async def achat(
        self,
        messages: Sequence[ChatMessage],
        stop: Optional[List[str]] = None,
        **kwargs: Any,
    ) -> ChatResponse:
        """
        Calls the async chat implementation of the SambaNovaCloud model.

        Args:
            messages: the prompt composed of a list of messages.
            stop: a list of strings on which the model should stop generating.
                  If generation stops due to a stop token, the stop token itself
                  SHOULD BE INCLUDED as part of the output. This is not enforced
                  across models right now, but it's a good practice to follow since
                  it makes it much easier to parse the output of the model
                  downstream and understand why generation stopped.

        Returns:
            ChatResponse with async model generation

        """
        messages_dicts = _create_message_dicts(messages)
        response = await self._handle_request_async(messages_dicts, stop)
        message = ChatMessage(
            role=MessageRole.ASSISTANT,
            content=response["choices"][0]["message"]["content"],
            additional_kwargs={
                "id": response["id"],
                "finish_reason": response["choices"][0]["finish_reason"],
                "usage": response.get("usage"),
                "model_name": response["model"],
                "system_fingerprint": response["system_fingerprint"],
                "created": response["created"],
            },
        )
        return ChatResponse(message=message)

        Calls the async chat implementation of the SambaNovaCloud model.

        Args:
            messages: the prompt composed of a list of messages.
            stop: a list of strings on which the model should stop generating.
                  If generation stops due to a stop token, the stop token itself
                  SHOULD BE INCLUDED as part of the output. This is not enforced
                  across models right now, but it's a good practice to follow since
                  it makes it much easier to parse the output of the model
                  downstream and understand why generation stopped.

        Returns:
            ChatResponse with async model generation

        
llama-index-integrations/llms/llama-index-llms-sambanovasystems/llama_index/llms/sambanovasystems/base.py