VoiceNotes AI

Transform your voice into smart study notes instantly! A lightweight Streamlit app that records audio lectures, transcribes them with Groq's Whisper AI, and generates structured study materials using Llama 3.3.

✨ Features

• 🎙️ Live Audio Recording — Built-in mic recorder for seamless audio capture
• 🔊 Fast Transcription — Groq Whisper-large-v3 for accurate, lightning-fast audio-to-text conversion
• 📝 Smart Summaries — AI-powered 3-sentence summaries of your lectures
• 🔑 Key Concepts — Automatically extracts 5 important bullet points
• 🃏 Flashcards — Generates 5 interactive study flashcards (question ↔ answer pairs)
• 📊 JSON Output — Structured data for easy integration with other tools
• ⚡ Real-time UI — Tabbed interface with summary, flashcards, and transcript views
• 🔐 Secure — API key stored locally in .env, never exposed

Quick Overview

• App entry: app.py
• Tech Stack: Streamlit (UI), Groq API (Whisper + Llama 3.3), Python 3.10+
• Use case: Students, researchers, professionals who want instant study notes from lectures

Prerequisites

• Python 3.10 or higher
• A Groq API key (free tier available at console.groq.com)
• ~500MB free disk space for dependencies

Installation & Setup

1. Clone the Repository

git clone https://github.com/prutxvi/VoiceNotes-AI.git
cd "VoiceNotes-AI"

2. Create Virtual Environment (Recommended)

python -m venv .venv
.\.venv\Scripts\Activate.ps1

3. Install Dependencies

python -m pip install --upgrade pip
pip install -r requirements.txt

4. Configure Environment Variables

Create a .env file (or copy from .env.example):

GROQ_API_KEY=your_groq_api_key_here

Get your free API key: https://console.groq.com/keys

🚀 Running the App

streamlit run app.py

The app will open at http://localhost:8501

Quick Steps in the App

1. Click "⏺️ Start Recording" to begin recording
2. Click "⏹️ Stop Recording" when done
3. Click "⚡ Transcribe & Generate" to process
4. Review your Summary, Flashcards, and Transcript in the tabs

Project Structure

VoiceNotes-AI/
├── app.py                    # Main Streamlit application
├── requirements.txt          # Python dependencies
├── .env.example             # Environment variable template
├── LICENSE                  # MIT License
├── README.md               # This file
├── CONTRIBUTING.md         # Contribution guidelines
├── CODE_OF_CONDUCT.md      # Code of conduct
├── .gitignore              # Git ignore rules
├── .github/
│   └── workflows/
│       └── ci.yml          # GitHub Actions CI/CD
└── tests/
    └── test_app_file.py    # Basic smoke tests

📋 Requirements

All dependencies are in requirements.txt:

• streamlit — Web UI framework
• groq — API client for Groq (Whisper + Llama)
• python-dotenv — Environment variable management
• streamlit-mic-recorder — Audio input widget
• pytest — Testing framework

🔧 Configuration

API Keys & Secrets

Never commit .env files! The .gitignore already excludes them.

• Get a free Groq API key: https://console.groq.com/keys
• Store in .env — it's automatically loaded by the app

Models Used

• Whisper Large V3 — Fast, accurate transcription
• Llama 3.3 70B Versatile — Study note generation & flashcards

📝 Usage Examples

Example 1: Lecture Recording

Record a 5-minute lecture on photosynthesis → Get:

• 3-sentence summary
• 5 key concepts
• 5 flashcards for review

Example 2: Interview Notes

Record a 10-minute interview → Organize into:

• Summary of main topics
• Bullet points for reference
• Question-answer pairs for later

🤝 Contributing

See CONTRIBUTING.md for guidelines.

Quick steps:

1. Fork the repo
2. Create a feature branch (git checkout -b feature/your-feature)
3. Commit changes (git commit -m "feat: add new feature")
4. Push to branch (git push origin feature/your-feature)
5. Open a Pull Request

📜 License

This project is licensed under the MIT License — see LICENSE for details.

🙏 Acknowledgments

• Built with Streamlit
• Powered by Groq API (Whisper + Llama)
• Community contributions welcome!

📞 Support & Feedback

Found a bug? Have a feature request? Open an issue.

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Happy note-taking! 🎓