* 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>
7.2 KiB
macOS Package Setup Complete
Date: 2025-11-21 Status: ✅ Package structure ready, awaiting binary builds
📦 macOS Packages Configured
@ruvector/core-darwin-x64 (Intel Macs)
Location: /workspaces/ruvector/npm/core/platforms/darwin-x64
Contents:
- ✅ index.js (327B) - Module loader
- ✅ package.json (603B) - Package configuration
- ✅ README.md (876B) - Documentation
- ⏳ ruvector.node - Needs to be built via GitHub Actions
@ruvector/core-darwin-arm64 (Apple Silicon)
Location: /workspaces/ruvector/npm/core/platforms/darwin-arm64
Contents:
- ✅ index.js (329B) - Module loader
- ✅ package.json (627B) - Package configuration
- ✅ README.md (910B) - Documentation
- ⏳ ruvector.node - Needs to be built via GitHub Actions
🔧 Package Configuration
darwin-x64 package.json
{
"name": "@ruvector/core-darwin-x64",
"version": "0.1.1",
"main": "index.js",
"os": ["darwin"],
"cpu": ["x64"],
"files": [
"index.js",
"ruvector.node",
"*.node",
"README.md"
]
}
darwin-arm64 package.json
{
"name": "@ruvector/core-darwin-arm64",
"version": "0.1.1",
"main": "index.js",
"os": ["darwin"],
"cpu": ["arm64"],
"files": [
"index.js",
"ruvector.node",
"*.node",
"README.md"
]
}
🚀 Building macOS Binaries
Option 1: GitHub Actions (Recommended)
The multi-platform build workflow is already configured in .github/workflows/build-native.yml.
Trigger the workflow:
# Commit current changes
git add .
git commit -m "feat: Add macOS package configuration"
# Push to main branch (triggers workflow)
git push origin main
# Or manually trigger via GitHub Actions UI
Workflow will:
- Build on macOS-13 (Intel) for darwin-x64
- Build on macOS-14 (Apple Silicon) for darwin-arm64
- Upload artifacts to GitHub
- Binaries will be at:
npm/packages/core/native/{darwin-x64,darwin-arm64}/ruvector.node
Option 2: Local Build (Requires macOS)
If you have access to a Mac:
For Intel Macs (darwin-x64):
cd npm/packages/core
npm install
npm run build:napi -- --target x86_64-apple-darwin
# Binary will be in: native/darwin-x64/ruvector.node
For Apple Silicon (darwin-arm64):
cd npm/packages/core
npm install
npm run build:napi -- --target aarch64-apple-darwin
# Binary will be in: native/darwin-arm64/ruvector.node
📋 After Binaries Are Built
1. Copy Binaries to Platform Packages
# For darwin-x64
cp npm/packages/core/native/darwin-x64/ruvector.node \
npm/core/platforms/darwin-x64/
# For darwin-arm64
cp npm/packages/core/native/darwin-arm64/ruvector.node \
npm/core/platforms/darwin-arm64/
2. Verify Package Contents
# darwin-x64
cd npm/core/platforms/darwin-x64
npm pack --dry-run
# darwin-arm64
cd npm/core/platforms/darwin-arm64
npm pack --dry-run
Expected output (similar to linux-x64-gnu):
npm notice 📦 @ruvector/core-darwin-x64@0.1.1
npm notice === Tarball Contents ===
npm notice 876B README.md
npm notice 327B index.js
npm notice 603B package.json
npm notice 4.5MB ruvector.node
npm notice === Tarball Details ===
npm notice package size: 1.9 MB
npm notice unpacked size: 4.5 MB
npm notice total files: 4
3. Test Package (On macOS)
# Copy test script
cp npm/core/test-package.cjs npm/core/platforms/darwin-x64/test.cjs
# OR
cp npm/core/test-package.cjs npm/core/platforms/darwin-arm64/test.cjs
# Update platformDir in test script to current directory
sed -i 's|platforms/linux-x64-gnu|.|' test.cjs
# Run tests
node test.cjs
4. Publish to npm
# darwin-x64
cd npm/core/platforms/darwin-x64
npm publish --access public
# darwin-arm64
cd npm/core/platforms/darwin-arm64
npm publish --access public
🎯 Current Status
Package Structure: ✅ Complete
- index.js loaders created
- package.json configured correctly
- README.md documentation added
- Files array includes ruvector.node
- Platform constraints set (os, cpu)
Binary Building: ⏳ Pending
- darwin-x64 binary needs to be built
- darwin-arm64 binary needs to be built
- Binaries need to be copied to platform directories
- Package contents need to be verified with npm pack
Testing: ⏳ Pending Binary Build
- darwin-x64 package needs testing on Intel Mac
- darwin-arm64 package needs testing on Apple Silicon
- All 4 test suites need to pass
Publishing: ⏳ Pending Testing
- darwin-x64 publish to npm
- darwin-arm64 publish to npm
🔗 Related Packages
Already Published
- ✅ @ruvector/core-linux-x64-gnu - Ready for publishing
Also Need Binaries
- ⏳ @ruvector/core-linux-arm64-gnu - Awaiting build
- ⏳ @ruvector/core-win32-x64-msvc - Awaiting build
📝 GitHub Actions Workflow Details
Workflow File: .github/workflows/build-native.yml
macOS Build Configuration:
- host: macos-13
target: x86_64-apple-darwin
build: npm run build:napi -- --target x86_64-apple-darwin
platform: darwin-x64
- host: macos-14
target: aarch64-apple-darwin
build: npm run build:napi -- --target aarch64-apple-darwin
platform: darwin-arm64
Workflow Triggers:
- Push to main branch
- Pull requests to main
- Manual trigger via
workflow_dispatch - Git tags matching
v*
Artifacts:
- Name:
bindings-darwin-x64 - Name:
bindings-darwin-arm64 - Path:
npm/packages/core/native/{platform}/
🎓 Key Differences: macOS vs Linux
Similarities
- Same API (VectorDb, async methods)
- Same package structure (index.js loader + binary)
- Same Node.js version requirement (>= 18)
- Similar binary size (~4.3MB)
Differences
- Platform constraint:
os: ["darwin"](not "linux") - CPU variants: x64 (Intel) vs arm64 (Apple Silicon)
- Build hosts: macOS-13 (Intel) vs macOS-14 (ARM)
- File paths: May differ in temp directory handling
✅ Verification Checklist
Before publishing macOS packages, verify:
- Binary exists:
ls -lh npm/core/platforms/darwin-x64/ruvector.node - Binary size: Should be ~4.3MB
- npm pack shows 4 files (index.js, package.json, README.md, ruvector.node)
- Package size: ~4.5MB unpacked, ~1.9MB compressed
- Test script passes all 4 tests
- Module loads without errors
- Database operations work (insert, search, count, delete)
🚨 Important Notes
- Cannot build on Linux: macOS binaries must be built on macOS runners
- Two macOS versions needed: macos-13 for Intel, macos-14 for ARM
- Platform detection: npm will auto-select correct package based on os/cpu
- Universal binaries: Not used - separate packages for Intel and ARM
- Testing required: Each platform must be tested on actual hardware
📚 Next Steps
- Trigger GitHub Actions - Push changes to build binaries
- Download artifacts - Get binaries from workflow run
- Copy to packages - Move binaries to platform directories
- Verify with npm pack - Ensure binaries are included
- Test on macOS - Run test suite on both Intel and ARM Macs
- Publish to npm - Make packages available
Package Structure: ✅ Complete and ready Binary Build: ⏳ Awaiting GitHub Actions workflow Testing: ⏳ Pending binary availability Publishing: ⏳ Pending testing completion