| # 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* | |