Importa documentos desde Bigtable

Importa documentos desde Bigtable

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Para obtener documentación en la que se incluye esta muestra de código, consulta lo siguiente:

Muestra de código

Python

Para obtener más información, consulta la documentación de referencia de la API de Python del compilador de agentes de Vertex AI.

Para autenticarte en Vertex AI Agent Builder, configura las credenciales predeterminadas de la aplicación. Si deseas obtener más información, consulta Configura la autenticación para un entorno de desarrollo local. 

from google.api_core.client_options import ClientOptions
from google.cloud import discoveryengine

# TODO(developer): Uncomment these variables before running the sample.
# project_id = "YOUR_PROJECT_ID"
# location = "YOUR_LOCATION" # Values: "global"
# data_store_id = "YOUR_DATA_STORE_ID"
# bigtable_project_id = "YOUR_BIGTABLE_PROJECT_ID"
# bigtable_instance_id = "YOUR_BIGTABLE_INSTANCE_ID"
# bigtable_table_id = "YOUR_BIGTABLE_TABLE_ID"

#  For more information, refer to:
# https://cloud.google.com/generative-ai-app-builder/docs/locations#specify_a_multi-region_for_your_data_store
client_options = (
    ClientOptions(api_endpoint=f"{location}-discoveryengine.googleapis.com")
    if location != "global"
    else None
)

# Create a client
client = discoveryengine.DocumentServiceClient(client_options=client_options)

# The full resource name of the search engine branch.
# e.g. projects/{project}/locations/{location}/dataStores/{data_store_id}/branches/{branch}
parent = client.branch_path(
    project=project_id,
    location=location,
    data_store=data_store_id,
    branch="default_branch",
)

bigtable_options = discoveryengine.BigtableOptions(
    families={
        "family_name_1": discoveryengine.BigtableOptions.BigtableColumnFamily(
            type_=discoveryengine.BigtableOptions.Type.STRING,
            encoding=discoveryengine.BigtableOptions.Encoding.TEXT,
            columns=[
                discoveryengine.BigtableOptions.BigtableColumn(
                    qualifier="qualifier_1".encode("utf-8"),
                    field_name="field_name_1",
                ),
            ],
        ),
        "family_name_2": discoveryengine.BigtableOptions.BigtableColumnFamily(
            type_=discoveryengine.BigtableOptions.Type.INTEGER,
            encoding=discoveryengine.BigtableOptions.Encoding.BINARY,
        ),
    }
)

request = discoveryengine.ImportDocumentsRequest(
    parent=parent,
    bigtable_source=discoveryengine.BigtableSource(
        project_id=bigtable_project_id,
        instance_id=bigtable_instance_id,
        table_id=bigtable_table_id,
        bigtable_options=bigtable_options,
    ),
    # Options: `FULL`, `INCREMENTAL`
    reconciliation_mode=discoveryengine.ImportDocumentsRequest.ReconciliationMode.INCREMENTAL,
)

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

print(f"Waiting for operation to complete: {operation.operation.name}")
response = operation.result()

# After the operation is complete,
# get information from operation metadata
metadata = discoveryengine.ImportDocumentsMetadata(operation.metadata)

# Handle the response
print(response)
print(metadata)

¿Qué sigue?

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