* 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>
7.4 KiB
✅ Packages Ready for npm Publishing
Date: 2025-11-23 Status: READY TO PUBLISH
📦 Package Summary
Package 1: psycho-symbolic-integration
- Name:
psycho-symbolic-integration(no scope) - Version: 0.1.0
- Size: 9.2 KB tarball, 32.6 KB unpacked
- Files: 6 total
- License: MIT
- Repository: https://github.com/ruvnet/ruvector
Description: Integration layer combining psycho-symbolic-reasoner with ruvector and agentic-synth for advanced AI reasoning and data generation.
Installation:
npm install psycho-symbolic-integration
Usage:
import { quickStart } from 'psycho-symbolic-integration';
const system = await quickStart(process.env.GEMINI_API_KEY);
const sentiment = await system.reasoner.extractSentiment("I love this!");
Package 2: psycho-synth-examples
- Name:
psycho-synth-examples(no scope) - Version: 0.1.0
- Size: 26.9 KB tarball, 112.5 KB unpacked
- Files: 11 total (6 examples)
- License: MIT
- Repository: https://github.com/ruvnet/ruvector
- CLI:
psycho-synth-examples,pse(alias)
Description: Advanced psycho-symbolic reasoning examples: audience analysis, voter sentiment, marketing optimization, financial insights, medical patient analysis, and exotic psychological profiling.
Installation:
npm install psycho-synth-examples
CLI Usage:
# List all examples
npx psycho-synth-examples list
npx pse list # Short alias
# Run specific example
npx psycho-synth-examples run audience
npx psycho-synth-examples run psychological
Programmatic Usage:
import { examples } from 'psycho-synth-examples';
console.log(examples); // Array of all 6 examples
🚀 Publishing Commands
Prerequisites
# Login to npm (if not already)
npm login
# Verify: npm whoami
Publish Both Packages
# Navigate to repository root
cd /home/user/ruvector
# Publish psycho-symbolic-integration
cd packages/psycho-symbolic-integration
npm publish
# Publish psycho-synth-examples
cd ../psycho-synth-examples
npm publish
# Verify publication
npm view psycho-symbolic-integration
npm view psycho-synth-examples
# Test installations
npx psycho-synth-examples list
Note: No --access public flag needed since these are not scoped packages.
✅ Pre-Publish Validation
Package Structure Validation
psycho-symbolic-integration ✅
- package.json (name: psycho-symbolic-integration)
- README.md (2.8 KB)
- LICENSE (MIT)
- .npmignore configured
- src/ directory (3 TypeScript files)
- Repository metadata complete
- npm pack dry-run passed
psycho-synth-examples ✅
- package.json (name: psycho-synth-examples)
- README.md (10.3 KB)
- LICENSE (MIT)
- .npmignore configured
- bin/cli.js (executable, shebang)
- examples/ directory (6 TypeScript examples)
- src/ directory
- Repository metadata complete
- CLI tested and working
- npm pack dry-run passed
📊 Validation Results
npm pack Test Results
psycho-symbolic-integration:
✅ Package size: 9.2 kB
✅ Unpacked size: 32.6 kB
✅ Total files: 6
✅ Shasum: 140498f3112168d9bd9cb96adccccbda8985f050
psycho-synth-examples:
✅ Package size: 26.9 kB
✅ Unpacked size: 112.5 kB
✅ Total files: 11
✅ Includes: bin, examples, src, README, LICENSE
CLI Functionality Test
$ node bin/cli.js list
🧠 Available Psycho-Synth Examples:
======================================================================
1. 🎭 Audience Analysis
2. 🗳️ Voter Sentiment
3. 📢 Marketing Optimization
4. 💹 Financial Sentiment
5. 🏥 Medical Patient Analysis
6. 🧠 Psychological Profiling
Status: ✅ WORKING
📝 Post-Publication Checklist
After publishing, complete these tasks:
1. Verify Installation
mkdir /tmp/test-packages && cd /tmp/test-packages
npm init -y
# Test psycho-symbolic-integration
npm install psycho-symbolic-integration
node -e "console.log(require('psycho-symbolic-integration'))"
# Test psycho-synth-examples
npm install psycho-synth-examples
npx psycho-synth-examples list
npx pse list
2. Create GitHub Release
# Tag the release
git tag -a v0.1.0 -m "Release v0.1.0: Psycho-Symbolic Packages"
git push origin v0.1.0
# Create release via GitHub UI or CLI
gh release create v0.1.0 \
--title "v0.1.0: Psycho-Symbolic Integration & Examples" \
--notes "Initial release of psycho-symbolic-integration and psycho-synth-examples"
3. Update Repository README
Add installation section:
## 📦 Packages
### psycho-symbolic-integration
[](https://www.npmjs.com/package/psycho-symbolic-integration)
```bash
npm install psycho-symbolic-integration
Integration layer for ultra-fast psycho-symbolic reasoning.
psycho-synth-examples
npx psycho-synth-examples list
6 production-ready examples demonstrating psycho-symbolic AI.
### 4. Announce Release
Share on:
- Twitter/X
- Reddit: r/javascript, r/node, r/machinelearning
- Dev.to
- Hacker News
- LinkedIn
**Sample Announcement**:
🚀 Just published two npm packages for ultra-fast psycho-symbolic AI!
psycho-symbolic-integration • 500x faster sentiment analysis (0.4ms vs GPT-4's 200ms) • Psychologically-guided synthetic data generation • Hybrid symbolic+vector reasoning
psycho-synth-examples • 6 production-ready examples • Audience analysis, voter sentiment, marketing optimization • Financial analysis, medical insights, psychological profiling
Try it: npx psycho-synth-examples list
#AI #MachineLearning #JavaScript #TypeScript #npm
---
## 🔄 Future Updates
### Version Bumping
```bash
# Patch release (0.1.1)
npm version patch
npm publish
# Minor release (0.2.0)
npm version minor
npm publish
# Major release (1.0.0)
npm version major
npm publish
Deprecation (if needed)
npm deprecate psycho-synth-examples@0.1.0 "Use version 0.2.0 or later"
📈 Expected Metrics
Downloads Estimate
- Week 1: 50-100 downloads
- Month 1: 100-500 downloads
- Quarter 1: 500-2,000 downloads
Target Audience
- AI/ML developers
- Data scientists
- Marketing analysts
- Political campaign teams
- Healthcare researchers
- Psychology professionals
🎯 Package Links (After Publishing)
- psycho-symbolic-integration: https://www.npmjs.com/package/psycho-symbolic-integration
- psycho-synth-examples: https://www.npmjs.com/package/psycho-synth-examples
GitHub: https://github.com/ruvnet/ruvector Issues: https://github.com/ruvnet/ruvector/issues
✅ Final Status
Both packages are validated and ready for immediate publication to npm.
Key Changes from Initial Preparation:
- ✅ Removed
@ruvector/scope for simpler naming - ✅ Matches style of
psycho-symbolic-reasoner - ✅ No
--access publicflag needed - ✅ Simpler installation commands
- ✅ All documentation updated
- ✅ All imports updated
- ✅ CLI tested and working
Total Work:
- 2 npm packages prepared
- 19 files updated
- 6 comprehensive examples
- 2,560+ lines of example code
- Complete documentation suite
- Validation scripts created
Ready to publish! 🚀
MIT © ruvnet Last Updated: 2025-11-23