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Spyros01/polyglot-meeting-assistant

sourceHugging Facemitupdated 1y agoView on Hugging Face
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App README

Polyglot Meeting Assistant

An AI-powered meeting transcription and analysis tool that automatically transcribes audio, extracts key insights, and provides semantic search across your meetings.

✨ Features

  • —🎙️ Audio Transcription - Upload audio files (MP3, WAV, M4A) for automatic transcription
  • —📄 Text Processing - Upload text files (TXT, MD, RTF) for analysis
  • —🧠 AI-Powered Analysis - Automatic summarization, action item extraction, and key decision identification
  • —🔍 Semantic Search - Search across all your meetings using natural language
  • —👥 Session Management - Isolated user sessions with persistent data
  • —📱 Modern UI - Clean, responsive interface built with React and Material-UI

🚀 Quick Start

Using Docker (Recommended)

bash
git clone https://github.com/yourusername/polyglot-meeting-assistant.git
cd polyglot-meeting-assistant
docker-compose up --build

Visit http://localhost:3000 to start using the application.

Local Development

bash
# Backend
cd backend
pip install -r requirements.txt
python -m uvicorn src.api:app --reload --port 8000

# Frontend
cd frontend
npm install
npm start

🛠️ Tech Stack

  • —Backend: FastAPI, Python 3.11+
  • —Frontend: React 19, Material-UI
  • —AI/ML: OpenAI Whisper (ASR), HuggingFace Transformers (NLP), FAISS (Vector Search)
  • —Deployment: Docker, HuggingFace Spaces

📖 Usage

  1. 1.Upload Files - Drag and drop audio or text files
  2. 2.Automatic Processing - AI models transcribe and analyze content
  3. 3.View Insights - Get summaries, action items, and key decisions
  4. 4.Search - Use natural language to find specific content across meetings

🔧 API Endpoints

  • —POST /api/v1/upload - Upload and process files
  • —POST /api/v1/search - Search across meetings
  • —GET /api/v1/statistics - Get session statistics
  • —GET /api/v1/health - Health check

📝 License

MIT License - see LICENSE file for details.

🤝 Contributing

  1. 1.Fork the repository
  2. 2.Create a feature branch
  3. 3.Make your changes
  4. 4.Submit a pull request