@maxim_mazurok/gapi.client.aiplatform-v1beta1 v0.0.20241026
TypeScript typings for Vertex AI API v1beta1
Train high-quality custom machine learning models with minimal machine learning expertise and effort. For detailed description please check documentation.
Installing
Install typings for Vertex AI API:
npm install @types/gapi.client.aiplatform-v1beta1 --save-dev
Usage
You need to initialize Google API client in your code:
gapi.load('client', () => {
// now we can use gapi.client
// ...
});
Then load api client wrapper:
gapi.client.load(
'https://aiplatform.googleapis.com/$discovery/rest?version=v1beta1',
() => {
// now we can use:
// gapi.client.aiplatform
}
);
// Deprecated, use discovery document URL, see https://github.com/google/google-api-javascript-client/blob/master/docs/reference.md#----gapiclientloadname----version----callback--
gapi.client.load('aiplatform', 'v1beta1', () => {
// now we can use:
// gapi.client.aiplatform
});
Don't forget to authenticate your client before sending any request to resources:
// declare client_id registered in Google Developers Console
var client_id = '',
scope = [
// See, edit, configure, and delete your Google Cloud data and see the email address for your Google Account.
'https://www.googleapis.com/auth/cloud-platform',
// View your data across Google Cloud services and see the email address of your Google Account
'https://www.googleapis.com/auth/cloud-platform.read-only',
],
immediate = true;
// ...
gapi.auth.authorize(
{client_id: client_id, scope: scope, immediate: immediate},
authResult => {
if (authResult && !authResult.error) {
/* handle successful authorization */
} else {
/* handle authorization error */
}
}
);
After that you can use Vertex AI API resources:
/*
Creates a Dataset.
*/
await gapi.client.aiplatform.datasets.create({});
/*
Deletes a Dataset.
*/
await gapi.client.aiplatform.datasets.delete({name: 'name'});
/*
Gets a Dataset.
*/
await gapi.client.aiplatform.datasets.get({name: 'name'});
/*
Lists Datasets in a Location.
*/
await gapi.client.aiplatform.datasets.list({});
/*
Updates a Dataset.
*/
await gapi.client.aiplatform.datasets.patch({name: 'name'});
/*
Return a list of tokens based on the input text.
*/
await gapi.client.aiplatform.endpoints.computeTokens({endpoint: 'endpoint'});
/*
Perform a token counting.
*/
await gapi.client.aiplatform.endpoints.countTokens({endpoint: 'endpoint'});
/*
Generate content with multimodal inputs.
*/
await gapi.client.aiplatform.endpoints.generateContent({model: 'model'});
/*
Generate content with multimodal inputs with streaming support.
*/
await gapi.client.aiplatform.endpoints.streamGenerateContent({model: 'model'});
/*
Upload a file into a RagCorpus.
*/
await gapi.client.aiplatform.media.upload({parent: 'parent'});
/*
Gets a GenAI cache config.
*/
await gapi.client.aiplatform.projects.getCacheConfig({name: 'name'});
/*
Updates a cache config.
*/
await gapi.client.aiplatform.projects.updateCacheConfig({name: 'name'});
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