generate() — langchain Function Reference

Architecture documentation for the generate() function in llms.py from the langchain codebase.

Function python LangChainCore LanguageModelBase calls 6 called by 1

Entity Profile

LangChainCore→ LanguageModelBase→ generate() — langchain Function Reference

Dependency Diagram

graph TD
  3ab24a73_7222_b6b9_1708_d227f0b8a684["generate()"]
  ce4aa464_3868_179e_5d99_df48bc307c5f["BaseLLM"]
  3ab24a73_7222_b6b9_1708_d227f0b8a684 -->|defined in| ce4aa464_3868_179e_5d99_df48bc307c5f
  bb2bf093_28c4_0d6f_65af_734ed19d76d4["generate_prompt()"]
  bb2bf093_28c4_0d6f_65af_734ed19d76d4 -->|calls| 3ab24a73_7222_b6b9_1708_d227f0b8a684
  4573eeb7_3c0a_7ca6_23d7_ed5efc46fdb1["_get_ls_params()"]
  3ab24a73_7222_b6b9_1708_d227f0b8a684 -->|calls| 4573eeb7_3c0a_7ca6_23d7_ed5efc46fdb1
  028461e5_de04_9807_5074_7a6e87bec6f3["_get_run_ids_list()"]
  3ab24a73_7222_b6b9_1708_d227f0b8a684 -->|calls| 028461e5_de04_9807_5074_7a6e87bec6f3
  b4a028e5_e42e_3478_739f_03ee8ab9100d["dict()"]
  3ab24a73_7222_b6b9_1708_d227f0b8a684 -->|calls| b4a028e5_e42e_3478_739f_03ee8ab9100d
  8ed672d1_e64a_9b66_6a84_5934f70d0441["_generate_helper()"]
  3ab24a73_7222_b6b9_1708_d227f0b8a684 -->|calls| 8ed672d1_e64a_9b66_6a84_5934f70d0441
  9ba11b11_f2bb_a080_89d9_77a37ac38030["get_prompts()"]
  3ab24a73_7222_b6b9_1708_d227f0b8a684 -->|calls| 9ba11b11_f2bb_a080_89d9_77a37ac38030
  37c0466f_ed37_9b74_0dad_7d106ca16ce8["update_cache()"]
  3ab24a73_7222_b6b9_1708_d227f0b8a684 -->|calls| 37c0466f_ed37_9b74_0dad_7d106ca16ce8
  style 3ab24a73_7222_b6b9_1708_d227f0b8a684 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/core/langchain_core/language_models/llms.py lines 840–1054

    def generate(
        self,
        prompts: list[str],
        stop: list[str] | None = None,
        callbacks: Callbacks | list[Callbacks] | None = None,
        *,
        tags: list[str] | list[list[str]] | None = None,
        metadata: dict[str, Any] | list[dict[str, Any]] | None = None,
        run_name: str | list[str] | None = None,
        run_id: uuid.UUID | list[uuid.UUID | None] | None = None,
        **kwargs: Any,
    ) -> LLMResult:
        """Pass a sequence of prompts to a model and return generations.

        This method should make use of batched calls for models that expose a batched
        API.

        Use this method when you want to:

        1. Take advantage of batched calls,
        2. Need more output from the model than just the top generated value,
        3. Are building chains that are agnostic to the underlying language model
            type (e.g., pure text completion models vs chat models).

        Args:
            prompts: List of string prompts.
            stop: Stop words to use when generating.

                Model output is cut off at the first occurrence of any of these
                substrings.
            callbacks: `Callbacks` to pass through.

                Used for executing additional functionality, such as logging or
                streaming, throughout generation.
            tags: List of tags to associate with each prompt. If provided, the length
                of the list must match the length of the prompts list.
            metadata: List of metadata dictionaries to associate with each prompt. If
                provided, the length of the list must match the length of the prompts
                list.
            run_name: List of run names to associate with each prompt. If provided, the
                length of the list must match the length of the prompts list.
            run_id: List of run IDs to associate with each prompt. If provided, the
                length of the list must match the length of the prompts list.
            **kwargs: Arbitrary additional keyword arguments.

                These are usually passed to the model provider API call.

        Raises:
            ValueError: If prompts is not a list.
            ValueError: If the length of `callbacks`, `tags`, `metadata`, or
                `run_name` (if provided) does not match the length of prompts.

        Returns:
            An `LLMResult`, which contains a list of candidate `Generations` for each
                input prompt and additional model provider-specific output.
        """
        if not isinstance(prompts, list):
            msg = (
                "Argument 'prompts' is expected to be of type list[str], received"
                f" argument of type {type(prompts)}."
            )
            raise ValueError(msg)  # noqa: TRY004
        # Create callback managers
        if isinstance(metadata, list):
            metadata = [
                {
                    **(meta or {}),
                    **self._get_ls_params(stop=stop, **kwargs),
                }
                for meta in metadata
            ]
        elif isinstance(metadata, dict):
            metadata = {
                **(metadata or {}),
                **self._get_ls_params(stop=stop, **kwargs),
            }
        if (
            isinstance(callbacks, list)
            and callbacks
            and (
                isinstance(callbacks[0], (list, BaseCallbackManager))