callback_manager = CallbackManager.configure(
                config.get("callbacks"),
                self.callbacks,
                self.verbose,
                config.get("tags"),
                self.tags,
                config.get("metadata"),
                self.metadata,
            )
            (run_manager,) = callback_manager.on_chat_model_start(
                dumpd(self),
                [messages],
                invocation_params=params,
                options=options,
                name=config.get("run_name"),
            )
            try:
                generation: Optional[ChatGenerationChunk] = None
                for chunk in self._stream(
                    messages, stop=stop, run_manager=run_manager, **kwargs
                ):
                    yield chunk.message
                    if generation is None:
                        generation = chunk
                    else:
                        generation += chunk
                assert generation is not None
            except BaseException as e:
                run_manager.on_llm_error(e)
                raise e
            else:
                run_manager.on_llm_end(
                    LLMResult(generations=[[generation]]),
                )
[docs]    async def astream(
        self,
        input: LanguageModelInput,
        config: Optional[RunnableConfig] = None,
        *,
        stop: Optional[List[str]] = None,
        **kwargs: Any,
    ) -> AsyncIterator[BaseMessageChunk]:
        if type(self)._astream == BaseChatModel._astream:
            # model doesn't implement streaming, so use default implementation
            yield self.invoke(input, config=config, stop=stop, **kwargs)
        else:
            config = config or {}
            messages = self._convert_input(input).to_messages()
            params = self._get_invocation_params(stop=stop, **kwargs)
            options = {"stop": stop, **kwargs}