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

# 追踪 Semantic Kernel 应用

LangSmith 可以利用其内置的 OpenTelemetry 支持捕获由 [Semantic Kernel](https://learn.microsoft.com/en-us/semantic-kernel/overview/) 生成的追踪信息。本指南将向您展示如何自动捕获来自 Semantic Kernel 应用的追踪数据，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 semantic-kernel opentelemetry-instrumentation-openai
  ```

  ```bash uv theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
  uv add langsmith semantic-kernel 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=<您的_langsmith_api_key>
export LANGSMITH_PROJECT=<您的项目名称>
export OPENAI_API_KEY=<您的_openai_api_key>
```

### 2. 配置 OpenTelemetry 集成

在您的 Semantic Kernel 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 configure
from opentelemetry.instrumentation.openai import OpenAIInstrumentor

# 配置 LangSmith 追踪
configure(project_name="semantic-kernel-demo")

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

<Note>
  您无需设置任何 OpenTelemetry 环境变量或手动配置导出器——`configure()` 会自动处理所有内容。
</Note>

### 3. 创建并运行您的 Semantic Kernel 应用

配置完成后，您的 Semantic Kernel 应用将自动向 LangSmith 发送追踪数据：

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
import asyncio
from semantic_kernel import Kernel
from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion
from semantic_kernel.prompt_template import InputVariable, PromptTemplateConfig
from langsmith.integrations.otel import configure
from opentelemetry.instrumentation.openai import OpenAIInstrumentor

# 配置 LangSmith 追踪
configure(project_name="semantic-kernel-assistant")

# 检测 OpenAI 调用
OpenAIInstrumentor().instrument()

# 配置 Semantic Kernel
kernel = Kernel()
kernel.add_service(OpenAIChatCompletion())

# 创建提示模板
code_analysis_prompt = """
分析以下代码并提供见解：

代码：{{$code}}

请提供：
1. 代码功能的简要总结
2. 任何潜在的改进建议
3. 代码质量评估
"""

prompt_template_config = PromptTemplateConfig(
    template=code_analysis_prompt,
    name="code_analyzer",
    template_format="semantic-kernel",
    input_variables=[
        InputVariable(name="code", description="要分析的代码", is_required=True),
    ],
)

# 将函数添加到内核
code_analyzer = kernel.add_function(
    function_name="analyzeCode",
    plugin_name="codeAnalysisPlugin",
    prompt_template_config=prompt_template_config,
)

async def main():
    sample_code = """
def fibonacci(n):
    if n <= 1:
        return n
    return fibonacci(n-1) + fibonacci(n-2)
    """

    result = await kernel.invoke(code_analyzer, code=sample_code)
    print("代码分析：")
    print(result)

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向追踪中添加自定义元数据：

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

tracer = trace.get_tracer(__name__)

async def analyze_with_metadata(code: str):
    with tracer.start_as_current_span("semantic_kernel_workflow") as span:
        span.set_attribute("langsmith.metadata.workflow_type", "code_analysis")
        span.set_attribute("langsmith.metadata.user_id", "developer_123")
        span.set_attribute("langsmith.span.tags", "semantic-kernel,code-analysis")

        result = await kernel.invoke(code_analyzer, code=code)
        return result
```

### 与其他检测器结合使用

您可以将 Semantic Kernel 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

* [Semantic Kernel 文档](https://learn.microsoft.com/en-us/semantic-kernel/overview/)
* [Semantic Kernel 可观测性指南](https://learn.microsoft.com/en-us/semantic-kernel/concepts/enterprise-readiness/observability/)
* [LangSmith OpenTelemetry 指南](/langsmith/trace-with-opentelemetry)

***

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