Class v1.ModelServiceClient (3.4.0)

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the parent ModelEvaluationSlice resource.
   *  Format:
   *  `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}/slices/{slice}`
   */
  // const parent = 'abc123'
  /**
   *  Required. Evaluated annotations resource to be imported.
   */
  // const evaluatedAnnotations = [1,2,3,4]

  // Imports the Aiplatform library
  const {ModelServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new ModelServiceClient();

  async function callBatchImportEvaluatedAnnotations() {
    // Construct request
    const request = {
      parent,
      evaluatedAnnotations,
    };

    // Run request
    const response = await aiplatformClient.batchImportEvaluatedAnnotations(request);
    console.log(response);
  }

  callBatchImportEvaluatedAnnotations();

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the parent ModelEvaluation resource.
   *  Format:
   *  `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}`
   */
  // const parent = 'abc123'
  /**
   *  Required. Model evaluation slice resource to be imported.
   */
  // const modelEvaluationSlices = [1,2,3,4]

  // Imports the Aiplatform library
  const {ModelServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new ModelServiceClient();

  async function callBatchImportModelEvaluationSlices() {
    // Construct request
    const request = {
      parent,
      modelEvaluationSlices,
    };

    // Run request
    const response = await aiplatformClient.batchImportModelEvaluationSlices(request);
    console.log(response);
  }

  callBatchImportModelEvaluationSlices();

const client = longrunning.operationsClient();
await client.cancelOperation({name: ''});

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Optional. Copy source_model into a new Model with this ID. The ID will
   *  become the final component of the model resource name.
   *  This value may be up to 63 characters, and valid characters are
   *  `[a-z0-9_-]`. The first character cannot be a number or hyphen.
   */
  // const modelId = 'abc123'
  /**
   *  Optional. Specify this field to copy source_model into this existing
   *  Model as a new version. Format:
   *  `projects/{project}/locations/{location}/models/{model}`
   */
  // const parentModel = 'abc123'
  /**
   *  Required. The resource name of the Location into which to copy the Model.
   *  Format: `projects/{project}/locations/{location}`
   */
  // const parent = 'abc123'
  /**
   *  Required. The resource name of the Model to copy. That Model must be in the
   *  same Project. Format:
   *  `projects/{project}/locations/{location}/models/{model}`
   */
  // const sourceModel = 'abc123'
  /**
   *  Customer-managed encryption key options. If this is set,
   *  then the Model copy will be encrypted with the provided encryption key.
   */
  // const encryptionSpec = {}

  // Imports the Aiplatform library
  const {ModelServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new ModelServiceClient();

  async function callCopyModel() {
    // Construct request
    const request = {
      parent,
      sourceModel,
    };

    // Run request
    const [operation] = await aiplatformClient.copyModel(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callCopyModel();

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the Model resource to be deleted.
   *  Format: `projects/{project}/locations/{location}/models/{model}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {ModelServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new ModelServiceClient();

  async function callDeleteModel() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const [operation] = await aiplatformClient.deleteModel(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callDeleteModel();

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the model version to be deleted, with a version ID
   *  explicitly included.
   *  Example: `projects/{project}/locations/{location}/models/{model}@1234`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {ModelServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new ModelServiceClient();

  async function callDeleteModelVersion() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const [operation] = await aiplatformClient.deleteModelVersion(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callDeleteModelVersion();

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the Model to export.
   *  The resource name may contain version id or version alias to specify the
   *  version, if no version is specified, the default version will be exported.
   */
  // const name = 'abc123'
  /**
   *  Required. The desired output location and configuration.
   */
  // const outputConfig = {}

  // Imports the Aiplatform library
  const {ModelServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new ModelServiceClient();

  async function callExportModel() {
    // Construct request
    const request = {
      name,
      outputConfig,
    };

    // Run request
    const [operation] = await aiplatformClient.exportModel(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callExportModel();

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the Model to update.
   *  Format: `projects/{project}/locations/{location}/models/{model}`
   */
  // const model = 'abc123'
  /**
   *  The example config containing the location of the dataset.
   */
  // const examples = {}

  // Imports the Aiplatform library
  const {ModelServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new ModelServiceClient();

  async function callUpdateExplanationDataset() {
    // Construct request
    const request = {
      model,
    };

    // Run request
    const [operation] = await aiplatformClient.updateExplanationDataset(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callUpdateExplanationDataset();

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the Location into which to upload the Model.
   *  Format: `projects/{project}/locations/{location}`
   */
  // const parent = 'abc123'
  /**
   *  Optional. The resource name of the model into which to upload the version.
   *  Only specify this field when uploading a new version.
   */
  // const parentModel = 'abc123'
  /**
   *  Optional. The ID to use for the uploaded Model, which will become the final
   *  component of the model resource name.
   *  This value may be up to 63 characters, and valid characters are
   *  `[a-z0-9_-]`. The first character cannot be a number or hyphen.
   */
  // const modelId = 'abc123'
  /**
   *  Required. The Model to create.
   */
  // const model = {}
  /**
   *  Optional. The user-provided custom service account to use to do the model
   *  upload. If empty, Vertex AI Service
   *  Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents)
   *  will be used. Users uploading the Model must have the
   *  `iam.serviceAccounts.actAs` permission on this service account. Also, this
   *  account must belong to the project specified in the `parent` field and have
   *  all necessary read permissions.
   */
  // const serviceAccount = 'abc123'

  // Imports the Aiplatform library
  const {ModelServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new ModelServiceClient();

  async function callUploadModel() {
    // Construct request
    const request = {
      parent,
      model,
    };

    // Run request
    const [operation] = await aiplatformClient.uploadModel(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callUploadModel();

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Optional. Copy source_model into a new Model with this ID. The ID will
   *  become the final component of the model resource name.
   *  This value may be up to 63 characters, and valid characters are
   *  `[a-z0-9_-]`. The first character cannot be a number or hyphen.
   */
  // const modelId = 'abc123'
  /**
   *  Optional. Specify this field to copy source_model into this existing
   *  Model as a new version. Format:
   *  `projects/{project}/locations/{location}/models/{model}`
   */
  // const parentModel = 'abc123'
  /**
   *  Required. The resource name of the Location into which to copy the Model.
   *  Format: `projects/{project}/locations/{location}`
   */
  // const parent = 'abc123'
  /**
   *  Required. The resource name of the Model to copy. That Model must be in the
   *  same Project. Format:
   *  `projects/{project}/locations/{location}/models/{model}`
   */
  // const sourceModel = 'abc123'
  /**
   *  Customer-managed encryption key options. If this is set,
   *  then the Model copy will be encrypted with the provided encryption key.
   */
  // const encryptionSpec = {}

  // Imports the Aiplatform library
  const {ModelServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new ModelServiceClient();

  async function callCopyModel() {
    // Construct request
    const request = {
      parent,
      sourceModel,
    };

    // Run request
    const [operation] = await aiplatformClient.copyModel(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callCopyModel();

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the Model resource to be deleted.
   *  Format: `projects/{project}/locations/{location}/models/{model}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {ModelServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new ModelServiceClient();

  async function callDeleteModel() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const [operation] = await aiplatformClient.deleteModel(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callDeleteModel();

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the model version to be deleted, with a version ID
   *  explicitly included.
   *  Example: `projects/{project}/locations/{location}/models/{model}@1234`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {ModelServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new ModelServiceClient();

  async function callDeleteModelVersion() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const [operation] = await aiplatformClient.deleteModelVersion(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callDeleteModelVersion();

const client = longrunning.operationsClient();
await client.deleteOperation({name: ''});

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the Model to export.
   *  The resource name may contain version id or version alias to specify the
   *  version, if no version is specified, the default version will be exported.
   */
  // const name = 'abc123'
  /**
   *  Required. The desired output location and configuration.
   */
  // const outputConfig = {}

  // Imports the Aiplatform library
  const {ModelServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new ModelServiceClient();

  async function callExportModel() {
    // Construct request
    const request = {
      name,
      outputConfig,
    };

    // Run request
    const [operation] = await aiplatformClient.exportModel(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callExportModel();

const [response] = await client.getLocation(request);

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the Model resource.
   *  Format: `projects/{project}/locations/{location}/models/{model}`
   *  In order to retrieve a specific version of the model, also provide
   *  the version ID or version alias.
   *    Example: `projects/{project}/locations/{location}/models/{model}@2`
   *               or
   *             `projects/{project}/locations/{location}/models/{model}@golden`
   *  If no version ID or alias is specified, the "default" version will be
   *  returned. The "default" version alias is created for the first version of
   *  the model, and can be moved to other versions later on. There will be
   *  exactly one default version.
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {ModelServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new ModelServiceClient();

  async function callGetModel() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const response = await aiplatformClient.getModel(request);
    console.log(response);
  }

  callGetModel();

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the ModelEvaluation resource.
   *  Format:
   *  `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {ModelServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new ModelServiceClient();

  async function callGetModelEvaluation() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const response = await aiplatformClient.getModelEvaluation(request);
    console.log(response);
  }

  callGetModelEvaluation();

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the ModelEvaluationSlice resource.
   *  Format:
   *  `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}/slices/{slice}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {ModelServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new ModelServiceClient();

  async function callGetModelEvaluationSlice() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const response = await aiplatformClient.getModelEvaluationSlice(request);
    console.log(response);
  }

  callGetModelEvaluationSlice();