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WebRTC P2P Implementation: - Add webrtc.js with WebRTCPeerManager and WebRTCPeerConnection classes - Real WebRTC data channels with ICE/STUN/TURN support - Automatic reconnection with exponential backoff - Heartbeat monitoring (5s interval, 15s timeout) - Connection quality metrics (latency, throughput) - Fallback to simulation mode when signaling unavailable Signaling Server: - Add WebRTC signaling handlers (offer/answer/ice/disconnect) - Update origin validation for Node.js test connections - Rate limiting: 100 msg/min per node - Message size limits: 64KB max - Connection limits: 5 per IP Genesis Nodes (Google Cloud): - us-central1: edge-net-genesis-us.ruvector.dev - europe-west1: edge-net-genesis-eu.ruvector.dev - asia-east1: edge-net-genesis-asia.ruvector.dev Browser Integration: - Update join.html with real WebRTC data channels - Direct peer-to-peer communication via RTCPeerConnection - DTLS encryption for data channel security Testing & Benchmarks: - webrtc-p2p-test.js: Connectivity testing - security-audit.js: 8 security tests (rate limiting, injection, etc.) - benchmark-latency.js: Signaling and P2P latency measurement Documentation: - Add comprehensive WebRTC section to README.md - Document security features, testing, and browser integration 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> |
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| apify | ||
| docs | ||
| edge | ||
| edge-full/pkg | ||
| edge-net | ||
| exo-ai-2025 | ||
| google-cloud | ||
| graph | ||
| meta-cognition-spiking-neural-network | ||
| mincut | ||
| neural-trader | ||
| nodejs | ||
| onnx-embeddings | ||
| onnx-embeddings-wasm | ||
| refrag-pipeline | ||
| rust | ||
| ruvLLM | ||
| scipix | ||
| spiking-network | ||
| subpolynomial-time | ||
| ultra-low-latency-sim | ||
| wasm/ios | ||
| wasm-react | ||
| wasm-vanilla | ||
| bounded_instance_demo.rs | ||
| README.md | ||
RuVector Examples
Comprehensive examples demonstrating RuVector's capabilities across multiple platforms and use cases.
Directory Structure
examples/
├── rust/ # Rust SDK examples
├── nodejs/ # Node.js SDK examples
├── graph/ # Graph database features
├── wasm-react/ # React + WebAssembly integration
├── wasm-vanilla/ # Vanilla JS + WebAssembly
├── agentic-jujutsu/ # AI agent version control
├── exo-ai-2025/ # Advanced cognitive substrate
├── refrag-pipeline/ # Document processing pipeline
└── docs/ # Additional documentation
Quick Start by Platform
Rust
cd rust
cargo run --example basic_usage
cargo run --example advanced_features
cargo run --example agenticdb_demo
Node.js
cd nodejs
npm install
node basic_usage.js
node semantic_search.js
WebAssembly (React)
cd wasm-react
npm install
npm run dev
WebAssembly (Vanilla)
cd wasm-vanilla
# Open index.html in browser
Example Categories
| Category | Directory | Description |
|---|---|---|
| Core API | rust/basic_usage.rs |
Vector DB fundamentals |
| Batch Ops | rust/batch_operations.rs |
High-throughput ingestion |
| RAG Pipeline | rust/rag_pipeline.rs |
Retrieval-Augmented Generation |
| Advanced | rust/advanced_features.rs |
Hypergraphs, neural hashing |
| AgenticDB | rust/agenticdb_demo.rs |
AI agent memory system |
| GNN | rust/gnn_example.rs |
Graph Neural Networks |
| Graph | graph/ |
Cypher queries, clustering |
| Node.js | nodejs/ |
JavaScript integration |
| WASM React | wasm-react/ |
Modern React apps |
| WASM Vanilla | wasm-vanilla/ |
Browser without framework |
| Agentic Jujutsu | agentic-jujutsu/ |
Multi-agent version control |
| EXO-AI 2025 | exo-ai-2025/ |
Cognitive substrate research |
| Refrag | refrag-pipeline/ |
Document fragmentation |
Feature Highlights
Vector Database Core
- High-performance similarity search
- Multiple distance metrics (Cosine, Euclidean, Dot Product)
- Metadata filtering
- Batch operations
Advanced Features
- Hypergraph Index: Multi-entity relationships
- Temporal Hypergraph: Time-aware relationships
- Causal Memory: Cause-effect chains
- Learned Index: ML-optimized indexing
- Neural Hash: Locality-sensitive hashing
- Topological Analysis: Persistent homology
AgenticDB
- Reflexion episodes (self-critique)
- Skill library (consolidated patterns)
- Causal memory (hypergraph relationships)
- Learning sessions (RL training data)
- Vector embeddings (core storage)
EXO-AI Cognitive Substrate
- exo-core: IIT consciousness, thermodynamics
- exo-temporal: Causal memory coordination
- exo-hypergraph: Topological structures
- exo-manifold: Continuous deformation
- exo-exotic: 10 cutting-edge experiments
- exo-wasm: Browser deployment
- exo-federation: Distributed consensus
- exo-node: Native bindings
- exo-backend-classical: Classical compute
Running Benchmarks
# Rust benchmarks
cargo bench --example advanced_features
# Refrag pipeline benchmarks
cd refrag-pipeline
cargo bench
# EXO-AI benchmarks
cd exo-ai-2025
cargo bench
Related Documentation
License
MIT OR Apache-2.0