mirror of
https://github.com/hwchase17/langchain
synced 2024-11-11 19:11:02 +00:00
89 lines
3.1 KiB
Python
89 lines
3.1 KiB
Python
from typing import Iterator, Optional
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from langchain_core.documents import Document
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from langchain_community.document_loaders.base import BaseLoader
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from langchain_community.document_loaders.blob_loaders import Blob
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from langchain_community.document_loaders.parsers import (
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AzureAIDocumentIntelligenceParser,
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)
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class AzureAIDocumentIntelligenceLoader(BaseLoader):
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"""Loads a PDF with Azure Document Intelligence"""
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def __init__(
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self,
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api_endpoint: str,
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api_key: str,
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file_path: Optional[str] = None,
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url_path: Optional[str] = None,
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api_version: Optional[str] = None,
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api_model: str = "prebuilt-layout",
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mode: str = "markdown",
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) -> None:
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"""
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Initialize the object for file processing with Azure Document Intelligence
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(formerly Form Recognizer).
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This constructor initializes a AzureAIDocumentIntelligenceParser object to be
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used for parsing files using the Azure Document Intelligence API. The load
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method generates Documents whose content representations are determined by the
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mode parameter.
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Parameters:
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-----------
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api_endpoint: str
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The API endpoint to use for DocumentIntelligenceClient construction.
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api_key: str
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The API key to use for DocumentIntelligenceClient construction.
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file_path : Optional[str]
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The path to the file that needs to be loaded.
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Either file_path or url_path must be specified.
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url_path : Optional[str]
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The URL to the file that needs to be loaded.
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Either file_path or url_path must be specified.
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api_version: Optional[str]
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The API version for DocumentIntelligenceClient. Setting None to use
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the default value from SDK.
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api_model: str
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The model name or ID to be used for form recognition in Azure.
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mode: Optional[str]
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The type of content representation of the generated Documents.
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Examples:
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---------
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>>> obj = AzureAIDocumentIntelligenceLoader(
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... file_path="path/to/file",
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... api_endpoint="https://endpoint.azure.com",
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... api_key="APIKEY",
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... api_version="2023-10-31-preview",
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... model="prebuilt-document",
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... mode="markdown"
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... )
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"""
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assert (
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file_path is not None or url_path is not None
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), "file_path or url_path must be provided"
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self.file_path = file_path
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self.url_path = url_path
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self.parser = AzureAIDocumentIntelligenceParser(
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api_endpoint=api_endpoint,
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api_key=api_key,
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api_version=api_version,
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api_model=api_model,
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mode=mode,
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)
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def lazy_load(
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self,
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) -> Iterator[Document]:
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"""Lazy load given path as pages."""
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if self.file_path is not None:
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blob = Blob.from_path(self.file_path)
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yield from self.parser.parse(blob)
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else:
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yield from self.parser.parse_url(self.url_path) # type: ignore[arg-type]
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