> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pezzo.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# LangChain Integration

Pezzo supports integration with LangChain for observability and monitoring. Integration is as easy as configuring the LLM to proxy requests to Pezzo.

<Note>
  If you want to learn more about the Pezzo Proxy, [click here](/platform/proxy/overview).
</Note>

## Example: LangChain with OpenAI

Below is an example using `ChatOpenAI`. The same can be applied to chains and agents.

<Tabs>
  <Tab title="LangChain + Node.js">
    ```ts theme={null}
    import { ChatOpenAI } from "langchain/chat_models/openai";

    const llm = new ChatOpenAI({
      openAIApiKey: process.env.OPENAI_API_KEY,
      temperature: 0,
      configuration: {
        baseURL: "https://proxy.pezzo.ai/openai/v1",
        defaultHeaders: {
          "X-Pezzo-Api-Key": "<Your API Key>",
          "X-Pezzo-Project-Id": "<Your Project ID>",
          "X-Pezzo-Environment": "Production",
        },
      },
    });

    const llmResult = await llm.predict("Tell me 5 fun facts about yourself!");
    ```
  </Tab>

  <Tab title="LangChain + Python">
    ```py theme={null}
    from langchain.chat_models import ChatOpenAI

    llm = ChatOpenAI(
        openai_api_key='<>',
        openai_api_base="https://proxy.pezzo.ai/openai/v1",
        default_headers={
          "X-Pezzo-Api-Key": "<Your API Key>",
          "X-Pezzo-Project-Id": "<Your Project ID>",
          "X-Pezzo-Environment": "Production",
        }
    )

    llm_result = llm.predict("Tell me 5 fun facts about yourself!")
    ```
  </Tab>
</Tabs>