npm install @google-cloud/automl

Cloud AutoML API client for Node.js

About @google-cloud/automl

The npm package "@google-cloud/automl" unlocks the power of machine learning for developers using Node.js, providing a streamlined path to integrating advanced ML models into applications without requiring extensive machine learning expertise. This tool is part of the Google Cloud AutoML suite, designed to train high-quality custom models with minimal effort and machine learning knowledge. It supports a variety of data types including video, images, and text, making it a versatile solution for many industries such as retail, manufacturing, and healthcare. By leveraging this package, developers can enhance their applications with capabilities such as image recognition, language translation, and more, harnessing the cutting-edge AI technology developed by Google.

To get started with this powerful tool, developers can simply run the command "npm install @google-cloud/automl" in their project's directory. This command installs the necessary library files into the Node.js environment, setting up a direct line to Google’s robust ML frameworks. Once installed, developers can easily access the AutoML API, allowing them to create, train, and utilize custom models tailored to their specific needs. The simplicity of this installation process means that even developers with limited machine learning background can quickly begin implementing sophisticated ML features in their projects.

The benefits of using "@google-cloud/automail" extend beyond simple machine learning integration. This package automatically handles many of the complexities associated with training and deploying machine learning models, such as data preprocessing, feature selection, and model evaluation. This not only saves valuable development time but also ensures that the models produced are both efficient and effective. Additionally, since it is built on Google Cloud infrastructure, it offers seamless scalability and reliability, ensuring that machine learning capabilities can grow with your application’s needs. Whether you're building a small app or an enterprise-grade solution, "@google-cloud/automail" provides the tools necessary to incorporate AI seamlessly and effectively.

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Documentation

A README file for the @google-cloud/automl code repository. View Code

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THIS REPOSITORY IS DEPRECATED. ALL OF ITS CONTENT AND HISTORY HAS BEEN MOVED TO GOOGLE-CLOUD-NODE

Cloud AutoML: Node.js Client

release level npm version

🔔 AutoML API NodeJS Client is now available in Vertex AI. Please visit node-js-aiplatform for the new NodeJS Vertex AI client. Vertex AI is our next generation AI Platform, with many new features that are unavailable in the current platform. Migrate your resources to Vertex AI to get the latest machine learning features, simplify end-to-end journeys, and productionize models with MLOps.

Cloud AutoML API client for Node.js

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

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

  1. Select or create a Cloud Platform project.
  2. Enable billing for your project.
  3. Enable the Cloud AutoML API.
  4. 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

const automl = require('@google-cloud/automl');
const fs = require('fs');

// Create client for prediction service.
const client = new automl.PredictionServiceClient();

/**
 * TODO(developer): Uncomment the following line before running the sample.
 */
// const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
// const computeRegion = `region-name, e.g. "us-central1"`;
// const modelId = `id of the model, e.g. “ICN723541179344731436”`;
// const filePath = `local text file path of content to be classified, e.g. "./resources/flower.png"`;
// const scoreThreshold = `value between 0.0 and 1.0, e.g. "0.5"`;

// Get the full path of the model.
const modelFullId = client.modelPath(projectId, computeRegion, modelId);

// Read the file content for prediction.
const content = fs.readFileSync(filePath, 'base64');

const params = {};

if (scoreThreshold) {
  params.score_threshold = scoreThreshold;
}

// Set the payload by giving the content and type of the file.
const payload = {};
payload.image = {imageBytes: content};

// params is additional domain-specific parameters.
// currently there is no additional parameters supported.
const [response] = await client.predict({
  name: modelFullId,
  payload: payload,
  params: params,
});
console.log('Prediction results:');
response.payload.forEach(result => {
  console.log(`Predicted class name: ${result.displayName}`);
  console.log(`Predicted class score: ${result.classification.score}`);
});

Samples

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

Sample Source Code Try it
Quickstart source code Open in Cloud Shell

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:

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