langchain/libs/community/langchain_community/document_loaders/doc_intelligence.py

89 lines
3.1 KiB
Python
Raw Normal View History

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,
)
class AzureAIDocumentIntelligenceLoader(BaseLoader):
"""Loads a PDF with Azure Document Intelligence"""
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,
)
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]