AzureAIDocumentIntelligenceLoader#

class langchain_community.document_loaders.doc_intelligence.AzureAIDocumentIntelligenceLoader(api_endpoint: str, api_key: str, file_path: str | None = None, url_path: str | None = None, api_version: str | None = None, api_model: str = 'prebuilt-layout', mode: str = 'markdown', *, analysis_features: List[str] | None = None)[source]#

Load a PDF with Azure Document Intelligence.

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_pathOptional[str]

The path to the file that needs to be loaded. Either file_path or url_path must be specified.

url_pathOptional[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 azure-ai-documentintelligence package.

api_model: str

Unique document model name. Default value is “prebuilt-layout”. Note that overriding this default value may result in unsupported behavior.

mode: Optional[str]

The type of content representation of the generated Documents. Use either “single”, “page”, or “markdown”. Default value is “markdown”.

analysis_features: Optional[List[str]]

List of optional analysis features, each feature should be passed as a str that conforms to the enum DocumentAnalysisFeature in azure-ai-documentintelligence package. Default value is None.

Examples:#

>>> obj = AzureAIDocumentIntelligenceLoader(
...     file_path="path/to/file",
...     api_endpoint="https://endpoint.azure.com",
...     api_key="APIKEY",
...     api_version="2023-10-31-preview",
...     api_model="prebuilt-layout",
...     mode="markdown"
... )

Methods

__init__(api_endpoint, api_key[, file_path, ...])

Initialize the object for file processing with Azure Document Intelligence (formerly Form Recognizer).

alazy_load()

A lazy loader for Documents.

aload()

Load data into Document objects.

lazy_load()

Lazy load given path as pages.

load()

Load data into Document objects.

load_and_split([text_splitter])

Load Documents and split into chunks.
__init__(api_endpoint: str, api_key: str, file_path: str | None = None, url_path: str | None = None, api_version: str | None = None, api_model: str = 'prebuilt-layout', mode: str = 'markdown', *, analysis_features: List[str] | None = None) → None[source]#

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_pathOptional[str]

The path to the file that needs to be loaded. Either file_path or url_path must be specified.

url_pathOptional[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 azure-ai-documentintelligence package.

api_model: str

Unique document model name. Default value is “prebuilt-layout”. Note that overriding this default value may result in unsupported behavior.

mode: Optional[str]

The type of content representation of the generated Documents. Use either “single”, “page”, or “markdown”. Default value is “markdown”.

analysis_features: Optional[List[str]]

List of optional analysis features, each feature should be passed as a str that conforms to the enum DocumentAnalysisFeature in azure-ai-documentintelligence package. Default value is None.

Examples:#

>>> obj = AzureAIDocumentIntelligenceLoader(
...     file_path="path/to/file",
...     api_endpoint="https://endpoint.azure.com",
...     api_key="APIKEY",
...     api_version="2023-10-31-preview",
...     api_model="prebuilt-layout",
...     mode="markdown"
... )
Parameters:

  • api_endpoint (str) –

  • api_key (str) –

  • file_path (str | None) –

  • url_path (str | None) –

  • api_version (str | None) –

  • api_model (str) –

  • mode (str) –

  • analysis_features (List[str] | None) –

Return type:

None

async alazy_load() → AsyncIterator[Document]#

A lazy loader for Documents.

Return type:

AsyncIterator[Document]

async aload() → List[Document]#

Load data into Document objects.

Return type:

List[Document]

lazy_load() → Iterator[Document][source]#

Lazy load given path as pages.

Return type:

Iterator[Document]

load() → List[Document]#

Load data into Document objects.

Return type:

List[Document]

load_and_split(text_splitter: TextSplitter | None = None) → List[Document]#

Load Documents and split into chunks. Chunks are returned as Documents.

Do not override this method. It should be considered to be deprecated!

Parameters:

text_splitter (Optional[TextSplitter]) – TextSplitter instance to use for splitting documents. Defaults to RecursiveCharacterTextSplitter.

Returns:

List of Documents.

Return type:

List[Document]

Parameters:

  • api_endpoint (str) –

  • api_key (str) –

  • file_path (str | None) –

  • url_path (str | None) –

  • api_version (str | None) –

  • api_model (str) –

  • mode (str) –

  • analysis_features (List[str] | None) –

Examples using AzureAIDocumentIntelligenceLoader

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