}
        if self.return_intermediate_steps:
            schema["intermediate_steps"] = (List[str], None)
        if self.metadata_keys:
            schema.update({key: (Any, None) for key in self.metadata_keys})
        return create_model("MapRerankOutput", **schema)
    @property
    def output_keys(self) -> List[str]:
        """Expect input key.
        :meta private:
        """
        _output_keys = super().output_keys
        if self.return_intermediate_steps:
            _output_keys = _output_keys + ["intermediate_steps"]
        if self.metadata_keys is not None:
            _output_keys += self.metadata_keys
        return _output_keys
    @root_validator()
    def validate_llm_output(cls, values: Dict) -> Dict:
        """Validate that the combine chain outputs a dictionary."""
        output_parser = values["llm_chain"].prompt.output_parser
        if not isinstance(output_parser, RegexParser):
            raise ValueError(
                "Output parser of llm_chain should be a RegexParser,"
                f" got {output_parser}"
            )
        output_keys = output_parser.output_keys
        if values["rank_key"] not in output_keys:
            raise ValueError(
                f"Got {values['rank_key']} as key to rank on, but did not find "
                f"it in the llm_chain output keys ({output_keys})"
            )
        if values["answer_key"] not in output_keys:
            raise ValueError(
                f"Got {values['answer_key']} as key to return, but did not find "
                f"it in the llm_chain output keys ({output_keys})"
            )
        return values
    @root_validator(pre=True)