Toggle Menu
Prev Up Next

# Source code for langchain_community.document_transformers.doctran_text_qa

    from typing import Any, Optional, Sequence

    from langchain_core.documents import BaseDocumentTransformer, Document
    from langchain_core.utils import get_from_env

    class DoctranQATransformer(BaseDocumentTransformer):
        """Extract QA from text documents using doctran.

        Arguments:
            openai_api_key: OpenAI API key. Can also be specified via environment variable
                ``OPENAI_API_KEY``.

        Example:
            .. code-block:: python

                from langchain_community.document_transformers import DoctranQATransformer

                # Pass in openai_api_key or set env var OPENAI_API_KEY
                qa_transformer = DoctranQATransformer()
                transformed_document = await qa_transformer.atransform_documents(documents)
        """

        def __init__(
            self,
            openai_api_key: Optional[str] = None,
            openai_api_model: Optional[str] = None,
        ) -> None:
            self.openai_api_key = openai_api_key or get_from_env(
                "openai_api_key", "OPENAI_API_KEY"
            )
            self.openai_api_model = openai_api_model or get_from_env(
                "openai_api_model", "OPENAI_API_MODEL"
            )

        async def atransform_documents(
            self, documents: Sequence[Document], **kwargs: Any
        ) -> Sequence[Document]:
            raise NotImplementedError

        def transform_documents(
            self, documents: Sequence[Document], **kwargs: Any
        ) -> Sequence[Document]:
            """Extracts QA from text documents using doctran."""
            try:
                from doctran import Doctran

                doctran = Doctran(
                    openai_api_key=self.openai_api_key, openai_model=self.openai_api_model
                )
            except ImportError:
                raise ImportError(
                    "Install doctran to use this parser. (pip install doctran)"
                )
            for d in documents:
                doctran_doc = doctran.parse(content=d.page_content).interrogate().execute()
                questions_and_answers = doctran_doc.extracted_properties.get(
                    "questions_and_answers"
                )
                d.metadata["questions_and_answers"] = questions_and_answers
            return documents