SuperInstance Documentation

This directory contains comprehensive documentation for the SuperInstance ecosystem.

📚 Unified Documentation (mdBook)

The primary documentation is built with mdBook and provides a unified view of the entire ecosystem.

View Online

• GitHub Pages: https://superinstance.github.io/Tripartite1/ (when deployed)
• Local: See "Building Locally" below

Build Locally

# Install mdBook
cargo install mdbook

# Build the documentation
cd docs/book
mdbook build

# Serve with live reload
mdbook serve
# Visit http://localhost:3000

Documentation Structure

docs/book/
├── book.toml              # mdBook configuration
├── src/
│   ├── SUMMARY.md         # Table of contents
│   ├── README.md          # Introduction
│   ├── getting-started/   # Installation, quick start, overview
│   ├── ecosystem/         # Architecture and design
│   ├── crates/            # Individual crate docs (privox, tripartite-rs, etc.)
│   ├── integrations/      # Integration guides
│   ├── tutorials/         # Step-by-step tutorials
│   ├── reference/         # API reference, FAQ, contributing
│   └── appendix/          # Benchmarks, security, troubleshooting
└── book/                  # Built HTML output

🎯 Quick Navigation

Getting Started

1. Installation - Set up your environment
2. Quick Start - 5-minute tutorial
3. Ecosystem Overview - Understand the architecture

Core Crates

• privox - Privacy-first redaction for LLMs
• tripartite-rs - Multi-agent consensus
• knowledge-vault - Vector database & RAG
• hwscan - Hardware detection
• model-registry - Model management
• token-vault - Token storage
• quicunnel - QUIC tunnel
• usemeter - Usage metering

Integration Guides

• Integration Patterns - Common patterns
• Building CLI Apps - CLI applications
• Building Web Services - Web services
• Building Desktop Apps - Desktop applications

Tutorials

• Privacy-First LLM - Build privacy-aware LLM apps
• Multi-Agent System - Multi-agent AI systems
• RAG Application - Retrieval-augmented generation
• Hardware-Aware Models - Hardware detection
• Full-Stack App - Complete application

📖 Legacy Documentation

The following directories contain older documentation that is being migrated to mdBook:

• tutorials/ - Step-by-step tutorials
• guides/ - In-depth guides
• reference/ - Reference material
• contributing/ - Contributing guidelines
• api/ - API documentation
• architecture/ - Architecture documentation

Note: These are being migrated to the unified mdBook. Please check mdBook first for current information.

🚀 Learning Paths

Beginner (New to the Ecosystem)

1. Installation
2. Quick Start
3. Your First Project
4. Tutorial: Privacy-First LLM

Intermediate (Familiar with Rust)

1. Ecosystem Overview
2. Core Crates
3. Integration Patterns
4. Tutorial: Multi-Agent System

Advanced (Building Production Apps)

1. Architecture
2. Design Principles
3. API Reference
4. Performance Benchmarks

🛠️ Contributing

Found a typo? Missing information? We welcome improvements!

Quick Fixes

1. Edit the markdown file in docs/book/src/
2. Rebuild: cd docs/book && mdbook build
3. Submit a PR

Larger Changes

1. Check existing issues with documentation label
2. Follow the Documentation Guide
3. Test all code examples
4. Ensure mdbook build succeeds

Documentation Standards

• ✅ Use clear, concise language
• ✅ Include runnable code examples
• ✅ Add links to related topics
• ✅ Test all examples before submitting
• ✅ Build documentation before committing

🔧 Building and Testing

Build Documentation

cd docs/book
mdbook build

Test Locally

cd docs/book
mdbook serve
# Visit http://localhost:3000

Check Links

cargo install mdbook-linkcheck
cd docs/book
mdbook build

📦 Automatic Deployment

The documentation is automatically built and deployed to GitHub Pages:

• Trigger: Push to main branch
• Path filter: docs/book/**
• Workflow: .github/workflows/docs.yml

See the workflow file for details.

🌐 External Resources

Rust Documentation

• The Rust Programming Language
• Rust by Example
• API Guidelines

AI/ML Resources

• Awesome Rust Machine Learning
• Burn Framework - Deep learning in Rust
• Candle - ML framework by Hugging Face

💬 Getting Help

Still have questions?

• GitHub Issues: Post a question
• GitHub Discussions: Start a discussion
• FAQ: Common questions
• Troubleshooting: Solve problems

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Documentation Version: v0.2.0 Last Updated: 2026-01-08 Maintained By: SuperInstance Team