ArchiveNET

> Where AI memories live forever - A decentralized semantic memory platform powered by blockchain and vector search

ArchiveNET is a revolutionary decentralized memory management platform that combines the power of AI embeddings with blockchain permanence. Built on Arweave, it provides enterprise-grade semantic search capabilities through advanced vector database technology, enabling applications to store, search, and retrieve contextual information with unprecedented permanence and accuracy.

Key Features

• Semantic Memory: AI-powered contextual memory storage and retrieval
• Blockchain Persistence: Permanent storage on Arweave blockchain
• Vector Search: State-of-the-art HNSW algorithm for similarity search
• High Performance: O(log N) search complexity for millions of vectors
• Decentralized: No single point of failure or censorship
• Rich Metadata: Comprehensive metadata support for enhanced search
• Enterprise-Ready: Production-grade API with authentication and monitoring

Architecture

ArchiveNET is a comprehensive monorepo consisting of four main components:

Eizen - Vector Database Engine

The world's first decentralized vector engine built on Arweave blockchain, implementing the Hierarchical Navigable Small Worlds (HNSW) algorithm for approximate nearest neighbor search.

Key Features:

• HNSW algorithm with O(log N) complexity
• Blockchain-based persistence via HollowDB
• Protobuf encoding for efficient storage
• Database-agnostic interface
• Handles millions of high-dimensional vectors

API - Backend Service

A robust Express.js API service providing semantic memory management with AI-powered search capabilities.

Stack:

• Express.js with TypeScript
• Neon PostgreSQL with Drizzle ORM
• EizenDB for vector operations
• Redis for caching
• JWT authentication
• Comprehensive validation with Zod

Frontend - Web Interface

A modern Next.js application providing an intuitive interface for memory management and search operations.

Features:

• React-based UI with TypeScript
• Real-time search capabilities
• Memory visualization
• User dashboard
• Responsive design

Eva - MCP Agent

The central Model Context Protocol (MCP) server that orchestrates memory operations and provides intelligent context management.

Quick Start

Prerequisites

• Node.js 18+
• Docker & Docker Compose
• PostgreSQL database
• Redis server
• Arweave wallet

Installation

1. Clone the repository:

git clone https://github.com/s9swata/archivenet.git
   cd ArchiveNET

2. Start with Docker Compose:

docker-compose up -d

3. Manual setup (alternative):

# API Setup
   cd API
   npm install
   npm run build
   npx drizzle-kit push
   npm run dev

   # Frontend Setup
   cd ../client
   npm install
   npm run dev

### Configuration

Create `.env` files in respective directories:

**API/.env**:

DATABASE_URL=your_postgres_url

REDIS_URL=redis://localhost:6379

JWT_SECRET=your_jwt_secret

ARWEAVE_WALLET_PATH=./data/wallet.json

### API Integration

// Store a memory

const response = await fetch("/api/memories", {

method: "POST",

headers: { "Content-Type": "application/json" },

body: JSON.stringify({

content: "Project discussion about AI integration",

metadata: { project: "AI-Platform", priority: "high" },

}),

});

// Search memories

const searchResults = await fetch("/api/memories/search", {

method: "POST",

headers: { "Content-Type": "application/json" },

body: JSON.stringify({

query: "AI project discussions",

limit: 10,

}),

});

### Contributing

1. Fork the repository
2. Create a feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request

## Documentation

- [Developer Guide](./Docs/DEVELOPER_GUIDE.md) - Comprehensive API documentation
- [Backend Integration](./Docs/BACKEND_INTEGRATION_GUIDE.md) - Backend implementation examples
- [Eizen Engine](./Docs/Eizen.md) - Vector database engine details
- [HNSW Guide](./Docs/HNSW_GUIDE.md) - Algorithm implementation details

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

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**Made with ❤️ for the decentralized AI future**