fallacy_critique_request="Tell if this answer meets criteria.",
                        fallacy_revision_request=\
                        "Give an answer that meets better criteria.",
                    )
                ],
            )
            fallacy_chain.run(question="How do I know if the earth is round?")
    """
    chain: LLMChain
    logical_fallacies: List[LogicalFallacy]
    fallacy_critique_chain: LLMChain
    fallacy_revision_chain: LLMChain
    return_intermediate_steps: bool = False
[docs]    @classmethod
    def get_fallacies(cls, names: Optional[List[str]] = None) -> List[LogicalFallacy]:
        if names is None:
            return list(FALLACIES.values())
        else:
            return [FALLACIES[name] for name in names]
[docs]    @classmethod
    def from_llm(
        cls,
        llm: BaseLanguageModel,
        chain: LLMChain,
        fallacy_critique_prompt: BasePromptTemplate = FALLACY_CRITIQUE_PROMPT,
        fallacy_revision_prompt: BasePromptTemplate = FALLACY_REVISION_PROMPT,
        **kwargs: Any,
    ) -> "FallacyChain":
        """Create a chain from an LLM."""
        fallacy_critique_chain = LLMChain(llm=llm, prompt=fallacy_critique_prompt)
        fallacy_revision_chain = LLMChain(llm=llm, prompt=fallacy_revision_prompt)
        return cls(
            chain=chain,
            fallacy_critique_chain=fallacy_critique_chain,
            fallacy_revision_chain=fallacy_revision_chain,
            **kwargs,
        )
    @property
    def input_keys(self) -> List[str]:
        """Input keys."""