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/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
- 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
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.
Client libraries targeting some end-of-life versions of Node.js are available, and
can be installed via npm dist-tags
.
The dist-tags follow the naming convention legacy-(version)
.
Legacy Node.js versions are supported as a best effort:
- Legacy versions will not be tested in continuous integration.
- Some security patches may not be able to be backported.
- Dependencies will not be kept up-to-date, and features will not be backported.
Legacy tags available
-
legacy-8
: install client libraries from this dist-tag for versions compatible with Node.js 8.
Versioning
This library follows Semantic Versioning .
This library is considered to be General Availability (GA). This means it is 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 GAlibraries 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