Dash Documentation Boilerplate

A modern, markdown-driven documentation system for Dash applications built on Dash Mantine Components, with first-class AI/LLM and SEO integration via dash-improve-my-llms 2.0.

Welcome to:

![logo](assets/intro_img.jpg)

A modern, responsive documentation system for Dash applications built with Dash Mantine Components

Create beautiful, interactive documentation for your Dash components, data science workflows, and applications with markdown-driven content, live code examples, and automatic theme persistence.

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What is This?

The Dash Documentation Boilerplate is a production-ready framework for creating professional documentation sites for your Dash projects. Whether you're documenting a component library, showcasing data visualizations, or building a comprehensive application guide, this boilerplate provides everything you need.

Built With Modern Technologies

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Key Features

📝 Markdown-Driven Documentation

Write your documentation in markdown files with full Python integration. The framework automatically discovers markdown files in the docs/ directory and generates pages with:

🎨 Beautiful UI/UX

Built with Dash Mantine Components for a modern, professional look:

🔧 Custom Directives

Powerful directives to enhance your documentation:

🤖 AI/LLM Integration

Powered by [dash-improve-my-llms](https://pypi.org/project/dash-improve-my-llms/) 2.0:

🐋 Production Ready

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Quick Start

1. Installation

```bash

Clone the repository

git clone https://github.com/pip-install-python/Dash-Documentation-Boilerplate.git cd Dash-Documentation-Boilerplate

Install Python dependencies

pip install -r requirements.txt

Install Node dependencies (for Mantine components)

npm install ```

2. Run the Development Server

``bash python run.py ``

Visit http://localhost:8553 in your browser.

3. Create Your First Documentation Page

Create a new folder in docs/ with a markdown file:

```markdown --- name: My Component description: Description of my awesome component endpoint: /components/my-component icon: mdi:code-tags ---

My Component

Your documentation content here...

.. toc::

Features

```

That's it! Your page will automatically appear in the navigation.

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Example Documentation

This site includes several example pages to demonstrate the capabilities:

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Project Structure

`` dash-documentation-boilerplate/ ├── assets/ # Static assets and CSS │ ├── m2d.css # Markdown-to-Dash styling │ └── main.css # Custom styles │ ├── components/ # Reusable UI components │ ├── appshell.py # Main app layout │ ├── header.py # Header with search and theme toggle │ └── navbar.py # Navigation sidebar │ ├── docs/ # Your documentation content │ └── your-component/ │ ├── component.md # Markdown documentation │ └── examples.py # Python interactive examples │ ├── lib/ # Utility libraries │ ├── constants.py # App-wide constants │ └── directives/ # Custom markdown directives │ ├── kwargs.py # Component props tables │ ├── source.py # Source code display │ └── toc.py # Table of contents │ ├── pages/ # Dash multi-page app │ ├── home.md # This home page │ ├── home.py # Home page layout │ └── markdown.py # Dynamic markdown loader │ ├── templates/ │ └── index.html # Custom HTML template │ ├── CHANGELOG.md # Version history ├── README.md # Full documentation ├── LLMS_INTEGRATION.md # AI/LLM integration guide ├── requirements.txt # Python dependencies ├── package.json # Node dependencies ├── Dockerfile # Docker container └── run.py # Application entry point ``

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Customization

Change Primary Color

Edit lib/constants.py:

``python PRIMARY_COLOR = "teal" # Change to any Mantine color ``

Modify Styles

Configure AI/LLM Integration

Update run.py to configure bot management and SEO:

```python from dash_improve_my_llms import RobotsConfig

app._base_url = "https://your-production-url.com" app._robots_config = RobotsConfig( block_ai_training=True, allow_ai_search=True, crawl_delay=10 ) ```

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Deployment

Docker

```bash

Build the image

docker build -t dash-docs-boilerplate .

Run the container

docker run -p 8550:8550 dash-docs-boilerplate ```

Docker Compose

``bash docker-compose up ``

Visit http://localhost:8550

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Resources

Community

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License

MIT License - see [LICENSE](https://github.com/pip-install-python/Dash-Documentation-Boilerplate/blob/main/LICENSE) for details.

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Ready to start? Check out the example documentation pages to see what you can build!

Note for AI agents: This is the static, prerendered view of an interactive Dash application served because we detected a non-JS user agent. Full prose docs: