chat_result.py — langchain Source File

Architecture documentation for chat_result.py, a python file in the langchain codebase. 2 imports, 0 dependents.

File python 2 imports 1 classes

Entity Profile

Dependency Diagram

graph LR
  1b9b7eaf_6c6b_3125_32c2_ca3cac5f4f32["chat_result.py"]
  6e58aaea_f08e_c099_3cc7_f9567bfb1ae7["pydantic"]
  1b9b7eaf_6c6b_3125_32c2_ca3cac5f4f32 --> 6e58aaea_f08e_c099_3cc7_f9567bfb1ae7
  3bd68d31_2a9b_9448_d8ba_c386f0e45f29["langchain_core.outputs.chat_generation"]
  1b9b7eaf_6c6b_3125_32c2_ca3cac5f4f32 --> 3bd68d31_2a9b_9448_d8ba_c386f0e45f29
  style 1b9b7eaf_6c6b_3125_32c2_ca3cac5f4f32 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

"""Chat result schema."""

from pydantic import BaseModel

from langchain_core.outputs.chat_generation import ChatGeneration


class ChatResult(BaseModel):
    """Use to represent the result of a chat model call with a single prompt.

    This container is used internally by some implementations of chat model, it will
    eventually be mapped to a more general `LLMResult` object, and  then projected into
    an `AIMessage` object.

    LangChain users working with chat models will usually access information via
    `AIMessage` (returned from runnable interfaces) or `LLMResult` (available via
    callbacks). Please refer the `AIMessage` and `LLMResult` schema documentation for
    more information.
    """

    generations: list[ChatGeneration]
    """List of the chat generations.

    Generations is a list to allow for multiple candidate generations for a single
    input prompt.
    """

    llm_output: dict | None = None
    """For arbitrary LLM provider specific output.

    This dictionary is a free-form dictionary that can contain any information that the
    provider wants to return. It is not standardized and is provider-specific.

    Users should generally avoid relying on this field and instead rely on accessing
    relevant information from standardized fields present in `AIMessage`.
    """