Track images via xet

.gitattributes

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+*.png filter=lfs diff=lfs merge=lfs -text
 *.7z filter=lfs diff=lfs merge=lfs -text
 *.arrow filter=lfs diff=lfs merge=lfs -text
 *.bin filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,50 +1,88 @@
 ---
-title: KCH
-emoji: 🌖
+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
-short_description: Kashi Coding Handbook
 ---
 
-To get started working with quarto we recommend you first [install quarto](https://quarto.org/docs/get-started/) locally so that you can render the site without Docker.
-We also recommend the [Quarto VS Code Extension](https://marketplace.visualstudio.com/items?itemName=quarto.quarto) which provides syntax highlighting, code completion, a preview button and more.
+<p align="center">
+  <img src="src/images/KashiAI.png" alt="KashiAI Logo" width="220"/>
+</p>
 
-The quarto source is located in `src` and you can preview the site with:
+# 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
 ```
 
-A web browser should open up with a live preview of the site.
+We recommend the [Quarto VS Code Extension](https://marketplace.visualstudio.com/items?itemName=quarto.quarto) for syntax highlighting, code completion, and live preview.
+
+---
 
-## Making changes
+## Handbook Structure
 
-The `src/_quarto.yml` contains the site-level configuration for the quarto website and tells quarto which files to render, and how they should be organized.
-For example if you wanted to modify the [site navigation](https://quarto.org/docs/reference/site-navigation.html) you should modify this file.
+The handbook is organized as follows (see [`src/_quarto.yml`](src/_quarto.yml)):
 
-Quarto can render markdown, ipynb, and .qmd files, and you can mix formats in a single document.
+- **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
 
-## Executing code
+See [`src/chapters/`](src/chapters/) for all chapter sources.
 
-One of the main virtues of Quarto is that it lets you combine code and text in a single document.
-By default if you include a code chunk in your document, Quarto will execute that code and include the output in the rendered document.
-This is great for reproducibility and for creating documents that are always up-to-date.
+---
 
-```{python}
-import seaborn as sns
-import matplotlib.pyplot as plt
+## Documentation & Resources
 
-# Sample data
-tips = sns.load_dataset("tips")
+- [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
 
-# Create a seaborn plot
-sns.set_style("whitegrid")
-g = sns.lmplot(x="total_bill", y="tip", data=tips, aspect=2)
-g = (g.set_axis_labels("Total bill (USD)", "Tip").set(xlim=(0, 60), ylim=(0, 12)))
+---
 
-plt.title("Tip by Total Bill")
-plt.show()
-```
+## 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

scripts/install-xet.sh

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+#!/bin/sh
+
+curl --proto '=https' --tlsv1.2 -sSf https://raw.githubusercontent.com/huggingface/xet-core/refs/heads/main/git_xet/install.sh | sh