Source code for langchain_community.document_transformers.doctran_text_extract

from typing import Any, List, Optional, Sequence

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


[docs] class DoctranPropertyExtractor(BaseDocumentTransformer): """Extract properties from text documents using doctran. Arguments: properties: A list of the properties to extract. 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 DoctranPropertyExtractor properties = [ { "name": "category", "description": "What type of email this is.", "type": "string", "enum": ["update", "action_item", "customer_feedback", "announcement", "other"], "required": True, }, { "name": "mentions", "description": "A list of all people mentioned in this email.", "type": "array", "items": { "name": "full_name", "description": "The full name of the person mentioned.", "type": "string", }, "required": True, }, { "name": "eli5", "description": "Explain this email to me like I'm 5 years old.", "type": "string", "required": True, }, ] # Pass in openai_api_key or set env var OPENAI_API_KEY property_extractor = DoctranPropertyExtractor(properties) transformed_document = await qa_transformer.atransform_documents(documents) """ # noqa: E501
[docs] def __init__( self, properties: List[dict], openai_api_key: Optional[str] = None, openai_api_model: Optional[str] = None, ) -> None: self.properties = properties 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" )
[docs] async def atransform_documents( self, documents: Sequence[Document], **kwargs: Any ) -> Sequence[Document]: """Extracts properties from text documents using doctran.""" try: from doctran import Doctran, ExtractProperty 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)" ) properties = [ExtractProperty(**property) for property in self.properties] for d in documents: doctran_doc = ( doctran.parse(content=d.page_content) .extract(properties=properties) .execute() ) d.metadata["extracted_properties"] = doctran_doc.extracted_properties return documents
[docs] def transform_documents( self, documents: Sequence[Document], **kwargs: Any ) -> Sequence[Document]: """Extracts properties from text documents using doctran.""" try: from doctran import Doctran, ExtractProperty 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)" ) properties = [ExtractProperty(**property) for property in self.properties] for d in documents: doctran_doc = ( doctran.parse(content=d.page_content) .extract(properties=properties) .execute() ) d.metadata["extracted_properties"] = doctran_doc.extracted_properties return documents