List of relevant documents
        """
        from langchain.callbacks.manager import CallbackManager
        callback_manager = CallbackManager.configure(
            callbacks,
            None,
            verbose=kwargs.get("verbose", False),
            inheritable_tags=tags,
            local_tags=self.tags,
            inheritable_metadata=metadata,
            local_metadata=self.metadata,
        )
        run_manager = callback_manager.on_retriever_start(
            dumpd(self),
            query,
            **kwargs,
        )
        try:
            _kwargs = kwargs if self._expects_other_args else {}
            if self._new_arg_supported:
                result = self._get_relevant_documents(
                    query, run_manager=run_manager, **_kwargs
                )
            else:
                result = self._get_relevant_documents(query, **_kwargs)
        except Exception as e:
            run_manager.on_retriever_error(e)
            raise e
        else:
            run_manager.on_retriever_end(
                result,
                **kwargs,
            )
            return result
[docs]    async def aget_relevant_documents(
        self,
        query: str,
        *,
        callbacks: Callbacks = None,
        tags: Optional[List[str]] = None,
        metadata: Optional[Dict[str, Any]] = None,
        **kwargs: Any,
    ) -> List[Document]:
        """Asynchronously get documents relevant to a query.
        Args:
            query: string to find relevant documents for
            callbacks: Callback manager or list of callbacks
            tags: Optional list of tags associated with the retriever. Defaults to None
                These tags will be associated with each call to this retriever,
                and passed as arguments to the handlers defined in `callbacks`.