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Schema für strukturierte Daten löschen

Sie können ein Schema nur löschen, wenn alle mit dem Schema verknüpften Dokumente gelöscht wurden. Andernfalls schlägt der Versuch fehl. Nachdem Sie ein Schema gelöscht haben, können Sie rufen Sie die Methode schemas.create auf, um eine neue zu erstellen.

So löschen Sie ein Schema für strukturierte Daten:

REST

Suchen Sie die Datenspeicher-ID. Wenn Sie bereits einen Datenspeicher haben ID verwenden, fahren Sie mit dem nächsten Schritt fort.
1. Rufen Sie in der Google Cloud Console die Seite Agent Builder auf und klicken Sie im Navigationsmenü auf Datenspeicher.
  
  Zur Seite „Datenspeicher“
2. Klicken Sie auf den Namen des Datenspeichers.
3. Rufen Sie auf der Datenseite Ihres Datenspeichers die Datenspeicher-ID ab.

Löschen Sie das Schema.

curl -X DELETE \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json" \
"https://discoveryengine.googleapis.com/v1beta/projects/PROJECT_ID/locations/global/collections/default_collection/dataStores/DATA_STORE_ID/schemas/default_schema"

PROJECT_ID: Die ID Ihres Projekts.
DATA_STORE_ID: Die ID Ihres Datenspeichers.

C#

Weitere Informationen finden Sie in der Referenzdokumentation zur Vertex AI Agent Builder C# API.

Richten Sie zur Authentifizierung bei Vertex AI Agent Builder Standardanmeldedaten für Anwendungen ein. Weitere Informationen finden Sie unter Authentifizierung für eine lokale Entwicklungsumgebung einrichten.

using Google.Cloud.DiscoveryEngine.V1;
using Google.LongRunning;
using Google.Protobuf.WellKnownTypes;

public sealed partial class GeneratedSchemaServiceClientSnippets
{
    /// <summary>Snippet for DeleteSchema</summary>
    /// <remarks>
    /// This snippet has been automatically generated and should be regarded as a code template only.
    /// It will require modifications to work:
    /// - It may require correct/in-range values for request initialization.
    /// - It may require specifying regional endpoints when creating the service client as shown in
    ///   https://cloud.google.com/dotnet/docs/reference/help/client-configuration#endpoint.
    /// </remarks>
    public void DeleteSchemaRequestObject()
    {
        // Create client
        SchemaServiceClient schemaServiceClient = SchemaServiceClient.Create();
        // Initialize request argument(s)
        DeleteSchemaRequest request = new DeleteSchemaRequest
        {
            SchemaName = SchemaName.FromProjectLocationDataStoreSchema("[PROJECT]", "[LOCATION]", "[DATA_STORE]", "[SCHEMA]"),
        };
        // Make the request
        Operation<Empty, DeleteSchemaMetadata> response = schemaServiceClient.DeleteSchema(request);

        // Poll until the returned long-running operation is complete
        Operation<Empty, DeleteSchemaMetadata> completedResponse = response.PollUntilCompleted();
        // Retrieve the operation result
        Empty result = completedResponse.Result;

        // Or get the name of the operation
        string operationName = response.Name;
        // This name can be stored, then the long-running operation retrieved later by name
        Operation<Empty, DeleteSchemaMetadata> retrievedResponse = schemaServiceClient.PollOnceDeleteSchema(operationName);
        // Check if the retrieved long-running operation has completed
        if (retrievedResponse.IsCompleted)
        {
            // If it has completed, then access the result
            Empty retrievedResult = retrievedResponse.Result;
        }
    }
}

Go

Weitere Informationen finden Sie in der Referenzdokumentation zur Vertex AI Agent Builder Go API.


package main

import (
	"context"

	discoveryengine "cloud.google.com/go/discoveryengine/apiv1"
	discoveryenginepb "cloud.google.com/go/discoveryengine/apiv1/discoveryenginepb"
)

func main() {
	ctx := context.Background()
	// This snippet has been automatically generated and should be regarded as a code template only.
	// It will require modifications to work:
	// - It may require correct/in-range values for request initialization.
	// - It may require specifying regional endpoints when creating the service client as shown in:
	//   https://pkg.go.dev/cloud.google.com/go#hdr-Client_Options
	c, err := discoveryengine.NewSchemaClient(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	defer c.Close()

	req := &discoveryenginepb.DeleteSchemaRequest{
		// TODO: Fill request struct fields.
		// See https://pkg.go.dev/cloud.google.com/go/discoveryengine/apiv1/discoveryenginepb#DeleteSchemaRequest.
	}
	op, err := c.DeleteSchema(ctx, req)
	if err != nil {
		// TODO: Handle error.
	}

	err = op.Wait(ctx)
	if err != nil {
		// TODO: Handle error.
	}
}

Java

Weitere Informationen finden Sie in der Referenzdokumentation zur Vertex AI Agent Builder Java API.

import com.google.cloud.discoveryengine.v1.DeleteSchemaRequest;
import com.google.cloud.discoveryengine.v1.SchemaName;
import com.google.cloud.discoveryengine.v1.SchemaServiceClient;
import com.google.protobuf.Empty;

public class SyncDeleteSchema {

  public static void main(String[] args) throws Exception {
    syncDeleteSchema();
  }

  public static void syncDeleteSchema() throws Exception {
    // This snippet has been automatically generated and should be regarded as a code template only.
    // It will require modifications to work:
    // - It may require correct/in-range values for request initialization.
    // - It may require specifying regional endpoints when creating the service client as shown in
    // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
    try (SchemaServiceClient schemaServiceClient = SchemaServiceClient.create()) {
      DeleteSchemaRequest request =
          DeleteSchemaRequest.newBuilder()
              .setName(
                  SchemaName.ofProjectLocationDataStoreSchemaName(
                          "[PROJECT]", "[LOCATION]", "[DATA_STORE]", "[SCHEMA]")
                      .toString())
              .build();
      schemaServiceClient.deleteSchemaAsync(request).get();
    }
  }
}

Python

Weitere Informationen finden Sie in der Referenzdokumentation zur Vertex AI Agent Builder Python API.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import discoveryengine_v1


def sample_delete_schema():
    # Create a client
    client = discoveryengine_v1.SchemaServiceClient()

    # Initialize request argument(s)
    request = discoveryengine_v1.DeleteSchemaRequest(
        name="name_value",
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)

Ruby

Weitere Informationen finden Sie in der Referenzdokumentation zur Vertex AI Agent Builder Ruby API.

require "google/cloud/discovery_engine/v1"

##
# Snippet for the delete_schema call in the SchemaService service
#
# This snippet has been automatically generated and should be regarded as a code
# template only. It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in https://cloud.google.com/ruby/docs/reference.
#
# This is an auto-generated example demonstrating basic usage of
# Google::Cloud::DiscoveryEngine::V1::SchemaService::Client#delete_schema.
#
def delete_schema
  # Create a client object. The client can be reused for multiple calls.
  client = Google::Cloud::DiscoveryEngine::V1::SchemaService::Client.new

  # Create a request. To set request fields, pass in keyword arguments.
  request = Google::Cloud::DiscoveryEngine::V1::DeleteSchemaRequest.new

  # Call the delete_schema method.
  result = client.delete_schema request

  # The returned object is of type Gapic::Operation. You can use it to
  # check the status of an operation, cancel it, or wait for results.
  # Here is how to wait for a response.
  result.wait_until_done! timeout: 60
  if result.response?
    p result.response
  else
    puts "No response received."
  end
end