AI Course Generator 🚀

An intelligent CLI tool for generating structured educational content using AI models.

Table of Contents

• Key Features
• Quick Start
• Installation Options
• Usage Guide
  • Interactive Mode
  • Direct Command Usage
• Configuration Reference
• Examples
• Technical Documentation
• Contributing
• License

Key Features

✔ Multi-format Output - Generate courses in PDF, DOCX, and EPUB formats
✔ Smart Configuration - Customize length, difficulty, and content depth
✔ Model Flexibility - Supports multiple AI models including Gemini
✔ User-Friendly CLI - Interactive prompts or direct command options
✔ Structured Content - Automatically generates chapters and outlines
✔ Advanced Workflows - Powered by QuantaLogic Flow engine (Technical Details)

Quick Start

# Run in interactive mode (recommended for first-time users)
python -m ai_course_generator.generate_course --interactive

Installation Options

Standard Installation

git clone https://github.com/raphaelmansuy/course-generator.git
cd course-generator
pip install -e .

Isolated Installation (recommended)

pipx install git+https://github.com/raphaelmansuy/course-generator.git

Usage Guide

Interactive Mode

python -m ai_course_generator.generate_course --interactive
# or
python -m ai_course_generator.generate_course -i

The interactive mode will guide you through all configuration options with sensible defaults.

Direct Command Usage

Required Parameters

All of these must be provided either via command line or interactive mode:

• --subject: Course subject (string)
• --number-of-chapters: Number of chapters (integer)
• --level: Difficulty level (beginner/intermediate/advanced)
• --words-by-chapter: Target word count per chapter (integer)
• --target-directory: Output directory path (string)

Complete Command Example:

python -m ai_course_generator.generate_course \
  --subject "Python Basics" \
  --number-of-chapters 5 \
  --level beginner \
  --words-by-chapter 800 \
  --target-directory "./output_courses"

With Optional Flags:

python -m ai_course_generator.generate_course \
  --subject "Advanced ML" \
  --number-of-chapters 8 \
  --level advanced \
  --words-by-chapter 1500 \
  --target-directory "./ml_courses" \
  --no-pdf \
  --model-name "gemini/gemini-2.0-pro"

Configuration Reference

Examples

1. Beginner-Friendly Course

python -m ai_course_generator.generate_course \
  --subject "Python Basics" \
  --level beginner \
  --words-by-chapter 600

2. Technical Deep Dive

python -m ai_course_generator.generate_course \
  --subject "Advanced Kubernetes" \
  --level advanced \
  --words-by-chapter 2000 \
  --model-name "gemini/gemini-2.0-pro"

Technical Documentation

For in-depth technical information about the architecture and implementation, see our Technical Documentation which covers:

• Workflow engine design
• AI integration patterns
• Content generation pipeline
• Performance characteristics

Contributing

We welcome contributions! Please see our Contribution Guidelines for details.

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

License

Distributed under the MIT License. See LICENSE for more information.