AI-Tutor

AI-Tutor is a comprehensive AI-powered educational content creation platform developed by HexaElite. The system leverages advanced AI to automate and enhance the process of creating educational materials.

🌟 Project Overview

AI-Tutor consists of two main components:

1. Backend (TuteAI): An intelligent course generation system that uses Google's Gemini AI to create structured educational content.
2. Frontend (Flutter App): A cross-platform mobile and web application that provides a user-friendly interface for interacting with the AI-powered backend.

🛠️ Technical Architecture

Backend (TuteAI)

The backend follows a clean, modular architecture designed for maintainability and scalability:

• API Layer: Versioned endpoints (v1 and v2) with clean separation of resource-specific routes
• Models: Pydantic data models for request validation and response serialization
• Services: AI service layer abstracting communication with Gemini AI
• Utils: Helper functions and utilities
• Configuration: Environment-based settings management

Frontend (Flutter App)

The frontend is built using Flutter to provide a consistent user experience across multiple platforms:

• Mobile: Android and iOS applications
• Web: Browser-based interface
• Desktop: Windows, macOS, and Linux support

✨ Key Features

• Complete Course Planning: Generate course outlines with customized titles, descriptions, and modules
• Module Development: Create detailed module plans with logical lesson sequencing
• Lesson Content Generation: Develop comprehensive lesson content aligned with learning objectives
• Quiz Generation: Automatically create assessment questions with explanations
• Document Upload: Generate courses from uploaded documents (PDF, DOCX, PPTX)
• API-First Architecture: Access all functionality through a well-documented RESTful API
• Versioned API Design: Built for long-term extensibility and backward compatibility

🚀 Getting Started

Backend Setup

1. Navigate to the Backend directory:

   cd BackEnd

2. Follow the installation instructions in the Backend README.

Frontend Setup

1. Navigate to the Flutter app directory:

   cd ai_tutor

2. Install Flutter dependencies:

   flutter pub get

3. Run the application:

   flutter run

📚 Documentation

• Backend API Documentation: Available at http://localhost:8000/docs or http://localhost:8000/redoc when the server is running
• Flutter App Documentation: See ai_tutor/README.md

🧠 AI Integration

AI-Tutor utilizes Google's Gemini 2.0 model for content generation. The system has evolved through two major architectural approaches:

1. Version 1: Used LangChain and Model Context Protocol (MCP) for AI orchestration, incorporating tools like FindIt for web search capabilities.
2. Version 2: Direct integration with Google Generative AI SDK for improved control, performance, and sophisticated prompt engineering.

🌱 Future Development

The project's architecture is designed for extensibility with planned enhancements:

1. Database Persistence: Implementing full content storage using a database
2. User Authentication: Adding user accounts and role-based access
3. Expanded Export Formats: Support for PDF, DOCX, and LMS-specific formats
4. Analytics & Progress Tracking: For monitoring engagement and learning
5. Multi-AI Model Support: Abstract the AI service to support different AI providers

📄 License

This project is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

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