MentorMind is an AI-powered research and note-taking platform that transforms diverse content sources into structured knowledge through intelligent transcription and analysis. Multi-format content processing with real-time transcription, AI summaries, interactive assessments, and conversational AI assistant, currently used by 15+ researchers across different parts of the country.

🌟 Features

• Audio Transcription: Upload audio recordings and get accurate transcriptions with timestamps
• YouTube Processing: Generate transcripts and educational content from YouTube videos
• AI-Generated Summaries: Create concise, bullet-point summaries of lectures
• Interactive Quizzes: Test knowledge with automatically generated multiple-choice questions
• Conversational AI Tutor (Ask Tutor): Get answers to questions about lecture content using Consversational AI Agent

🛠️ Technologies Used

Backend

• FastAPI - High-performance Python web framework
• Deepgram - AI-powered speech recognition
• Groq - Ultra-fast LLM inference API
• LLama 3.3 - Open-source large language model
• Python - Programming language

Frontend

• Next.js - React framework for production
• React - JavaScript library for building user interfaces
• Tailwind CSS - Utility-first CSS framework
• Framer Motion - Animation library for React

📋 Installation

Prerequisites

• Node.js (v18 or newer)
• Python (v3.9 or newer)
• API keys for Deepgram and Groq

Backend Setup

1. Clone the repository

   git clone https://github.com/yourusername/MentorMind.git
   cd MentorMind

2. Set up the Python virtual environment

   cd backend
   python -m venv venv
   source venv/bin/activate  # On Windows, use: venv\Scripts\activate

3. Install dependencies

   pip install -r requirements.txt

4. Create a .env file in the backend directory

   DEEPGRAM_API_KEY=your_deepgram_api_key
   GROQ_API_KEY=your_groq_api_key
   

5. Start the backend server

   uvicorn app:app --reload

Frontend Setup

1. Navigate to the frontend directory

   cd ../frontend

2. Install dependencies

   npm install

3. Start the development server

   npm run dev

🚀 Usage

1. Upload Content:

   • Upload an audio file (MP3, WAV, etc.)
   • Upload a PDF document
   • Provide a YouTube URL

2. View Transcription:

   • See the full transcription with timestamps
   • Click on timestamps to jump to that part in the audio
   • Listen to the audio with the integrated player

3. Read Summary:

   • View an AI-generated bullet-point summary
   • Download the summary as text or PDF
   • Copy the summary to clipboard

4. Test Knowledge:

   • Take a quiz based on the lecture content
   • Get immediate feedback on your answers
   • View explanations for incorrect answers

5. Ask Tutor:

   • Ask questions about the lecture content
   • Get AI-generated answers based on the transcript

📂 Project Structure

MentorMind/
├── backend/
│   ├── app.py              # FastAPI application
│   ├── requirements.txt    # Python dependencies
│   └── uploads/            # Temporary storage for uploads
├── frontend/
│   ├── public/             # Static assets
│   ├── src/
│   │   ├── app/            # Next.js app router
│   │   ├── components/     # React components
│   │   ├── hooks/          # Custom React hooks
│   │   ├── lib/            # Utility functions
│   │   └── utils/          # Helper functions
│   ├── package.json        # Node.js dependencies
│   └── tailwind.config.js  # Tailwind CSS configuration
└── README.md               # Project documentation

👥 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

🙏 Acknowledgements

• Deepgram for speech recognition technology
• Groq for fast LLM inference
• Meta AI for the LLama 3.3 models
• All the open-source libraries that made this project possible