critique_chain: LLMChain
    revision_chain: LLMChain
    return_intermediate_steps: bool = False
[docs]    @classmethod
    def get_principles(
        cls, names: Optional[List[str]] = None
    ) -> List[ConstitutionalPrinciple]:
        if names is None:
            return list(PRINCIPLES.values())
        else:
            return [PRINCIPLES[name] for name in names]
[docs]    @classmethod
    def from_llm(
        cls,
        llm: BaseLanguageModel,
        chain: LLMChain,
        critique_prompt: BasePromptTemplate = CRITIQUE_PROMPT,
        revision_prompt: BasePromptTemplate = REVISION_PROMPT,
        **kwargs: Any,
    ) -> "ConstitutionalChain":
        """Create a chain from an LLM."""
        critique_chain = LLMChain(llm=llm, prompt=critique_prompt)
        revision_chain = LLMChain(llm=llm, prompt=revision_prompt)
        return cls(
            chain=chain,
            critique_chain=critique_chain,
            revision_chain=revision_chain,
            **kwargs,
        )
    @property
    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", "critiques_and_revisions", "initial_output"]
        return ["output"]
    def _call(
        self,
        inputs: Dict[str, Any],
        run_manager: Optional[CallbackManagerForChainRun] = None,
    ) -> Dict[str, Any]: