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)

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)

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]

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]

Parameters:

url (str)

Return type:

Iterator[Document]