title	emoji	colorFrom	colorTo	sdk	sdk_version	app_file	pinned
Transcriptocast AI Demo	🎙️	blue	purple	docker	3.10.0	app.py	false

🎙️ Transcriptocast AI

A powerful AI-powered application that provides audio transcription, text summarization, and multi-language translation capabilities. Built with FastAPI and deployed on Hugging Face Spaces.

🌟 Key Features

• Audio Transcription: Convert audio to text using OpenAI's Whisper model
• Text Summarization: Generate concise summaries using Facebook's BART model
• Multi-language Translation: Translate between multiple languages using mBART

🚀 Quick Start

Local Development

1. Clone the repository:

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

2. Install dependencies:

pip install -r requirements.txt

3. Run the application:

uvicorn app:app --host 0.0.0.0 --port 7860

Docker Deployment

Build and run using Docker:

docker build -t transcriptocast .
docker run -p 7860:7860 transcriptocast

📚 API Documentation

Endpoints

1. Transcribe Audio (POST /transcribe)

   • Converts audio files to text
   • Accepts: Audio file (MP3, WAV, etc.)
   • Returns: Transcribed text

2. Summarize Text (POST /summarize)

   • Generates concise summaries
   • Accepts: Text input
   • Returns: Summary

3. Translate Text (POST /translate)

   • Translates text between languages
   • Accepts: Text and language codes
   • Returns: Translated text

🛠️ Technical Stack

• Backend Framework: FastAPI
• AI Models:
  • Whisper (OpenAI) for transcription
  • BART (Facebook) for summarization
  • mBART (Facebook) for translation
• Deployment: Hugging Face Spaces
• Container: Docker

🔧 Configuration

The application uses the following environment variables:

• TRANSFORMERS_CACHE: Cache directory for models
• HF_HOME: Hugging Face home directory

📦 Model Information

Whisper Model

• Type: Speech-to-Text
• Version: Base
• Use Case: Audio transcription
• Size: ~1GB

BART Model

• Type: Text Summarization
• Model: facebook/bart-large-cnn
• Use Case: Text summarization
• Features: Abstractive summarization

mBART Model

• Type: Machine Translation
• Model: facebook/mbart-large-50-many-to-many-mmt
• Use Case: Multi-language translation
• Languages: 50+ languages

🌐 Live Demo

Try the live demo at: Hugging Face Space

📝 License

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

🤝 Contributing

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

📫 Contact

For any questions or suggestions, please open an issue in the repository.

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Made with ❤️ by Prashant Ambati

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference