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Ruvnet Ecosystem Downloader & Artifacts

πŸ“Š Repository Stats: 486 total artifacts | 159 Rust crates | 162 NPM packages | 165 GitHub repositories

This repository provides tools to automatically discover, download, and manage the complete Ruvnet ecosystem across multiple platforms. It's a comprehensive collection of production-grade packages for AI agents, robotics, financial trading, distributed systems, and advanced computation.

πŸ“š Documentation

  • Complete Ecosystem Guide - Comprehensive documentation with detailed package descriptions, performance metrics, and integration patterns
  • This README provides quick-start instructions and an overview

Repository Structure

ruv_downloads/
β”œβ”€β”€ crates/                    # 159 Rust crates
β”‚   β”œβ”€β”€ download_ruvnet_crates.sh
β”‚   └── crates.dynamic.txt     # Auto-maintained manifest
β”‚
β”œβ”€β”€ npmjs/                     # 162 NPM packages  
β”‚   β”œβ”€β”€ download_ruvnet_packages.sh
β”‚   └── packagelist.dynamic.txt
β”‚
β”œβ”€β”€ github/                    # 165 GitHub repositories
β”‚   β”œβ”€β”€ download_ruvnet_repos.sh
β”‚   β”œβ”€β”€ repos.dynamic.txt
β”‚   └── by-tier/              # Organized by development tier
β”‚
β”œβ”€β”€ 00_crates/                # Rust .crate archives
β”‚   └── legacy_crates/        # Previous versions
β”‚
└── 00_tgz/                   # NPM .tgz archives
    └── legacy_tgz/           # Previous versions

Key Features

  • πŸ” Automatic Discovery: Queries NPM registry, Crates.io, and GitHub API to find new ruvnet packages
  • πŸ“¦ Version Management: Keeps only the latest version in main directory, archives older versions
  • πŸ”„ Incremental Updates: Smart update strategy checks remote hashes before downloading
  • πŸ“‚ Auto-Extraction: Automatically unpacks archives for easy code inspection
  • πŸ“ Manifest-Driven: Single source of truth via dynamic .txt manifests
  • 🎯 Multi-Platform: Darwin, Linux, Windows support (x64, ARM64)

Quick Start

🌍 All-In-One: RUV WORLD Script

The easiest way to download and update everything:

# Run centralized script (discovers and downloads all artifacts)
./ruv_world.sh

# This will:
# 1. Download/update all Rust crates
# 2. Download/update all NPM packages
# 3. Download/update all GitHub repositories
# 4. Auto-update documentation if counts change

Features:

  • 🎨 Colorful progress output
  • πŸ“Š Change detection and reporting
  • πŸ“ Automatic documentation updates
  • ⚑ Single command for everything

Options:

./ruv_world.sh --no-discover      # Update existing only (no discovery)
./ruv_world.sh --no-update-docs   # Skip documentation updates
./ruv_world.sh --help             # Show help

Manual: Download All Artifacts

# Navigate to repository
cd ruv_downloads

# Discover and download all Rust crates
./crates/download_ruvnet_crates.sh --discover

# Discover and download all NPM packages
./npmjs/download_ruvnet_packages.sh --discover

# Discover and download all GitHub repositories
./github/download_ruvnet_repos.sh --discover

# Verify downloads
cat crates/crates.dynamic.txt | wc -l      # Should be ~159
cat npmjs/packagelist.dynamic.txt | wc -l  # Should be ~162
cat github/repos.dynamic.txt | wc -l       # Should be ~165

Update Existing Artifacts

# Update Rust crates (no --discover flag)
./crates/download_ruvnet_crates.sh

# Update NPM packages
./npmjs/download_ruvnet_packages.sh

# Update GitHub repositories (incremental)
./github/download_ruvnet_repos.sh

Ecosystem Highlights

Agentic Systems

  • agentic-jujutsu - Lock-free version control for AI agents (350 ops/s, 23x faster than Git)
  • agentic-robotics-core - ROS2-compatible robotics middleware (<1Β΅s latency, 10x faster)
  • agentic-payments - Dual-protocol payment infrastructure (10k+ TPS)

AI Security & Defense

  • aimds-detection - Real-time threat detection (<10ms latency)
  • aimds-analysis - Behavioral analysis with LTL verification (<520ms)

Vector Databases

  • ruvector-core - High-performance HNSW indexing (1M vectors, <5ms search)
  • ruvector-gnn - Graph neural network integration (10x compression)

Neural Trading

  • nt-core - Neural trading system foundation
  • nt-backtesting - Historical backtesting engine (100x real-time)

Distributed Systems

  • qudag - Quantum-resistant DAG consensus (100k+ ops/sec, <100ms finality)
  • qudag-crypto - Post-quantum cryptography (ML-DSA, ML-KEM)

Performance Highlights

System Metric Value
agentic-robotics-core Pub/sub latency <1 Β΅s
aimds-detection Threat detection <10ms
ruvector Search latency <5ms (p99)
qudag Consensus latency <100ms
agentic-jujutsu Concurrent commits 350 ops/s

Usage Examples

Using Individual Rust Crates

# Add to your Cargo.toml
cargo add agentic-robotics-core
cargo add ruvector-core
cargo add qudag

# Use in Rust code
use agentic_robotics_core::Node;
let node = Node::new("robot")?;

Using Individual NPM Packages

# Install from local directory
npm install ./npmjs/agentic-robotics-2.1.5

# Import in TypeScript/JavaScript
import { RoboticSystem } from 'agentic-robotics';
const robot = new RoboticSystem('warehouse-bot');

Archive Operations

# View downloaded .crate files
ls -lh 00_crates/*.crate | head -20

# View downloaded .tgz files  
ls -lh 00_tgz/*.tgz | head -20

# Check legacy archives
ls 00_crates/legacy_crates/
ls 00_tgz/legacy_tgz/

# Manually extract a crate
cd 00_crates && tar xzf qudag-1.4.0.crate

# Manually extract an NPM package
cd 00_tgz && tar xzf neural-trader-2.6.3.tgz

Contributing

This repository automatically tracks the Ruvnet ecosystem. To add packages to the manifests, use the --discover flag which queries the registries.

License

MIT/Apache-2.0 (dual) - See individual package licenses


Last Updated: December 16, 2025 Maintained by: Ruvnet Community
Complete Documentation: RUV_DOWNLOADS_COMPLETE_GUIDE.md

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