You can access the Vector Loader — Document Embedding & Vector DB Ingestion programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

1import { ApifyClient } from 'apify-client';
2
3// Initialize the ApifyClient with your Apify API token
4// Replace the '<YOUR_API_TOKEN>' with your token
5const client = new ApifyClient({
6    token: '<YOUR_API_TOKEN>',
7});
8
9// Prepare Actor input
10const input = {
11    "pineconeIndex": "job-listings"
12};
13
14// Run the Actor and wait for it to finish
15const run = await client.actor("apricot_blackberry/vector-loader").call(input);
16
17// Fetch and print Actor results from the run's dataset (if any)
18console.log('Results from dataset');
19console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
20const { items } = await client.dataset(run.defaultDatasetId).listItems();
21items.forEach((item) => {
22    console.dir(item);
23});
24
25// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

Vector Loader - AI & ML API in JavaScript

The Apify API client for JavaScript is the official library that allows you to use Vector Loader — Document Embedding & Vector DB Ingestion API in JavaScript or TypeScript, providing convenience functions and automatic retries on errors.

Install the apify-client

$npm install apify-client

Other API clients include:

Vector Loader — Document Embedding & Vector DB Ingestion API in Python

Vector Loader — Document Embedding & Vector DB Ingestion API through CLI

Vector Loader — Document Embedding & Vector DB Ingestion OpenAPI definition

Vector Loader — Document Embedding & Vector DB Ingestion API

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