ruvector/docs/status/NPM_READY_STATUS.md
rUv 6c00b84e1d
feat(micro-hnsw-wasm): Add Neuromorphic HNSW v2.3 with SNN Integration (#40)
* docs: Add comprehensive GNN v2 implementation plans

Add 22 detailed planning documents for 19 advanced GNN features:

Tier 1 (Immediate - 3-6 months):
- GNN-Guided HNSW Routing (+25% QPS)
- Incremental Graph Learning/ATLAS (10-100x faster updates)
- Neuro-Symbolic Query Execution (hybrid neural + logical)

Tier 2 (Medium-Term - 6-12 months):
- Hyperbolic Embeddings (Poincaré ball model)
- Degree-Aware Adaptive Precision (2-4x memory reduction)
- Continuous-Time Dynamic GNN (concept drift detection)

Tier 3 (Research - 12+ months):
- Graph Condensation (10-100x smaller graphs)
- Native Sparse Attention (8-15x GPU speedup)
- Quantum-Inspired Attention (long-range dependencies)

Novel Innovations (10 experimental features):
- Gravitational Embedding Fields, Causal Attention Networks
- Topology-Aware Gradient Routing, Embedding Crystallization
- Semantic Holography, Entangled Subspace Attention
- Predictive Prefetch Attention, Morphological Attention
- Adversarial Robustness Layer, Consensus Attention

Includes comprehensive regression prevention strategy with:
- Feature flag system for safe rollout
- Performance baseline (186 tests + 6 search_v2 tests)
- Automated rollback mechanisms

Related to #38

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat(micro-hnsw-wasm): Add neuromorphic HNSW v2.3 with SNN integration

## New Crate: micro-hnsw-wasm v2.3.0
- Published to crates.io: https://crates.io/crates/micro-hnsw-wasm
- 11.8KB WASM binary with 58 exported functions
- Neuromorphic vector search combining HNSW + Spiking Neural Networks

### Core Features
- HNSW graph-based approximate nearest neighbor search
- Multi-distance metrics: L2, Cosine, Dot product
- GNN extensions: typed nodes, edge weights, neighbor aggregation
- Multi-core sharding: 256 cores × 32 vectors = 8K total

### Spiking Neural Network (SNN)
- LIF (Leaky Integrate-and-Fire) neurons with membrane dynamics
- STDP (Spike-Timing Dependent Plasticity) learning
- Spike propagation through graph topology
- HNSW→SNN bridge for similarity-driven neural activation

### Novel Neuromorphic Features (v2.3)
- Spike-Timing Vector Encoding (rate-to-time conversion)
- Homeostatic Plasticity (self-stabilizing thresholds)
- Oscillatory Resonance (40Hz gamma synchronization)
- Winner-Take-All Circuits (competitive selection)
- Dendritic Computation (nonlinear branch integration)
- Temporal Pattern Recognition (spike history matching)
- Combined Neuromorphic Search pipeline

### Performance Optimizations
- 5.5x faster SNN tick (2,726ns → 499ns)
- 18% faster STDP learning
- Pre-computed reciprocal constants
- Division elimination in hot paths

### Documentation & Organization
- Reorganized docs into subdirectories (gnn/, implementation/, publishing/, status/)
- Added comprehensive README with badges, SEO, citations
- Added benchmark.js and test_wasm.js test suites
- Added DEEP_REVIEW.md with performance analysis
- Added Verilog RTL for ASIC synthesis

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

---------

Co-authored-by: Claude <noreply@anthropic.com>
2025-12-01 22:30:15 -05:00

5 KiB

NPM Package Ready for Publishing

Date: 2025-11-21 Status: ALL TESTS PASSING - READY FOR PUBLICATION

📦 Package Verification Summary

Platform Package: @ruvector/core-linux-x64-gnu

Location: /workspaces/ruvector/npm/core/platforms/linux-x64-gnu

Package Contents (Verified):

npm notice 📦  @ruvector/core-linux-x64-gnu@0.1.1
npm notice === Tarball Contents ===
npm notice 272B  README.md
npm notice 330B  index.js
npm notice 612B  package.json
npm notice 4.5MB ruvector.node
npm notice === Tarball Details ===
npm notice package size:  1.9 MB (compressed)
npm notice unpacked size: 4.5 MB
npm notice total files:   4

Test Results (4/4 Passed)

Test 1: File Structure

  • index.js (0.32 KB) - Module loader
  • ruvector.node (4.27 MB) - Native binary
  • package.json (0.60 KB) - Package configuration
  • README.md (0.27 KB) - Documentation

Test 2: Module Loading

  • Native module loads successfully
  • Exports available: hello, version, JsDistanceMetric, VectorDb

Test 3: Database Creation

  • VectorDb instance created successfully
  • Constructor accepts configuration options
  • No initialization errors

Test 4: Basic Operations

  • Insert: Vector inserted with ID test_vector
  • Count: Returns correct count (1 vector)
  • Search: Returns 1 result with perfect score (0.000000)
  • Delete: Successfully deletes vector (returns true)

🎯 Verified API Methods

Constructor

const db = new VectorDb({
  dimensions: 3,
  maxElements: 100,
  storagePath: '/path/to/db.db'
});

Insert (async)

const id = await db.insert({
  id: 'my-id',
  vector: new Float32Array([0.1, 0.2, 0.3])
});

Search (async)

const results = await db.search({
  vector: new Float32Array([0.1, 0.2, 0.3]),
  k: 10
});

Count (async)

const count = await db.len();

Delete (async)

const deleted = await db.delete('my-id');

📋 Configuration Details

package.json

{
  "name": "@ruvector/core-linux-x64-gnu",
  "version": "0.1.1",
  "main": "index.js",
  "type": "commonjs",
  "os": ["linux"],
  "cpu": ["x64"],
  "files": [
    "index.js",
    "ruvector.node",
    "*.node",
    "README.md"
  ]
}

index.js (Loader)

const { join } = require('path');

let nativeBinding;
try {
  nativeBinding = require('./ruvector.node');
} catch (error) {
  throw new Error(
    'Failed to load native binding for linux-x64-gnu. ' +
    'This package may have been installed incorrectly. ' +
    'Error: ' + error.message
  );
}

module.exports = nativeBinding;

🚀 Ready to Publish

Prerequisites Complete

  • Native binary built and included (4.3MB)
  • Package.json correctly configured
  • Module loader working
  • All tests passing
  • API methods verified
  • npm pack shows correct size (4.5MB unpacked, 1.9MB compressed)

Publishing Command

cd /workspaces/ruvector/npm/core/platforms/linux-x64-gnu
npm login
npm publish --access public

📊 Performance Metrics

  • Binary Size: 4.3 MB uncompressed
  • Package Size: 1.9 MB compressed (56% compression)
  • Insert Performance: Tested with 3D vectors
  • Search Accuracy: Perfect match returns 0.0 distance
  • Node.js Version: >= 18 (as specified in engines)

Main Package: @ruvector/core

  • Platform detection and auto-loading
  • TypeScript definitions
  • Unified API across platforms

Other Platform Packages

  • @ruvector/core-linux-arm64-gnu (pending)
  • @ruvector/core-darwin-x64 (pending)
  • @ruvector/core-darwin-arm64 (pending)
  • @ruvector/core-win32-x64-msvc (pending)

🎓 Key Learnings

  1. NAPI-RS Async Methods: All database operations are async (return Promises)
  2. API Differences: Method names differ from FFI bindings:
    • count()len()
    • Parameters passed as objects, not positional
  3. Storage Locking: Each database instance needs unique storage path
  4. Module Loading: Loader handles missing binary with clear error message
  5. File Inclusion: Explicit listing in files array required for binaries

Success Criteria Met

  • Native binary included in package
  • Binary loads without errors
  • Database can be created
  • Insert operations work
  • Search operations work
  • Delete operations work
  • Count operations work
  • API matches documentation
  • npm pack shows correct size
  • All tests automated and passing

📝 Next Steps

  1. Publish linux-x64-gnu (current platform)
  2. Build and test other platforms via GitHub Actions
  3. Publish all platform packages
  4. Publish main @ruvector/core package
  5. Test cross-platform installation

Test Script: /workspaces/ruvector/npm/core/test-package.cjs Package Directory: /workspaces/ruvector/npm/core/platforms/linux-x64-gnu Publishing Guide: /workspaces/ruvector/docs/NPM_PUBLISHING.md

🎉 Package is production-ready and verified!