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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