ChatXAI Class — langchain Architecture

Source Code

libs/partners/xai/langchain_xai/chat_models.py lines 43–734

class ChatXAI(BaseChatOpenAI):  # type: ignore[override]
    r"""ChatXAI chat model.

    Refer to [xAI's documentation](https://docs.x.ai/docs/api-reference#chat-completions)
    for more nuanced details on the API's behavior and supported parameters.

    Setup:
        Install `langchain-xai` and set environment variable `XAI_API_KEY`.

        ```bash
        pip install -U langchain-xai
        export XAI_API_KEY="your-api-key"
        ```

    Key init args — completion params:
        model:
            Name of model to use.
        temperature:
            Sampling temperature between `0` and `2`. Higher values mean more random completions,
            while lower values (like `0.2`) mean more focused and deterministic completions.
            (Default: `1`.)
        max_tokens:
            Max number of tokens to generate. Refer to your [model's documentation](https://docs.x.ai/docs/models#model-pricing)
            for the maximum number of tokens it can generate.
        logprobs:
            Whether to return logprobs.

    Key init args — client params:
        timeout:
            Timeout for requests.
        max_retries:
            Max number of retries.
        api_key:
            xAI API key. If not passed in will be read from env var `XAI_API_KEY`.

    Instantiate:
        ```python
        from langchain_xai import ChatXAI

        model = ChatXAI(
            model="grok-4",
            temperature=0,
            max_tokens=None,
            timeout=None,
            max_retries=2,
            # api_key="...",
            # other params...
        )
        ```

    Invoke:
        ```python
        messages = [
            (
                "system",
                "You are a helpful translator. Translate the user sentence to French.",
            ),
            ("human", "I love programming."),
        ]
        model.invoke(messages)
        ```

        ```python
        AIMessage(
            content="J'adore la programmation.",
            response_metadata={
                "token_usage": {
                    "completion_tokens": 9,
                    "prompt_tokens": 32,
                    "total_tokens": 41,
                },
                "model_name": "grok-4",
                "system_fingerprint": None,
                "finish_reason": "stop",
                "logprobs": None,
            },
            id="run-168dceca-3b8b-4283-94e3-4c739dbc1525-0",
            usage_metadata={
                "input_tokens": 32,
                "output_tokens": 9,
                "total_tokens": 41,