async def _avectara_query(
        self,
        query_bundle: QueryBundle,
        chat: bool = False,
        conv_id: Optional[str] = None,
        verbose: bool = False,
        **kwargs: Any,
    ) -> Tuple[List[NodeWithScore], Dict]:
        """
        Asynchronously query Vectara index to get for top k most similar nodes.

        Args:
            query: Query Bundle
            chat: whether to use chat API in Vectara
            conv_id: conversation ID, if adding to existing chat
            verbose: whether to print verbose output (e.g. for debugging)
            Additional keyword arguments

        Returns:
            List[NodeWithScore]: list of nodes with scores
            Dict: summary

        """
        return await self._vectara_query(query_bundle, chat, conv_id, verbose, **kwargs)

        Asynchronously query Vectara index to get for top k most similar nodes.

        Args:
            query: Query Bundle
            chat: whether to use chat API in Vectara
            conv_id: conversation ID, if adding to existing chat
            verbose: whether to print verbose output (e.g. for debugging)
            Additional keyword arguments

        Returns:
            List[NodeWithScore]: list of nodes with scores
            Dict: summary

        
llama-index-integrations/indices/llama-index-indices-managed-vectara/llama_index/indices/managed/vectara/retriever.py