src/index.qmd

# Kashi Coding Handbook

Welcome to the **Kashi Coding Handbook** – your comprehensive guide to building AI-powered CLI tools with Python using modern development practices.

## What You'll Learn

This handbook teaches you how to build professional command-line interface (CLI) applications enhanced with artificial intelligence capabilities. You'll learn:

- **Modern Python Development**: Using pixi for package management and GitHub Copilot for AI-assisted coding
- **CLI Development**: Building robust command-line tools with Typer and Rich
- **AI Integration**: Incorporating LLMs using HuggingFace, Docker Model Runner, and MCP servers
- **Production Practices**: Testing, code quality, and publishing to PyPI
- **Real-World Applications**: Complete project examples demonstrating all concepts

## Who This Is For

This handbook is designed for developers with basic Python knowledge who want to:

- Build practical CLI tools for automation and productivity
- Integrate AI/LLM capabilities into their applications
- Learn modern Python development workflows
- Deploy and publish professional-grade packages

## Prerequisites

Before starting, you should have:

- Basic Python syntax knowledge (variables, functions, loops, conditionals)
- Ability to run Python scripts from the command line
- Basic understanding of files and directories
- Familiarity with text editors or IDEs

## How to Use This Handbook

The handbook is organized into **7 chapters** that build upon each other:

1. **Foundation Setup** - Development environment and project structure
2. **CLI Development** - Building command-line interfaces with Typer
3. **AI Integration** - Adding LLM capabilities with multiple deployment options
4. **Advanced Features** - Interactive elements and batch processing
5. **Testing & Quality** - Writing tests and maintaining code quality
6. **Publishing** - Preparing and publishing packages to PyPI
7. **Real-World Projects** - Complete example: FileOrganizer with multi-agent system

Each chapter includes:

- Clear learning objectives
- Hands-on code examples
- GitHub Copilot prompts to accelerate development
- Best practices and tips

## Learning Path

We recommend following the chapters in order, as each builds on concepts from previous chapters. However, if you're already familiar with certain topics, feel free to skip ahead.

**Estimated Time**: 10-12 weeks (assuming 5-10 hours per week)

## About Kashi School of Computing

The Kashi School of Computing is inspired by the legacy of **Jamshid Kashani** (Ghiyāth al-Dīn Jamshīd Masʿūd al-Kāshī), the brilliant 15th-century Persian mathematician and astronomer. Just as Kashani advanced computational mathematics and astronomical instruments, we advance modern computational practices through:

- **Vibe Coding**: Intuitive, flow-state development enhanced by AI
- **Multi-Agent Systems**: Collaborative AI architectures for complex problems
- **Real-World Impact**: Building tools that solve actual problems

## Ready to Begin?

Let's start your journey into building AI-powered CLI tools. Head to **Chapter 1: Foundation Setup** to set up your development environment.

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*"The purpose of computing is insight, not numbers." - Inspired by Richard Hamming*