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JavaScript SDK - Unum · USearch 2.19.3 documentation

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USearch is a high-performance library for building and querying vector search indexes, optimized for Node.js and WASM environments.

For Node.js environments, install USearch using npm:

Create an index, add vectors, and perform searches with ease:

const assert = require('node:assert');
const usearch = require('usearch');
const index = new usearch.Index({ metric: 'l2sq', connectivity: 16, dimensions: 3 });
index.add(42n, new Float32Array([0.2, 0.6, 0.4]));
const results = index.search(new Float32Array([0.2, 0.6, 0.4]), 10);

assert(index.size() === 1);
assert.deepEqual(results.keys, new BigUint64Array([42n]));
assert.deepEqual(results.distances, new Float32Array([0]));

index.remove(42n);

Persist and restore your index with serialization methods:

index.save('index.usearch'); // Save the index to a file
index.load('index.usearch'); // Load the index from a file
index.view('index.usearch'); // View the index from a file without loading into memory

Customize your index with additional configuration options:

const index = new usearch.Index({
  dimensions: 128,
  metric: 'ip',
  quantization: 'f32',
  connectivity: 10,
  expansion_add: 5,
  expansion_search: 3,
  multi: true
});

Process multiple vectors at once for efficiency. For performance reasons we prefer a flattened TypedArray over an Array of Arrays:

const keys = new BigUint64Array([15n, 16n]);
const vectors = new Float32Array([10, 20, 10, 25]);
index.add(keys, vectors);

Retrieve batch search results:

const batchResults = index.search(vectors, 2);
const firstMatch = batchResults.get(0);

Multi-threading is supported for batch operations:

const threads_count = 0; // Zero for auto-detection or pass an unsigned integer
index.add(keys, vectors, threads_count);
const batchResults = index.search(vectors, 2, threads_count);

Inspect and interact with the index:

const dimensions = index.dimensions(); // Get the number of dimensions
const containsKey = index.contains(42n); // Check if a key is in the index
const count = index.count(42n); // Get the count of vectors for a key

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

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