LLMCheckerChain Class — langchain Architecture

Architecture documentation for the LLMCheckerChain class in base.py from the langchain codebase.

Class python

Entity Profile

Dependency Diagram

graph TD
  5aa56bcf_82c4_0170_f600_dbc266dbf61b["LLMCheckerChain"]
  f3cef70e_11b0_61c9_7ec0_7308f4b45056["Chain"]
  5aa56bcf_82c4_0170_f600_dbc266dbf61b -->|extends| f3cef70e_11b0_61c9_7ec0_7308f4b45056
  a0a672f2_fe43_2701_45f8_1b60a2179f97["base.py"]
  5aa56bcf_82c4_0170_f600_dbc266dbf61b -->|defined in| a0a672f2_fe43_2701_45f8_1b60a2179f97
  f272a350_2fd9_70c0_9de4_c963a07940fa["_raise_deprecation()"]
  5aa56bcf_82c4_0170_f600_dbc266dbf61b -->|method| f272a350_2fd9_70c0_9de4_c963a07940fa
  cbea931f_01c5_0277_221a_83340cfd87db["input_keys()"]
  5aa56bcf_82c4_0170_f600_dbc266dbf61b -->|method| cbea931f_01c5_0277_221a_83340cfd87db
  4c43974a_92e4_3b83_be05_9f17f4be391d["output_keys()"]
  5aa56bcf_82c4_0170_f600_dbc266dbf61b -->|method| 4c43974a_92e4_3b83_be05_9f17f4be391d
  f81221be_a2ac_a3e7_7819_30fb88a7c9bc["_call()"]
  5aa56bcf_82c4_0170_f600_dbc266dbf61b -->|method| f81221be_a2ac_a3e7_7819_30fb88a7c9bc
  d0efdd08_c13a_b40f_e1fb_986721a195b7["_chain_type()"]
  5aa56bcf_82c4_0170_f600_dbc266dbf61b -->|method| d0efdd08_c13a_b40f_e1fb_986721a195b7
  62540c68_956e_907e_7735_12e71501527a["from_llm()"]
  5aa56bcf_82c4_0170_f600_dbc266dbf61b -->|method| 62540c68_956e_907e_7735_12e71501527a

Relationship Graph

Source Code

libs/langchain/langchain_classic/chains/llm_checker/base.py lines 75–199

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

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

        model = OpenAI(temperature=0.7)
        checker_chain = LLMCheckerChain.from_llm(model)
        ```
    """

    question_to_checked_assertions_chain: SequentialChain

    llm: BaseLanguageModel | None = None
    """[Deprecated] LLM wrapper to use."""
    create_draft_answer_prompt: PromptTemplate = CREATE_DRAFT_ANSWER_PROMPT
    """[Deprecated]"""
    list_assertions_prompt: PromptTemplate = LIST_ASSERTIONS_PROMPT
    """[Deprecated]"""
    check_assertions_prompt: PromptTemplate = CHECK_ASSERTIONS_PROMPT
    """[Deprecated]"""
    revised_answer_prompt: PromptTemplate = REVISED_ANSWER_PROMPT
    """[Deprecated] Prompt to use when questioning the documents."""
    input_key: str = "query"
    output_key: str = "result"

    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 LLMCheckerChain with an llm is deprecated. "
                "Please instantiate with question_to_checked_assertions_chain "
                "or using the from_llm class method.",
                stacklevel=5,
            )
            if (
                "question_to_checked_assertions_chain" not in values
                and values["llm"] is not None
            ):
                question_to_checked_assertions_chain = (
                    _load_question_to_checked_assertions_chain(
                        values["llm"],
                        values.get(
                            "create_draft_answer_prompt",
                            CREATE_DRAFT_ANSWER_PROMPT,
                        ),
                        values.get("list_assertions_prompt", LIST_ASSERTIONS_PROMPT),
                        values.get("check_assertions_prompt", CHECK_ASSERTIONS_PROMPT),
                        values.get("revised_answer_prompt", REVISED_ANSWER_PROMPT),
                    )
                )
                values["question_to_checked_assertions_chain"] = (
                    question_to_checked_assertions_chain
                )
        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()
        question = inputs[self.input_key]