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ruvector-wasm-v0.1.31

supertone-oss-archive/supertonicruvector-wasm-v0.1.31Jun 15, 2026by ruvnet

AI Summary

This release corrects the RuvectorWasmAdapter to properly handle HNSW availability, similarity scoring logic, and metadata round-tripping functionality.

Key Highlights

  • Corrects HNSW feature availability (now surfaces flat index vs hnsw)
  • Fixes similarity score logic (now returns 'higher is better' similarity)
  • Restores metadata round-tripping for search and get operations

Breaking Changes

  • The 'score' return value changed from cosine distance to similarity
  • Metadata functionality was previously broken and is now restored

New Features

  • RuvectorWasmAdapter with corrected metric handling
  • Metadata sidecar for keeping track of document id mappings

Full Release Notes

## @ruvector/wasm 0.1.31

Ships the **RuvectorWasmAdapter** (`@ruvector/wasm/adapter`) from #568 and restores a **functional published package** — 0.1.30 had shipped with only `package.json` (empty `pkg/`); 0.1.31 includes the built web `pkg/` (WASM + JS bindings) plus the adapter.

### The adapter corrects three behaviours of the raw WASM build
1. **HNSW not active** — the wasm32 target compiles without the `hnsw` feature and falls back to a flat (brute-force) index. The adapter surfaces this via `indexType` / `WASM_HNSW_AVAILABLE` instead of letting callers assume O(log n).
2. **`score` was a cosine distance** (lower is better), contradicting the `.d.ts`. The adapter exposes a real `similarity = 1 - distance` (per-metric) so "higher is better" holds, with the raw `distance` preserved.
3. **Metadata did not round-trip** — `search`/`get` returned `{}`. The adapter keeps an in-process metadata sidecar keyed by id and re-attaches it on the way out.

### Usage
```js
import { RuvectorWasmAdapter } from '@ruvector/wasm/adapter';
const index = await RuvectorWasmAdapter.create({ dimensions: 384, metric: 'cosine' });
index.insert({ id: 'doc_1', vector: embedding, metadata: { title: 'My Document' } });
const results = index.search({ vector: query, k: 10 });
// results[i].similarity (higher better), .distance (raw), .metadata (round-trips), index.indexType ('flat')
```

- Tarball: 13 files, 381 kB unpacked · npm: https://www.npmjs.com/package/@ruvector/wasm
- Adapter validated by 7 Node tests (all 3 findings + filter/batch/delete). PR #568.