@google-cloud/automl

Cloud AutoML: Node.js Client

Cloud AutoML API client for Node.js

A comprehensive list of changes in each version may be found in the CHANGELOG.

• Cloud AutoML Node.js Client API Reference
• Cloud AutoML Documentation
• github.com/googleapis/google-cloud-node/packages/google-cloud-automl

Read more about the client libraries for Cloud APIs, including the older Google APIs Client Libraries, in Client Libraries Explained.

Table of contents:

• Quickstart
  • Before you begin
  • Installing the client library
  • Using the client library
• Samples
• Versioning
• Contributing
• License

Quickstart

Before you begin

• Select or create a Cloud Platform project.
• Enable billing for your project.
• Enable the Cloud AutoML API.
• Set up authentication with a service account so you can access the API from your local workstation.

Installing the client library

npm install @google-cloud/automl

Using the client library

/**
 * TODO(developer): Uncomment these variables before running the sample.
 */
// const projectId = 'YOUR_PROJECT_ID';
// const location = 'us-central1';

// Imports the Google Cloud AutoML library
const {AutoMlClient} = require('@google-cloud/automl').v1;

// Instantiates a client
const client = new AutoMlClient();

async function listDatasets() {
  // Construct request
  const request = {
    parent: client.locationPath(projectId, location),
    filter: 'translation_dataset_metadata:*',
  };

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

  console.log('List of datasets:');
  for (const dataset of response) {
    console.log(`Dataset name: ${dataset.name}`);
    console.log(
      `Dataset id: ${
        dataset.name.split('/')[dataset.name.split('/').length - 1]
      }`
    );
    console.log(`Dataset display name: ${dataset.displayName}`);
    console.log('Dataset create time');
    console.log(`\tseconds ${dataset.createTime.seconds}`);
    console.log(`\tnanos ${dataset.createTime.nanos / 1e9}`);
    console.log(
      `Text extraction dataset metadata: ${dataset.textExtractionDatasetMetadata}`
    );

    console.log(
      `Text sentiment dataset metadata: ${dataset.textSentimentDatasetMetadata}`
    );

    console.log(
      `Text classification dataset metadata: ${dataset.textClassificationDatasetMetadata}`
    );

    if (dataset.translationDatasetMetadata !== undefined) {
      console.log('Translation dataset metadata:');
      console.log(
        `\tSource language code: ${dataset.translationDatasetMetadata.sourceLanguageCode}`
      );
      console.log(
        `\tTarget language code: ${dataset.translationDatasetMetadata.targetLanguageCode}`
      );
    }

    console.log(
      `Image classification dataset metadata: ${dataset.imageClassificationDatasetMetadata}`
    );

    console.log(
      `Image object detection dataset metatdata: ${dataset.imageObjectDetectionDatasetMetatdata}`
    );
  }
}

listDatasets();

Samples

Samples are in the samples/ directory. Each sample's README.md has instructions for running its sample.

Sample	Source Code	Try it
Auto_ml.create_dataset	source code
Auto_ml.create_model	source code
Auto_ml.delete_dataset	source code
Auto_ml.delete_model	source code
Auto_ml.deploy_model	source code
Auto_ml.export_data	source code
Auto_ml.export_model	source code
Auto_ml.get_annotation_spec	source code
Auto_ml.get_dataset	source code
Auto_ml.get_model	source code
Auto_ml.get_model_evaluation	source code
Auto_ml.import_data	source code
Auto_ml.list_datasets	source code
Auto_ml.list_model_evaluations	source code
Auto_ml.list_models	source code
Auto_ml.undeploy_model	source code
Auto_ml.update_dataset	source code
Auto_ml.update_model	source code
Prediction_service.batch_predict	source code
Prediction_service.predict	source code
Auto_ml.create_dataset	source code
Auto_ml.create_model	source code
Auto_ml.delete_dataset	source code
Auto_ml.delete_model	source code
Auto_ml.deploy_model	source code
Auto_ml.export_data	source code
Auto_ml.export_evaluated_examples	source code
Auto_ml.export_model	source code
Auto_ml.get_annotation_spec	source code
Auto_ml.get_column_spec	source code
Auto_ml.get_dataset	source code
Auto_ml.get_model	source code
Auto_ml.get_model_evaluation	source code
Auto_ml.get_table_spec	source code
Auto_ml.import_data	source code
Auto_ml.list_column_specs	source code
Auto_ml.list_datasets	source code
Auto_ml.list_model_evaluations	source code
Auto_ml.list_models	source code
Auto_ml.list_table_specs	source code
Auto_ml.undeploy_model	source code
Auto_ml.update_column_spec	source code
Auto_ml.update_dataset	source code
Auto_ml.update_table_spec	source code
Prediction_service.batch_predict	source code
Prediction_service.predict	source code
Quickstart	source code

The Cloud AutoML Node.js Client API Reference documentation also contains samples.

Supported Node.js Versions

Our client libraries follow the Node.js release schedule. Libraries are compatible with all current active and maintenance versions of Node.js. If you are using an end-of-life version of Node.js, we recommend that you update as soon as possible to an actively supported LTS version.

Google's client libraries support legacy versions of Node.js runtimes on a best-efforts basis with the following warnings:

• Legacy versions are not tested in continuous integration.
• Some security patches and features cannot be backported.
• Dependencies cannot be kept up-to-date.

Client libraries targeting some end-of-life versions of Node.js are available, and can be installed through npm dist-tags. The dist-tags follow the naming convention legacy-(version). For example, npm install @google-cloud/automl@legacy-8 installs client libraries for versions compatible with Node.js 8.

Versioning

This library follows Semantic Versioning.

This library is considered to be stable. The code surface will not change in backwards-incompatible ways unless absolutely necessary (e.g. because of critical security issues) or with an extensive deprecation period. Issues and requests against stable libraries are addressed with the highest priority.

More Information: Google Cloud Platform Launch Stages

Contributing

Contributions welcome! See the Contributing Guide.

Please note that this README.md, the samples/README.md, and a variety of configuration files in this repository (including .nycrc and tsconfig.json) are generated from a central template. To edit one of these files, make an edit to its templates in directory.

License

Apache Version 2.0

See LICENSE