async def aevaluate_response_strs(
        self,
        queries: Optional[List[str]] = None,
        response_strs: Optional[List[str]] = None,
        contexts_list: Optional[List[List[str]]] = None,
        **eval_kwargs_lists: Dict[str, Any],
    ) -> Dict[str, List[EvaluationResult]]:
        """
        Evaluate query, response pairs.

        This evaluates queries, responses, contexts as string inputs.
        Can supply additional kwargs to the evaluator in eval_kwargs_lists.

        Args:
            queries (Optional[List[str]]): List of query strings. Defaults to None.
            response_strs (Optional[List[str]]): List of response strings.
                Defaults to None.
            contexts_list (Optional[List[List[str]]]): List of context lists.
                Defaults to None.
            **eval_kwargs_lists (Dict[str, Any]): Dict of either dicts or lists
                of kwargs to pass to evaluator. Defaults to None.
                    multiple evaluators: {evaluator: {kwarg: [list of values]},...}
                    single evaluator:    {kwarg: [list of values]}

        """
        queries, response_strs, contexts_list = self._validate_and_clean_inputs(
            queries, response_strs, contexts_list
        )
        eval_kwargs_lists = self._validate_nested_eval_kwargs_types(eval_kwargs_lists)

        # boolean to check if using multi kwarg evaluator
        multi_kwargs = len(eval_kwargs_lists) > 0 and isinstance(
            next(iter(eval_kwargs_lists.values())), dict
        )

        # run evaluations
        eval_jobs = []
        for idx, query in enumerate(cast(List[str], queries)):
            response_str = cast(List, response_strs)[idx]
            contexts = cast(List, contexts_list)[idx]
            for name, evaluator in self.evaluators.items():
                if multi_kwargs:
                    # multi-evaluator - get appropriate runtime kwargs if present
                    kwargs = (
                        eval_kwargs_lists[name] if name in eval_kwargs_lists else {}
                    )
                else:
                    # single evaluator (maintain backwards compatibility)
                    kwargs = eval_kwargs_lists
                eval_kwargs = self._get_eval_kwargs(kwargs, idx)
                eval_jobs.append(
                    eval_worker(
                        self.semaphore,
                        evaluator,
                        name,
                        query=query,
                        response_str=response_str,
                        contexts=contexts,
                        eval_kwargs=eval_kwargs,
                    )
                )
        results = await self.asyncio_mod.gather(*eval_jobs)

        # Format results
        return self._format_results(results)

        Evaluate query, response pairs.

        This evaluates queries, responses, contexts as string inputs.
        Can supply additional kwargs to the evaluator in eval_kwargs_lists.

        Args:
            queries (Optional[List[str]]): List of query strings. Defaults to None.
            response_strs (Optional[List[str]]): List of response strings.
                Defaults to None.
            contexts_list (Optional[List[List[str]]]): List of context lists.
                Defaults to None.
            **eval_kwargs_lists (Dict[str, Any]): Dict of either dicts or lists
                of kwargs to pass to evaluator. Defaults to None.
                    multiple evaluators: {evaluator: {kwarg: [list of values]},...}
                    single evaluator:    {kwarg: [list of values]}

        
llama-index-core/llama_index/core/evaluation/batch_runner.py