Args:
            inputs (Dict[str, Any]): The input values.
            run_manager (AsyncCallbackManagerForChainRun , optional):
                The callback manager.
        Returns:
            Dict[str, Any]: The evaluation results containing the score.
        """
        return {
            "score": self.compute_metric(inputs["prediction"], inputs["prediction_b"])
        }
    def _evaluate_string_pairs(
        self,
        *,
        prediction: str,
        prediction_b: str,
        callbacks: Callbacks = None,
        tags: Optional[List[str]] = None,
        metadata: Optional[Dict[str, Any]] = None,
        include_run_info: bool = False,
        **kwargs: Any,
    ) -> dict:
        """
        Evaluate the string distance between two predictions.
        Args:
            prediction (str): The first prediction string.
            prediction_b (str): The second prediction string.
            callbacks (Callbacks, optional): The callbacks to use.
            tags (List[str], optional): Tags to apply to traces.
            metadata (Dict[str, Any], optional): Metadata to apply to traces.
            **kwargs: Additional keyword arguments.
        Returns:
            dict: The evaluation results containing the score.
        """
        result = self(
            inputs={"prediction": prediction, "prediction_b": prediction_b},
            callbacks=callbacks,
            tags=tags,
            metadata=metadata,
            include_run_info=include_run_info,
        )
        return self._prepare_output(result)
    async def _aevaluate_string_pairs(
        self,
        *,
        prediction: str,
        prediction_b: str,
        callbacks: Callbacks = None,
        tags: Optional[List[str]] = None,