ruvector/docs/status/READY-TO-PUBLISH.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

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
[![npm version](https://badge.fury.io/js/psycho-symbolic-integration.svg)](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

npm version

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

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 public flag 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