LLMSummarizationCheckerChain Class — langchain Architecture

Source Code

libs/langchain/langchain_classic/chains/llm_summarization_checker/base.py lines 80–213

class LLMSummarizationCheckerChain(Chain):
    """Chain for question-answering with self-verification.

    Example:
        ```python
        from langchain_openai import OpenAI
        from langchain_classic.chains import LLMSummarizationCheckerChain

        model = OpenAI(temperature=0.0)
        checker_chain = LLMSummarizationCheckerChain.from_llm(model)
        ```
    """

    sequential_chain: SequentialChain
    llm: BaseLanguageModel | None = None
    """[Deprecated] LLM wrapper to use."""

    create_assertions_prompt: PromptTemplate = CREATE_ASSERTIONS_PROMPT
    """[Deprecated]"""
    check_assertions_prompt: PromptTemplate = CHECK_ASSERTIONS_PROMPT
    """[Deprecated]"""
    revised_summary_prompt: PromptTemplate = REVISED_SUMMARY_PROMPT
    """[Deprecated]"""
    are_all_true_prompt: PromptTemplate = ARE_ALL_TRUE_PROMPT
    """[Deprecated]"""

    input_key: str = "query"
    output_key: str = "result"
    max_checks: int = 2
    """Maximum number of times to check the assertions. Default to double-checking."""

    model_config = ConfigDict(
        arbitrary_types_allowed=True,
        extra="forbid",
    )

    @model_validator(mode="before")
    @classmethod
    def _raise_deprecation(cls, values: dict) -> Any:
        if "llm" in values:
            warnings.warn(
                "Directly instantiating an LLMSummarizationCheckerChain with an llm is "
                "deprecated. Please instantiate with"
                " sequential_chain argument or using the from_llm class method.",
                stacklevel=5,
            )
            if "sequential_chain" not in values and values["llm"] is not None:
                values["sequential_chain"] = _load_sequential_chain(
                    values["llm"],
                    values.get("create_assertions_prompt", CREATE_ASSERTIONS_PROMPT),
                    values.get("check_assertions_prompt", CHECK_ASSERTIONS_PROMPT),
                    values.get("revised_summary_prompt", REVISED_SUMMARY_PROMPT),
                    values.get("are_all_true_prompt", ARE_ALL_TRUE_PROMPT),
                    verbose=values.get("verbose", False),
                )
        return values

    @property
    def input_keys(self) -> list[str]:
        """Return the singular input key."""
        return [self.input_key]

    @property
    def output_keys(self) -> list[str]:
        """Return the singular output key."""
        return [self.output_key]

    def _call(
        self,
        inputs: dict[str, Any],
        run_manager: CallbackManagerForChainRun | None = None,
    ) -> dict[str, str]:
        _run_manager = run_manager or CallbackManagerForChainRun.get_noop_manager()
        all_true = False
        count = 0
        output = None
        original_input = inputs[self.input_key]
        chain_input = original_input
        while not all_true and count < self.max_checks:
            output = self.sequential_chain(
                {"summary": chain_input},