@aigentic/diskann

@aigentic/diskann

DiskANN/Vamana approximate nearest neighbor search — built in Rust, runs on all platforms.

Implements the Vamana graph algorithm from "DiskANN: Fast Accurate Billion-point Nearest Neighbor Search on a Single Node" (NeurIPS 2019).

Install

npm install @aigentic/diskann

Usage

const { DiskAnn } = require('@aigentic/diskann');

const index = new DiskAnn({ dim: 128 });

// Insert vectors
for (let i = 0; i < 1000; i++) {
  const vec = new Float32Array(128);
  for (let d = 0; d < 128; d++) vec[d] = Math.random();
  index.insert(`vec-${i}`, vec);
}

// Build Vamana graph
index.build();

// Search
const query = new Float32Array(128).fill(0.5);
const results = index.search(query, 10);
console.log(results); // [{ id: 'vec-42', distance: 0.123 }, ...]

// Persist
index.save('./my-index');
const loaded = DiskAnn.load('./my-index');

Performance

Metric	Value
Search latency	55µs (5K vectors, 128d, k=10)
Recall@10	0.998
Build	~6s for 5K vectors

API

See full documentation at github.com/ruvnet/ruvector.

License

MIT