def input_keys(self) -> List[str]:
        """Input keys."""
        return self.chain.input_keys
    @property
    def output_keys(self) -> List[str]:
        """Output keys."""
        if self.return_intermediate_steps:
            return ["output", "fallacy_critiques_and_revisions", "initial_output"]
        return ["output"]
    def _call(
        self,
        inputs: Dict[str, Any],
        run_manager: Optional[CallbackManagerForChainRun] = None,
    ) -> Dict[str, Any]:
        _run_manager = run_manager or CallbackManagerForChainRun.get_noop_manager()
        response = self.chain.run(
            **inputs,
            callbacks=_run_manager.get_child("original"),
        )
        initial_response = response
        input_prompt = self.chain.prompt.format(**inputs)
        _run_manager.on_text(
            text="Initial response: " + response + "\n\n",
            verbose=self.verbose,
            color="yellow",
        )
        fallacy_critiques_and_revisions = []
        for logical_fallacy in self.logical_fallacies:
            # Fallacy critique below
            fallacy_raw_critique = self.fallacy_critique_chain.run(
                input_prompt=input_prompt,
                output_from_model=response,
                fallacy_critique_request=logical_fallacy.fallacy_critique_request,
                callbacks=_run_manager.get_child("fallacy_critique"),
            )
            fallacy_critique = self._parse_critique(
                output_string=fallacy_raw_critique,
            ).strip()
            # if fallacy critique contains "No fallacy critique needed" then done
            if "no fallacy critique needed" in fallacy_critique.lower():