|
|
--- |
|
|
title: Kashi Coding Handbook |
|
|
description: A handbook for coding best practices and guidelines |
|
|
author: KashiAI |
|
|
colorFrom: green |
|
|
colorTo: pink |
|
|
sdk: docker |
|
|
pinned: false |
|
|
license: mit |
|
|
thumbnail: >- |
|
|
https://cdn-uploads.huggingface.co/production/uploads/6455a62fbda0fbba412d170d/k8-D6PGmmfUulVCehX2_J.png |
|
|
--- |
|
|
|
|
|
<p align="center"> |
|
|
<img src="src/images/KashiAI.png" alt="KashiAI Logo" width="220"/> |
|
|
</p> |
|
|
|
|
|
# Kashi Coding Handbook |
|
|
|
|
|
**Build AI-powered CLI tools with Python, from modern packaging to production deployment.** |
|
|
|
|
|
## What is this? |
|
|
|
|
|
The Kashi Coding Handbook is a comprehensive, project-driven guide for: |
|
|
- Python developers and data scientists building robust CLI tools |
|
|
- AI engineers integrating LLMs and multi-agent systems |
|
|
- Anyone seeking reproducible, production-grade Python workflows |
|
|
|
|
|
The handbook is a Quarto website ([see `src/`](src/)) with: |
|
|
- 7 core chapters (see `src/chapters/`) |
|
|
- Real-world projects (see [`docs/projects/`](docs/projects/)) |
|
|
- A 12-month [content plan](docs/content-plan.md) and [learning path](docs/learning-path.md) |
|
|
- Deep dives on [Docker AI](docs/docker-ai.md), MCP, and more |
|
|
|
|
|
--- |
|
|
|
|
|
## Quickstart |
|
|
|
|
|
```bash |
|
|
# 1. Install Quarto (https://quarto.org/docs/get-started/) |
|
|
# 2. Clone this repo and install dependencies (pixi recommended) |
|
|
git clone <this-repo-url> |
|
|
cd KCH |
|
|
pixi install |
|
|
# 3. Preview the site |
|
|
quarto preview src |
|
|
``` |
|
|
|
|
|
We recommend the [Quarto VS Code Extension](https://marketplace.visualstudio.com/items?itemName=quarto.quarto) for syntax highlighting, code completion, and live preview. |
|
|
|
|
|
--- |
|
|
|
|
|
## Handbook Structure |
|
|
|
|
|
The handbook is organized as follows (see [`src/_quarto.yml`](src/_quarto.yml)): |
|
|
|
|
|
- **Chapter 1: Foundation Setup** – Environment, project structure |
|
|
- **Chapter 2: CLI Development** – Typer, config management |
|
|
- **Chapter 3: AI Integration** – HuggingFace, Docker, MCP, prompt engineering |
|
|
- **Chapter 4: Advanced Features** – Interactive elements, batch processing |
|
|
- **Chapter 5: Testing & Quality** – Tests, code quality |
|
|
- **Chapter 6: Publishing** – Packaging, PyPI |
|
|
- **Chapter 7: Real-World Projects** – e.g., [FileOrganizer](docs/projects/FileOrganizer.md) |
|
|
- **Appendices** – Pixi commands, learning resources |
|
|
|
|
|
See [`src/chapters/`](src/chapters/) for all chapter sources. |
|
|
|
|
|
--- |
|
|
|
|
|
## Documentation & Resources |
|
|
|
|
|
- [Learning Path](docs/learning-path.md): Step-by-step curriculum |
|
|
- [Content Plan](docs/content-plan.md): 12-month roadmap |
|
|
- [Docker AI Guide](docs/docker-ai.md): LLM/MCP deployment |
|
|
- [Project Blueprints](docs/projects/): Real-world project specs |
|
|
|
|
|
--- |
|
|
|
|
|
## Contributing |
|
|
|
|
|
Contributions, suggestions, and questions are welcome! |
|
|
1. Fork the repo and create a feature branch |
|
|
2. Open a pull request with a clear description |
|
|
3. For major changes, please open an issue first to discuss |
|
|
|
|
|
--- |
|
|
|
|
|
## License |
|
|
|
|
|
MIT |
