📚 Book GPT (AI Book Generator)

Transform your ideas into comprehensive books using state-of-the-art AI powered by Groq's ultra-fast infrastructure.

🌟 Features

• 📖 Complete Book Generation
• ⚡ Ultra-fast Processing with Groq
• 🎨 Customizable Content Structure
• 📑 Multiple Export Formats (PDF/Markdown)
• 🔧 Advanced Configuration Options
• 🎯 Topic-focused Structure
• 🤖 Multiple AI Model Support

🚀 Quick Start

Prerequisites

• Python 3.9+
• Groq API Key
• Required system dependencies for PDF generation

Installation

1. Clone the repository:

git clone https://github.com/tech-rakesh-ai/book-gpt.git

2. Install dependencies:

pip install -r requirements.txt

3. Create a .env file in the root directory and add your Groq API key:

GROQ_API_KEY=your_groq_api_key

4. Run the application:

streamlit run main.py

📚 Documentation

For more detailed information on how to use the AI Book Generator, please refer to the Documentation.

🛠️ Features in Detail

Basic Mode

• Simple interface for quick book generation
• Topic input and additional instructions
• Streamlined process with default settings

Advanced Mode

• Multiple AI model selection for different generation tasks
• Customizable writing style and complexity levels
• Seed content integration
• File upload support
• Detailed generation statistics

Export Options

• Download as PDF with styled formatting
• Export as Markdown/Text file
• Structured content with proper headings

🤖 Supported AI Models

• LLaMA 3.3 70B
• Mixtral 8x7B
• Gemma 2 9B
• LLaMA 3.1 8B
• Other Groq-supported models

🐳 Docker Support

Build and run using Docker:

docker build -t book-gpt .
docker run -p 8000:8000 book-gpt

🔧 Technical Architecture

The project is structured into several key components:

• agents/: AI generation logic for titles, structure, and content
• ui/: Streamlit interface components
• tools/: Utility functions for file handling
• inference/: Generation statistics and monitoring

💡 Usage Tips

1. Use advanced mode for more control over generation
2. Provide detailed instructions for better results
3. Upload seed content for context-aware generation
4. Experiment with different AI models for optimal results

👨‍💻 Developer

Rakesh Kumar

• Senior Software Engineer & AI Enthusiast
• Expertise in Prompt Engineering, GenAI, and NLP
• LinkedIn
• GitHub

📄 License

MIT License - See LICENSE file for details

🙏 Acknowledgments

• Powered by Groq's Infrastructure
• Built with Streamlit
• PDF generation using WeasyPrint