>>> chat = ChatOpenAI(
        ...     temperature=0,
        ...     headers={"user_id": "123"},
        ...     callbacks=[context_callback],
        ...     openai_api_key="API_KEY_HERE",
        ... )
        >>> messages = [
        ...     SystemMessage(content="You translate English to French."),
        ...     HumanMessage(content="I love programming with LangChain."),
        ... ]
        >>> chat(messages)
    Chain Example:
        >>> from langchain.chains import LLMChain
        >>> from langchain.chat_models import ChatOpenAI
        >>> from langchain.callbacks import ContextCallbackHandler
        >>> context_callback = ContextCallbackHandler(
        ...     token="<CONTEXT_TOKEN_HERE>",
        ... )
        >>> human_message_prompt = HumanMessagePromptTemplate(
        ...     prompt=PromptTemplate(
        ...         template="What is a good name for a company that makes {product}?",
        ...         input_variables=["product"],
        ...    ),
        ... )
        >>> chat_prompt_template = ChatPromptTemplate.from_messages(
        ...   [human_message_prompt]
        ... )
        >>> callback = ContextCallbackHandler(token)
        >>> # Note: the same callback object must be shared between the
        ...   LLM and the chain.
        >>> chat = ChatOpenAI(temperature=0.9, callbacks=[callback])
        >>> chain = LLMChain(
        ...   llm=chat,
        ...   prompt=chat_prompt_template,
        ...   callbacks=[callback]
        ... )
        >>> chain.run("colorful socks")
    """
[docs]    def __init__(self, token: str = "", verbose: bool = False, **kwargs: Any) -> None:
        (
            self.context,
            self.credential,