🚀 AI Programming Education Platform

Master AI-Assisted Development Through Interactive Learning

A comprehensive educational platform that teaches AI-assisted programming through hands-on tutorials, practical projects, and best practices.
Features interactive learning modules, modern development workflows, and real-world project implementations.
Fork it and host your own learning environment FREE on Cloudflare.

Live Demo · Documentation · Blog · Issues

Share This Project

^{🌟 Pioneering the future of AI-assisted programming education. Built for the next generation of developers.}

✨ See it live

Legacy screenshot (pre-2026-07 redesign): AI programming learning platform homepage with the TECHNEST curriculum

📚 Curriculum outline — 12-week TECHNEST AI track with sidebar nav

TECHNEST Track Curriculum page — 12-week AI developer track, delegation rules, weekly plan, and capstone evaluation criteria with sidebar navigation

📱 Mobile view

Legacy mobile screenshot (pre-2026-07 redesign): homepage hero above the platform heading

📸 Project Screenshots

[!NOTE] The screenshots in this section pre-date the 2026-07 "MindMarket" redesign (cream-paper editorial theme, oversized Inter type, paper-cut illustrations, light-only). They are kept as a record of the platform's visual evolution; for the current look, visit the live site.

[!TIP] See the evolution of the platform's UI/UX over time, from the original design through the "Version 2" refresh below.

🌟 "Version 2" refresh - Enhanced UI/UX (pre-2026-07 redesign)

Version 2 Main Dashboard - Redesigned with modern aesthetics and improved navigation

Version 2 Documentation - Enhanced reading experience with better typography

Version 2 Interface Showcase - Mobile responsive and feature highlights

📱 Previous Version (Version 1) & Version Comparison

📱 Previous Version (Version 1) - Original Design

Version 1 Main Dashboard - Original comprehensive learning modules and navigation

Version 1 Tutorials & Blog - Original interactive content sections

Version 1 Mobile View - Original responsive design foundation

🔄 Version Evolution Highlights:

✨ Enhanced Visual Design: Modern color scheme and typography
🎨 Improved UI Components: Better buttons, cards, and interactive elements
📱 Mobile Optimization: Superior responsive design across all devices
🚀 Performance Improvements: Faster loading and smoother interactions

🎬 Demo Video

[!NOTE] Watch our platform in action with this comprehensive demo.

2024-12-14.14-59-17.mp4

Complete platform walkthrough showing all major features

Tech Stack Badges:

Important

This platform demonstrates modern educational technology with interactive learning modules. It combines comprehensive documentation with hands-on tutorials to provide a complete AI programming education experience. Features include step-by-step tutorials, practical projects, and modern development tool integration.

📑 Table of Contents

🌟 Introduction

We are passionate educators and developers creating the next generation of AI programming education. By adopting modern educational technologies and comprehensive learning methodologies, we aim to provide learners with powerful, accessible, and engaging AI programming education.

Whether you're a beginner looking to enter the world of AI programming or an experienced developer seeking to enhance your skills with AI tools, this platform will be your comprehensive learning companion. The platform is actively maintained and we welcome feedback for any issues encountered.

Note

Node.js >= 18.0 required for development
Modern web browser for optimal experience
GitHub account recommended for accessing additional resources
No prior AI experience required - we start from the basics!

	No installation required! Visit our live demo to start learning immediately.
	Get intelligent answers about the project using AI

Tip

⭐ Star us to receive all updates and new learning content from GitHub!

✨ Key Features

`1` Interactive Learning Modules

Experience next-generation educational content through our comprehensive module system. Our innovative approach provides structured learning paths through carefully designed tutorials covering everything from AI communication basics to advanced development workflows.

Interactive learning modules with step-by-step guidance

Key capabilities include:

🎯 Progressive Learning: Structured curriculum from basics to advanced
🛠️ Hands-on Practice: Real-world projects and exercises
📱 Responsive Design: Learn on any device, anywhere
🌐 Bilingual Support: Content available in multiple languages

`2` Comprehensive Tutorial System

Revolutionary tutorial system that transforms how learners interact with AI programming concepts. With our structured approach and practical examples, students can master AI-assisted development while building real projects.

Available Learning Tracks:

Environment Setup: Development environment configuration
Basic Concepts: AI communication and prompt engineering
Tool Mastery: Cursor, v0, and modern development tools
Project Implementation: Complete project walkthroughs
Advanced Topics: AI drawing, chat systems, and Coze integration

`3` AI Chat Assistant with RAG

An intelligent AI chat assistant powered by Cloudflare Workers AI, providing real-time Q&A support based on the course content. The assistant uses Retrieval-Augmented Generation (RAG) to provide accurate, context-aware answers.

sequenceDiagram
    participant User
    participant ChatWidget
    participant Worker as Cloudflare Worker
    participant Vectorize
    participant AI as Workers AI

    User->>ChatWidget: Ask question
    ChatWidget->>Worker: POST /api/chat
    Worker->>Vectorize: Search relevant docs
    Vectorize-->>Worker: Return matching chunks
    Worker->>AI: Generate response with context
    AI-->>Worker: Stream response
    Worker-->>ChatWidget: SSE stream
    ChatWidget-->>User: Display answer

Key Capabilities:

🤖 Intelligent Q&A: Answers questions based on course documentation
📚 RAG-Powered: Uses vector search to find relevant content
🌊 Streaming Responses: Real-time typing effect for better UX
🌐 Bilingual Support: Supports both Chinese and English
🎨 On-Brand UI: Paper-styled chat widget that matches the MindMarket design system

`*` Additional Features

Beyond the core learning modules, this platform includes:

✨ New content and features are continuously added as the field evolves.

🛠️ Tech Stack

Docusaurus 3.8

React 18

TypeScript

Workers AI

MDX

Pages

Frontend Stack:

Framework: Docusaurus 3.8.1 with React 18
Design System: "MindMarket" — a cream-paper editorial theme (oversized Inter type, paper-cut illustrations, no shadows or gradients, light theme only — dark mode is intentionally disabled)
Styling: Hand-authored CSS under src/css/ — custom.css is an @import manifest over 8 files (tokens.css, base.css, animations.css, navbar.css, footer.css, docs.css, blog.css, pages.css). No CSS-in-JS, styled-components, or Tailwind
Illustrations: Flat paper-cut PNG/webp assets in static/img/illustrations/, generated via scripts/generate-illustrations.mjs (OpenAI gpt-image-1 + sharp post-processing)
Brand assets: Logo, favicons, and social card under static/img/brand/
Content: MDX for rich interactive documentation
Search: Algolia DocSearch integration
i18n: Chinese (zh-Hans) and English support
Components: Custom React components (ChatWidget, MusicPlayer, TechNest, homepage sections, etc.)

Backend Stack (AI Chat):

Runtime: Cloudflare Workers (Edge Computing)
Public URL: https://programming-api.chanmeng.org
AI Model: @cf/meta/llama-3.1-8b-instruct-fp8 via Workers AI
Embeddings: @cf/baai/bge-base-en-v1.5 (768 dimensions)
Vector Database: Cloudflare Vectorize (~4,800 document chunks)
Storage: Cloudflare KV (sessions, message board cache, capstone votes)
Content DB: Notion (message board & capstone showcase)
API: RESTful with SSE streaming

Development Tools:

Build System: Rspack-based Docusaurus build (@docusaurus/faster)
Development Server: Hot reload development environment
Content Management: File-based content system with versioning
Deployment: Cloudflare Pages (Frontend) + Cloudflare Workers (Backend)
Version Control: Git-based workflow

Tip

Each technology was selected for educational effectiveness, ease of maintenance, and optimal learning experience.

🏗️ Architecture

System Architecture

Tip

This architecture supports easy content management and scalable educational delivery, making it perfect for educational institutions and self-learners.

graph TB
    subgraph "Frontend - Docusaurus"
        A[MDX Documentation] --> B[React Components]
        B --> C[ChatWidget]
        B --> D[Theme Components]
        C --> E[i18n Support]
    end

    subgraph "Backend - Cloudflare Workers"
        F[Worker Entry] --> G[Chat Handler]
        G --> H[RAG Module]
        H --> I[Vectorize Search]
        H --> J[Workers AI]
        G --> K[KV Sessions]
    end

    subgraph "Deployment"
        L[Cloudflare Pages CDN]
        M[Cloudflare Edge]
    end

    C -->|API Request| F
    J -->|Llama 3.1 8B| G
    I -->|BGE Embeddings| H
    A --> L
    F --> M

AI Chat Architecture

The AI Chat system uses a RAG (Retrieval-Augmented Generation) architecture to provide accurate, context-aware responses:

flowchart LR
    subgraph "Document Processing"
        A[MDX Files] -->|Parse| B[Text Chunks]
        B -->|Embed| C[Vector Store]
    end

    subgraph "Query Processing"
        D[User Query] -->|Embed| E[Query Vector]
        E -->|Search| C
        C -->|Top 3 Matches| F[Context]
    end

    subgraph "Response Generation"
        F --> G[System Prompt]
        D --> G
        G -->|Llama 3.1| H[AI Response]
        H -->|SSE Stream| I[Chat UI]
    end

Component	Technology	Purpose
Vector DB	Cloudflare Vectorize (`docs-index`)	Store 4,800+ document embeddings
Embeddings	`@cf/baai/bge-base-en-v1.5`	Convert text to 768-dim vectors
LLM	`@cf/meta/llama-3.1-8b-instruct-fp8`	Generate conversational responses
Sessions	Cloudflare KV	Maintain conversation history
Streaming	Server-Sent Events	Real-time response delivery

Project Structure

ai-programming-teaching-project/
├── docs/                        # Current version documentation
│   ├── basics/                  # Fundamental concepts
│   ├── practice/                # Project implementations
│   └── website/                 # Website development tutorials
├── versioned_docs/              # Versioned documentation
│   ├── version-2024-winter/     # Winter 2024 curriculum
│   └── version-2025-summer/     # Summer 2025 curriculum
├── blog/                        # Blog posts
├── i18n/                        # Internationalization
│   ├── en/                      # English translations
│   └── zh-Hans/                 # Chinese translations
├── src/
│   ├── components/              # React components
│   │   ├── ChatWidget/          # AI Chat assistant
│   │   ├── MusicPlayer/         # Navbar music player
│   │   ├── Home/                # Homepage sections (Hero, Programs, HowItWorks, Community)
│   │   ├── TechNest/            # Curriculum step/badge components
│   │   ├── MintlifyShim/        # Docs UI primitives (Steps, Card, Accordion)
│   │   ├── AITracker/           # AI-referrer analytics
│   │   └── GEOHead/             # Per-page AI/SEO instructions
│   ├── pages/                   # Custom pages (index, message-board, capstone-showcase, feeds)
│   ├── theme/                   # Theme customizations & swizzles
│   └── css/                     # MindMarket design system (8-file @import manifest via custom.css)
├── worker/                      # Cloudflare Worker backend
│   ├── src/
│   │   ├── index.ts             # Worker entry point & routing
│   │   ├── chat.ts              # Chat logic & streaming
│   │   ├── rag.ts               # RAG & vector search
│   │   ├── messages.ts          # Message board (Notion-backed)
│   │   ├── capstones.ts         # Capstone showcase & voting
│   │   └── types.ts             # TypeScript types
│   ├── scripts/
│   │   ├── seed-vectors.ts      # Document vectorization
│   │   ├── smoke-test.mjs       # End-to-end RAG check
│   │   └── namespace-test.mjs   # Namespace-scoped retrieval check
│   ├── wrangler.toml            # Cloudflare configuration
│   └── package.json             # Worker dependencies
├── static/                      # Static assets
├── docusaurus.config.js         # Docusaurus configuration
├── sidebars.js                  # Sidebar configuration
└── package.json                 # Project dependencies

🚀 Getting Started

Prerequisites

Important

Ensure you have the following installed:

Node.js 18.0+ (Download)
npm/yarn/pnpm package manager
Git (Download)
Modern web browser

Quick Installation

1. Clone Repository

git clone https://github.com/ChanMeng666/ai-programming-teaching-project.git
cd ai-programming-teaching-project

2. Install Dependencies

# Using npm
npm install

# Using yarn
yarn install

# Using pnpm (recommended)
pnpm install

3. Start Development Server

npm start

🎉 Success! Open http://localhost:3000 to access the learning platform.

Development Mode

# Start with hot reload
npm start

# Build for production
npm run build

# Serve production build
npm run serve

# Clear cache
npm run clear

🛳 Deployment

Important

The frontend and the backend ship independently. The site auto-deploys from main; the Worker only deploys when you run wrangler deploy by hand. Pushing a change to worker/ ships nothing on its own.

`A` Frontend Deployment (Cloudflare Pages)

The site is a Cloudflare Pages project connected to the GitHub repository. Pushing to main is the deploy.

git push origin main   # Cloudflare Pages builds and publishes automatically

Pages project settings:

Setting	Value
Production branch	`main`
Build command	`npm run build`
Build output directory	`build`
Domains	`programming.chanmeng.org`, `ai-programming-teaching-project.pages.dev`

To host your own copy, fork the repo, create a Pages project in the Cloudflare dashboard, connect it to your fork, and enter the settings above.

Warning

Ignore the deploy script in the root package.json — it is Docusaurus' built-in gh-pages command and is not how this site ships.

`B` Backend Deployment (Cloudflare Workers)

Prerequisites:

Cloudflare account with Workers AI, KV and Vectorize enabled
Wrangler CLI (npx wrangler — no global install needed)

Step 1: Configure Cloudflare Resources

cd worker

# Login to Cloudflare
npx wrangler login

# Create the KV namespaces
npx wrangler kv namespace create CHAT_SESSIONS
npx wrangler kv namespace create MESSAGE_BOARD
npx wrangler kv namespace create CAPSTONE_VOTES

# Create Vectorize index for RAG
npx wrangler vectorize create docs-index --dimensions=768 --metric=cosine

Step 2: Update wrangler.toml

Paste the namespace IDs printed by the commands above, and point the route at your own domain.

name = "ai-chat-worker"
main = "src/index.ts"
compatibility_date = "2024-12-01"
compatibility_flags = ["nodejs_compat"]

# WAF rate limiting rules only apply to custom domains, never to *.workers.dev,
# so the workers.dev entrypoint stays off: leaving it on would let any client
# reach /api/chat while bypassing every rate limiting rule on the zone.
workers_dev = false

[[routes]]
pattern = "programming-api.chanmeng.org"
custom_domain = true

[ai]
binding = "AI"

[[kv_namespaces]]
binding = "CHAT_SESSIONS"
id = "<YOUR_CHAT_SESSIONS_KV_ID>"

[[vectorize]]
binding = "VECTORIZE"
index_name = "docs-index"

[[kv_namespaces]]
binding = "MESSAGE_BOARD"
id = "<YOUR_MESSAGE_BOARD_KV_ID>"

[[kv_namespaces]]
binding = "CAPSTONE_VOTES"
id = "<YOUR_CAPSTONE_VOTES_KV_ID>"

[vars]
# Comma-separated allow-list. Any https://<hash>.ai-programming-teaching-project.pages.dev
# preview origin is additionally matched by suffix in src/index.ts.
CORS_ORIGIN = "https://programming.chanmeng.org,https://ai-programming-teaching-project.pages.dev,http://localhost:3000"

Step 3: Set Secrets

Six secrets live outside the repo. Set each one once; wrangler deploy does not clobber them.

npx wrangler secret put NOTION_TOKEN                  # Message board + capstone Notion integration
npx wrangler secret put NOTION_DATABASE_ID            # Message board database
npx wrangler secret put NOTION_CAPSTONE_DATABASE_ID   # Capstone showcase database
npx wrangler secret put CAPSTONE_ADMIN_TOKEN          # Guards POST /api/capstones/admin
npx wrangler secret put SEED_TOKEN                    # Guards POST /api/seed
npx wrangler secret put SETUP_SECRET                  # Guards the one-time /setup routes

Step 4: Deploy Worker

Important

Always cd worker first. Running wrangler deploy from the repository root makes wrangler infer the Worker name from the directory and publish an empty stub called ai-programming-teaching-project.

cd worker

# Install dependencies
npm install

# Deploy to Cloudflare — this is a manual step, not part of git push
npx wrangler deploy

Step 5: Seed Vector Database

# Index the docs into Vectorize
npm run seed

Step 6: Verify

# Sends 6 real RAG questions to /api/chat and prints latency + citations
node scripts/smoke-test.mjs

# Namespace-scoped retrieval check
node scripts/namespace-test.mjs

Point the frontend at your Worker. The API base URL is hardcoded — there is no environment variable. Update all three:

src/components/ChatWidget/index.js (API_URL)
src/pages/message-board.js (API_BASE)
src/pages/capstone-showcase.js (API_BASE)

Deployment Architecture

graph LR
    subgraph "User"
        A[Browser]
    end

    subgraph "Cloudflare Pages"
        B[Static Site CDN]
    end

    subgraph "Cloudflare Workers"
        C[Workers Edge]
        D[KV Storage]
        E[Vectorize]
        F[Workers AI]
    end

    A -->|HTTPS| B
    A -->|API Calls| C
    C --> D
    C --> E
    C --> F

📡 API Reference

The backend is served from a single origin: https://programming-api.chanmeng.org

Endpoints

Method	Path	Auth	Description
`POST`	`/api/chat`	—	Streaming SSE chat with RAG over the course docs
`GET`	`/api/messages`	—	List message board entries (Notion-backed, 300s KV cache)
`POST`	`/api/messages`	—	Post a message to the board
`GET`	`/api/capstones`	—	List published capstone projects
`POST`	`/api/capstones/vote`	—	Vote for a capstone project
`POST`	`/api/capstones/admin`	`CAPSTONE_ADMIN_TOKEN`	Publish a capstone project
`POST`	`/api/seed`	`SEED_TOKEN`	Index documents into Vectorize
`POST`	`/api/seed/delete`	`SEED_TOKEN`	Remove documents from Vectorize
`POST`	`/api/messages/setup`	`SETUP_SECRET`	One-time Notion database setup
`POST`	`/api/capstones/setup`	`SETUP_SECRET`	One-time Notion database setup
`GET`	`/api/health`, `/`	—	Health check

Example — chat:

curl -N https://programming-api.chanmeng.org/api/chat \
  -H 'Content-Type: application/json' \
  -d '{"message": "What is prompt engineering?"}'

message is required. Optional sessionId continues a conversation, and optional contextNamespace scopes retrieval to one course version. The response is a text/event-stream; the session id comes back in the X-Session-Id header.

Rate Limits

Two independent layers guard the API. Both are per-IP.

Layer	Scope	Limit	Response when exceeded
Cloudflare WAF (edge)	`POST /api/chat`	20 requests / 10 seconds	`error code: 1015`, plain text, no CORS headers
Worker	`POST /api/chat`	30 requests / hour	`429` + JSON `{"error": "..."}`
Worker	`POST /api/messages`	5 requests / hour	`429` + JSON `{"error": "..."}`
Worker	`POST /api/capstones/vote`	30 requests / hour	`429` + JSON `{"error": "..."}`

The WAF layer blocks at the edge, so the request never reaches the Worker and the browser sees an opaque failure rather than a JSON error. /api/chat charges its hourly quota before invoking the model — a request that times out has still consumed Workers AI, so it still counts.

Note

The Worker's workers.dev subdomain is disabled (workers_dev = false) and returns 404 / error code 1042. WAF rules are never evaluated on *.workers.dev, so leaving it enabled would let anyone bypass the edge rate limit.

CORS

CORS_ORIGIN is a comma-separated allow-list of exact origins. In addition, any https://<hash>.ai-programming-teaching-project.pages.dev preview origin is matched by suffix, because Pages mints a new immutable origin on every production build. Responses carry Vary: Origin; a disallowed origin simply gets no Access-Control-Allow-Origin header.

Warning

CORS is a browser control. It stops other websites from reading the API from a page, but it does nothing against curl or scripts — that is what the rate limits are for.

📖 Learning Path

Beginner Level

Getting Started (Week 1-2):

Environment Setup - Configure your development environment
AI Communication - Learn effective AI interaction
Markdown Basics - Master documentation formatting

Intermediate Level

Tool Mastery (Week 3-5):

Cursor Editor - Advanced code editing with AI
v0 Platform - Rapid prototyping and development
Workflow Integration - Streamlined development processes

Advanced Level

Project Implementation (Week 6-8):

Complete Projects - Build real-world applications
AI Drawing - Creative AI applications
Chat Systems - Conversational AI development

Note

Each module includes hands-on exercises, practical examples, and assessment opportunities.

🔌 Integrations

We support integration with leading development and AI platforms:

Category	Platform	Status	Description
AI Chat	Cloudflare Workers AI	✅ Active	Llama 3.1 8B for intelligent Q&A
Vector Search	Cloudflare Vectorize	✅ Active	RAG-powered document retrieval
Session Storage	Cloudflare KV	✅ Active	Conversation history management
Code Editors	Cursor	✅ Active	AI-assisted code editing tutorials
Development	v0 Platform	✅ Active	Rapid prototyping guides
Deployment	Cloudflare Pages	✅ Active	Frontend hosting & CDN
Content DB	Notion	✅ Active	Message board & capstone showcase
Search	Algolia DocSearch	✅ Active	Full-text documentation search
AI Tools	Coze	✅ Active	Chatbot development tutorials

Cloudflare Services Pricing

Service	Free Tier	Paid Pricing
Workers AI	10,000 Neurons/day	$0.011/1,000 Neurons
KV Storage	100K reads/day, 1GB	$0.50/million reads
Vectorize	30M queried dims/month	$0.01/million dims

Note

For typical educational usage (~50 daily conversations), the platform operates within free tier limits.

⌨️ Development

Local Development

Setup Development Environment:

# Clone repository
git clone https://github.com/ChanMeng666/ai-programming-teaching-project.git
cd ai-programming-teaching-project

# Install dependencies
npm install

# Start development server
npm start

Adding Content

Creating New Documentation:

# Create new doc file
touch docs/new-topic/index.mdx

Adding Blog Posts:

# Create new blog post
touch blog/YYYY-MM-DD-post-title.mdx

Content Structure:

---
title: Your Title
sidebar_position: 1
---

# Your Content

Your educational content here...

🤝 Contributing

We welcome contributions! Here's how you can help improve this educational platform:

Content Contributions:

📚 Add new tutorials and learning modules
🐛 Fix typos and improve existing content
💡 Suggest new topics and learning paths
🌐 Help with translations and localization

Technical Contributions:

🔧 Improve platform functionality
🎨 Enhance UI/UX design
📱 Optimize mobile experience
⚡ Performance improvements

Pull Request Process:

Fork the repository
Create your feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add some amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

Open Source Benefits:

✅ Free for educational use
✅ Modification allowed
✅ Distribution permitted
✅ Commercial use allowed

👥 Team

_{Chan Meng}
Creator & Lead Developer
UI/UX Designer & Full Stack Developer

🙋‍♀️ Author

Chan Meng

LinkedIn: chanmeng666
GitHub: ChanMeng666
Email: chanmeng.dev@gmail.com
Website: chanmeng.org

🚀 Building the Future of AI Programming Education 🌟
Empowering developers and learners worldwide

⭐ Star us on GitHub • 📖 Read the Documentation • 🐛 Report Issues • 💡 Request Features • 🤝 Contribute

Made with ❤️ by the AI Programming Education team

Chan Meng
Need a custom app like this one? I build them — let's talk.

Name		Name	Last commit message	Last commit date
Latest commit History 247 Commits
.claude		.claude
.github		.github
.idea		.idea
blog		blog
docs		docs
i18n/zh-Hans		i18n/zh-Hans
scripts		scripts
src		src
static		static
versioned_docs		versioned_docs
versioned_sidebars		versioned_sidebars
worker		worker
.env.example		.env.example
.gitattributes		.gitattributes
.gitignore		.gitignore
CAPSTONE_SHOWCASE.md		CAPSTONE_SHOWCASE.md
CHANGELOG.md		CHANGELOG.md
CLAUDE.md		CLAUDE.md
CODE_OF_CONDUCT.md		CODE_OF_CONDUCT.md
CONTRIBUTING.md		CONTRIBUTING.md
DESIGN.md		DESIGN.md
GOVERNANCE.md		GOVERNANCE.md
LICENSE		LICENSE
README.md		README.md
SECURITY.md		SECURITY.md
SUPPORT.md		SUPPORT.md
docusaurus.config.js		docusaurus.config.js
package-lock.json		package-lock.json
package.json		package.json
sidebars.js		sidebars.js
versions.json		versions.json

Uh oh!

Folders and files

Latest commit

History

Repository files navigation

🚀 AI Programming Education Platform

Master AI-Assisted Development Through Interactive Learning

✨ See it live

📸 Project Screenshots

🌟 "Version 2" refresh - Enhanced UI/UX (pre-2026-07 redesign)

📱 Previous Version (Version 1) - Original Design

🔄 Version Evolution Highlights:

🎬 Demo Video

TOC

🌟 Introduction

✨ Key Features

1 Interactive Learning Modules

2 Comprehensive Tutorial System

3 AI Chat Assistant with RAG

* Additional Features

🛠️ Tech Stack

🏗️ Architecture

System Architecture

AI Chat Architecture

Project Structure

🚀 Getting Started

Prerequisites

Quick Installation

Development Mode

🛳 Deployment

A Frontend Deployment (Cloudflare Pages)

B Backend Deployment (Cloudflare Workers)

Deployment Architecture

📡 API Reference

Endpoints

Rate Limits

CORS

📖 Learning Path

Beginner Level

Intermediate Level

Advanced Level

🔌 Integrations

Cloudflare Services Pricing

⌨️ Development

Local Development

Adding Content

🤝 Contributing

📄 License

👥 Team

🙋‍♀️ Author

About

Topics

Resources

Code of conduct

Contributing

Security policy

Stars

Watchers

Forks

Releases

Sponsor this project

Packages

Used by

Contributors

Languages

`1` Interactive Learning Modules

`2` Comprehensive Tutorial System

`3` AI Chat Assistant with RAG

`*` Additional Features

`A` Frontend Deployment (Cloudflare Pages)

`B` Backend Deployment (Cloudflare Workers)