Class DocumentProcessorServiceClient (1.5.1)

Service to call Cloud DocumentAI to process documents according to the processor's definition. Processors are built using state-of-the-art Google AI such as natural language, computer vision, and translation to extract structured information from unstructured or semi-structured documents.

Returns the transport used by the client instance.

Instantiates the document processor service client.

Releases underlying transport's resources.

LRO endpoint to batch process many documents. The output is written to Cloud Storage as JSON in the [Document] format.

from google.cloud import documentai_v1

def sample_batch_process_documents():
    # Create a client
    client = documentai_v1.DocumentProcessorServiceClient()

    # Initialize request argument(s)
    request = documentai_v1.BatchProcessRequest(
        name="name_value",
    )

    # Make the request
    operation = client.batch_process_documents(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

Returns a fully-qualified billing_account string.

Returns a fully-qualified folder string.

Returns a fully-qualified location string.

Returns a fully-qualified organization string.

Returns a fully-qualified project string.

Creates an instance of this client using the provided credentials file.

Creates an instance of this client using the provided credentials info.

Creates an instance of this client using the provided credentials file.

Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not "true", the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "always", use the default mTLS endpoint; if the environment variabel is "never", use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Returns a fully-qualified human_review_config string.

Parse a billing_account path into its component segments.

Parse a folder path into its component segments.

Parse a location path into its component segments.

Parse a organization path into its component segments.

Parse a project path into its component segments.

Parses a human_review_config path into its component segments.

Parses a processor path into its component segments.

Processes a single document.

from google.cloud import documentai_v1

def sample_process_document():
    # Create a client
    client = documentai_v1.DocumentProcessorServiceClient()

    # Initialize request argument(s)
    inline_document = documentai_v1.Document()
    inline_document.uri = "uri_value"

    request = documentai_v1.ProcessRequest(
        inline_document=inline_document,
        name="name_value",
    )

    # Make the request
    response = client.process_document(request=request)

    # Handle the response
    print(response)

Returns a fully-qualified processor string.

Send a document for Human Review. The input document should be processed by the specified processor.

from google.cloud import documentai_v1

def sample_review_document():
    # Create a client
    client = documentai_v1.DocumentProcessorServiceClient()

    # Initialize request argument(s)
    inline_document = documentai_v1.Document()
    inline_document.uri = "uri_value"

    request = documentai_v1.ReviewDocumentRequest(
        inline_document=inline_document,
        human_review_config="human_review_config_value",
    )

    # Make the request
    operation = client.review_document(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)