Source code for langchain_community.document_loaders.doc_intelligence

from typing import Iterator, Optional

from langchain_core.documents import Document

from langchain_community.document_loaders.base import BaseLoader
from langchain_community.document_loaders.blob_loaders import Blob
from langchain_community.document_loaders.parsers import (
    AzureAIDocumentIntelligenceParser,
)


[docs]class AzureAIDocumentIntelligenceLoader(BaseLoader): """Loads a PDF with Azure Document Intelligence"""
[docs] def __init__( self, api_endpoint: str, api_key: str, file_path: Optional[str] = None, url_path: Optional[str] = None, api_version: Optional[str] = None, api_model: str = "prebuilt-layout", mode: str = "markdown", ) -> None: """ Initialize the object for file processing with Azure Document Intelligence (formerly Form Recognizer). This constructor initializes a AzureAIDocumentIntelligenceParser object to be used for parsing files using the Azure Document Intelligence API. The load method generates Documents whose content representations are determined by the mode parameter. Parameters: ----------- api_endpoint: str The API endpoint to use for DocumentIntelligenceClient construction. api_key: str The API key to use for DocumentIntelligenceClient construction. file_path : Optional[str] The path to the file that needs to be loaded. Either file_path or url_path must be specified. url_path : Optional[str] The URL to the file that needs to be loaded. Either file_path or url_path must be specified. api_version: Optional[str] The API version for DocumentIntelligenceClient. Setting None to use the default value from SDK. api_model: str The model name or ID to be used for form recognition in Azure. mode: Optional[str] The type of content representation of the generated Documents. Examples: --------- >>> obj = AzureAIDocumentIntelligenceLoader( ... file_path="path/to/file", ... api_endpoint="https://endpoint.azure.com", ... api_key="APIKEY", ... api_version="2023-10-31-preview", ... model="prebuilt-document", ... mode="markdown" ... ) """ assert ( file_path is not None or url_path is not None ), "file_path or url_path must be provided" self.file_path = file_path self.url_path = url_path self.parser = AzureAIDocumentIntelligenceParser( api_endpoint=api_endpoint, api_key=api_key, api_version=api_version, api_model=api_model, mode=mode, )
[docs] def lazy_load( self, ) -> Iterator[Document]: """Lazy load given path as pages.""" if self.file_path is not None: blob = Blob.from_path(self.file_path) yield from self.parser.parse(blob) else: yield from self.parser.parse_url(self.url_path) # type: ignore[arg-type]