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Claude 85eb5c6e53 feat(dag): implement Neural Self-Learning DAG with QuDAG integration 
Complete implementation of the Neural DAG Learning system combining RuVector
vector database with QuDAG quantum-resistant consensus.

Core Features:
- QueryDag structure with HashMap-based adjacency and cycle detection
- 18+ operator types (SeqScan, HnswScan, HashJoin, NestedLoop, etc.)
- Topological, DFS, and BFS traversal iterators
- JSON/binary serialization

Attention Mechanisms (7 total):
- Basic: Topological, CausalCone, CriticalPath, MinCutGated
- Advanced: HierarchicalLorentz, ParallelBranch, TemporalBTSP
- UCB bandit selector for automatic mechanism selection
- LRU attention cache with 10k entry default

SONA (Self-Optimizing Neural Architecture):
- MicroLoRA adaptation (<100μs, rank-2)
- TrajectoryBuffer with lock-free ArrayQueue (10k capacity)
- ReasoningBank with K-means++ clustering
- EWC++ for catastrophic forgetting prevention (λ=5000)

MinCut Optimization:
- O(n^0.12) subpolynomial amortized updates
- Local k-cut approximation for sublinear bottleneck detection
- Criticality-based flow computation
- Redundancy analysis and repair suggestions

Self-Healing System:
- Z-score anomaly detection with adaptive thresholds
- Index health monitoring (HNSW/IVFFlat metrics)
- Learning drift detection with ADWIN algorithm
- Repair strategies: reindex, parameter tuning, learning reset

QuDAG Integration:
- ML-KEM-768 quantum-resistant encryption
- ML-DSA-65 quantum-resistant signatures
- Differential privacy (Laplace/Gaussian mechanisms)
- rUv token staking, rewards (5% APY), governance (67% threshold)

PostgreSQL Extension:
- GUC variables for configuration
- Planner/executor hooks for query interception
- Background worker for continuous learning
- 50+ SQL functions for all features

Testing:
- 46+ integration tests across all modules
- 11 benchmark groups for performance validation
- Test fixtures and data generators
- Mock QuDAG client for isolated testing

Documentation:
- Comprehensive README with architecture overview
- 5 example programs demonstrating all features
- Implementation notes for attention mechanisms

Total: ~12,000+ lines of new Rust code
2025-12-29 22:58:43 +00:00
..
api docs: Add Cypher reference, include Tiny Dancer, fix WASM build 2025-11-26 12:54:04 +00:00
architecture docs: Reorganize documentation and add postgres README 2025-12-02 16:45:44 +00:00
benchmarks feat(postgres): Add HNSW index and embedding functions support (#62) 2025-12-09 11:14:52 -05:00
cloud-architecture Implement global streaming optimization for 500M concurrent streams 2025-11-20 18:51:26 +00:00
dag docs(dag): add comprehensive Neural DAG Learning implementation plan 2025-12-29 22:15:55 +00:00
development feat(micro-hnsw-wasm): Add Neuromorphic HNSW v2.3 with SNN Integration (#40) 2025-12-01 22:30:15 -05:00
examples feat(nervous-system): Complete bio-inspired neural architecture implementation 2025-12-28 04:05:08 +00:00
gnn feat(micro-hnsw-wasm): Add Neuromorphic HNSW v2.3 with SNN Integration (#40) 2025-12-01 22:30:15 -05:00
guides feat(postgres): Add HNSW index and embedding functions support (#62) 2025-12-09 11:14:52 -05:00
hnsw docs: Reorganize documentation and add postgres README 2025-12-02 16:45:44 +00:00
hooks feat(cli): Implement full hooks system in Rust CLI 2025-12-27 01:08:36 +00:00
implementation feat(micro-hnsw-wasm): Add Neuromorphic HNSW v2.3 with SNN Integration (#40) 2025-12-01 22:30:15 -05:00
integration feat(micro-hnsw-wasm): Add Neuromorphic HNSW v2.3 with SNN Integration (#40) 2025-12-01 22:30:15 -05:00
nervous-system feat(nervous-system): Complete bio-inspired neural architecture implementation 2025-12-28 04:05:08 +00:00
optimization chore(docs): Clean up and reorganize documentation structure 2025-12-25 19:39:44 +00:00
plans/subpolynomial-time-mincut chore(docs): Clean up and reorganize documentation structure 2025-12-25 19:39:44 +00:00
postgres Feat/ruvector postgres v2 (#82) 2025-12-25 17:02:55 -05:00
project-phases Clean up repository structure and organize documentation 2025-11-20 19:50:03 +00:00
publishing feat(micro-hnsw-wasm): Add Neuromorphic HNSW v2.3 with SNN Integration (#40) 2025-12-01 22:30:15 -05:00
research chore(docs): Clean up and reorganize documentation structure 2025-12-25 19:39:44 +00:00
sql feat(postgres): Add ruvector-postgres extension with SIMD optimizations (#42) 2025-12-02 09:55:07 -05:00
testing Clean up repository structure and organize documentation 2025-11-20 19:50:03 +00:00
.gitkeep Clean up repository structure and organize documentation 2025-11-20 19:50:03 +00:00
algorithmic-optimization-analysis.md docs: Add performance optimization analysis reports 2025-12-26 17:41:13 +00:00
BTSP_IMPLEMENTATION.md feat(nervous-system): Complete bio-inspired neural architecture implementation 2025-12-28 04:05:08 +00:00
code-review-mincut-gated-transformer.md fix(security): Critical security and performance improvements 2025-12-26 16:25:02 +00:00
dendrite-implementation-summary.md feat(nervous-system): Complete bio-inspired neural architecture implementation 2025-12-28 04:05:08 +00:00
INDEX.md chore(docs): Clean up and reorganize documentation structure 2025-12-25 19:39:44 +00:00
mincut-transformer-memory-optimization-analysis.md docs: Add performance optimization analysis reports 2025-12-26 17:41:13 +00:00
nervous-system-eventbus-summary.md feat(nervous-system): Complete bio-inspired neural architecture implementation 2025-12-28 04:05:08 +00:00
qudag-token-implementation.md feat(dag): implement Neural Self-Learning DAG with QuDAG integration 2025-12-29 22:58:43 +00:00
README.md Clean up repository structure and organize documentation 2025-11-20 19:50:03 +00:00
REPO_STRUCTURE.md feat(micro-hnsw-wasm): Add Neuromorphic HNSW v2.3 with SNN Integration (#40) 2025-12-01 22:30:15 -05:00
simd-optimization-analysis.md docs: Add performance optimization analysis reports 2025-12-26 17:41:13 +00:00
SPECULATIVE_DECODING.md docs(mincut-transformer): Add examples and documentation for SOTA features 2025-12-26 19:55:06 +00:00
workspace-implementation-summary.md feat(nervous-system): Complete bio-inspired neural architecture implementation 2025-12-28 04:05:08 +00:00

README.md

RuVector Documentation

Complete documentation for RuVector, the high-performance Rust vector database with global scale capabilities.

📚 Documentation Structure

Getting Started

Quick start guides and tutorials for new users:

Architecture & Design

System architecture and design documentation:

API Reference

API documentation for different platforms:

User Guides

Comprehensive user guides:

Performance & Optimization

Performance tuning and benchmarking:

Development

Contributing and development guides:

Testing

Testing documentation and reports:

Project History

Historical project phase documentation:

Implementation Summary

🚀 Quick Links

For New Users

  1. Start with Getting Started Guide
  2. Try the Basic Tutorial
  3. Review API Documentation

For Cloud Deployment

  1. Read Architecture Overview
  2. Follow Deployment Guide
  3. Apply Performance Optimizations

For Contributors

  1. Read Contributing Guidelines
  2. Review Technical Plan
  3. Check Migration Guide

For Performance Tuning

  1. Review Optimization Guide
  2. Run Benchmarks
  3. Apply Query Optimizations

📊 Documentation Status

Category Files Status
Getting Started 7 ✅ Complete
Architecture 11 ✅ Complete
API Reference 2 ✅ Complete
User Guides 4 ✅ Complete
Optimization 4 ✅ Complete
Development 3 ✅ Complete
Testing 2 ✅ Complete
Project Phases 8 📚 Historical

Total Documentation: 40+ comprehensive documents

🔗 External Resources

Last Updated: 2025-11-20 | Version: 0.1.0 | Status: Production Ready