
|
||||
timestamp=datetime.utcnow().isoformat()
|
||||
)
|
||||
else:
|
||||
result = await fetch_url_content(request.url, api_key)
|
||||
|
||||
if not result["success"]:
|
||||
raise HTTPException(
|
||||
status_code=500,
|
||||
detail=f"提取内容失败: {result.get('error', '未知错误')}"
|
||||
)
|
||||
|
||||
return SearchResponse(
|
||||
url=result["url"],
|
||||
title=result.get("title"),
|
||||
content=result["content"],
|
||||
timestamp=datetime.utcnow().isoformat()
|
||||
)
|
||||
|
||||
|
||||
@app.get("/search")
|
||||
@app.get("/fetch")
|
||||
async def fetch_content_get(
|
||||
url: str = Query(..., description="要提取内容的 URL"),
|
||||
user_id: Optional[str] = Query(None, description="用户ID（用于计费回调）"),
|
||||
jina_api_key: Optional[str] = Query(None, description="Jina API 密钥")
|
||||
):
|
||||
"""GET 方式提取内容"""
|
||||
request = SearchRequest(url=url, user_id=user_id, jina_api_key=jina_api_key)
|
||||
return await fetch_content(request)
|
||||
|
||||
|
||||
@app.post("/batch", response_model=BatchSearchResponse)
|
||||
async def batch_fetch_content(request: BatchSearchRequest):
|
||||
"""批量提取多个 URL 的内容"""
|
||||
api_key = request.jina_api_key or JINA_API_KEY
|
||||
|
||||
if not api_key:
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail="Jina API key 未设置"
|
||||
)
|
||||
|
||||
# 使用回调上下文管理器
|
||||
if CALLBACK_ENABLED and callback_handler and request.user_id:
|
||||
with CallbackContextManager(
|
||||
handler=callback_handler,
|
||||
user_id=request.user_id,
|
||||
request_id=f"jina-batch-{int(datetime.utcnow().timestamp())}"
|
||||
) as ctx:
|
||||
ctx.add_tool("jina_reader")
|
||||
ctx.add_tool("batch_web_extraction")
|
||||
|
||||
results = []
|
||||
success_count = 0
|
||||
failed_count = 0
|
||||
|
||||
for url in request.urls:
|
||||
result = await fetch_url_content(url, api_key)
|
||||
if result["success"]:
|
||||
results.append(SearchResponse(
|
||||
url=result["url"],
|
||||
title=result.get("title"),
|
||||
content=result["content"],
|
||||
timestamp=datetime.utcnow().isoformat()
|
||||
))
|
||||
success_count += 1
|
||||
else:
|
||||
failed_count += 1
|
||||
|
||||
return BatchSearchResponse(
|
||||
results=results,
|
||||
success_count=success_count,
|
||||
failed_count=failed_count,
|
||||
timestamp=datetime.utcnow().isoformat()
|
||||
)
|
||||
else:
|
||||
results = []
|
||||
success_count = 0
|
||||
failed_count = 0
|
||||
|
||||
for url in request.urls:
|
||||
result = await fetch_url_content(url, api_key)
|
||||
if result["success"]:
|
||||
results.append(SearchResponse(
|
||||
url=result["url"],
|
||||
title=result.get("title"),
|
||||
content=result["content"],
|
||||
timestamp=datetime.utcnow().isoformat()
|
||||
))
|
||||
success_count += 1
|
||||
else:
|
||||
failed_count += 1
|
||||
|
||||
return BatchSearchResponse(
|
||||
results=results,
|
||||
success_count=success_count,
|
||||
failed_count=failed_count,
|
||||
timestamp=datetime.utcnow().isoformat()
|
||||
)
|
||||
|
||||
|
||||
# ==================== 主入口 ====================
|
||||
|
||||
def main():
|
||||
"""主函数"""
|
||||
logger.info(f"启动 Jina Search Agent - {POD_NAME}")
|
||||
logger.info(f"Jina API Key: {'已配置' if JINA_API_KEY else '未配置'}")
|
||||
logger.info(f"回调功能: {'已启用' if CALLBACK_ENABLED else '未启用'}")
|
||||
|
||||
uvicorn.run(app, host=SERVICE_HOST, port=SERVICE_PORT, log_level="info")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,46 @@
|
||||
FROM python:3.11-slim
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
# 安装系统依赖
|
||||
RUN apt-get update && apt-get install -y \
|
||||
curl \
|
||||
default-libmysqlclient-dev \
|
||||
build-essential \
|
||||
pkg-config \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
|
||||
# 安装 Python 依赖
|
||||
RUN pip install --no-cache-dir \
|
||||
fastapi==0.109.0 \
|
||||
uvicorn[standard]==0.27.0 \
|
||||
pydantic==2.5.3 \
|
||||
requests>=2.31.0 \
|
||||
langchain>=0.1.0 \
|
||||
langchain-community>=0.0.10 \
|
||||
langchain-openai>=0.0.2 \
|
||||
pymysql>=1.1.0 \
|
||||
cryptography>=41.0.0
|
||||
|
||||
# 复制 common 模块（回调工具）
|
||||
COPY common/agent_callback_utils.py /app/common/
|
||||
RUN touch /app/common/__init__.py
|
||||
|
||||
# 复制应用代码
|
||||
COPY agents/mysql_agent/mysql_agent.py /app/
|
||||
|
||||
# 环境变量
|
||||
ENV PYTHONUNBUFFERED=1
|
||||
ENV SERVICE_HOST=0.0.0.0
|
||||
ENV SERVICE_PORT=8000
|
||||
|
||||
# 回调配置
|
||||
ENV AGENT_CALLBACK_URL=http://mcp-server:8002/api/v1/billing/agent-callback
|
||||
|
||||
# 健康检查
|
||||
HEALTHCHECK --interval=30s --timeout=10s --start-period=30s --retries=3 \
|
||||
CMD python3 -c "import urllib.request; urllib.request.urlopen('http://localhost:8000/health').read()" || exit 1
|
||||
|
||||
EXPOSE 8000
|
||||
|
||||
CMD ["python3", "-u", "mysql_agent.py"]
|
||||
@@ -0,0 +1,289 @@
|
||||
"""
|
||||
MySQL Database Agent - 基于 LangChain 的 MySQL 数据库查询代理
|
||||
"""
|
||||
import os
|
||||
import sys
|
||||
import logging
|
||||
from typing import Optional
|
||||
from datetime import datetime
|
||||
|
||||
from fastapi import FastAPI, HTTPException
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
from pydantic import BaseModel, Field
|
||||
import uvicorn
|
||||
|
||||
# 添加 common 模块路径
|
||||
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
|
||||
|
||||
# 导入回调工具
|
||||
try:
|
||||
from common.agent_callback_utils import AgentCallbackHandler, CallbackContextManager
|
||||
CALLBACK_ENABLED = True
|
||||
except ImportError:
|
||||
CALLBACK_ENABLED = False
|
||||
AgentCallbackHandler = None
|
||||
CallbackContextManager = None
|
||||
|
||||
# 配置日志
|
||||
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# 环境变量
|
||||
SERVICE_HOST = os.getenv("SERVICE_HOST", "0.0.0.0")
|
||||
SERVICE_PORT = int(os.getenv("SERVICE_PORT", "8000"))
|
||||
POD_NAME = os.getenv("POD_NAME", "mysql-agent")
|
||||
USER_ID = os.getenv("USER_ID", "")
|
||||
|
||||
# MySQL 配置
|
||||
MYSQL_HOST = os.getenv("MYSQL_HOST", "")
|
||||
MYSQL_PORT = int(os.getenv("MYSQL_PORT", "3306"))
|
||||
MYSQL_USER = os.getenv("MYSQL_USER", "")
|
||||
MYSQL_PASSWORD = os.getenv("MYSQL_PASSWORD", "")
|
||||
MYSQL_DATABASE = os.getenv("MYSQL_DATABASE", "")
|
||||
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY", "")
|
||||
MODEL_NAME = os.getenv("MODEL_NAME", "gpt-3.5-turbo")
|
||||
|
||||
# FastAPI 应用
|
||||
app = FastAPI(
|
||||
title="MySQL Database Agent",
|
||||
description="基于 LangChain 的 MySQL 数据库查询代理",
|
||||
version="1.0.0"
|
||||
)
|
||||
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
allow_origins=["*"],
|
||||
allow_credentials=True,
|
||||
allow_methods=["*"],
|
||||
allow_headers=["*"],
|
||||
)
|
||||
|
||||
|
||||
# ==================== 请求/响应模型 ====================
|
||||
|
||||
class QueryRequest(BaseModel):
|
||||
"""查询请求"""
|
||||
query: str = Field(..., description="自然语言查询")
|
||||
user_id: Optional[str] = Field(None, description="用户ID（用于计费回调）")
|
||||
openai_api_key: Optional[str] = Field(None, description="OpenAI API 密钥（可选，覆盖环境变量）")
|
||||
|
||||
|
||||
class QueryResponse(BaseModel):
|
||||
"""查询响应"""
|
||||
query: str
|
||||
result: str
|
||||
sql: Optional[str] = None
|
||||
timestamp: str
|
||||
|
||||
|
||||
class ConnectRequest(BaseModel):
|
||||
"""连接请求"""
|
||||
host: str = Field(..., description="MySQL 主机地址")
|
||||
port: int = Field(default=3306, description="MySQL 端口")
|
||||
user: str = Field(..., description="MySQL 用户名")
|
||||
password: str = Field(..., description="MySQL 密码")
|
||||
database: str = Field(..., description="数据库名")
|
||||
|
||||
|
||||
class HealthResponse(BaseModel):
|
||||
"""健康检查响应"""
|
||||
status: str
|
||||
pod_name: str
|
||||
connected: bool
|
||||
callback_enabled: bool
|
||||
database: Optional[str] = None
|
||||
timestamp: str
|
||||
|
||||
|
||||
# ==================== 全局变量 ====================
|
||||
|
||||
db_agent = None
|
||||
db_connection_info = None
|
||||
callback_handler: Optional[AgentCallbackHandler] = None
|
||||
|
||||
|
||||
# ==================== 生命周期 ====================
|
||||
|
||||
@app.on_event("startup")
|
||||
async def startup_event():
|
||||
"""应用启动时初始化"""
|
||||
global callback_handler
|
||||
|
||||
if CALLBACK_ENABLED:
|
||||
callback_handler = AgentCallbackHandler(
|
||||
agent_name=POD_NAME,
|
||||
user_id=USER_ID
|
||||
)
|
||||
logger.info(f"回调处理器已初始化: callback_url={callback_handler.callback_url}")
|
||||
else:
|
||||
logger.warning("回调模块未加载，计费回调功能不可用")
|
||||
|
||||
# 尝试自动连接
|
||||
if all([MYSQL_HOST, MYSQL_USER, MYSQL_PASSWORD, MYSQL_DATABASE, OPENAI_API_KEY]):
|
||||
try:
|
||||
create_db_agent(
|
||||
host=MYSQL_HOST,
|
||||
port=MYSQL_PORT,
|
||||
user=MYSQL_USER,
|
||||
password=MYSQL_PASSWORD,
|
||||
database=MYSQL_DATABASE,
|
||||
api_key=OPENAI_API_KEY
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning(f"自动连接失败: {e}")
|
||||
|
||||
|
||||
# ==================== 辅助函数 ====================
|
||||
|
||||
def create_db_agent(host: str, port: int, user: str, password: str, database: str, api_key: str):
|
||||
"""创建数据库 Agent"""
|
||||
global db_agent, db_connection_info
|
||||
|
||||
try:
|
||||
from langchain_community.utilities import SQLDatabase
|
||||
from langchain_community.agent_toolkits import create_sql_agent
|
||||
from langchain_openai import ChatOpenAI
|
||||
|
||||
# 创建数据库连接
|
||||
db_uri = f"mysql+pymysql://{user}:{password}@{host}:{port}/{database}"
|
||||
db = SQLDatabase.from_uri(db_uri)
|
||||
|
||||
# 创建 LLM
|
||||
llm = ChatOpenAI(
|
||||
model=MODEL_NAME,
|
||||
temperature=0,
|
||||
openai_api_key=api_key
|
||||
)
|
||||
|
||||
# 创建 SQL Agent
|
||||
db_agent = create_sql_agent(llm, db=db, agent_type="openai-tools", verbose=True)
|
||||
db_connection_info = {"host": host, "port": port, "database": database}
|
||||
|
||||
logger.info(f"MySQL Agent 连接成功: {host}:{port}/{database}")
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.error(f"创建 MySQL Agent 失败: {e}")
|
||||
raise
|
||||
|
||||
|
||||
# ==================== API 端点 ====================
|
||||
|
||||
@app.get("/health", response_model=HealthResponse)
|
||||
@app.get("/", response_model=HealthResponse)
|
||||
async def health_check():
|
||||
"""健康检查"""
|
||||
return HealthResponse(
|
||||
status="healthy",
|
||||
pod_name=POD_NAME,
|
||||
connected=db_agent is not None,
|
||||
callback_enabled=CALLBACK_ENABLED,
|
||||
database=db_connection_info.get("database") if db_connection_info else None,
|
||||
timestamp=datetime.utcnow().isoformat()
|
||||
)
|
||||
|
||||
|
||||
@app.post("/connect")
|
||||
async def connect_database(request: ConnectRequest):
|
||||
"""连接数据库"""
|
||||
api_key = OPENAI_API_KEY
|
||||
if not api_key:
|
||||
raise HTTPException(status_code=400, detail="OPENAI_API_KEY 未设置")
|
||||
|
||||
try:
|
||||
create_db_agent(
|
||||
host=request.host,
|
||||
port=request.port,
|
||||
user=request.user,
|
||||
password=request.password,
|
||||
database=request.database,
|
||||
api_key=api_key
|
||||
)
|
||||
return {
|
||||
"status": "connected",
|
||||
"database": request.database,
|
||||
"timestamp": datetime.utcnow().isoformat()
|
||||
}
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
@app.post("/query", response_model=QueryResponse)
|
||||
async def query_database(request: QueryRequest):
|
||||
"""执行自然语言查询"""
|
||||
global db_agent
|
||||
|
||||
# 获取 API key - 优先使用请求中的
|
||||
api_key = request.openai_api_key or OPENAI_API_KEY
|
||||
if not api_key:
|
||||
raise HTTPException(status_code=400, detail="OPENAI_API_KEY 未设置，请在请求中传入 openai_api_key 或设置环境变量")
|
||||
|
||||
# 如果未连接，尝试使用环境变量连接
|
||||
if db_agent is None:
|
||||
if not all([MYSQL_HOST, MYSQL_USER, MYSQL_PASSWORD, MYSQL_DATABASE]):
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail="数据库未连接。请先调用 /connect 或设置环境变量"
|
||||
)
|
||||
|
||||
create_db_agent(
|
||||
host=MYSQL_HOST,
|
||||
port=MYSQL_PORT,
|
||||
user=MYSQL_USER,
|
||||
password=MYSQL_PASSWORD,
|
||||
database=MYSQL_DATABASE,
|
||||
api_key=api_key
|
||||
)
|
||||
elif request.openai_api_key:
|
||||
# 如果请求中提供了新的 API key，重新创建 agent
|
||||
logger.info(f"使用请求中的 OpenAI API Key 重新初始化 Agent...")
|
||||
create_db_agent(
|
||||
host=db_connection_info["host"],
|
||||
port=db_connection_info["port"],
|
||||
user=MYSQL_USER,
|
||||
password=MYSQL_PASSWORD,
|
||||
database=db_connection_info["database"],
|
||||
api_key=api_key
|
||||
)
|
||||
|
||||
try:
|
||||
# 使用回调上下文管理器
|
||||
if CALLBACK_ENABLED and callback_handler and request.user_id:
|
||||
with CallbackContextManager(
|
||||
handler=callback_handler,
|
||||
user_id=request.user_id,
|
||||
request_id=f"mysql-query-{int(datetime.utcnow().timestamp())}"
|
||||
) as ctx:
|
||||
ctx.add_tool("mysql_query")
|
||||
ctx.add_tool("sql_agent")
|
||||
|
||||
result = db_agent.invoke({"input": request.query})
|
||||
|
||||
return QueryResponse(
|
||||
query=request.query,
|
||||
result=result.get("output", str(result)),
|
||||
timestamp=datetime.utcnow().isoformat()
|
||||
)
|
||||
else:
|
||||
result = db_agent.invoke({"input": request.query})
|
||||
return QueryResponse(
|
||||
query=request.query,
|
||||
result=result.get("output", str(result)),
|
||||
timestamp=datetime.utcnow().isoformat()
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"查询失败: {e}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
# ==================== 主入口 ====================
|
||||
|
||||
def main():
|
||||
"""主函数"""
|
||||
logger.info(f"启动 MySQL Agent - {POD_NAME}")
|
||||
logger.info(f"回调功能: {'已启用' if CALLBACK_ENABLED else '未启用'}")
|
||||
|
||||
uvicorn.run(app, host=SERVICE_HOST, port=SERVICE_PORT, log_level="info")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,44 @@
|
||||
FROM python:3.11-slim
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
# 安装系统依赖
|
||||
RUN apt-get update && apt-get install -y \
|
||||
curl \
|
||||
libpq-dev \
|
||||
build-essential \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
|
||||
# 安装 Python 依赖
|
||||
RUN pip install --no-cache-dir \
|
||||
fastapi==0.109.0 \
|
||||
uvicorn[standard]==0.27.0 \
|
||||
pydantic==2.5.3 \
|
||||
requests>=2.31.0 \
|
||||
langchain>=0.1.0 \
|
||||
langchain-community>=0.0.10 \
|
||||
langchain-openai>=0.0.2 \
|
||||
psycopg2-binary>=2.9.9
|
||||
|
||||
# 复制 common 模块（回调工具）
|
||||
COPY common/agent_callback_utils.py /app/common/
|
||||
RUN touch /app/common/__init__.py
|
||||
|
||||
# 复制应用代码
|
||||
COPY agents/postgresql_agent/postgresql_agent.py /app/
|
||||
|
||||
# 环境变量
|
||||
ENV PYTHONUNBUFFERED=1
|
||||
ENV SERVICE_HOST=0.0.0.0
|
||||
ENV SERVICE_PORT=8000
|
||||
|
||||
# 回调配置
|
||||
ENV AGENT_CALLBACK_URL=http://mcp-server:8002/api/v1/billing/agent-callback
|
||||
|
||||
# 健康检查
|
||||
HEALTHCHECK --interval=30s --timeout=10s --start-period=30s --retries=3 \
|
||||
CMD python3 -c "import urllib.request; urllib.request.urlopen('http://localhost:8000/health').read()" || exit 1
|
||||
|
||||
EXPOSE 8000
|
||||
|
||||
CMD ["python3", "-u", "postgresql_agent.py"]
|
||||
@@ -0,0 +1,289 @@
|
||||
"""
|
||||
PostgreSQL Database Agent - 基于 LangChain 的 PostgreSQL 数据库查询代理
|
||||
"""
|
||||
import os
|
||||
import sys
|
||||
import logging
|
||||
from typing import Optional
|
||||
from datetime import datetime
|
||||
|
||||
from fastapi import FastAPI, HTTPException
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
from pydantic import BaseModel, Field
|
||||
import uvicorn
|
||||
|
||||
# 添加 common 模块路径
|
||||
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
|
||||
|
||||
# 导入回调工具
|
||||
try:
|
||||
from common.agent_callback_utils import AgentCallbackHandler, CallbackContextManager
|
||||
CALLBACK_ENABLED = True
|
||||
except ImportError:
|
||||
CALLBACK_ENABLED = False
|
||||
AgentCallbackHandler = None
|
||||
CallbackContextManager = None
|
||||
|
||||
# 配置日志
|
||||
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# 环境变量
|
||||
SERVICE_HOST = os.getenv("SERVICE_HOST", "0.0.0.0")
|
||||
SERVICE_PORT = int(os.getenv("SERVICE_PORT", "8000"))
|
||||
POD_NAME = os.getenv("POD_NAME", "postgresql-agent")
|
||||
USER_ID = os.getenv("USER_ID", "")
|
||||
|
||||
# PostgreSQL 配置
|
||||
POSTGRES_HOST = os.getenv("POSTGRES_HOST", "")
|
||||
POSTGRES_PORT = int(os.getenv("POSTGRES_PORT", "5432"))
|
||||
POSTGRES_USER = os.getenv("POSTGRES_USER", "")
|
||||
POSTGRES_PASSWORD = os.getenv("POSTGRES_PASSWORD", "")
|
||||
POSTGRES_DATABASE = os.getenv("POSTGRES_DATABASE", "")
|
||||
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY", "")
|
||||
MODEL_NAME = os.getenv("MODEL_NAME", "gpt-3.5-turbo")
|
||||
|
||||
# FastAPI 应用
|
||||
app = FastAPI(
|
||||
title="PostgreSQL Database Agent",
|
||||
description="基于 LangChain 的 PostgreSQL 数据库查询代理",
|
||||
version="1.0.0"
|
||||
)
|
||||
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
allow_origins=["*"],
|
||||
allow_credentials=True,
|
||||
allow_methods=["*"],
|
||||
allow_headers=["*"],
|
||||
)
|
||||
|
||||
|
||||
# ==================== 请求/响应模型 ====================
|
||||
|
||||
class QueryRequest(BaseModel):
|
||||
"""查询请求"""
|
||||
query: str = Field(..., description="自然语言查询")
|
||||
user_id: Optional[str] = Field(None, description="用户ID（用于计费回调）")
|
||||
openai_api_key: Optional[str] = Field(None, description="OpenAI API 密钥（可选，覆盖环境变量）")
|
||||
|
||||
|
||||
class QueryResponse(BaseModel):
|
||||
"""查询响应"""
|
||||
query: str
|
||||
result: str
|
||||
sql: Optional[str] = None
|
||||
timestamp: str
|
||||
|
||||
|
||||
class ConnectRequest(BaseModel):
|
||||
"""连接请求"""
|
||||
host: str = Field(..., description="PostgreSQL 主机地址")
|
||||
port: int = Field(default=5432, description="PostgreSQL 端口")
|
||||
user: str = Field(..., description="PostgreSQL 用户名")
|
||||
password: str = Field(..., description="PostgreSQL 密码")
|
||||
database: str = Field(..., description="数据库名")
|
||||
|
||||
|
||||
class HealthResponse(BaseModel):
|
||||
"""健康检查响应"""
|
||||
status: str
|
||||
pod_name: str
|
||||
connected: bool
|
||||
callback_enabled: bool
|
||||
database: Optional[str] = None
|
||||
timestamp: str
|
||||
|
||||
|
||||
# ==================== 全局变量 ====================
|
||||
|
||||
db_agent = None
|
||||
db_connection_info = None
|
||||
callback_handler: Optional[AgentCallbackHandler] = None
|
||||
|
||||
|
||||
# ==================== 生命周期 ====================
|
||||
|
||||
@app.on_event("startup")
|
||||
async def startup_event():
|
||||
"""应用启动时初始化"""
|
||||
global callback_handler
|
||||
|
||||
if CALLBACK_ENABLED:
|
||||
callback_handler = AgentCallbackHandler(
|
||||
agent_name=POD_NAME,
|
||||
user_id=USER_ID
|
||||
)
|
||||
logger.info(f"回调处理器已初始化: callback_url={callback_handler.callback_url}")
|
||||
else:
|
||||
logger.warning("回调模块未加载，计费回调功能不可用")
|
||||
|
||||
# 尝试自动连接
|
||||
if all([POSTGRES_HOST, POSTGRES_USER, POSTGRES_PASSWORD, POSTGRES_DATABASE, OPENAI_API_KEY]):
|
||||
try:
|
||||
create_db_agent(
|
||||
host=POSTGRES_HOST,
|
||||
port=POSTGRES_PORT,
|
||||
user=POSTGRES_USER,
|
||||
password=POSTGRES_PASSWORD,
|
||||
database=POSTGRES_DATABASE,
|
||||
api_key=OPENAI_API_KEY
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning(f"自动连接失败: {e}")
|
||||
|
||||
|
||||
# ==================== 辅助函数 ====================
|
||||
|
||||
def create_db_agent(host: str, port: int, user: str, password: str, database: str, api_key: str):
|
||||
"""创建数据库 Agent"""
|
||||
global db_agent, db_connection_info
|
||||
|
||||
try:
|
||||
from langchain_community.utilities import SQLDatabase
|
||||
from langchain_community.agent_toolkits import create_sql_agent
|
||||
from langchain_openai import ChatOpenAI
|
||||
|
||||
# 创建数据库连接
|
||||
db_uri = f"postgresql+psycopg2://{user}:{password}@{host}:{port}/{database}"
|
||||
db = SQLDatabase.from_uri(db_uri)
|
||||
|
||||
# 创建 LLM
|
||||
llm = ChatOpenAI(
|
||||
model=MODEL_NAME,
|
||||
temperature=0,
|
||||
openai_api_key=api_key
|
||||
)
|
||||
|
||||
# 创建 SQL Agent
|
||||
db_agent = create_sql_agent(llm, db=db, agent_type="openai-tools", verbose=True)
|
||||
db_connection_info = {"host": host, "port": port, "database": database}
|
||||
|
||||
logger.info(f"PostgreSQL Agent 连接成功: {host}:{port}/{database}")
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.error(f"创建 PostgreSQL Agent 失败: {e}")
|
||||
raise
|
||||
|
||||
|
||||
# ==================== API 端点 ====================
|
||||
|
||||
@app.get("/health", response_model=HealthResponse)
|
||||
@app.get("/", response_model=HealthResponse)
|
||||
async def health_check():
|
||||
"""健康检查"""
|
||||
return HealthResponse(
|
||||
status="healthy",
|
||||
pod_name=POD_NAME,
|
||||
connected=db_agent is not None,
|
||||
callback_enabled=CALLBACK_ENABLED,
|
||||
database=db_connection_info.get("database") if db_connection_info else None,
|
||||
timestamp=datetime.utcnow().isoformat()
|
||||
)
|
||||
|
||||
|
||||
@app.post("/connect")
|
||||
async def connect_database(request: ConnectRequest):
|
||||
"""连接数据库"""
|
||||
api_key = OPENAI_API_KEY
|
||||
if not api_key:
|
||||
raise HTTPException(status_code=400, detail="OPENAI_API_KEY 未设置")
|
||||
|
||||
try:
|
||||
create_db_agent(
|
||||
host=request.host,
|
||||
port=request.port,
|
||||
user=request.user,
|
||||
password=request.password,
|
||||
database=request.database,
|
||||
api_key=api_key
|
||||
)
|
||||
return {
|
||||
"status": "connected",
|
||||
"database": request.database,
|
||||
"timestamp": datetime.utcnow().isoformat()
|
||||
}
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
@app.post("/query", response_model=QueryResponse)
|
||||
async def query_database(request: QueryRequest):
|
||||
"""执行自然语言查询"""
|
||||
global db_agent
|
||||
|
||||
# 获取 API key - 优先使用请求中的
|
||||
api_key = request.openai_api_key or OPENAI_API_KEY
|
||||
if not api_key:
|
||||
raise HTTPException(status_code=400, detail="OPENAI_API_KEY 未设置，请在请求中传入 openai_api_key 或设置环境变量")
|
||||
|
||||
# 如果未连接，尝试使用环境变量连接
|
||||
if db_agent is None:
|
||||
if not all([POSTGRES_HOST, POSTGRES_USER, POSTGRES_PASSWORD, POSTGRES_DATABASE]):
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail="数据库未连接。请先调用 /connect 或设置环境变量"
|
||||
)
|
||||
|
||||
create_db_agent(
|
||||
host=POSTGRES_HOST,
|
||||
port=POSTGRES_PORT,
|
||||
user=POSTGRES_USER,
|
||||
password=POSTGRES_PASSWORD,
|
||||
database=POSTGRES_DATABASE,
|
||||
api_key=api_key
|
||||
)
|
||||
elif request.openai_api_key:
|
||||
# 如果请求中提供了新的 API key，重新创建 agent
|
||||
logger.info(f"使用请求中的 OpenAI API Key 重新初始化 Agent...")
|
||||
create_db_agent(
|
||||
host=db_connection_info["host"],
|
||||
port=db_connection_info["port"],
|
||||
user=POSTGRES_USER,
|
||||
password=POSTGRES_PASSWORD,
|
||||
database=db_connection_info["database"],
|
||||
api_key=api_key
|
||||
)
|
||||
|
||||
try:
|
||||
# 使用回调上下文管理器
|
||||
if CALLBACK_ENABLED and callback_handler and request.user_id:
|
||||
with CallbackContextManager(
|
||||
handler=callback_handler,
|
||||
user_id=request.user_id,
|
||||
request_id=f"postgresql-query-{int(datetime.utcnow().timestamp())}"
|
||||
) as ctx:
|
||||
ctx.add_tool("postgresql_query")
|
||||
ctx.add_tool("sql_agent")
|
||||
|
||||
result = db_agent.invoke({"input": request.query})
|
||||
|
||||
return QueryResponse(
|
||||
query=request.query,
|
||||
result=result.get("output", str(result)),
|
||||
timestamp=datetime.utcnow().isoformat()
|
||||
)
|
||||
else:
|
||||
result = db_agent.invoke({"input": request.query})
|
||||
return QueryResponse(
|
||||
query=request.query,
|
||||
result=result.get("output", str(result)),
|
||||
timestamp=datetime.utcnow().isoformat()
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"查询失败: {e}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
# ==================== 主入口 ====================
|
||||
|
||||
def main():
|
||||
"""主函数"""
|
||||
logger.info(f"启动 PostgreSQL Agent - {POD_NAME}")
|
||||
logger.info(f"回调功能: {'已启用' if CALLBACK_ENABLED else '未启用'}")
|
||||
|
||||
uvicorn.run(app, host=SERVICE_HOST, port=SERVICE_PORT, log_level="info")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,185 @@
|
||||
# 智能搜索AI Agent API接口文档
|
||||
|
||||
## 基础信息
|
||||
|
||||
- **服务名称**: Intelligent Search AI Agent
|
||||
- **版本**: 1.0.0
|
||||
- **基础URL**: `域名`
|
||||
- **Content-Type**: `application/json`
|
||||
|
||||
---
|
||||
|
||||
## 核心接口
|
||||
|
||||
### 执行搜索
|
||||
|
||||
#### POST /search
|
||||
|
||||
执行智能搜索，根据查询返回答案和相关来源。
|
||||
|
||||
**请求参数**:
|
||||
|
||||
| 字段 | 类型 | 必填 | 说明 |
|
||||
|------|------|------|------|
|
||||
| query | string | 是 | 搜索查询 |
|
||||
| llm_api_key | string | 是 | LLM API密钥（用户的API密钥） |
|
||||
| user_id | string | 否 | 用户ID（用于计费回调） |
|
||||
|
||||
**请求示例**:
|
||||
```json
|
||||
{
|
||||
"query": "什么是人工智能？",
|
||||
"llm_api_key": "your-llm-api-key",
|
||||
"user_id": "user123"
|
||||
}
|
||||
```
|
||||
|
||||
**响应示例**:
|
||||
```json
|
||||
{
|
||||
"query": "什么是人工智能？",
|
||||
"answer": "人工智能（AI）是计算机科学的一个分支，致力于创建能够执行通常需要人类智能的任务的系统...",
|
||||
"sources": [
|
||||
{
|
||||
"index": 1,
|
||||
"title": "人工智能 - 维基百科",
|
||||
"url": "https://zh.wikipedia.org/wiki/人工智能"
|
||||
},
|
||||
{
|
||||
"index": 2,
|
||||
"title": "什么是AI？",
|
||||
"url": "https://example.com/ai-introduction"
|
||||
}
|
||||
],
|
||||
"confidence": "high",
|
||||
"iterations": 2,
|
||||
"total_sources": 5,
|
||||
"search_queries": [
|
||||
"什么是人工智能",
|
||||
"AI定义"
|
||||
],
|
||||
"timestamp": "2024-01-01T00:00:00.000000"
|
||||
}
|
||||
```
|
||||
|
||||
**响应字段说明**:
|
||||
|
||||
| 字段 | 类型 | 说明 |
|
||||
|------|------|------|
|
||||
| query | string | 原始查询 |
|
||||
| answer | string | 生成的答案内容（Markdown格式） |
|
||||
| sources | array | 来源列表 |
|
||||
| sources[].index | integer | 来源索引 |
|
||||
| sources[].title | string | 来源标题 |
|
||||
| sources[].url | string | 来源URL |
|
||||
| confidence | string | 置信度："high" / "medium" / "low" |
|
||||
| iterations | integer | 迭代次数 |
|
||||
| total_sources | integer | 参考来源总数 |
|
||||
| search_queries | array[string] | 使用的搜索查询列表 |
|
||||
| timestamp | string | 时间戳（ISO格式） |
|
||||
|
||||
**错误响应**:
|
||||
|
||||
400 Bad Request（参数错误）:
|
||||
```json
|
||||
{
|
||||
"detail": "llm_api_key 是必须的参数"
|
||||
}
|
||||
```
|
||||
|
||||
500 Internal Server Error（服务器错误）:
|
||||
```json
|
||||
{
|
||||
"detail": "搜索失败: {错误详情}"
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### 聊天接口
|
||||
|
||||
#### POST /chat
|
||||
|
||||
聊天接口，是 `/search` 接口的别名，功能和参数完全相同。
|
||||
|
||||
**请求参数**: 与 `/search` 接口相同
|
||||
|
||||
**请求示例**: 与 `/search` 接口相同
|
||||
|
||||
**响应示例**: 与 `/search` 接口相同
|
||||
|
||||
---
|
||||
|
||||
## 其他接口
|
||||
|
||||
### 健康检查
|
||||
|
||||
#### GET /health
|
||||
|
||||
检查服务健康状态。
|
||||
|
||||
**请求示例**:
|
||||
```
|
||||
GET /health
|
||||
```
|
||||
|
||||
**响应示例**:
|
||||
```json
|
||||
{
|
||||
"status": "healthy",
|
||||
"pod_name": "search-agent",
|
||||
"template_type": "search_agent",
|
||||
"configured": true,
|
||||
"llm_base_url": "https://api.example.com",
|
||||
"llm_model": "xchat52",
|
||||
"timestamp": "2024-01-01T00:00:00.000000"
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### 获取状态
|
||||
|
||||
#### GET /status
|
||||
|
||||
获取服务状态信息。
|
||||
|
||||
**请求示例**:
|
||||
```
|
||||
GET /status
|
||||
```
|
||||
|
||||
**响应示例**:
|
||||
```json
|
||||
{
|
||||
"status": "running",
|
||||
"pod_name": "search-agent",
|
||||
"template_type": "search_agent",
|
||||
"configured": true,
|
||||
"timestamp": "2024-01-01T00:00:00.000000"
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 使用说明
|
||||
|
||||
**重要提示**：
|
||||
- 用户只需要传递 `query` 和 `llm_api_key` 参数
|
||||
- `llm_base_url`、`llm_model` 等配置参数已通过环境变量在部署时配置，**不需要**在请求中传递
|
||||
- `user_id` 为可选参数，用于计费回调
|
||||
|
||||
**请求参数说明**：
|
||||
- `query` - 搜索查询内容（必填）
|
||||
- `llm_api_key` - 用户的LLM API密钥（必填）
|
||||
- `user_id` - 用户ID（可选）
|
||||
|
||||
---
|
||||
|
||||
## 错误码说明
|
||||
|
||||
| HTTP状态码 | 说明 |
|
||||
|-----------|------|
|
||||
| 200 | 请求成功 |
|
||||
| 400 | 请求参数错误 |
|
||||
| 500 | 服务器内部错误 |
|
||||
@@ -0,0 +1,137 @@
|
||||
apiVersion: v1
|
||||
kind: Namespace
|
||||
metadata:
|
||||
name: agent-search-test
|
||||
---
|
||||
apiVersion: v1
|
||||
kind: Secret
|
||||
metadata:
|
||||
name: search-agent-secrets
|
||||
namespace: agent-search-test
|
||||
type: Opaque
|
||||
stringData:
|
||||
# LLM API Key 在请求中传入，环境变量可以留空
|
||||
LLM_API_KEY: ""
|
||||
# Serper 搜索 API Key (必须)
|
||||
SERPER_API_KEY: "8253b4f240b520194065312f90e85f9be0fa205f"
|
||||
# Jina Reader API Key (必须)
|
||||
JINA_API_KEY: "jina_e26dc30420a44a1e859216528065b203TkMRmsoz-FgMDQC5FZX9jr5oF2CI"
|
||||
---
|
||||
apiVersion: apps/v1
|
||||
kind: Deployment
|
||||
metadata:
|
||||
name: search-agent
|
||||
namespace: agent-search-test
|
||||
labels:
|
||||
app: search-agent
|
||||
managed-by: manual-test
|
||||
spec:
|
||||
replicas: 1
|
||||
selector:
|
||||
matchLabels:
|
||||
app: search-agent
|
||||
template:
|
||||
metadata:
|
||||
labels:
|
||||
app: search-agent
|
||||
managed-by: manual-test
|
||||
spec:
|
||||
nodeSelector:
|
||||
kubernetes.io/arch: arm64
|
||||
|
||||
imagePullSecrets:
|
||||
- name: acr-secret
|
||||
|
||||
containers:
|
||||
- name: search-agent
|
||||
image: agnettaiji.azurecr.io/ai-agents/search-agent:latest
|
||||
imagePullPolicy: Always
|
||||
ports:
|
||||
- containerPort: 8080
|
||||
name: http
|
||||
env:
|
||||
- name: POD_NAME
|
||||
valueFrom:
|
||||
fieldRef:
|
||||
fieldPath: metadata.name
|
||||
- name: TEMPLATE_TYPE
|
||||
value: "search_agent"
|
||||
- name: SERVICE_HOST
|
||||
value: "0.0.0.0"
|
||||
- name: SERVICE_PORT
|
||||
value: "8080"
|
||||
- name: LOG_LEVEL
|
||||
value: "INFO"
|
||||
# LLM 配置 (必须)
|
||||
- name: LLM_BASE_URL
|
||||
value: "https://litellm.graystone-fb459c5d.southeastasia.azurecontainerapps.io/"
|
||||
- name: LLM_MODEL
|
||||
value: "taiji/gpt-4o-mini"
|
||||
# LLM_API_KEY 可选，在请求中传入
|
||||
- name: LLM_API_KEY
|
||||
valueFrom:
|
||||
secretKeyRef:
|
||||
name: search-agent-secrets
|
||||
key: LLM_API_KEY
|
||||
# Serper API Key (必须)
|
||||
- name: SERPER_API_KEY
|
||||
valueFrom:
|
||||
secretKeyRef:
|
||||
name: search-agent-secrets
|
||||
key: SERPER_API_KEY
|
||||
# Jina API Key (必须)
|
||||
- name: JINA_API_KEY
|
||||
valueFrom:
|
||||
secretKeyRef:
|
||||
name: search-agent-secrets
|
||||
key: JINA_API_KEY
|
||||
# 搜索配置
|
||||
- name: MAX_ITERATIONS
|
||||
value: "3"
|
||||
- name: MAX_RESULTS_PER_QUERY
|
||||
value: "10"
|
||||
- name: CONTENT_MAX_LENGTH
|
||||
value: "5000"
|
||||
- name: TIMEOUT
|
||||
value: "60"
|
||||
resources:
|
||||
requests:
|
||||
cpu: "500m"
|
||||
memory: "512Mi"
|
||||
limits:
|
||||
cpu: "1000m"
|
||||
memory: "1Gi"
|
||||
livenessProbe:
|
||||
httpGet:
|
||||
path: /health
|
||||
port: 8080
|
||||
initialDelaySeconds: 60
|
||||
periodSeconds: 30
|
||||
timeoutSeconds: 10
|
||||
failureThreshold: 3
|
||||
readinessProbe:
|
||||
httpGet:
|
||||
path: /health
|
||||
port: 8080
|
||||
initialDelaySeconds: 30
|
||||
periodSeconds: 10
|
||||
timeoutSeconds: 5
|
||||
failureThreshold: 3
|
||||
---
|
||||
apiVersion: v1
|
||||
kind: Service
|
||||
metadata:
|
||||
name: search-agent
|
||||
namespace: agent-search-test
|
||||
labels:
|
||||
app: search-agent
|
||||
managed-by: manual-test
|
||||
spec:
|
||||
type: LoadBalancer
|
||||
selector:
|
||||
app: search-agent
|
||||
ports:
|
||||
- port: 80
|
||||
targetPort: 8080
|
||||
protocol: TCP
|
||||
name: http
|
||||
@@ -0,0 +1,43 @@
|
||||
FROM python:3.11-slim
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
# 安装系统依赖
|
||||
RUN apt-get update && apt-get install -y \
|
||||
curl \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
|
||||
# 复制requirements文件
|
||||
COPY agents/search_agent/search_agent/requirements.txt /app/search_agent_requirements.txt
|
||||
|
||||
# 安装Python依赖
|
||||
RUN pip install --no-cache-dir \
|
||||
fastapi==0.109.0 \
|
||||
uvicorn[standard]==0.27.0 \
|
||||
pydantic==2.5.3 \
|
||||
&& pip install --no-cache-dir -r /app/search_agent_requirements.txt
|
||||
|
||||
# 复制search_agent目录
|
||||
COPY agents/search_agent/search_agent/ /app/search_agent/
|
||||
|
||||
# 复制主agent文件和共享工具
|
||||
COPY agents/search_agent/search_agent_main.py /app/
|
||||
COPY common/agent_callback_utils.py /app/common/
|
||||
COPY common/api_key_utils.py /app/common/
|
||||
|
||||
# 设置环境变量
|
||||
ENV PYTHONUNBUFFERED=1
|
||||
ENV SERVICE_HOST=0.0.0.0
|
||||
ENV SERVICE_PORT=8080
|
||||
ENV PYTHONPATH=/app
|
||||
|
||||
# 默认 API 密钥（硬编码）
|
||||
ENV JINA_API_KEY=jina_e26dc30420a44a1e859216528065b203TkMRmsoz-FgMDQC5FZX9jr5oF2CI
|
||||
ENV SERPER_API_KEY=8253b4f240b520194065312f90e85f9be0fa205f
|
||||
|
||||
# 健康检查 - 使用Python避免僵尸进程
|
||||
HEALTHCHECK --interval=30s --timeout=10s --start-period=40s --retries=3 \
|
||||
CMD python3 -c "import urllib.request; urllib.request.urlopen('http://localhost:8080/health').read()" || exit 1
|
||||
|
||||
# 运行agent (直接使用Python，避免shell)
|
||||
CMD ["python3", "-u", "search_agent_main.py"]
|
||||
@@ -0,0 +1,19 @@
|
||||
# LLM配置 (xchat52)
|
||||
LLM_BASE_URL=https://apis.openroutex.com/openai/deployments/xchat52
|
||||
LLM_API_KEY=a76ef8d69da64ad99c4bf9739f09585b
|
||||
LLM_MODEL=xchat52
|
||||
|
||||
# Serper配置
|
||||
SERPER_API_KEY=8253b4f240b520194065312f90e85f9be0fa205f
|
||||
|
||||
# Jina配置
|
||||
JINA_API_KEY=jina_e26dc30420a44a1e859216528065b203TkMRmsoz-FgMDQC5FZX9jr5oF2CI
|
||||
|
||||
# Agent配置
|
||||
MAX_ITERATIONS=3
|
||||
MAX_RESULTS_PER_QUERY=10
|
||||
CONTENT_MAX_LENGTH=5000
|
||||
|
||||
# 日志配置
|
||||
LOG_LEVEL=INFO
|
||||
TIMEOUT=30
|
||||
@@ -0,0 +1,247 @@
|
||||
<#
|
||||
.Synopsis
|
||||
Activate a Python virtual environment for the current PowerShell session.
|
||||
|
||||
.Description
|
||||
Pushes the python executable for a virtual environment to the front of the
|
||||
$Env:PATH environment variable and sets the prompt to signify that you are
|
||||
in a Python virtual environment. Makes use of the command line switches as
|
||||
well as the `pyvenv.cfg` file values present in the virtual environment.
|
||||
|
||||
.Parameter VenvDir
|
||||
Path to the directory that contains the virtual environment to activate. The
|
||||
default value for this is the parent of the directory that the Activate.ps1
|
||||
script is located within.
|
||||
|
||||
.Parameter Prompt
|
||||
The prompt prefix to display when this virtual environment is activated. By
|
||||
default, this prompt is the name of the virtual environment folder (VenvDir)
|
||||
surrounded by parentheses and followed by a single space (ie. '(.venv) ').
|
||||
|
||||
.Example
|
||||
Activate.ps1
|
||||
Activates the Python virtual environment that contains the Activate.ps1 script.
|
||||
|
||||
.Example
|
||||
Activate.ps1 -Verbose
|
||||
Activates the Python virtual environment that contains the Activate.ps1 script,
|
||||
and shows extra information about the activation as it executes.
|
||||
|
||||
.Example
|
||||
Activate.ps1 -VenvDir C:\Users\MyUser\Common\.venv
|
||||
Activates the Python virtual environment located in the specified location.
|
||||
|
||||
.Example
|
||||
Activate.ps1 -Prompt "MyPython"
|
||||
Activates the Python virtual environment that contains the Activate.ps1 script,
|
||||
and prefixes the current prompt with the specified string (surrounded in
|
||||
parentheses) while the virtual environment is active.
|
||||
|
||||
.Notes
|
||||
On Windows, it may be required to enable this Activate.ps1 script by setting the
|
||||
execution policy for the user. You can do this by issuing the following PowerShell
|
||||
command:
|
||||
|
||||
PS C:\> Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
|
||||
|
||||
For more information on Execution Policies:
|
||||
https://go.microsoft.com/fwlink/?LinkID=135170
|
||||
|
||||
#>
|
||||
Param(
|
||||
[Parameter(Mandatory = $false)]
|
||||
[String]
|
||||
$VenvDir,
|
||||
[Parameter(Mandatory = $false)]
|
||||
[String]
|
||||
$Prompt
|
||||
)
|
||||
|
||||
<# Function declarations --------------------------------------------------- #>
|
||||
|
||||
<#
|
||||
.Synopsis
|
||||
Remove all shell session elements added by the Activate script, including the
|
||||
addition of the virtual environment's Python executable from the beginning of
|
||||
the PATH variable.
|
||||
|
||||
.Parameter NonDestructive
|
||||
If present, do not remove this function from the global namespace for the
|
||||
session.
|
||||
|
||||
#>
|
||||
function global:deactivate ([switch]$NonDestructive) {
|
||||
# Revert to original values
|
||||
|
||||
# The prior prompt:
|
||||
if (Test-Path -Path Function:_OLD_VIRTUAL_PROMPT) {
|
||||
Copy-Item -Path Function:_OLD_VIRTUAL_PROMPT -Destination Function:prompt
|
||||
Remove-Item -Path Function:_OLD_VIRTUAL_PROMPT
|
||||
}
|
||||
|
||||
# The prior PYTHONHOME:
|
||||
if (Test-Path -Path Env:_OLD_VIRTUAL_PYTHONHOME) {
|
||||
Copy-Item -Path Env:_OLD_VIRTUAL_PYTHONHOME -Destination Env:PYTHONHOME
|
||||
Remove-Item -Path Env:_OLD_VIRTUAL_PYTHONHOME
|
||||
}
|
||||
|
||||
# The prior PATH:
|
||||
if (Test-Path -Path Env:_OLD_VIRTUAL_PATH) {
|
||||
Copy-Item -Path Env:_OLD_VIRTUAL_PATH -Destination Env:PATH
|
||||
Remove-Item -Path Env:_OLD_VIRTUAL_PATH
|
||||
}
|
||||
|
||||
# Just remove the VIRTUAL_ENV altogether:
|
||||
if (Test-Path -Path Env:VIRTUAL_ENV) {
|
||||
Remove-Item -Path env:VIRTUAL_ENV
|
||||
}
|
||||
|
||||
# Just remove VIRTUAL_ENV_PROMPT altogether.
|
||||
if (Test-Path -Path Env:VIRTUAL_ENV_PROMPT) {
|
||||
Remove-Item -Path env:VIRTUAL_ENV_PROMPT
|
||||
}
|
||||
|
||||
# Just remove the _PYTHON_VENV_PROMPT_PREFIX altogether:
|
||||
if (Get-Variable -Name "_PYTHON_VENV_PROMPT_PREFIX" -ErrorAction SilentlyContinue) {
|
||||
Remove-Variable -Name _PYTHON_VENV_PROMPT_PREFIX -Scope Global -Force
|
||||
}
|
||||
|
||||
# Leave deactivate function in the global namespace if requested:
|
||||
if (-not $NonDestructive) {
|
||||
Remove-Item -Path function:deactivate
|
||||
}
|
||||
}
|
||||
|
||||
<#
|
||||
.Description
|
||||
Get-PyVenvConfig parses the values from the pyvenv.cfg file located in the
|
||||
given folder, and returns them in a map.
|
||||
|
||||
For each line in the pyvenv.cfg file, if that line can be parsed into exactly
|
||||
two strings separated by `=` (with any amount of whitespace surrounding the =)
|
||||
then it is considered a `key = value` line. The left hand string is the key,
|
||||
the right hand is the value.
|
||||
|
||||
If the value starts with a `'` or a `"` then the first and last character is
|
||||
stripped from the value before being captured.
|
||||
|
||||
.Parameter ConfigDir
|
||||
Path to the directory that contains the `pyvenv.cfg` file.
|
||||
#>
|
||||
function Get-PyVenvConfig(
|
||||
[String]
|
||||
$ConfigDir
|
||||
) {
|
||||
Write-Verbose "Given ConfigDir=$ConfigDir, obtain values in pyvenv.cfg"
|
||||
|
||||
# Ensure the file exists, and issue a warning if it doesn't (but still allow the function to continue).
|
||||
$pyvenvConfigPath = Join-Path -Resolve -Path $ConfigDir -ChildPath 'pyvenv.cfg' -ErrorAction Continue
|
||||
|
||||
# An empty map will be returned if no config file is found.
|
||||
$pyvenvConfig = @{ }
|
||||
|
||||
if ($pyvenvConfigPath) {
|
||||
|
||||
Write-Verbose "File exists, parse `key = value` lines"
|
||||
$pyvenvConfigContent = Get-Content -Path $pyvenvConfigPath
|
||||
|
||||
$pyvenvConfigContent | ForEach-Object {
|
||||
$keyval = $PSItem -split "\s*=\s*", 2
|
||||
if ($keyval[0] -and $keyval[1]) {
|
||||
$val = $keyval[1]
|
||||
|
||||
# Remove extraneous quotations around a string value.
|
||||
if ("'""".Contains($val.Substring(0, 1))) {
|
||||
$val = $val.Substring(1, $val.Length - 2)
|
||||
}
|
||||
|
||||
$pyvenvConfig[$keyval[0]] = $val
|
||||
Write-Verbose "Adding Key: '$($keyval[0])'='$val'"
|
||||
}
|
||||
}
|
||||
}
|
||||
return $pyvenvConfig
|
||||
}
|
||||
|
||||
|
||||
<# Begin Activate script --------------------------------------------------- #>
|
||||
|
||||
# Determine the containing directory of this script
|
||||
$VenvExecPath = Split-Path -Parent $MyInvocation.MyCommand.Definition
|
||||
$VenvExecDir = Get-Item -Path $VenvExecPath
|
||||
|
||||
Write-Verbose "Activation script is located in path: '$VenvExecPath'"
|
||||
Write-Verbose "VenvExecDir Fullname: '$($VenvExecDir.FullName)"
|
||||
Write-Verbose "VenvExecDir Name: '$($VenvExecDir.Name)"
|
||||
|
||||
# Set values required in priority: CmdLine, ConfigFile, Default
|
||||
# First, get the location of the virtual environment, it might not be
|
||||
# VenvExecDir if specified on the command line.
|
||||
if ($VenvDir) {
|
||||
Write-Verbose "VenvDir given as parameter, using '$VenvDir' to determine values"
|
||||
}
|
||||
else {
|
||||
Write-Verbose "VenvDir not given as a parameter, using parent directory name as VenvDir."
|
||||
$VenvDir = $VenvExecDir.Parent.FullName.TrimEnd("\\/")
|
||||
Write-Verbose "VenvDir=$VenvDir"
|
||||
}
|
||||
|
||||
# Next, read the `pyvenv.cfg` file to determine any required value such
|
||||
# as `prompt`.
|
||||
$pyvenvCfg = Get-PyVenvConfig -ConfigDir $VenvDir
|
||||
|
||||
# Next, set the prompt from the command line, or the config file, or
|
||||
# just use the name of the virtual environment folder.
|
||||
if ($Prompt) {
|
||||
Write-Verbose "Prompt specified as argument, using '$Prompt'"
|
||||
}
|
||||
else {
|
||||
Write-Verbose "Prompt not specified as argument to script, checking pyvenv.cfg value"
|
||||
if ($pyvenvCfg -and $pyvenvCfg['prompt']) {
|
||||
Write-Verbose " Setting based on value in pyvenv.cfg='$($pyvenvCfg['prompt'])'"
|
||||
$Prompt = $pyvenvCfg['prompt'];
|
||||
}
|
||||
else {
|
||||
Write-Verbose " Setting prompt based on parent's directory's name. (Is the directory name passed to venv module when creating the virtual environment)"
|
||||
Write-Verbose " Got leaf-name of $VenvDir='$(Split-Path -Path $venvDir -Leaf)'"
|
||||
$Prompt = Split-Path -Path $venvDir -Leaf
|
||||
}
|
||||
}
|
||||
|
||||
Write-Verbose "Prompt = '$Prompt'"
|
||||
Write-Verbose "VenvDir='$VenvDir'"
|
||||
|
||||
# Deactivate any currently active virtual environment, but leave the
|
||||
# deactivate function in place.
|
||||
deactivate -nondestructive
|
||||
|
||||
# Now set the environment variable VIRTUAL_ENV, used by many tools to determine
|
||||
# that there is an activated venv.
|
||||
$env:VIRTUAL_ENV = $VenvDir
|
||||
|
||||
if (-not $Env:VIRTUAL_ENV_DISABLE_PROMPT) {
|
||||
|
||||
Write-Verbose "Setting prompt to '$Prompt'"
|
||||
|
||||
# Set the prompt to include the env name
|
||||
# Make sure _OLD_VIRTUAL_PROMPT is global
|
||||
function global:_OLD_VIRTUAL_PROMPT { "" }
|
||||
Copy-Item -Path function:prompt -Destination function:_OLD_VIRTUAL_PROMPT
|
||||
New-Variable -Name _PYTHON_VENV_PROMPT_PREFIX -Description "Python virtual environment prompt prefix" -Scope Global -Option ReadOnly -Visibility Public -Value $Prompt
|
||||
|
||||
function global:prompt {
|
||||
Write-Host -NoNewline -ForegroundColor Green "($_PYTHON_VENV_PROMPT_PREFIX) "
|
||||
_OLD_VIRTUAL_PROMPT
|
||||
}
|
||||
$env:VIRTUAL_ENV_PROMPT = $Prompt
|
||||
}
|
||||
|
||||
# Clear PYTHONHOME
|
||||
if (Test-Path -Path Env:PYTHONHOME) {
|
||||
Copy-Item -Path Env:PYTHONHOME -Destination Env:_OLD_VIRTUAL_PYTHONHOME
|
||||
Remove-Item -Path Env:PYTHONHOME
|
||||
}
|
||||
|
||||
# Add the venv to the PATH
|
||||
Copy-Item -Path Env:PATH -Destination Env:_OLD_VIRTUAL_PATH
|
||||
$Env:PATH = "$VenvExecDir$([System.IO.Path]::PathSeparator)$Env:PATH"
|
||||
@@ -0,0 +1,70 @@
|
||||
# This file must be used with "source bin/activate" *from bash*
|
||||
# You cannot run it directly
|
||||
|
||||
deactivate () {
|
||||
# reset old environment variables
|
||||
if [ -n "${_OLD_VIRTUAL_PATH:-}" ] ; then
|
||||
PATH="${_OLD_VIRTUAL_PATH:-}"
|
||||
export PATH
|
||||
unset _OLD_VIRTUAL_PATH
|
||||
fi
|
||||
if [ -n "${_OLD_VIRTUAL_PYTHONHOME:-}" ] ; then
|
||||
PYTHONHOME="${_OLD_VIRTUAL_PYTHONHOME:-}"
|
||||
export PYTHONHOME
|
||||
unset _OLD_VIRTUAL_PYTHONHOME
|
||||
fi
|
||||
|
||||
# Call hash to forget past commands. Without forgetting
|
||||
# past commands the $PATH changes we made may not be respected
|
||||
hash -r 2> /dev/null
|
||||
|
||||
if [ -n "${_OLD_VIRTUAL_PS1:-}" ] ; then
|
||||
PS1="${_OLD_VIRTUAL_PS1:-}"
|
||||
export PS1
|
||||
unset _OLD_VIRTUAL_PS1
|
||||
fi
|
||||
|
||||
unset VIRTUAL_ENV
|
||||
unset VIRTUAL_ENV_PROMPT
|
||||
if [ ! "${1:-}" = "nondestructive" ] ; then
|
||||
# Self destruct!
|
||||
unset -f deactivate
|
||||
fi
|
||||
}
|
||||
|
||||
# unset irrelevant variables
|
||||
deactivate nondestructive
|
||||
|
||||
# on Windows, a path can contain colons and backslashes and has to be converted:
|
||||
if [ "${OSTYPE:-}" = "cygwin" ] || [ "${OSTYPE:-}" = "msys" ] ; then
|
||||
# transform D:\path\to\venv to /d/path/to/venv on MSYS
|
||||
# and to /cygdrive/d/path/to/venv on Cygwin
|
||||
export VIRTUAL_ENV=$(cygpath /home/taiji/tools/aks_agent/.venv)
|
||||
else
|
||||
# use the path as-is
|
||||
export VIRTUAL_ENV=/home/taiji/tools/aks_agent/.venv
|
||||
fi
|
||||
|
||||
_OLD_VIRTUAL_PATH="$PATH"
|
||||
PATH="$VIRTUAL_ENV/"bin":$PATH"
|
||||
export PATH
|
||||
|
||||
# unset PYTHONHOME if set
|
||||
# this will fail if PYTHONHOME is set to the empty string (which is bad anyway)
|
||||
# could use `if (set -u; : $PYTHONHOME) ;` in bash
|
||||
if [ -n "${PYTHONHOME:-}" ] ; then
|
||||
_OLD_VIRTUAL_PYTHONHOME="${PYTHONHOME:-}"
|
||||
unset PYTHONHOME
|
||||
fi
|
||||
|
||||
if [ -z "${VIRTUAL_ENV_DISABLE_PROMPT:-}" ] ; then
|
||||
_OLD_VIRTUAL_PS1="${PS1:-}"
|
||||
PS1='(.venv) '"${PS1:-}"
|
||||
export PS1
|
||||
VIRTUAL_ENV_PROMPT='(.venv) '
|
||||
export VIRTUAL_ENV_PROMPT
|
||||
fi
|
||||
|
||||
# Call hash to forget past commands. Without forgetting
|
||||
# past commands the $PATH changes we made may not be respected
|
||||
hash -r 2> /dev/null
|
||||
@@ -0,0 +1,27 @@
|
||||
# This file must be used with "source bin/activate.csh" *from csh*.
|
||||
# You cannot run it directly.
|
||||
|
||||
# Created by Davide Di Blasi <davidedb@gmail.com>.
|
||||
# Ported to Python 3.3 venv by Andrew Svetlov <andrew.svetlov@gmail.com>
|
||||
|
||||
alias deactivate 'test $?_OLD_VIRTUAL_PATH != 0 && setenv PATH "$_OLD_VIRTUAL_PATH" && unset _OLD_VIRTUAL_PATH; rehash; test $?_OLD_VIRTUAL_PROMPT != 0 && set prompt="$_OLD_VIRTUAL_PROMPT" && unset _OLD_VIRTUAL_PROMPT; unsetenv VIRTUAL_ENV; unsetenv VIRTUAL_ENV_PROMPT; test "\!:*" != "nondestructive" && unalias deactivate'
|
||||
|
||||
# Unset irrelevant variables.
|
||||
deactivate nondestructive
|
||||
|
||||
setenv VIRTUAL_ENV /home/taiji/tools/aks_agent/.venv
|
||||
|
||||
set _OLD_VIRTUAL_PATH="$PATH"
|
||||
setenv PATH "$VIRTUAL_ENV/"bin":$PATH"
|
||||
|
||||
|
||||
set _OLD_VIRTUAL_PROMPT="$prompt"
|
||||
|
||||
if (! "$?VIRTUAL_ENV_DISABLE_PROMPT") then
|
||||
set prompt = '(.venv) '"$prompt"
|
||||
setenv VIRTUAL_ENV_PROMPT '(.venv) '
|
||||
endif
|
||||
|
||||
alias pydoc python -m pydoc
|
||||
|
||||
rehash
|
||||
@@ -0,0 +1,69 @@
|
||||
# This file must be used with "source <venv>/bin/activate.fish" *from fish*
|
||||
# (https://fishshell.com/). You cannot run it directly.
|
||||
|
||||
function deactivate -d "Exit virtual environment and return to normal shell environment"
|
||||
# reset old environment variables
|
||||
if test -n "$_OLD_VIRTUAL_PATH"
|
||||
set -gx PATH $_OLD_VIRTUAL_PATH
|
||||
set -e _OLD_VIRTUAL_PATH
|
||||
end
|
||||
if test -n "$_OLD_VIRTUAL_PYTHONHOME"
|
||||
set -gx PYTHONHOME $_OLD_VIRTUAL_PYTHONHOME
|
||||
set -e _OLD_VIRTUAL_PYTHONHOME
|
||||
end
|
||||
|
||||
if test -n "$_OLD_FISH_PROMPT_OVERRIDE"
|
||||
set -e _OLD_FISH_PROMPT_OVERRIDE
|
||||
# prevents error when using nested fish instances (Issue #93858)
|
||||
if functions -q _old_fish_prompt
|
||||
functions -e fish_prompt
|
||||
functions -c _old_fish_prompt fish_prompt
|
||||
functions -e _old_fish_prompt
|
||||
end
|
||||
end
|
||||
|
||||
set -e VIRTUAL_ENV
|
||||
set -e VIRTUAL_ENV_PROMPT
|
||||
if test "$argv[1]" != "nondestructive"
|
||||
# Self-destruct!
|
||||
functions -e deactivate
|
||||
end
|
||||
end
|
||||
|
||||
# Unset irrelevant variables.
|
||||
deactivate nondestructive
|
||||
|
||||
set -gx VIRTUAL_ENV /home/taiji/tools/aks_agent/.venv
|
||||
|
||||
set -gx _OLD_VIRTUAL_PATH $PATH
|
||||
set -gx PATH "$VIRTUAL_ENV/"bin $PATH
|
||||
|
||||
# Unset PYTHONHOME if set.
|
||||
if set -q PYTHONHOME
|
||||
set -gx _OLD_VIRTUAL_PYTHONHOME $PYTHONHOME
|
||||
set -e PYTHONHOME
|
||||
end
|
||||
|
||||
if test -z "$VIRTUAL_ENV_DISABLE_PROMPT"
|
||||
# fish uses a function instead of an env var to generate the prompt.
|
||||
|
||||
# Save the current fish_prompt function as the function _old_fish_prompt.
|
||||
functions -c fish_prompt _old_fish_prompt
|
||||
|
||||
# With the original prompt function renamed, we can override with our own.
|
||||
function fish_prompt
|
||||
# Save the return status of the last command.
|
||||
set -l old_status $status
|
||||
|
||||
# Output the venv prompt; color taken from the blue of the Python logo.
|
||||
printf "%s%s%s" (set_color 4B8BBE) '(.venv) ' (set_color normal)
|
||||
|
||||
# Restore the return status of the previous command.
|
||||
echo "exit $old_status" | .
|
||||
# Output the original/"old" prompt.
|
||||
_old_fish_prompt
|
||||
end
|
||||
|
||||
set -gx _OLD_FISH_PROMPT_OVERRIDE "$VIRTUAL_ENV"
|
||||
set -gx VIRTUAL_ENV_PROMPT '(.venv) '
|
||||
end
|
||||
Executable
+8
@@ -0,0 +1,8 @@
|
||||
#!/home/taiji/tools/aks_agent/.venv/bin/python3
|
||||
# -*- coding: utf-8 -*-
|
||||
import re
|
||||
import sys
|
||||
from dotenv.__main__ import cli
|
||||
if __name__ == '__main__':
|
||||
sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0])
|
||||
sys.exit(cli())
|
||||
+8
@@ -0,0 +1,8 @@
|
||||
#!/home/taiji/tools/aks_agent/.venv/bin/python3
|
||||
# -*- coding: utf-8 -*-
|
||||
import re
|
||||
import sys
|
||||
from charset_normalizer.cli import cli_detect
|
||||
if __name__ == '__main__':
|
||||
sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0])
|
||||
sys.exit(cli_detect())
|
||||
Executable
+8
@@ -0,0 +1,8 @@
|
||||
#!/home/taiji/tools/aks_agent/.venv/bin/python3
|
||||
# -*- coding: utf-8 -*-
|
||||
import re
|
||||
import sys
|
||||
from pip._internal.cli.main import main
|
||||
if __name__ == '__main__':
|
||||
sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0])
|
||||
sys.exit(main())
|
||||
Executable
+8
@@ -0,0 +1,8 @@
|
||||
#!/home/taiji/tools/aks_agent/.venv/bin/python3
|
||||
# -*- coding: utf-8 -*-
|
||||
import re
|
||||
import sys
|
||||
from pip._internal.cli.main import main
|
||||
if __name__ == '__main__':
|
||||
sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0])
|
||||
sys.exit(main())
|
||||
Executable
+8
@@ -0,0 +1,8 @@
|
||||
#!/home/taiji/tools/aks_agent/.venv/bin/python3
|
||||
# -*- coding: utf-8 -*-
|
||||
import re
|
||||
import sys
|
||||
from pip._internal.cli.main import main
|
||||
if __name__ == '__main__':
|
||||
sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0])
|
||||
sys.exit(main())
|
||||
@@ -0,0 +1 @@
|
||||
python3
|
||||
@@ -0,0 +1 @@
|
||||
/usr/bin/python3
|
||||
@@ -0,0 +1 @@
|
||||
python3
|
||||
BIN
Binary file not shown.
+1
@@ -0,0 +1 @@
|
||||
pip
|
||||
+279
@@ -0,0 +1,279 @@
|
||||
A. HISTORY OF THE SOFTWARE
|
||||
==========================
|
||||
|
||||
Python was created in the early 1990s by Guido van Rossum at Stichting
|
||||
Mathematisch Centrum (CWI, see https://www.cwi.nl) in the Netherlands
|
||||
as a successor of a language called ABC. Guido remains Python's
|
||||
principal author, although it includes many contributions from others.
|
||||
|
||||
In 1995, Guido continued his work on Python at the Corporation for
|
||||
National Research Initiatives (CNRI, see https://www.cnri.reston.va.us)
|
||||
in Reston, Virginia where he released several versions of the
|
||||
software.
|
||||
|
||||
In May 2000, Guido and the Python core development team moved to
|
||||
BeOpen.com to form the BeOpen PythonLabs team. In October of the same
|
||||
year, the PythonLabs team moved to Digital Creations, which became
|
||||
Zope Corporation. In 2001, the Python Software Foundation (PSF, see
|
||||
https://www.python.org/psf/) was formed, a non-profit organization
|
||||
created specifically to own Python-related Intellectual Property.
|
||||
Zope Corporation was a sponsoring member of the PSF.
|
||||
|
||||
All Python releases are Open Source (see https://opensource.org for
|
||||
the Open Source Definition). Historically, most, but not all, Python
|
||||
releases have also been GPL-compatible; the table below summarizes
|
||||
the various releases.
|
||||
|
||||
Release Derived Year Owner GPL-
|
||||
from compatible? (1)
|
||||
|
||||
0.9.0 thru 1.2 1991-1995 CWI yes
|
||||
1.3 thru 1.5.2 1.2 1995-1999 CNRI yes
|
||||
1.6 1.5.2 2000 CNRI no
|
||||
2.0 1.6 2000 BeOpen.com no
|
||||
1.6.1 1.6 2001 CNRI yes (2)
|
||||
2.1 2.0+1.6.1 2001 PSF no
|
||||
2.0.1 2.0+1.6.1 2001 PSF yes
|
||||
2.1.1 2.1+2.0.1 2001 PSF yes
|
||||
2.1.2 2.1.1 2002 PSF yes
|
||||
2.1.3 2.1.2 2002 PSF yes
|
||||
2.2 and above 2.1.1 2001-now PSF yes
|
||||
|
||||
Footnotes:
|
||||
|
||||
(1) GPL-compatible doesn't mean that we're distributing Python under
|
||||
the GPL. All Python licenses, unlike the GPL, let you distribute
|
||||
a modified version without making your changes open source. The
|
||||
GPL-compatible licenses make it possible to combine Python with
|
||||
other software that is released under the GPL; the others don't.
|
||||
|
||||
(2) According to Richard Stallman, 1.6.1 is not GPL-compatible,
|
||||
because its license has a choice of law clause. According to
|
||||
CNRI, however, Stallman's lawyer has told CNRI's lawyer that 1.6.1
|
||||
is "not incompatible" with the GPL.
|
||||
|
||||
Thanks to the many outside volunteers who have worked under Guido's
|
||||
direction to make these releases possible.
|
||||
|
||||
|
||||
B. TERMS AND CONDITIONS FOR ACCESSING OR OTHERWISE USING PYTHON
|
||||
===============================================================
|
||||
|
||||
Python software and documentation are licensed under the
|
||||
Python Software Foundation License Version 2.
|
||||
|
||||
Starting with Python 3.8.6, examples, recipes, and other code in
|
||||
the documentation are dual licensed under the PSF License Version 2
|
||||
and the Zero-Clause BSD license.
|
||||
|
||||
Some software incorporated into Python is under different licenses.
|
||||
The licenses are listed with code falling under that license.
|
||||
|
||||
|
||||
PYTHON SOFTWARE FOUNDATION LICENSE VERSION 2
|
||||
--------------------------------------------
|
||||
|
||||
1. This LICENSE AGREEMENT is between the Python Software Foundation
|
||||
("PSF"), and the Individual or Organization ("Licensee") accessing and
|
||||
otherwise using this software ("Python") in source or binary form and
|
||||
its associated documentation.
|
||||
|
||||
2. Subject to the terms and conditions of this License Agreement, PSF hereby
|
||||
grants Licensee a nonexclusive, royalty-free, world-wide license to reproduce,
|
||||
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|
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|
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|
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|
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CNRI LICENSE AGREEMENT FOR PYTHON 1.6.1
|
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---------------------------------------
|
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|
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prepare derivative works, distribute, and otherwise use Python 1.6.1
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License Agreement and CNRI's notice of copyright, i.e., "Copyright (c)
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Python 1.6.1 may be located on the internet using the following
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unique, persistent identifier (known as a handle): 1895.22/1013. This
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Agreement may also be obtained from a proxy server on the internet
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using the following URL: http://hdl.handle.net/1895.22/1013".
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3. In the event Licensee prepares a derivative work that is based on
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or incorporates Python 1.6.1 or any part thereof, and wants to make
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the derivative work available to others as provided herein, then
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Licensee hereby agrees to include in any such work a brief summary of
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4. CNRI is making Python 1.6.1 available to Licensee on an "AS IS"
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|
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ACCEPT
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|
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|
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CWI LICENSE AGREEMENT FOR PYTHON 0.9.0 THROUGH 1.2
|
||||
--------------------------------------------------
|
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|
||||
Copyright (c) 1991 - 1995, Stichting Mathematisch Centrum Amsterdam,
|
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The Netherlands. All rights reserved.
|
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Permission to use, copy, modify, and distribute this software and its
|
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|
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|
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|
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|
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Centrum or CWI not be used in advertising or publicity pertaining to
|
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|
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|
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STICHTING MATHEMATISCH CENTRUM DISCLAIMS ALL WARRANTIES WITH REGARD TO
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|
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|
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OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
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|
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ZERO-CLAUSE BSD LICENSE FOR CODE IN THE PYTHON DOCUMENTATION
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----------------------------------------------------------------------
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|
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Permission to use, copy, modify, and/or distribute this software for any
|
||||
purpose with or without fee is hereby granted.
|
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|
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THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
|
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REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY
|
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AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
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INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM
|
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LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR
|
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OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR
|
||||
PERFORMANCE OF THIS SOFTWARE.
|
||||
+123
@@ -0,0 +1,123 @@
|
||||
Metadata-Version: 2.3
|
||||
Name: aiohappyeyeballs
|
||||
Version: 2.6.1
|
||||
Summary: Happy Eyeballs for asyncio
|
||||
License: PSF-2.0
|
||||
Author: J. Nick Koston
|
||||
Author-email: nick@koston.org
|
||||
Requires-Python: >=3.9
|
||||
Classifier: Development Status :: 5 - Production/Stable
|
||||
Classifier: Intended Audience :: Developers
|
||||
Classifier: Natural Language :: English
|
||||
Classifier: Operating System :: OS Independent
|
||||
Classifier: Topic :: Software Development :: Libraries
|
||||
Classifier: Programming Language :: Python :: 3
|
||||
Classifier: Programming Language :: Python :: 3.9
|
||||
Classifier: Programming Language :: Python :: 3.10
|
||||
Classifier: Programming Language :: Python :: 3.11
|
||||
Classifier: Programming Language :: Python :: 3.12
|
||||
Classifier: Programming Language :: Python :: 3.13
|
||||
Classifier: License :: OSI Approved :: Python Software Foundation License
|
||||
Project-URL: Bug Tracker, https://github.com/aio-libs/aiohappyeyeballs/issues
|
||||
Project-URL: Changelog, https://github.com/aio-libs/aiohappyeyeballs/blob/main/CHANGELOG.md
|
||||
Project-URL: Documentation, https://aiohappyeyeballs.readthedocs.io
|
||||
Project-URL: Repository, https://github.com/aio-libs/aiohappyeyeballs
|
||||
Description-Content-Type: text/markdown
|
||||
|
||||
# aiohappyeyeballs
|
||||
|
||||
<p align="center">
|
||||
<a href="https://github.com/aio-libs/aiohappyeyeballs/actions/workflows/ci.yml?query=branch%3Amain">
|
||||
<img src="https://img.shields.io/github/actions/workflow/status/aio-libs/aiohappyeyeballs/ci-cd.yml?branch=main&label=CI&logo=github&style=flat-square" alt="CI Status" >
|
||||
</a>
|
||||
<a href="https://aiohappyeyeballs.readthedocs.io">
|
||||
<img src="https://img.shields.io/readthedocs/aiohappyeyeballs.svg?logo=read-the-docs&logoColor=fff&style=flat-square" alt="Documentation Status">
|
||||
</a>
|
||||
<a href="https://codecov.io/gh/aio-libs/aiohappyeyeballs">
|
||||
<img src="https://img.shields.io/codecov/c/github/aio-libs/aiohappyeyeballs.svg?logo=codecov&logoColor=fff&style=flat-square" alt="Test coverage percentage">
|
||||
</a>
|
||||
</p>
|
||||
<p align="center">
|
||||
<a href="https://python-poetry.org/">
|
||||
<img src="https://img.shields.io/badge/packaging-poetry-299bd7?style=flat-square&logo=data:image/png;base64,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" alt="Poetry">
|
||||
</a>
|
||||
<a href="https://github.com/astral-sh/ruff">
|
||||
<img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json" alt="Ruff">
|
||||
</a>
|
||||
<a href="https://github.com/pre-commit/pre-commit">
|
||||
<img src="https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white&style=flat-square" alt="pre-commit">
|
||||
</a>
|
||||
</p>
|
||||
<p align="center">
|
||||
<a href="https://pypi.org/project/aiohappyeyeballs/">
|
||||
<img src="https://img.shields.io/pypi/v/aiohappyeyeballs.svg?logo=python&logoColor=fff&style=flat-square" alt="PyPI Version">
|
||||
</a>
|
||||
<img src="https://img.shields.io/pypi/pyversions/aiohappyeyeballs.svg?style=flat-square&logo=python&logoColor=fff" alt="Supported Python versions">
|
||||
<img src="https://img.shields.io/pypi/l/aiohappyeyeballs.svg?style=flat-square" alt="License">
|
||||
</p>
|
||||
|
||||
---
|
||||
|
||||
**Documentation**: <a href="https://aiohappyeyeballs.readthedocs.io" target="_blank">https://aiohappyeyeballs.readthedocs.io </a>
|
||||
|
||||
**Source Code**: <a href="https://github.com/aio-libs/aiohappyeyeballs" target="_blank">https://github.com/aio-libs/aiohappyeyeballs </a>
|
||||
|
||||
---
|
||||
|
||||
[Happy Eyeballs](https://en.wikipedia.org/wiki/Happy_Eyeballs)
|
||||
([RFC 8305](https://www.rfc-editor.org/rfc/rfc8305.html))
|
||||
|
||||
## Use case
|
||||
|
||||
This library exists to allow connecting with
|
||||
[Happy Eyeballs](https://en.wikipedia.org/wiki/Happy_Eyeballs)
|
||||
([RFC 8305](https://www.rfc-editor.org/rfc/rfc8305.html))
|
||||
when you
|
||||
already have a list of addrinfo and not a DNS name.
|
||||
|
||||
The stdlib version of `loop.create_connection()`
|
||||
will only work when you pass in an unresolved name which
|
||||
is not a good fit when using DNS caching or resolving
|
||||
names via another method such as `zeroconf`.
|
||||
|
||||
## Installation
|
||||
|
||||
Install this via pip (or your favourite package manager):
|
||||
|
||||
`pip install aiohappyeyeballs`
|
||||
|
||||
## License
|
||||
|
||||
[aiohappyeyeballs is licensed under the same terms as cpython itself.](https://github.com/python/cpython/blob/main/LICENSE)
|
||||
|
||||
## Example usage
|
||||
|
||||
```python
|
||||
|
||||
addr_infos = await loop.getaddrinfo("example.org", 80)
|
||||
|
||||
socket = await start_connection(addr_infos)
|
||||
socket = await start_connection(addr_infos, local_addr_infos=local_addr_infos, happy_eyeballs_delay=0.2)
|
||||
|
||||
transport, protocol = await loop.create_connection(
|
||||
MyProtocol, sock=socket, ...)
|
||||
|
||||
# Remove the first address for each family from addr_info
|
||||
pop_addr_infos_interleave(addr_info, 1)
|
||||
|
||||
# Remove all matching address from addr_info
|
||||
remove_addr_infos(addr_info, "dead::beef::")
|
||||
|
||||
# Convert a local_addr to local_addr_infos
|
||||
local_addr_infos = addr_to_addr_infos(("127.0.0.1",0))
|
||||
```
|
||||
|
||||
## Credits
|
||||
|
||||
This package contains code from cpython and is licensed under the same terms as cpython itself.
|
||||
|
||||
This package was created with
|
||||
[Copier](https://copier.readthedocs.io/) and the
|
||||
[browniebroke/pypackage-template](https://github.com/browniebroke/pypackage-template)
|
||||
project template.
|
||||
|
||||
+16
@@ -0,0 +1,16 @@
|
||||
aiohappyeyeballs-2.6.1.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4
|
||||
aiohappyeyeballs-2.6.1.dist-info/LICENSE,sha256=Oy-B_iHRgcSZxZolbI4ZaEVdZonSaaqFNzv7avQdo78,13936
|
||||
aiohappyeyeballs-2.6.1.dist-info/METADATA,sha256=NSXlhJwAfi380eEjAo7BQ4P_TVal9xi0qkyZWibMsVM,5915
|
||||
aiohappyeyeballs-2.6.1.dist-info/RECORD,,
|
||||
aiohappyeyeballs-2.6.1.dist-info/WHEEL,sha256=XbeZDeTWKc1w7CSIyre5aMDU_-PohRwTQceYnisIYYY,88
|
||||
aiohappyeyeballs/__init__.py,sha256=x7kktHEtaD9quBcWDJPuLeKyjuVAI-Jj14S9B_5hcTs,361
|
||||
aiohappyeyeballs/__pycache__/__init__.cpython-312.pyc,,
|
||||
aiohappyeyeballs/__pycache__/_staggered.cpython-312.pyc,,
|
||||
aiohappyeyeballs/__pycache__/impl.cpython-312.pyc,,
|
||||
aiohappyeyeballs/__pycache__/types.cpython-312.pyc,,
|
||||
aiohappyeyeballs/__pycache__/utils.cpython-312.pyc,,
|
||||
aiohappyeyeballs/_staggered.py,sha256=edfVowFx-P-ywJjIEF3MdPtEMVODujV6CeMYr65otac,6900
|
||||
aiohappyeyeballs/impl.py,sha256=Dlcm2mTJ28ucrGnxkb_fo9CZzLAkOOBizOt7dreBbXE,9681
|
||||
aiohappyeyeballs/py.typed,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
|
||||
aiohappyeyeballs/types.py,sha256=YZJIAnyoV4Dz0WFtlaf_OyE4EW7Xus1z7aIfNI6tDDQ,425
|
||||
aiohappyeyeballs/utils.py,sha256=on9GxIR0LhEfZu8P6Twi9hepX9zDanuZM20MWsb3xlQ,3028
|
||||
+4
@@ -0,0 +1,4 @@
|
||||
Wheel-Version: 1.0
|
||||
Generator: poetry-core 2.1.1
|
||||
Root-Is-Purelib: true
|
||||
Tag: py3-none-any
|
||||
+14
@@ -0,0 +1,14 @@
|
||||
__version__ = "2.6.1"
|
||||
|
||||
from .impl import start_connection
|
||||
from .types import AddrInfoType, SocketFactoryType
|
||||
from .utils import addr_to_addr_infos, pop_addr_infos_interleave, remove_addr_infos
|
||||
|
||||
__all__ = (
|
||||
"AddrInfoType",
|
||||
"SocketFactoryType",
|
||||
"addr_to_addr_infos",
|
||||
"pop_addr_infos_interleave",
|
||||
"remove_addr_infos",
|
||||
"start_connection",
|
||||
)
|
||||
BIN
Binary file not shown.
BIN
Binary file not shown.
BIN
Binary file not shown.
BIN
Binary file not shown.
BIN
Binary file not shown.
+207
@@ -0,0 +1,207 @@
|
||||
import asyncio
|
||||
import contextlib
|
||||
|
||||
# PY3.9: Import Callable from typing until we drop Python 3.9 support
|
||||
# https://github.com/python/cpython/issues/87131
|
||||
from typing import (
|
||||
TYPE_CHECKING,
|
||||
Any,
|
||||
Awaitable,
|
||||
Callable,
|
||||
Iterable,
|
||||
List,
|
||||
Optional,
|
||||
Set,
|
||||
Tuple,
|
||||
TypeVar,
|
||||
Union,
|
||||
)
|
||||
|
||||
_T = TypeVar("_T")
|
||||
|
||||
RE_RAISE_EXCEPTIONS = (SystemExit, KeyboardInterrupt)
|
||||
|
||||
|
||||
def _set_result(wait_next: "asyncio.Future[None]") -> None:
|
||||
"""Set the result of a future if it is not already done."""
|
||||
if not wait_next.done():
|
||||
wait_next.set_result(None)
|
||||
|
||||
|
||||
async def _wait_one(
|
||||
futures: "Iterable[asyncio.Future[Any]]",
|
||||
loop: asyncio.AbstractEventLoop,
|
||||
) -> _T:
|
||||
"""Wait for the first future to complete."""
|
||||
wait_next = loop.create_future()
|
||||
|
||||
def _on_completion(fut: "asyncio.Future[Any]") -> None:
|
||||
if not wait_next.done():
|
||||
wait_next.set_result(fut)
|
||||
|
||||
for f in futures:
|
||||
f.add_done_callback(_on_completion)
|
||||
|
||||
try:
|
||||
return await wait_next
|
||||
finally:
|
||||
for f in futures:
|
||||
f.remove_done_callback(_on_completion)
|
||||
|
||||
|
||||
async def staggered_race(
|
||||
coro_fns: Iterable[Callable[[], Awaitable[_T]]],
|
||||
delay: Optional[float],
|
||||
*,
|
||||
loop: Optional[asyncio.AbstractEventLoop] = None,
|
||||
) -> Tuple[Optional[_T], Optional[int], List[Optional[BaseException]]]:
|
||||
"""
|
||||
Run coroutines with staggered start times and take the first to finish.
|
||||
|
||||
This method takes an iterable of coroutine functions. The first one is
|
||||
started immediately. From then on, whenever the immediately preceding one
|
||||
fails (raises an exception), or when *delay* seconds has passed, the next
|
||||
coroutine is started. This continues until one of the coroutines complete
|
||||
successfully, in which case all others are cancelled, or until all
|
||||
coroutines fail.
|
||||
|
||||
The coroutines provided should be well-behaved in the following way:
|
||||
|
||||
* They should only ``return`` if completed successfully.
|
||||
|
||||
* They should always raise an exception if they did not complete
|
||||
successfully. In particular, if they handle cancellation, they should
|
||||
probably reraise, like this::
|
||||
|
||||
try:
|
||||
# do work
|
||||
except asyncio.CancelledError:
|
||||
# undo partially completed work
|
||||
raise
|
||||
|
||||
Args:
|
||||
----
|
||||
coro_fns: an iterable of coroutine functions, i.e. callables that
|
||||
return a coroutine object when called. Use ``functools.partial`` or
|
||||
lambdas to pass arguments.
|
||||
|
||||
delay: amount of time, in seconds, between starting coroutines. If
|
||||
``None``, the coroutines will run sequentially.
|
||||
|
||||
loop: the event loop to use. If ``None``, the running loop is used.
|
||||
|
||||
Returns:
|
||||
-------
|
||||
tuple *(winner_result, winner_index, exceptions)* where
|
||||
|
||||
- *winner_result*: the result of the winning coroutine, or ``None``
|
||||
if no coroutines won.
|
||||
|
||||
- *winner_index*: the index of the winning coroutine in
|
||||
``coro_fns``, or ``None`` if no coroutines won. If the winning
|
||||
coroutine may return None on success, *winner_index* can be used
|
||||
to definitively determine whether any coroutine won.
|
||||
|
||||
- *exceptions*: list of exceptions returned by the coroutines.
|
||||
``len(exceptions)`` is equal to the number of coroutines actually
|
||||
started, and the order is the same as in ``coro_fns``. The winning
|
||||
coroutine's entry is ``None``.
|
||||
|
||||
"""
|
||||
loop = loop or asyncio.get_running_loop()
|
||||
exceptions: List[Optional[BaseException]] = []
|
||||
tasks: Set[asyncio.Task[Optional[Tuple[_T, int]]]] = set()
|
||||
|
||||
async def run_one_coro(
|
||||
coro_fn: Callable[[], Awaitable[_T]],
|
||||
this_index: int,
|
||||
start_next: "asyncio.Future[None]",
|
||||
) -> Optional[Tuple[_T, int]]:
|
||||
"""
|
||||
Run a single coroutine.
|
||||
|
||||
If the coroutine fails, set the exception in the exceptions list and
|
||||
start the next coroutine by setting the result of the start_next.
|
||||
|
||||
If the coroutine succeeds, return the result and the index of the
|
||||
coroutine in the coro_fns list.
|
||||
|
||||
If SystemExit or KeyboardInterrupt is raised, re-raise it.
|
||||
"""
|
||||
try:
|
||||
result = await coro_fn()
|
||||
except RE_RAISE_EXCEPTIONS:
|
||||
raise
|
||||
except BaseException as e:
|
||||
exceptions[this_index] = e
|
||||
_set_result(start_next) # Kickstart the next coroutine
|
||||
return None
|
||||
|
||||
return result, this_index
|
||||
|
||||
start_next_timer: Optional[asyncio.TimerHandle] = None
|
||||
start_next: Optional[asyncio.Future[None]]
|
||||
task: asyncio.Task[Optional[Tuple[_T, int]]]
|
||||
done: Union[asyncio.Future[None], asyncio.Task[Optional[Tuple[_T, int]]]]
|
||||
coro_iter = iter(coro_fns)
|
||||
this_index = -1
|
||||
try:
|
||||
while True:
|
||||
if coro_fn := next(coro_iter, None):
|
||||
this_index += 1
|
||||
exceptions.append(None)
|
||||
start_next = loop.create_future()
|
||||
task = loop.create_task(run_one_coro(coro_fn, this_index, start_next))
|
||||
tasks.add(task)
|
||||
start_next_timer = (
|
||||
loop.call_later(delay, _set_result, start_next) if delay else None
|
||||
)
|
||||
elif not tasks:
|
||||
# We exhausted the coro_fns list and no tasks are running
|
||||
# so we have no winner and all coroutines failed.
|
||||
break
|
||||
|
||||
while tasks or start_next:
|
||||
done = await _wait_one(
|
||||
(*tasks, start_next) if start_next else tasks, loop
|
||||
)
|
||||
if done is start_next:
|
||||
# The current task has failed or the timer has expired
|
||||
# so we need to start the next task.
|
||||
start_next = None
|
||||
if start_next_timer:
|
||||
start_next_timer.cancel()
|
||||
start_next_timer = None
|
||||
|
||||
# Break out of the task waiting loop to start the next
|
||||
# task.
|
||||
break
|
||||
|
||||
if TYPE_CHECKING:
|
||||
assert isinstance(done, asyncio.Task)
|
||||
|
||||
tasks.remove(done)
|
||||
if winner := done.result():
|
||||
return *winner, exceptions
|
||||
finally:
|
||||
# We either have:
|
||||
# - a winner
|
||||
# - all tasks failed
|
||||
# - a KeyboardInterrupt or SystemExit.
|
||||
|
||||
#
|
||||
# If the timer is still running, cancel it.
|
||||
#
|
||||
if start_next_timer:
|
||||
start_next_timer.cancel()
|
||||
|
||||
#
|
||||
# If there are any tasks left, cancel them and than
|
||||
# wait them so they fill the exceptions list.
|
||||
#
|
||||
for task in tasks:
|
||||
task.cancel()
|
||||
with contextlib.suppress(asyncio.CancelledError):
|
||||
await task
|
||||
|
||||
return None, None, exceptions
|
||||
+259
@@ -0,0 +1,259 @@
|
||||
"""Base implementation."""
|
||||
|
||||
import asyncio
|
||||
import collections
|
||||
import contextlib
|
||||
import functools
|
||||
import itertools
|
||||
import socket
|
||||
from typing import List, Optional, Sequence, Set, Union
|
||||
|
||||
from . import _staggered
|
||||
from .types import AddrInfoType, SocketFactoryType
|
||||
|
||||
|
||||
async def start_connection(
|
||||
addr_infos: Sequence[AddrInfoType],
|
||||
*,
|
||||
local_addr_infos: Optional[Sequence[AddrInfoType]] = None,
|
||||
happy_eyeballs_delay: Optional[float] = None,
|
||||
interleave: Optional[int] = None,
|
||||
loop: Optional[asyncio.AbstractEventLoop] = None,
|
||||
socket_factory: Optional[SocketFactoryType] = None,
|
||||
) -> socket.socket:
|
||||
"""
|
||||
Connect to a TCP server.
|
||||
|
||||
Create a socket connection to a specified destination. The
|
||||
destination is specified as a list of AddrInfoType tuples as
|
||||
returned from getaddrinfo().
|
||||
|
||||
The arguments are, in order:
|
||||
|
||||
* ``family``: the address family, e.g. ``socket.AF_INET`` or
|
||||
``socket.AF_INET6``.
|
||||
* ``type``: the socket type, e.g. ``socket.SOCK_STREAM`` or
|
||||
``socket.SOCK_DGRAM``.
|
||||
* ``proto``: the protocol, e.g. ``socket.IPPROTO_TCP`` or
|
||||
``socket.IPPROTO_UDP``.
|
||||
* ``canonname``: the canonical name of the address, e.g.
|
||||
``"www.python.org"``.
|
||||
* ``sockaddr``: the socket address
|
||||
|
||||
This method is a coroutine which will try to establish the connection
|
||||
in the background. When successful, the coroutine returns a
|
||||
socket.
|
||||
|
||||
The expected use case is to use this method in conjunction with
|
||||
loop.create_connection() to establish a connection to a server::
|
||||
|
||||
socket = await start_connection(addr_infos)
|
||||
transport, protocol = await loop.create_connection(
|
||||
MyProtocol, sock=socket, ...)
|
||||
"""
|
||||
if not (current_loop := loop):
|
||||
current_loop = asyncio.get_running_loop()
|
||||
|
||||
single_addr_info = len(addr_infos) == 1
|
||||
|
||||
if happy_eyeballs_delay is not None and interleave is None:
|
||||
# If using happy eyeballs, default to interleave addresses by family
|
||||
interleave = 1
|
||||
|
||||
if interleave and not single_addr_info:
|
||||
addr_infos = _interleave_addrinfos(addr_infos, interleave)
|
||||
|
||||
sock: Optional[socket.socket] = None
|
||||
# uvloop can raise RuntimeError instead of OSError
|
||||
exceptions: List[List[Union[OSError, RuntimeError]]] = []
|
||||
if happy_eyeballs_delay is None or single_addr_info:
|
||||
# not using happy eyeballs
|
||||
for addrinfo in addr_infos:
|
||||
try:
|
||||
sock = await _connect_sock(
|
||||
current_loop,
|
||||
exceptions,
|
||||
addrinfo,
|
||||
local_addr_infos,
|
||||
None,
|
||||
socket_factory,
|
||||
)
|
||||
break
|
||||
except (RuntimeError, OSError):
|
||||
continue
|
||||
else: # using happy eyeballs
|
||||
open_sockets: Set[socket.socket] = set()
|
||||
try:
|
||||
sock, _, _ = await _staggered.staggered_race(
|
||||
(
|
||||
functools.partial(
|
||||
_connect_sock,
|
||||
current_loop,
|
||||
exceptions,
|
||||
addrinfo,
|
||||
local_addr_infos,
|
||||
open_sockets,
|
||||
socket_factory,
|
||||
)
|
||||
for addrinfo in addr_infos
|
||||
),
|
||||
happy_eyeballs_delay,
|
||||
)
|
||||
finally:
|
||||
# If we have a winner, staggered_race will
|
||||
# cancel the other tasks, however there is a
|
||||
# small race window where any of the other tasks
|
||||
# can be done before they are cancelled which
|
||||
# will leave the socket open. To avoid this problem
|
||||
# we pass a set to _connect_sock to keep track of
|
||||
# the open sockets and close them here if there
|
||||
# are any "runner up" sockets.
|
||||
for s in open_sockets:
|
||||
if s is not sock:
|
||||
with contextlib.suppress(OSError):
|
||||
s.close()
|
||||
open_sockets = None # type: ignore[assignment]
|
||||
|
||||
if sock is None:
|
||||
all_exceptions = [exc for sub in exceptions for exc in sub]
|
||||
try:
|
||||
first_exception = all_exceptions[0]
|
||||
if len(all_exceptions) == 1:
|
||||
raise first_exception
|
||||
else:
|
||||
# If they all have the same str(), raise one.
|
||||
model = str(first_exception)
|
||||
if all(str(exc) == model for exc in all_exceptions):
|
||||
raise first_exception
|
||||
# Raise a combined exception so the user can see all
|
||||
# the various error messages.
|
||||
msg = "Multiple exceptions: {}".format(
|
||||
", ".join(str(exc) for exc in all_exceptions)
|
||||
)
|
||||
# If the errno is the same for all exceptions, raise
|
||||
# an OSError with that errno.
|
||||
if isinstance(first_exception, OSError):
|
||||
first_errno = first_exception.errno
|
||||
if all(
|
||||
isinstance(exc, OSError) and exc.errno == first_errno
|
||||
for exc in all_exceptions
|
||||
):
|
||||
raise OSError(first_errno, msg)
|
||||
elif isinstance(first_exception, RuntimeError) and all(
|
||||
isinstance(exc, RuntimeError) for exc in all_exceptions
|
||||
):
|
||||
raise RuntimeError(msg)
|
||||
# We have a mix of OSError and RuntimeError
|
||||
# so we have to pick which one to raise.
|
||||
# and we raise OSError for compatibility
|
||||
raise OSError(msg)
|
||||
finally:
|
||||
all_exceptions = None # type: ignore[assignment]
|
||||
exceptions = None # type: ignore[assignment]
|
||||
|
||||
return sock
|
||||
|
||||
|
||||
async def _connect_sock(
|
||||
loop: asyncio.AbstractEventLoop,
|
||||
exceptions: List[List[Union[OSError, RuntimeError]]],
|
||||
addr_info: AddrInfoType,
|
||||
local_addr_infos: Optional[Sequence[AddrInfoType]] = None,
|
||||
open_sockets: Optional[Set[socket.socket]] = None,
|
||||
socket_factory: Optional[SocketFactoryType] = None,
|
||||
) -> socket.socket:
|
||||
"""
|
||||
Create, bind and connect one socket.
|
||||
|
||||
If open_sockets is passed, add the socket to the set of open sockets.
|
||||
Any failure caught here will remove the socket from the set and close it.
|
||||
|
||||
Callers can use this set to close any sockets that are not the winner
|
||||
of all staggered tasks in the result there are runner up sockets aka
|
||||
multiple winners.
|
||||
"""
|
||||
my_exceptions: List[Union[OSError, RuntimeError]] = []
|
||||
exceptions.append(my_exceptions)
|
||||
family, type_, proto, _, address = addr_info
|
||||
sock = None
|
||||
try:
|
||||
if socket_factory is not None:
|
||||
sock = socket_factory(addr_info)
|
||||
else:
|
||||
sock = socket.socket(family=family, type=type_, proto=proto)
|
||||
if open_sockets is not None:
|
||||
open_sockets.add(sock)
|
||||
sock.setblocking(False)
|
||||
if local_addr_infos is not None:
|
||||
for lfamily, _, _, _, laddr in local_addr_infos:
|
||||
# skip local addresses of different family
|
||||
if lfamily != family:
|
||||
continue
|
||||
try:
|
||||
sock.bind(laddr)
|
||||
break
|
||||
except OSError as exc:
|
||||
msg = (
|
||||
f"error while attempting to bind on "
|
||||
f"address {laddr!r}: "
|
||||
f"{(exc.strerror or '').lower()}"
|
||||
)
|
||||
exc = OSError(exc.errno, msg)
|
||||
my_exceptions.append(exc)
|
||||
else: # all bind attempts failed
|
||||
if my_exceptions:
|
||||
raise my_exceptions.pop()
|
||||
else:
|
||||
raise OSError(f"no matching local address with {family=} found")
|
||||
await loop.sock_connect(sock, address)
|
||||
return sock
|
||||
except (RuntimeError, OSError) as exc:
|
||||
my_exceptions.append(exc)
|
||||
if sock is not None:
|
||||
if open_sockets is not None:
|
||||
open_sockets.remove(sock)
|
||||
try:
|
||||
sock.close()
|
||||
except OSError as e:
|
||||
my_exceptions.append(e)
|
||||
raise
|
||||
raise
|
||||
except:
|
||||
if sock is not None:
|
||||
if open_sockets is not None:
|
||||
open_sockets.remove(sock)
|
||||
try:
|
||||
sock.close()
|
||||
except OSError as e:
|
||||
my_exceptions.append(e)
|
||||
raise
|
||||
raise
|
||||
finally:
|
||||
exceptions = my_exceptions = None # type: ignore[assignment]
|
||||
|
||||
|
||||
def _interleave_addrinfos(
|
||||
addrinfos: Sequence[AddrInfoType], first_address_family_count: int = 1
|
||||
) -> List[AddrInfoType]:
|
||||
"""Interleave list of addrinfo tuples by family."""
|
||||
# Group addresses by family
|
||||
addrinfos_by_family: collections.OrderedDict[int, List[AddrInfoType]] = (
|
||||
collections.OrderedDict()
|
||||
)
|
||||
for addr in addrinfos:
|
||||
family = addr[0]
|
||||
if family not in addrinfos_by_family:
|
||||
addrinfos_by_family[family] = []
|
||||
addrinfos_by_family[family].append(addr)
|
||||
addrinfos_lists = list(addrinfos_by_family.values())
|
||||
|
||||
reordered: List[AddrInfoType] = []
|
||||
if first_address_family_count > 1:
|
||||
reordered.extend(addrinfos_lists[0][: first_address_family_count - 1])
|
||||
del addrinfos_lists[0][: first_address_family_count - 1]
|
||||
reordered.extend(
|
||||
a
|
||||
for a in itertools.chain.from_iterable(itertools.zip_longest(*addrinfos_lists))
|
||||
if a is not None
|
||||
)
|
||||
return reordered
|
||||
+17
@@ -0,0 +1,17 @@
|
||||
"""Types for aiohappyeyeballs."""
|
||||
|
||||
import socket
|
||||
|
||||
# PY3.9: Import Callable from typing until we drop Python 3.9 support
|
||||
# https://github.com/python/cpython/issues/87131
|
||||
from typing import Callable, Tuple, Union
|
||||
|
||||
AddrInfoType = Tuple[
|
||||
Union[int, socket.AddressFamily],
|
||||
Union[int, socket.SocketKind],
|
||||
int,
|
||||
str,
|
||||
Tuple, # type: ignore[type-arg]
|
||||
]
|
||||
|
||||
SocketFactoryType = Callable[[AddrInfoType], socket.socket]
|
||||
+97
@@ -0,0 +1,97 @@
|
||||
"""Utility functions for aiohappyeyeballs."""
|
||||
|
||||
import ipaddress
|
||||
import socket
|
||||
from typing import Dict, List, Optional, Tuple, Union
|
||||
|
||||
from .types import AddrInfoType
|
||||
|
||||
|
||||
def addr_to_addr_infos(
|
||||
addr: Optional[
|
||||
Union[Tuple[str, int, int, int], Tuple[str, int, int], Tuple[str, int]]
|
||||
],
|
||||
) -> Optional[List[AddrInfoType]]:
|
||||
"""Convert an address tuple to a list of addr_info tuples."""
|
||||
if addr is None:
|
||||
return None
|
||||
host = addr[0]
|
||||
port = addr[1]
|
||||
is_ipv6 = ":" in host
|
||||
if is_ipv6:
|
||||
flowinfo = 0
|
||||
scopeid = 0
|
||||
addr_len = len(addr)
|
||||
if addr_len >= 4:
|
||||
scopeid = addr[3] # type: ignore[misc]
|
||||
if addr_len >= 3:
|
||||
flowinfo = addr[2] # type: ignore[misc]
|
||||
addr = (host, port, flowinfo, scopeid)
|
||||
family = socket.AF_INET6
|
||||
else:
|
||||
addr = (host, port)
|
||||
family = socket.AF_INET
|
||||
return [(family, socket.SOCK_STREAM, socket.IPPROTO_TCP, "", addr)]
|
||||
|
||||
|
||||
def pop_addr_infos_interleave(
|
||||
addr_infos: List[AddrInfoType], interleave: Optional[int] = None
|
||||
) -> None:
|
||||
"""
|
||||
Pop addr_info from the list of addr_infos by family up to interleave times.
|
||||
|
||||
The interleave parameter is used to know how many addr_infos for
|
||||
each family should be popped of the top of the list.
|
||||
"""
|
||||
seen: Dict[int, int] = {}
|
||||
if interleave is None:
|
||||
interleave = 1
|
||||
to_remove: List[AddrInfoType] = []
|
||||
for addr_info in addr_infos:
|
||||
family = addr_info[0]
|
||||
if family not in seen:
|
||||
seen[family] = 0
|
||||
if seen[family] < interleave:
|
||||
to_remove.append(addr_info)
|
||||
seen[family] += 1
|
||||
for addr_info in to_remove:
|
||||
addr_infos.remove(addr_info)
|
||||
|
||||
|
||||
def _addr_tuple_to_ip_address(
|
||||
addr: Union[Tuple[str, int], Tuple[str, int, int, int]],
|
||||
) -> Union[
|
||||
Tuple[ipaddress.IPv4Address, int], Tuple[ipaddress.IPv6Address, int, int, int]
|
||||
]:
|
||||
"""Convert an address tuple to an IPv4Address."""
|
||||
return (ipaddress.ip_address(addr[0]), *addr[1:])
|
||||
|
||||
|
||||
def remove_addr_infos(
|
||||
addr_infos: List[AddrInfoType],
|
||||
addr: Union[Tuple[str, int], Tuple[str, int, int, int]],
|
||||
) -> None:
|
||||
"""
|
||||
Remove an address from the list of addr_infos.
|
||||
|
||||
The addr value is typically the return value of
|
||||
sock.getpeername().
|
||||
"""
|
||||
bad_addrs_infos: List[AddrInfoType] = []
|
||||
for addr_info in addr_infos:
|
||||
if addr_info[-1] == addr:
|
||||
bad_addrs_infos.append(addr_info)
|
||||
if bad_addrs_infos:
|
||||
for bad_addr_info in bad_addrs_infos:
|
||||
addr_infos.remove(bad_addr_info)
|
||||
return
|
||||
# Slow path in case addr is formatted differently
|
||||
match_addr = _addr_tuple_to_ip_address(addr)
|
||||
for addr_info in addr_infos:
|
||||
if match_addr == _addr_tuple_to_ip_address(addr_info[-1]):
|
||||
bad_addrs_infos.append(addr_info)
|
||||
if bad_addrs_infos:
|
||||
for bad_addr_info in bad_addrs_infos:
|
||||
addr_infos.remove(bad_addr_info)
|
||||
return
|
||||
raise ValueError(f"Address {addr} not found in addr_infos")
|
||||
+1
@@ -0,0 +1 @@
|
||||
pip
|
||||
+262
@@ -0,0 +1,262 @@
|
||||
Metadata-Version: 2.4
|
||||
Name: aiohttp
|
||||
Version: 3.13.3
|
||||
Summary: Async http client/server framework (asyncio)
|
||||
Maintainer-email: aiohttp team <team@aiohttp.org>
|
||||
License: Apache-2.0 AND MIT
|
||||
Project-URL: Homepage, https://github.com/aio-libs/aiohttp
|
||||
Project-URL: Chat: Matrix, https://matrix.to/#/#aio-libs:matrix.org
|
||||
Project-URL: Chat: Matrix Space, https://matrix.to/#/#aio-libs-space:matrix.org
|
||||
Project-URL: CI: GitHub Actions, https://github.com/aio-libs/aiohttp/actions?query=workflow%3ACI
|
||||
Project-URL: Coverage: codecov, https://codecov.io/github/aio-libs/aiohttp
|
||||
Project-URL: Docs: Changelog, https://docs.aiohttp.org/en/stable/changes.html
|
||||
Project-URL: Docs: RTD, https://docs.aiohttp.org
|
||||
Project-URL: GitHub: issues, https://github.com/aio-libs/aiohttp/issues
|
||||
Project-URL: GitHub: repo, https://github.com/aio-libs/aiohttp
|
||||
Classifier: Development Status :: 5 - Production/Stable
|
||||
Classifier: Framework :: AsyncIO
|
||||
Classifier: Intended Audience :: Developers
|
||||
Classifier: Operating System :: POSIX
|
||||
Classifier: Operating System :: MacOS :: MacOS X
|
||||
Classifier: Operating System :: Microsoft :: Windows
|
||||
Classifier: Programming Language :: Python
|
||||
Classifier: Programming Language :: Python :: 3
|
||||
Classifier: Programming Language :: Python :: 3.9
|
||||
Classifier: Programming Language :: Python :: 3.10
|
||||
Classifier: Programming Language :: Python :: 3.11
|
||||
Classifier: Programming Language :: Python :: 3.12
|
||||
Classifier: Programming Language :: Python :: 3.13
|
||||
Classifier: Programming Language :: Python :: 3.14
|
||||
Classifier: Topic :: Internet :: WWW/HTTP
|
||||
Requires-Python: >=3.9
|
||||
Description-Content-Type: text/x-rst
|
||||
License-File: LICENSE.txt
|
||||
License-File: vendor/llhttp/LICENSE
|
||||
Requires-Dist: aiohappyeyeballs>=2.5.0
|
||||
Requires-Dist: aiosignal>=1.4.0
|
||||
Requires-Dist: async-timeout<6.0,>=4.0; python_version < "3.11"
|
||||
Requires-Dist: attrs>=17.3.0
|
||||
Requires-Dist: frozenlist>=1.1.1
|
||||
Requires-Dist: multidict<7.0,>=4.5
|
||||
Requires-Dist: propcache>=0.2.0
|
||||
Requires-Dist: yarl<2.0,>=1.17.0
|
||||
Provides-Extra: speedups
|
||||
Requires-Dist: aiodns>=3.3.0; extra == "speedups"
|
||||
Requires-Dist: Brotli>=1.2; platform_python_implementation == "CPython" and extra == "speedups"
|
||||
Requires-Dist: brotlicffi>=1.2; platform_python_implementation != "CPython" and extra == "speedups"
|
||||
Requires-Dist: backports.zstd; (platform_python_implementation == "CPython" and python_version < "3.14") and extra == "speedups"
|
||||
Dynamic: license-file
|
||||
|
||||
==================================
|
||||
Async http client/server framework
|
||||
==================================
|
||||
|
||||
.. image:: https://raw.githubusercontent.com/aio-libs/aiohttp/master/docs/aiohttp-plain.svg
|
||||
:height: 64px
|
||||
:width: 64px
|
||||
:alt: aiohttp logo
|
||||
|
||||
|
|
||||
|
||||
.. image:: https://github.com/aio-libs/aiohttp/workflows/CI/badge.svg
|
||||
:target: https://github.com/aio-libs/aiohttp/actions?query=workflow%3ACI
|
||||
:alt: GitHub Actions status for master branch
|
||||
|
||||
.. image:: https://codecov.io/gh/aio-libs/aiohttp/branch/master/graph/badge.svg
|
||||
:target: https://codecov.io/gh/aio-libs/aiohttp
|
||||
:alt: codecov.io status for master branch
|
||||
|
||||
.. image:: https://badge.fury.io/py/aiohttp.svg
|
||||
:target: https://pypi.org/project/aiohttp
|
||||
:alt: Latest PyPI package version
|
||||
|
||||
.. image:: https://img.shields.io/pypi/dm/aiohttp
|
||||
:target: https://pypistats.org/packages/aiohttp
|
||||
:alt: Downloads count
|
||||
|
||||
.. image:: https://readthedocs.org/projects/aiohttp/badge/?version=latest
|
||||
:target: https://docs.aiohttp.org/
|
||||
:alt: Latest Read The Docs
|
||||
|
||||
.. image:: https://img.shields.io/endpoint?url=https://codspeed.io/badge.json
|
||||
:target: https://codspeed.io/aio-libs/aiohttp
|
||||
:alt: Codspeed.io status for aiohttp
|
||||
|
||||
|
||||
Key Features
|
||||
============
|
||||
|
||||
- Supports both client and server side of HTTP protocol.
|
||||
- Supports both client and server Web-Sockets out-of-the-box and avoids
|
||||
Callback Hell.
|
||||
- Provides Web-server with middleware and pluggable routing.
|
||||
|
||||
|
||||
Getting started
|
||||
===============
|
||||
|
||||
Client
|
||||
------
|
||||
|
||||
To get something from the web:
|
||||
|
||||
.. code-block:: python
|
||||
|
||||
import aiohttp
|
||||
import asyncio
|
||||
|
||||
async def main():
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get('http://python.org') as response:
|
||||
|
||||
print("Status:", response.status)
|
||||
print("Content-type:", response.headers['content-type'])
|
||||
|
||||
html = await response.text()
|
||||
print("Body:", html[:15], "...")
|
||||
|
||||
asyncio.run(main())
|
||||
|
||||
This prints:
|
||||
|
||||
.. code-block::
|
||||
|
||||
Status: 200
|
||||
Content-type: text/html; charset=utf-8
|
||||
Body: <!doctype html> ...
|
||||
|
||||
Coming from `requests <https://requests.readthedocs.io/>`_ ? Read `why we need so many lines <https://aiohttp.readthedocs.io/en/latest/http_request_lifecycle.html>`_.
|
||||
|
||||
Server
|
||||
------
|
||||
|
||||
An example using a simple server:
|
||||
|
||||
.. code-block:: python
|
||||
|
||||
# examples/server_simple.py
|
||||
from aiohttp import web
|
||||
|
||||
async def handle(request):
|
||||
name = request.match_info.get('name', "Anonymous")
|
||||
text = "Hello, " + name
|
||||
return web.Response(text=text)
|
||||
|
||||
async def wshandle(request):
|
||||
ws = web.WebSocketResponse()
|
||||
await ws.prepare(request)
|
||||
|
||||
async for msg in ws:
|
||||
if msg.type == web.WSMsgType.text:
|
||||
await ws.send_str("Hello, {}".format(msg.data))
|
||||
elif msg.type == web.WSMsgType.binary:
|
||||
await ws.send_bytes(msg.data)
|
||||
elif msg.type == web.WSMsgType.close:
|
||||
break
|
||||
|
||||
return ws
|
||||
|
||||
|
||||
app = web.Application()
|
||||
app.add_routes([web.get('/', handle),
|
||||
web.get('/echo', wshandle),
|
||||
web.get('/{name}', handle)])
|
||||
|
||||
if __name__ == '__main__':
|
||||
web.run_app(app)
|
||||
|
||||
|
||||
Documentation
|
||||
=============
|
||||
|
||||
https://aiohttp.readthedocs.io/
|
||||
|
||||
|
||||
Demos
|
||||
=====
|
||||
|
||||
https://github.com/aio-libs/aiohttp-demos
|
||||
|
||||
|
||||
External links
|
||||
==============
|
||||
|
||||
* `Third party libraries
|
||||
<http://aiohttp.readthedocs.io/en/latest/third_party.html>`_
|
||||
* `Built with aiohttp
|
||||
<http://aiohttp.readthedocs.io/en/latest/built_with.html>`_
|
||||
* `Powered by aiohttp
|
||||
<http://aiohttp.readthedocs.io/en/latest/powered_by.html>`_
|
||||
|
||||
Feel free to make a Pull Request for adding your link to these pages!
|
||||
|
||||
|
||||
Communication channels
|
||||
======================
|
||||
|
||||
*aio-libs Discussions*: https://github.com/aio-libs/aiohttp/discussions
|
||||
|
||||
*Matrix*: `#aio-libs:matrix.org <https://matrix.to/#/#aio-libs:matrix.org>`_
|
||||
|
||||
We support `Stack Overflow
|
||||
<https://stackoverflow.com/questions/tagged/aiohttp>`_.
|
||||
Please add *aiohttp* tag to your question there.
|
||||
|
||||
Requirements
|
||||
============
|
||||
|
||||
- attrs_
|
||||
- multidict_
|
||||
- yarl_
|
||||
- frozenlist_
|
||||
|
||||
Optionally you may install the aiodns_ library (highly recommended for sake of speed).
|
||||
|
||||
.. _aiodns: https://pypi.python.org/pypi/aiodns
|
||||
.. _attrs: https://github.com/python-attrs/attrs
|
||||
.. _multidict: https://pypi.python.org/pypi/multidict
|
||||
.. _frozenlist: https://pypi.org/project/frozenlist/
|
||||
.. _yarl: https://pypi.python.org/pypi/yarl
|
||||
.. _async-timeout: https://pypi.python.org/pypi/async_timeout
|
||||
|
||||
License
|
||||
=======
|
||||
|
||||
``aiohttp`` is offered under the Apache 2 license.
|
||||
|
||||
|
||||
Keepsafe
|
||||
========
|
||||
|
||||
The aiohttp community would like to thank Keepsafe
|
||||
(https://www.getkeepsafe.com) for its support in the early days of
|
||||
the project.
|
||||
|
||||
|
||||
Source code
|
||||
===========
|
||||
|
||||
The latest developer version is available in a GitHub repository:
|
||||
https://github.com/aio-libs/aiohttp
|
||||
|
||||
Benchmarks
|
||||
==========
|
||||
|
||||
If you are interested in efficiency, the AsyncIO community maintains a
|
||||
list of benchmarks on the official wiki:
|
||||
https://github.com/python/asyncio/wiki/Benchmarks
|
||||
|
||||
--------
|
||||
|
||||
.. image:: https://img.shields.io/matrix/aio-libs:matrix.org?label=Discuss%20on%20Matrix%20at%20%23aio-libs%3Amatrix.org&logo=matrix&server_fqdn=matrix.org&style=flat
|
||||
:target: https://matrix.to/#/%23aio-libs:matrix.org
|
||||
:alt: Matrix Room — #aio-libs:matrix.org
|
||||
|
||||
.. image:: https://img.shields.io/matrix/aio-libs-space:matrix.org?label=Discuss%20on%20Matrix%20at%20%23aio-libs-space%3Amatrix.org&logo=matrix&server_fqdn=matrix.org&style=flat
|
||||
:target: https://matrix.to/#/%23aio-libs-space:matrix.org
|
||||
:alt: Matrix Space — #aio-libs-space:matrix.org
|
||||
|
||||
.. image:: https://insights.linuxfoundation.org/api/badge/health-score?project=aiohttp
|
||||
:target: https://insights.linuxfoundation.org/project/aiohttp
|
||||
:alt: LFX Health Score
|
||||
+139
@@ -0,0 +1,139 @@
|
||||
aiohttp-3.13.3.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4
|
||||
aiohttp-3.13.3.dist-info/METADATA,sha256=CQROZCStho-eb7xiFIuAzj30JuupEU_jHpYDFiG_HhM,8145
|
||||
aiohttp-3.13.3.dist-info/RECORD,,
|
||||
aiohttp-3.13.3.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
|
||||
aiohttp-3.13.3.dist-info/WHEEL,sha256=DxRnWQz-Kp9-4a4hdDHsSv0KUC3H7sN9Nbef3-8RjXU,190
|
||||
aiohttp-3.13.3.dist-info/licenses/LICENSE.txt,sha256=n4DQ2311WpQdtFchcsJw7L2PCCuiFd3QlZhZQu2Uqes,588
|
||||
aiohttp-3.13.3.dist-info/licenses/vendor/llhttp/LICENSE,sha256=68qFTgE0zSVtZzYnwgSZ9CV363S6zwi58ltianPJEnc,1105
|
||||
aiohttp-3.13.3.dist-info/top_level.txt,sha256=iv-JIaacmTl-hSho3QmphcKnbRRYx1st47yjz_178Ro,8
|
||||
aiohttp/.hash/_cparser.pxd.hash,sha256=pjs-sEXNw_eijXGAedwG-BHnlFp8B7sOCgUagIWaU2A,121
|
||||
aiohttp/.hash/_find_header.pxd.hash,sha256=_mbpD6vM-CVCKq3ulUvsOAz5Wdo88wrDzfpOsMQaMNA,125
|
||||
aiohttp/.hash/_http_parser.pyx.hash,sha256=RKkD9x-EhXksvXrpCaTNWYtffb52urLvuTnxbTN2Lmw,125
|
||||
aiohttp/.hash/_http_writer.pyx.hash,sha256=9txOh7t7c3y-vLmiuEY5dltmXvEo0CYyU4U853yyv9E,125
|
||||
aiohttp/.hash/hdrs.py.hash,sha256=v6IaKbsxjsdQxBzhb5AjP0x_9G3rUe84D7avf7AI4cs,116
|
||||
aiohttp/__init__.py,sha256=QWssFaD-DaFFcwP36lLUQzRmlSZ5KxivJBU-yg5C1wg,8302
|
||||
aiohttp/__pycache__/__init__.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/_cookie_helpers.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/abc.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/base_protocol.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/client.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/client_exceptions.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/client_middleware_digest_auth.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/client_middlewares.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/client_proto.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/client_reqrep.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/client_ws.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/compression_utils.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/connector.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/cookiejar.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/formdata.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/hdrs.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/helpers.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/http.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/http_exceptions.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/http_parser.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/http_websocket.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/http_writer.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/log.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/multipart.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/payload.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/payload_streamer.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/pytest_plugin.cpython-312.pyc,,
|
||||
aiohttp/__pycache__/resolver.cpython-312.pyc,,
|
||||
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||||
aiohttp/worker.py,sha256=zT0iWN5Xze194bO6_VjHou0x7lR_k0MviN6Kadnk22g,8152
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||||
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|
||||
Wheel-Version: 1.0
|
||||
Generator: setuptools (80.9.0)
|
||||
Root-Is-Purelib: false
|
||||
Tag: cp312-cp312-manylinux_2_17_x86_64
|
||||
Tag: cp312-cp312-manylinux2014_x86_64
|
||||
Tag: cp312-cp312-manylinux_2_28_x86_64
|
||||
|
||||
+13
@@ -0,0 +1,13 @@
|
||||
Copyright aio-libs contributors.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
+22
@@ -0,0 +1,22 @@
|
||||
This software is licensed under the MIT License.
|
||||
|
||||
Copyright Fedor Indutny, 2018.
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a
|
||||
copy of this software and associated documentation files (the
|
||||
"Software"), to deal in the Software without restriction, including
|
||||
without limitation the rights to use, copy, modify, merge, publish,
|
||||
distribute, sublicense, and/or sell copies of the Software, and to permit
|
||||
persons to whom the Software is furnished to do so, subject to the
|
||||
following conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be included
|
||||
in all copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
|
||||
OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
|
||||
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN
|
||||
NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,
|
||||
DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR
|
||||
OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE
|
||||
USE OR OTHER DEALINGS IN THE SOFTWARE.
|
||||
+1
@@ -0,0 +1 @@
|
||||
aiohttp
|
||||
+1
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|
||||
5276d46021e0e0d7577e0c9155800cbf62932d60a50783fec42aefb63febedec /home/runner/work/aiohttp/aiohttp/aiohttp/_cparser.pxd
|
||||
+1
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|
||||
d067f01423cddb3c442933b5fcc039b18ab651fcec1bc91c577693aafc25cf78 /home/runner/work/aiohttp/aiohttp/aiohttp/_find_header.pxd
|
||||
+1
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|
||||
f9823c608638b8a77fec1c2bd28dc5c043f08c775ec59e7e262dd74b4ebb7384 /home/runner/work/aiohttp/aiohttp/aiohttp/_http_parser.pyx
|
||||
+1
@@ -0,0 +1 @@
|
||||
56514404ce87a15bfc6b400026d73a270165b2fdbe70313cfa007de29ddd7e14 /home/runner/work/aiohttp/aiohttp/aiohttp/_http_writer.pyx
|
||||
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|
||||
dab8f933203eeb245d60f856e542a45b888d5a110094620e4811f90f816628d1 /home/runner/work/aiohttp/aiohttp/aiohttp/hdrs.py
|
||||
@@ -0,0 +1,278 @@
|
||||
__version__ = "3.13.3"
|
||||
|
||||
from typing import TYPE_CHECKING, Tuple
|
||||
|
||||
from . import hdrs as hdrs
|
||||
from .client import (
|
||||
BaseConnector,
|
||||
ClientConnectionError,
|
||||
ClientConnectionResetError,
|
||||
ClientConnectorCertificateError,
|
||||
ClientConnectorDNSError,
|
||||
ClientConnectorError,
|
||||
ClientConnectorSSLError,
|
||||
ClientError,
|
||||
ClientHttpProxyError,
|
||||
ClientOSError,
|
||||
ClientPayloadError,
|
||||
ClientProxyConnectionError,
|
||||
ClientRequest,
|
||||
ClientResponse,
|
||||
ClientResponseError,
|
||||
ClientSession,
|
||||
ClientSSLError,
|
||||
ClientTimeout,
|
||||
ClientWebSocketResponse,
|
||||
ClientWSTimeout,
|
||||
ConnectionTimeoutError,
|
||||
ContentTypeError,
|
||||
Fingerprint,
|
||||
InvalidURL,
|
||||
InvalidUrlClientError,
|
||||
InvalidUrlRedirectClientError,
|
||||
NamedPipeConnector,
|
||||
NonHttpUrlClientError,
|
||||
NonHttpUrlRedirectClientError,
|
||||
RedirectClientError,
|
||||
RequestInfo,
|
||||
ServerConnectionError,
|
||||
ServerDisconnectedError,
|
||||
ServerFingerprintMismatch,
|
||||
ServerTimeoutError,
|
||||
SocketTimeoutError,
|
||||
TCPConnector,
|
||||
TooManyRedirects,
|
||||
UnixConnector,
|
||||
WSMessageTypeError,
|
||||
WSServerHandshakeError,
|
||||
request,
|
||||
)
|
||||
from .client_middleware_digest_auth import DigestAuthMiddleware
|
||||
from .client_middlewares import ClientHandlerType, ClientMiddlewareType
|
||||
from .compression_utils import set_zlib_backend
|
||||
from .connector import (
|
||||
AddrInfoType as AddrInfoType,
|
||||
SocketFactoryType as SocketFactoryType,
|
||||
)
|
||||
from .cookiejar import CookieJar as CookieJar, DummyCookieJar as DummyCookieJar
|
||||
from .formdata import FormData as FormData
|
||||
from .helpers import BasicAuth, ChainMapProxy, ETag
|
||||
from .http import (
|
||||
HttpVersion as HttpVersion,
|
||||
HttpVersion10 as HttpVersion10,
|
||||
HttpVersion11 as HttpVersion11,
|
||||
WebSocketError as WebSocketError,
|
||||
WSCloseCode as WSCloseCode,
|
||||
WSMessage as WSMessage,
|
||||
WSMsgType as WSMsgType,
|
||||
)
|
||||
from .multipart import (
|
||||
BadContentDispositionHeader as BadContentDispositionHeader,
|
||||
BadContentDispositionParam as BadContentDispositionParam,
|
||||
BodyPartReader as BodyPartReader,
|
||||
MultipartReader as MultipartReader,
|
||||
MultipartWriter as MultipartWriter,
|
||||
content_disposition_filename as content_disposition_filename,
|
||||
parse_content_disposition as parse_content_disposition,
|
||||
)
|
||||
from .payload import (
|
||||
PAYLOAD_REGISTRY as PAYLOAD_REGISTRY,
|
||||
AsyncIterablePayload as AsyncIterablePayload,
|
||||
BufferedReaderPayload as BufferedReaderPayload,
|
||||
BytesIOPayload as BytesIOPayload,
|
||||
BytesPayload as BytesPayload,
|
||||
IOBasePayload as IOBasePayload,
|
||||
JsonPayload as JsonPayload,
|
||||
Payload as Payload,
|
||||
StringIOPayload as StringIOPayload,
|
||||
StringPayload as StringPayload,
|
||||
TextIOPayload as TextIOPayload,
|
||||
get_payload as get_payload,
|
||||
payload_type as payload_type,
|
||||
)
|
||||
from .payload_streamer import streamer as streamer
|
||||
from .resolver import (
|
||||
AsyncResolver as AsyncResolver,
|
||||
DefaultResolver as DefaultResolver,
|
||||
ThreadedResolver as ThreadedResolver,
|
||||
)
|
||||
from .streams import (
|
||||
EMPTY_PAYLOAD as EMPTY_PAYLOAD,
|
||||
DataQueue as DataQueue,
|
||||
EofStream as EofStream,
|
||||
FlowControlDataQueue as FlowControlDataQueue,
|
||||
StreamReader as StreamReader,
|
||||
)
|
||||
from .tracing import (
|
||||
TraceConfig as TraceConfig,
|
||||
TraceConnectionCreateEndParams as TraceConnectionCreateEndParams,
|
||||
TraceConnectionCreateStartParams as TraceConnectionCreateStartParams,
|
||||
TraceConnectionQueuedEndParams as TraceConnectionQueuedEndParams,
|
||||
TraceConnectionQueuedStartParams as TraceConnectionQueuedStartParams,
|
||||
TraceConnectionReuseconnParams as TraceConnectionReuseconnParams,
|
||||
TraceDnsCacheHitParams as TraceDnsCacheHitParams,
|
||||
TraceDnsCacheMissParams as TraceDnsCacheMissParams,
|
||||
TraceDnsResolveHostEndParams as TraceDnsResolveHostEndParams,
|
||||
TraceDnsResolveHostStartParams as TraceDnsResolveHostStartParams,
|
||||
TraceRequestChunkSentParams as TraceRequestChunkSentParams,
|
||||
TraceRequestEndParams as TraceRequestEndParams,
|
||||
TraceRequestExceptionParams as TraceRequestExceptionParams,
|
||||
TraceRequestHeadersSentParams as TraceRequestHeadersSentParams,
|
||||
TraceRequestRedirectParams as TraceRequestRedirectParams,
|
||||
TraceRequestStartParams as TraceRequestStartParams,
|
||||
TraceResponseChunkReceivedParams as TraceResponseChunkReceivedParams,
|
||||
)
|
||||
|
||||
if TYPE_CHECKING:
|
||||
# At runtime these are lazy-loaded at the bottom of the file.
|
||||
from .worker import (
|
||||
GunicornUVLoopWebWorker as GunicornUVLoopWebWorker,
|
||||
GunicornWebWorker as GunicornWebWorker,
|
||||
)
|
||||
|
||||
__all__: Tuple[str, ...] = (
|
||||
"hdrs",
|
||||
# client
|
||||
"AddrInfoType",
|
||||
"BaseConnector",
|
||||
"ClientConnectionError",
|
||||
"ClientConnectionResetError",
|
||||
"ClientConnectorCertificateError",
|
||||
"ClientConnectorDNSError",
|
||||
"ClientConnectorError",
|
||||
"ClientConnectorSSLError",
|
||||
"ClientError",
|
||||
"ClientHttpProxyError",
|
||||
"ClientOSError",
|
||||
"ClientPayloadError",
|
||||
"ClientProxyConnectionError",
|
||||
"ClientResponse",
|
||||
"ClientRequest",
|
||||
"ClientResponseError",
|
||||
"ClientSSLError",
|
||||
"ClientSession",
|
||||
"ClientTimeout",
|
||||
"ClientWebSocketResponse",
|
||||
"ClientWSTimeout",
|
||||
"ConnectionTimeoutError",
|
||||
"ContentTypeError",
|
||||
"Fingerprint",
|
||||
"FlowControlDataQueue",
|
||||
"InvalidURL",
|
||||
"InvalidUrlClientError",
|
||||
"InvalidUrlRedirectClientError",
|
||||
"NonHttpUrlClientError",
|
||||
"NonHttpUrlRedirectClientError",
|
||||
"RedirectClientError",
|
||||
"RequestInfo",
|
||||
"ServerConnectionError",
|
||||
"ServerDisconnectedError",
|
||||
"ServerFingerprintMismatch",
|
||||
"ServerTimeoutError",
|
||||
"SocketFactoryType",
|
||||
"SocketTimeoutError",
|
||||
"TCPConnector",
|
||||
"TooManyRedirects",
|
||||
"UnixConnector",
|
||||
"NamedPipeConnector",
|
||||
"WSServerHandshakeError",
|
||||
"request",
|
||||
# client_middleware
|
||||
"ClientMiddlewareType",
|
||||
"ClientHandlerType",
|
||||
# cookiejar
|
||||
"CookieJar",
|
||||
"DummyCookieJar",
|
||||
# formdata
|
||||
"FormData",
|
||||
# helpers
|
||||
"BasicAuth",
|
||||
"ChainMapProxy",
|
||||
"DigestAuthMiddleware",
|
||||
"ETag",
|
||||
"set_zlib_backend",
|
||||
# http
|
||||
"HttpVersion",
|
||||
"HttpVersion10",
|
||||
"HttpVersion11",
|
||||
"WSMsgType",
|
||||
"WSCloseCode",
|
||||
"WSMessage",
|
||||
"WebSocketError",
|
||||
# multipart
|
||||
"BadContentDispositionHeader",
|
||||
"BadContentDispositionParam",
|
||||
"BodyPartReader",
|
||||
"MultipartReader",
|
||||
"MultipartWriter",
|
||||
"content_disposition_filename",
|
||||
"parse_content_disposition",
|
||||
# payload
|
||||
"AsyncIterablePayload",
|
||||
"BufferedReaderPayload",
|
||||
"BytesIOPayload",
|
||||
"BytesPayload",
|
||||
"IOBasePayload",
|
||||
"JsonPayload",
|
||||
"PAYLOAD_REGISTRY",
|
||||
"Payload",
|
||||
"StringIOPayload",
|
||||
"StringPayload",
|
||||
"TextIOPayload",
|
||||
"get_payload",
|
||||
"payload_type",
|
||||
# payload_streamer
|
||||
"streamer",
|
||||
# resolver
|
||||
"AsyncResolver",
|
||||
"DefaultResolver",
|
||||
"ThreadedResolver",
|
||||
# streams
|
||||
"DataQueue",
|
||||
"EMPTY_PAYLOAD",
|
||||
"EofStream",
|
||||
"StreamReader",
|
||||
# tracing
|
||||
"TraceConfig",
|
||||
"TraceConnectionCreateEndParams",
|
||||
"TraceConnectionCreateStartParams",
|
||||
"TraceConnectionQueuedEndParams",
|
||||
"TraceConnectionQueuedStartParams",
|
||||
"TraceConnectionReuseconnParams",
|
||||
"TraceDnsCacheHitParams",
|
||||
"TraceDnsCacheMissParams",
|
||||
"TraceDnsResolveHostEndParams",
|
||||
"TraceDnsResolveHostStartParams",
|
||||
"TraceRequestChunkSentParams",
|
||||
"TraceRequestEndParams",
|
||||
"TraceRequestExceptionParams",
|
||||
"TraceRequestHeadersSentParams",
|
||||
"TraceRequestRedirectParams",
|
||||
"TraceRequestStartParams",
|
||||
"TraceResponseChunkReceivedParams",
|
||||
# workers (imported lazily with __getattr__)
|
||||
"GunicornUVLoopWebWorker",
|
||||
"GunicornWebWorker",
|
||||
"WSMessageTypeError",
|
||||
)
|
||||
|
||||
|
||||
def __dir__() -> Tuple[str, ...]:
|
||||
return __all__ + ("__doc__",)
|
||||
|
||||
|
||||
def __getattr__(name: str) -> object:
|
||||
global GunicornUVLoopWebWorker, GunicornWebWorker
|
||||
|
||||
# Importing gunicorn takes a long time (>100ms), so only import if actually needed.
|
||||
if name in ("GunicornUVLoopWebWorker", "GunicornWebWorker"):
|
||||
try:
|
||||
from .worker import GunicornUVLoopWebWorker as guv, GunicornWebWorker as gw
|
||||
except ImportError:
|
||||
return None
|
||||
|
||||
GunicornUVLoopWebWorker = guv # type: ignore[misc]
|
||||
GunicornWebWorker = gw # type: ignore[misc]
|
||||
return guv if name == "GunicornUVLoopWebWorker" else gw
|
||||
|
||||
raise AttributeError(f"module {__name__} has no attribute {name}")
|
||||
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Reference in New Issue
Block a user