qa_with_structure.py — langchain Source File

Source Code

from typing import Any, cast

from langchain_core._api import deprecated
from langchain_core.language_models import BaseLanguageModel
from langchain_core.messages import HumanMessage, SystemMessage
from langchain_core.output_parsers import BaseLLMOutputParser
from langchain_core.output_parsers.openai_functions import (
    OutputFunctionsParser,
    PydanticOutputFunctionsParser,
)
from langchain_core.prompts import PromptTemplate
from langchain_core.prompts.chat import ChatPromptTemplate, HumanMessagePromptTemplate
from langchain_core.utils.pydantic import is_basemodel_subclass
from pydantic import BaseModel, Field

from langchain_classic.chains.llm import LLMChain
from langchain_classic.chains.openai_functions.utils import get_llm_kwargs


class AnswerWithSources(BaseModel):
    """An answer to the question, with sources."""

    answer: str = Field(..., description="Answer to the question that was asked")
    sources: list[str] = Field(
        ...,
        description="List of sources used to answer the question",
    )


@deprecated(
    since="0.2.13",
    removal="1.0",
    message=(
        "This function is deprecated. Refer to this guide on retrieval and question "
        "answering with structured responses: "
        "https://python.langchain.com/docs/how_to/qa_sources/#structure-sources-in-model-response"
    ),
)
def create_qa_with_structure_chain(
    llm: BaseLanguageModel,
    schema: dict | type[BaseModel],
    output_parser: str = "base",
    prompt: PromptTemplate | ChatPromptTemplate | None = None,
    verbose: bool = False,  # noqa: FBT001,FBT002
) -> LLMChain:
    """Create a question answering chain with structure.

    Create a question answering chain that returns an answer with sources
    based on schema.

    Args:
        llm: Language model to use for the chain.
        schema: Pydantic schema to use for the output.
        output_parser: Output parser to use. Should be one of `'pydantic'` or `'base'`.
        prompt: Optional prompt to use for the chain.
        verbose: Whether to run the chain in verbose mode.

    Returns:
        The question answering chain.

// ... (83 more lines)