Project Red Queen: AI-Powered Chat Application

Project Red Queen is a sophisticated full-stack AI chat application that brings intelligent, context-aware conversations to users through a modern web interface. Named after the relentless character from Lewis Carroll's Through the Looking-Glass, the app embodies continuous adaptation and evolution in AI interactions.

🏗️ Architecture Overview

Backend (Django)

• Framework: Django 5.2+ with Django REST Framework
• AI Integration: Google Gemini for natural language processing and multimodal AI responses
• Vector Database: ChromaDB for persistent conversation memory and context retrieval
• Document Processing: LlamaIndex for intelligent document ingestion and querying
• Audio Capabilities: Text-to-speech synthesis using Edge TTS and audio analysis with Librosa
• Deployment: Railway with Nixpacks, supporting Python 3.12 and uv package management

Frontend (Next.js)

• Framework: Next.js with TypeScript
• UI/UX: Responsive design with real-time chat interface
• Deployment: Vercel for seamless hosting and CDN

🎯 Core Features

Intelligent Conversations

• Natural language processing with Google Gemini AI
• Context-aware responses using vector embeddings
• Multimodal input support (text, potentially images/audio)
• Persistent conversation history

Advanced AI Capabilities

• Document intelligence through LlamaIndex
• Audio processing for voice interactions
• Customizable system prompts
• Extensible AI model integrations

Production-Ready Infrastructure

• HTTPS-enabled secure communications
• CORS configuration for cross-origin requests
• Scalable deployment on Railway
• Environment-based configuration management

🔧 Technical Stack

• Backend: Python 3.12, Django, Google Generative AI, ChromaDB, LlamaIndex, Librosa, Edge TTS
• Frontend: TypeScript, Next.js, React
• Database: SQLite (development), configurable for PostgreSQL/MySQL in production
• Deployment: Railway (backend), Vercel (frontend)
• Package Management: uv for Python dependencies
• Version Control: Git with GitHub

🚀 Quick Start

Prerequisites

• Python 3.12+
• Node.js 18+
• Git

Installation

1. Clone the repository

   git clone https://github.com/eddietal2/Project_Red_Queen.git
   cd Project_Red_Queen

2. Backend Setup

   cd b-e
   uv sync
   cp .env.example .env  # Configure your environment variables
   python manage.py migrate
   python manage.py runserver

3. Frontend Setup

   cd f-e
   npm install
   cp .env.example .env.local  # Set NEXT_PUBLIC_API_URL to backend URL
   npm run dev

4. Access the application

   • Frontend: http://localhost:3000
   • Backend API: http://localhost:8000

📁 Project Structure

Project_Red_Queen/
├── b-e/                    # Backend (Django)
│   ├── config/            # Django settings
│   ├── ai_app/            # Main AI application
│   ├── manage.py
│   ├── pyproject.toml
│   └── uv.lock
├── f-e/                    # Frontend (Next.js)
│   ├── app/
│   ├── components/
│   ├── package.json
│   └── next.config.js
├── .gitignore
├── README.md
└── LICENSE

🔐 Environment Variables

Backend (.env)

GOOGLE_API_KEY=your_google_api_key
DEBUG=True
SECRET_KEY=your_django_secret_key
ALLOWED_HOSTS=localhost,127.0.0.1

Frontend (.env.local)

NEXT_PUBLIC_API_URL=http://localhost:8000

🚀 Deployment

Backend (Railway)

1. Connect your GitHub repository to Railway
2. Set environment variables in Railway dashboard
3. Deploy automatically on push

Frontend (Vercel)

1. Connect your GitHub repository to Vercel
2. Set NEXT_PUBLIC_API_URL to your Railway backend URL
3. Deploy automatically

🧪 Testing

Backend

cd b-e
python manage.py test

Frontend

cd f-e
npm test

🤝 Contributing

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

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

📊 Project Status

• Version: 1.0.0 (Stable Release)
• Development: Active
• License: MIT
• Contributors: Open to contributions

📞 Support

For support, email eddietaylor@example.com or join our Discord community.

🙏 Acknowledgments

Special thanks to the open-source community for the amazing libraries that made this project possible: Django, Next.js, Google AI, ChromaDB, and many more.

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The Red Queen is live and ready to chat! 🎭

For more information, visit our documentation or check out the issues page.