Cloud AutoML: Node.js Client

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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/nodejs-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

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: ${resu result 
playName}`);
  console.log(`Predicted class score: ${resu result 
ssification.score}`);
}); 

Samples

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

Sample	Source Code	Try it
Batch_predict	source code
Delete_dataset	source code
Delete_model	source code
Deploy_model	source code
Export_dataset	source code
Get_dataset	source code
Get_model	source code
Get_model_evaluation	source code
Get_operation_status	source code
Import_dataset	source code
Language_entity_extraction_create_dataset	source code
Language_entity_extraction_create_model	source code
Language_entity_extraction_predict	source code
Language_sentiment_analysis_create_dataset	source code
Language_sentiment_analysis_create_model	source code
Language_sentiment_analysis_predict	source code
Language_text_classification_create_dataset	source code
Language_text_classification_create_model	source code
Language_text_classification_predict	source code
List_datasets	source code
List_model_evaluations	source code
List_models	source code
List_operation_status	source code
Quickstart	source code
Translate_create_dataset	source code
Translate_create_model	source code
Translate_predict	source code
Undeploy_model	source code
Vision_classification_create_dataset	source code
Vision_classification_create_model	source code
Vision_classification_deploy_model_node_count	source code
Vision_classification_predict	source code
Vision_object_detection_create_dataset	source code
Vision_object_detection_create_model	source code
Vision_object_detection_deploy_model_node_count	source code
Vision_object_detection_predict	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 stablelibraries 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