vkcodes/ai-meeting-saas

AI Meeting Assistant

An intelligent meeting assistant that helps you transcribe, analyze, and summarize your meeting recordings. It processes audio files, generates transcripts, and provides AI-powered insights including meeting summaries, key points, and action items.

<img width="959" height="478" alt="Screenshot 2025-10-23 235722" src="https://github.com/user-attachments/assets/053f2df6-6e3c-46d1-b895-e3f778b97880" /> <img width="943" height="479" alt="Screenshot 2025-10-24 010754" src="https://github.com/user-attachments/assets/3750be10-f1da-48a2-aa43-f2e099c2c0b4" />

✨ Features

• —🎙️ Audio Processing
• —Upload and process audio recordings (WAV, MP3, OGG, M4A, WebM)
• —Automatic format conversion
• —Background noise reduction

• —📝 Transcription
• —High-accuracy speech-to-text
• —Speaker diarization
• —Timestamped transcripts

• —🤖 AI Analysis
• —Smart meeting title generation
• —Concise meeting summaries
• —Key points and action items
• —Sentiment analysis
• —Follow-up recommendations

• —🌐 Web Interface
• —Responsive design
• —Real-time processing status
• —Downloadable reports
• —Dark/Light theme

🚀 Getting Started

Prerequisites

• —Python 3.8+
• —uv (Modern Python package manager)
• —Google Gemini API key (for AI analysis)

Installation

1. 1.Clone the repository:

   git clone <repository-url>.git
   cd ai-meeting-saas

1. 1.Copy the example environment file and update with your API key:

   cp .env.example .env
   # Edit .env with your API key

1. 1.Install dependencies using uv:

   uv sync

Environment Variables

Create a .env file with the following variables:

# Required
GENAI_API_KEY=your_gemini_api_key
HF_API_KEY=your_hf_api_key

🚦 Usage

1. 1.Start the development server:

   uv run app.py

1. 1.Open your browser and navigate to http://localhost:8000

1. 1.Record your online meeting and upload to the server

1. 1.View the processed results including transcription and AI analysis

🏗️ Project Structure

ai-meeting-saas/
├── .env.example           # Example environment variables
├── app.py                # Main Flask application
├── pyproject.toml        # Project metadata and dependencies
├── services/
│   ├── __init__.py
│   ├── audio_transcriber.py  # Audio processing and transcription
│   └── ai_analyzer.py        # AI-powered meeting analysis
├── templates/             # HTML templates
│   ├── index.html
│   └── view.html
├── uploads/              # Store uploaded audio files
└── output/               # Generated transcripts

🛠️ Development

1. 1.Install development dependencies:

   uv pip install -e ".[dev]"

1. 1.Run the development server with auto-reload:

   python -m flask --app app.py --debug run

1. 1.Run tests:

   pytest

⚙️ Configuration

Application Settings

You can configure the application by setting environment variables in your .env file:

• —DEBUG: Enable debug mode (default: False)
• —UPLOAD_FOLDER: Directory for uploaded files (default: uploads)
• —MAX_CONTENT_LENGTH: Maximum file size in bytes (default: 100MB)
• —ALLOWED_EXTENSIONS: Comma-separated list of allowed file extensions (default: wav,mp3,ogg,m4a,webm)

AI Configuration

• —GENAI_API_KEY: Your Google Gemini API key (required)
• —MODEL_NAME: AI model to use (default: gemini-pro)
• —TEMPERATURE: Controls randomness in AI responses (0.0 to 1.0)

📚 Documentation

For detailed documentation, please refer to the docs directory.

📄 License

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

🤝 Contributing

Contributions are welcome! Please follow these steps:

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

Please ensure your code follows the project's style guidelines and includes appropriate tests.

Made with ❤️ in India