Boîte à outils - Démarrage rapide

Chargez un document traité (ou des fragments de document) à partir de Cloud Storage pour le post-traitement.

En savoir plus

Pour obtenir une documentation détaillée incluant cet exemple de code, consultez les articles suivants :

Exemple de code

Python

Pour en savoir plus, consultez la documentation de référence de l'API Document AI Python.

Pour vous authentifier auprès de Document AI, configurez les Identifiants par défaut de l'application. Pour en savoir plus, consultez Configurer l'authentification pour un environnement de développement local. 

from typing import Optional

from google.cloud import documentai
from google.cloud.documentai_toolbox import document, gcs_utilities

# TODO(developer): Uncomment these variables before running the sample.
# Given a Document JSON or sharded Document JSON in path gs://bucket/path/to/folder
# gcs_bucket_name = "bucket"
# gcs_prefix = "path/to/folder"

# Or, given a Document JSON in path gs://bucket/path/to/folder/document.json
# gcs_uri = "gs://bucket/path/to/folder/document.json"

# Or, given a Document JSON in path local/path/to/folder/document.json
# document_path = "local/path/to/folder/document.json"

# Or, given a Document object from Document AI
# documentai_document = documentai.Document()

# Or, given a BatchProcessMetadata object from Document AI
# operation = client.batch_process_documents(request)
# operation.result(timeout=timeout)
# batch_process_metadata = documentai.BatchProcessMetadata(operation.metadata)

# Or, given a BatchProcessOperation name from Document AI
# batch_process_operation = "projects/project_id/locations/location/operations/operation_id"


def quickstart_sample(
    gcs_bucket_name: Optional[str] = None,
    gcs_prefix: Optional[str] = None,
    gcs_uri: Optional[str] = None,
    document_path: Optional[str] = None,
    documentai_document: Optional[documentai.Document] = None,
    batch_process_metadata: Optional[documentai.BatchProcessMetadata] = None,
    batch_process_operation: Optional[str] = None,
) -> document.Document:
    if gcs_bucket_name and gcs_prefix:
        # Load from Google Cloud Storage Directory
        print("Document structure in Cloud Storage")
        gcs_utilities.print_gcs_document_tree(
            gcs_bucket_name=gcs_bucket_name, gcs_prefix=gcs_prefix
        )

        wrapped_document = document.Document.from_gcs(
            gcs_bucket_name=gcs_bucket_name, gcs_prefix=gcs_prefix
        )
    elif gcs_uri:
        # Load a single Document from a Google Cloud Storage URI
        wrapped_document = document.Document.from_gcs_uri(gcs_uri=gcs_uri)
    elif document_path:
        # Load from local `Document` JSON file
        wrapped_document = document.Document.from_document_path(document_path)
    elif documentai_document:
        # Load from `documentai.Document` object
        wrapped_document = document.Document.from_documentai_document(
            documentai_document
        )
    elif batch_process_metadata:
        # Load Documents from `BatchProcessMetadata` object
        wrapped_documents = document.Document.from_batch_process_metadata(
            metadata=batch_process_metadata
        )
        wrapped_document = wrapped_documents[0]
    elif batch_process_operation:
        wrapped_documents = document.Document.from_batch_process_operation(
            location="us", operation_name=batch_process_operation
        )
        wrapped_document = wrapped_documents[0]
    else:
        raise ValueError("No document source provided.")

    # For all properties and methods, refer to:
    # https://cloud.google.com/python/docs/reference/documentai-toolbox/latest/google.cloud.documentai_toolbox.wrappers.document.Document

    print("Document Successfully Loaded!")
    print(f"\t Number of Pages: {len(wrapped_document.pages)}")
    print(f"\t Number of Entities: {len(wrapped_document.entities)}")

    for page in wrapped_document.pages:
        print(f"Page {page.page_number}")
        for block in page.blocks:
            print(block.text)
        for paragraph in page.paragraphs:
            print(paragraph.text)
        for line in page.lines:
            print(line.text)
        for token in page.tokens:
            print(token.text)

        # Only supported with Form Parser processor
        # https://cloud.google.com/document-ai/docs/form-parser
        for form_field in page.form_fields:
            print(f"{form_field.field_name} : {form_field.field_value}")

        # Only supported with Enterprise Document OCR version `pretrained-ocr-v2.0-2023-06-02`
        # https://cloud.google.com/document-ai/docs/process-documents-ocr#enable_symbols
        for symbol in page.symbols:
            print(symbol.text)

        # Only supported with Enterprise Document OCR version `pretrained-ocr-v2.0-2023-06-02`
        # https://cloud.google.com/document-ai/docs/process-documents-ocr#math_ocr
        for math_formula in page.math_formulas:
            print(math_formula.text)

    # Only supported with Entity Extraction processors
    # https://cloud.google.com/document-ai/docs/processors-list
    for entity in wrapped_document.entities:
        print(f"{entity.type_} : {entity.mention_text}")
        if entity.normalized_text:
            print(f"\tNormalized Text: {entity.normalized_text}")

    # Only supported with Layout Parser
    for chunk in wrapped_document.chunks:
        print(f"Chunk {chunk.chunk_id}: {chunk.content}")

    for block in wrapped_document.document_layout_blocks:
        print(f"Document Layout Block {block.block_id}")

        if block.text_block:
            print(f"{block.text_block.type_}: {block.text_block.text}")
        if block.list_block:
            print(f"{block.list_block.type_}: {block.list_block.list_entries}")
        if block.table_block:
            print(block.table_block.header_rows, block.table_block.body_rows)

Étape suivante

Pour rechercher et filtrer des exemples de code pour d'autres produits Google Cloud , consultez l'explorateur d'exemplesGoogle Cloud .