> ## Documentation Index
> Fetch the complete documentation index at: https://cndoc-langchain.site/llms.txt
> Use this file to discover all available pages before exploring further.

# 追踪 AutoGen 应用

LangSmith 可以通过 OpenTelemetry 检测来捕获由 [AutoGen](https://microsoft.github.io/autogen/stable/) 生成的追踪。本指南将向您展示如何自动捕获 AutoGen 多智能体对话的追踪，并将其发送到 LangSmith 进行监控和分析。

## 安装

使用您偏好的包管理器安装所需的包：

<CodeGroup>
  ```bash pip theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
  pip install langsmith autogen-agentchat autogen-ext opentelemetry-instrumentation-openai
  ```

  ```bash uv theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
  uv add langsmith autogen-agentchat autogen-ext opentelemetry-instrumentation-openai
  ```
</CodeGroup>

## 设置

### 1. 配置环境变量

设置您的 [API 密钥](/langsmith/create-account-api-key) 和项目名称：

```bash theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
export LANGSMITH_API_KEY=<your_langsmith_api_key>
export LANGSMITH_PROJECT=<your_project_name>
export OPENAI_API_KEY=<your_openai_api_key>
```

### 2. 配置 OpenTelemetry 集成

在您的 AutoGen 应用中，配置 LangSmith OpenTelemetry 集成以及 OpenAI 检测器：

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from langsmith.integrations.otel import OtelSpanProcessor
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.instrumentation.openai import OpenAIInstrumentor

# 设置追踪提供者
tracer_provider = TracerProvider()
tracer_provider.add_span_processor(OtelSpanProcessor())
trace.set_tracer_provider(tracer_provider)

# 检测 OpenAI 调用
OpenAIInstrumentor().instrument()
```

### 3. 创建并运行您的 AutoGen 应用

配置完成后，您的 AutoGen 应用将自动向 LangSmith 发送追踪。将追踪提供者传递给运行时以获得完整的追踪覆盖：

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.conditions import MaxMessageTermination, TextMentionTermination
from autogen_agentchat.teams import SelectorGroupChat
from autogen_agentchat.ui import Console
from autogen_core import SingleThreadedAgentRuntime
from autogen_ext.models.openai import OpenAIChatCompletionClient
from langsmith.integrations.otel import OtelSpanProcessor
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.instrumentation.openai import OpenAIInstrumentor

# 设置追踪
tracer_provider = TracerProvider()
tracer_provider.add_span_processor(OtelSpanProcessor())
trace.set_tracer_provider(tracer_provider)
OpenAIInstrumentor().instrument()

# 定义一个工具
def percentage_change(start: float, end: float) -> float:
    """计算两个值之间的百分比变化。"""
    if start == 0:
        return float("inf")
    return ((end - start) / start) * 100

async def main():
    model_client = OpenAIChatCompletionClient(model="gpt-4o")
    tracer = trace.get_tracer("autogen-demo")

    with tracer.start_as_current_span("run_team"):
        planning_agent = AssistantAgent(
            "PlanningAgent",
            description="规划任务并委派。",
            model_client=model_client,
            system_message=(
                "你是一个规划代理。规划并委派任务。\n"
                "分配任务时，请使用：1. <agent> : <task>\n"
                '任务完成后，进行总结并以 "TERMINATE" 结束。'
            ),
        )

        data_analyst = AssistantAgent(
            "DataAnalystAgent",
            description="执行计算。",
            model_client=model_client,
            tools=[percentage_change],
            system_message="你是一个数据分析师。使用工具来计算结果。",
        )

        termination = TextMentionTermination("TERMINATE") | MaxMessageTermination(max_messages=25)

        # 将 tracer_provider 传递给运行时
        runtime = SingleThreadedAgentRuntime(tracer_provider=trace.get_tracer_provider())
        runtime.start()

        team = SelectorGroupChat(
            [planning_agent, data_analyst],
            model_client=model_client,
            termination_condition=termination,
            allow_repeated_speaker=True,
            runtime=runtime,
        )

        task = "你开始时有 100 个苹果，现在你有 120 个苹果。百分比变化是多少？"
        await Console(team.run_stream(task=task))

        await runtime.stop()

    await model_client.close()

if __name__ == "__main__":
    asyncio.run(main())
```

## 高级用法

### 自定义元数据和标签

您可以通过设置跨度属性为追踪添加自定义元数据：

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from opentelemetry import trace

tracer = trace.get_tracer(__name__)

async def run_with_metadata():
    with tracer.start_as_current_span("autogen_workflow") as span:
        span.set_attribute("langsmith.metadata.session_type", "multi_agent")
        span.set_attribute("langsmith.metadata.agent_count", "2")
        span.set_attribute("langsmith.span.tags", "autogen,planning")

        # 您的 AutoGen 代码在此处
        await Console(team.run_stream(task=task))
```

### 与其他检测器结合使用

您可以将 AutoGen 追踪与其他 OpenTelemetry 检测器结合使用：

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from opentelemetry.instrumentation.openai import OpenAIInstrumentor
from opentelemetry.instrumentation.httpx import HTTPXClientInstrumentor

# 初始化多个检测器
OpenAIInstrumentor().instrument()
HTTPXClientInstrumentor().instrument()
```

## 资源

* [AutoGen 文档](https://microsoft.github.io/autogen/stable/)
* [LangSmith OpenTelemetry 指南](/langsmith/trace-with-opentelemetry)

***

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