Files
modules/indexes-search/hyper-p2p-semantic-vector-index
Raven ScottandCursor e43e2e83f1 Deepen indexes-search: APIs, tests, and category docs
Extend all eight index/search packages with practical helpers for app
development and fix semantic-vector getStats() to expose real metrics.

Per-module code:
- bloom-gossip: listKeys(), clear()
- inverted-index: searchAll(and|or), getDocTerms()
- fulltext-lite: search(and|or), suggest(prefix)
- trie-prefix: countPrefix(), autocomplete(limit)
- graph-index: removeEdge(), outDegree(), edgeCount()
- similarity-lsh: nearVector(), bucketCount()
- semantic-vector-index: getStats() delegates to getMetrics() + PROTOCOL export
- spatial-index: listLocalPoints(), pointCount(), protocol in getStats()

Tests added for new APIs across six packages; all indexes-search npm test
suites pass (8/8).

Docs:
- Rewrite indexes-search category README (module table, composition)
- Expand bloom-gossip and semantic-vector architecture notes
- modules/README.md: link indexes-search doc hub

Parent workspace docs/indexes-search/README.md and MODULE_DOC_PASS.md
updated separately (outside this git root).

Co-authored-by: Cursor <[email protected]>
2026-05-21 00:20:56 -04:00
..
2026-05-20 23:36:32 -04:00
2026-05-20 21:02:45 -04:00
2026-05-21 00:07:44 -04:00
2026-05-20 21:19:52 -04:00
2026-05-20 21:02:45 -04:00
2026-05-20 23:36:32 -04:00

hyper-p2p-semantic-vector-index

HyperP2PSemanticVectorIndex Novel, production-grade semantic vector indexing and similarity search primitive for Bare/Pear P2P applications. Features:

Category: Indexes & search

Composes with: hyper-spatial-index, hyper-p2p-intent-router

Protocol: hyper-p2p-semantic-vector-index/v1

When to use

Multi-peer apps that need indexes & search over a shared Hyperswarm topic.

When not to use

Single-process tools with no P2P topic (use local APIs only or skip ready()).

Quick start

const HyperP2PSemanticVectorIndex = require('hyper-p2p-semantic-vector-index')
const index = new HyperP2PSemanticVectorIndex({ dimension: 128, topic: process.argv[2] })
const id = await index.insert([/* normalized vector */], { tags: ['docs'] })
const hits = await index.search([/* query */], 5, { minSimilarity: 0.7 })
console.log(id, hits)
await index.close()

Docs

Test

npm install && npm test