Class ChatCohere

libs/community/langchain_community/chat_models/cohere.py:101–251

`Cohere` chat large language models. To use, you should have the ``cohere`` python package installed, and the environment variable ``COHERE_API_KEY`` set with your API key, or pass it as a named parameter to the constructor. Example: .. code-block:: python from

    since="0.0.30", removal="0.3.0", alternative_import="langchain_cohere.ChatCohere"
)
class ChatCohere(BaseChatModel, BaseCohere):
    """`Cohere` chat large language models.

    To use, you should have the ``cohere`` python package installed, and the
    environment variable ``COHERE_API_KEY`` set with your API key, or pass
    it as a named parameter to the constructor.

    Example:
        .. code-block:: python

            from langchain_community.chat_models import ChatCohere
            from langchain_core.messages import HumanMessage

            chat = ChatCohere(model="command", max_tokens=256, temperature=0.75)

            messages = [HumanMessage(content="knock knock")]
            chat.invoke(messages)
    """

    class Config:
        """Configuration for this pydantic object."""

        allow_population_by_field_name = True
        arbitrary_types_allowed = True

    @property
    def _llm_type(self) -> str:
        """Return type of chat model."""
        return "cohere-chat"

    @property
    def _default_params(self) -> Dict[str, Any]:
        """Get the default parameters for calling Cohere API."""
        return {
            "temperature": self.temperature,
        }

    @property
    def _identifying_params(self) -> Dict[str, Any]:
        """Get the identifying parameters."""
        return {**{"model": self.model}, **self._default_params}

    def _stream(
        self,
        messages: List[BaseMessage],
        stop: Optional[List[str]] = None,
        run_manager: Optional[CallbackManagerForLLMRun] = None,
        **kwargs: Any,
    ) -> Iterator[ChatGenerationChunk]:
        request = get_cohere_chat_request(messages, **self._default_params, **kwargs)

        if hasattr(self.client, "chat_stream"):  # detect and support sdk v5
            stream = self.client.chat_stream(**request)
        else:
            stream = self.client.chat(**request, stream=True)

        for data in stream:
            if data.event_type == "text-generation":