ferrovecReal WASM · no server · no network
Semantic search, running entirely in this browser tab.
Everything below is the actual ferrovec Rust→WebAssembly core — the same 77 KB crate published to npm — doing live approximate-nearest-neighbour search over 24 sentence embeddings. The WASM binary and the vectors are baked into this single HTML file. Nothing is fetched; close your Wi-Fi and it still works.
Search
pick a query →These queries are pre-embedded with all-MiniLM-L6-v2. Click one — the ranking is computed live by the WASM core, not looked up. Note how matches share almost no words with the query.
- Pick a query above to run the WASM core.
The index
24 notesHow this runs with zero backend
Rust → WASM, inlined
The published ferrovec crate compiled to a 77 KB .wasm, base64-embedded in this page and instantiated with WebAssembly.instantiate. The HNSW graph, SIMD distances and search all execute in your browser's WASM sandbox.
MiniLM embeddings
Each note was embedded once with all-MiniLM-L6-v2 (384-dim, mean-pooled, normalised) and stored as plain numbers in the page. In a real app, transformers.js does this in a Web Worker on the fly.
Live k-NN ranking
On each query the core walks the HNSW graph and returns the nearest neighbours by cosine similarity — in well under a millisecond — exactly as it would over millions of vectors on a server or the edge.
// In a real app the same core drives a three-line API (npm: ferrovec):
import { Ferrovec } from 'ferrovec';
const db = await Ferrovec.open('notes'); // worker + model + OPFS
await db.insert('the cat curled up in the sun'); // embed + index
const hits = await db.query('a sleepy kitten', 5); // → ranked, nearest-first