AzureAIDocumentIntelligenceParser#

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

Loads a PDF with Azure Document Intelligence (formerly Forms Recognizer).

Methods

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

lazy_parse(blob)

Lazily parse the blob.

parse(blob)

Eagerly parse the blob into a document or documents.

parse_url(url)

Parameters:
  • api_endpoint (str) –

  • api_key (str) –

  • api_version (str | None) –

  • api_model (str) –

  • mode (str) –

  • analysis_features (List[str] | None) –

__init__(api_endpoint: str, api_key: str, api_version: str | None = None, api_model: str = 'prebuilt-layout', mode: str = 'markdown', analysis_features: List[str] | None = None)[source]#
Parameters:
  • api_endpoint (str) –

  • api_key (str) –

  • api_version (str | None) –

  • api_model (str) –

  • mode (str) –

  • analysis_features (List[str] | None) –

lazy_parse(blob: Blob) → Iterator[Document][source]#

Lazily parse the blob.

Parameters:

blob (Blob) –

Return type:

Iterator[Document]

parse(blob: Blob) → List[Document]#

Eagerly parse the blob into a document or documents.

This is a convenience method for interactive development environment.

Production applications should favor the lazy_parse method instead.

Subclasses should generally not over-ride this parse method.

Parameters:

blob (Blob) – Blob instance

Returns:

List of documents

Return type:

List[Document]

parse_url(url: str) → Iterator[Document][source]#
Parameters:

url (str) –

Return type:

Iterator[Document]