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Web application that converts audio and video to text using AI, supporting various formats and self-hosting.

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Whisper SeamlessM4T Hugging Face DeepL FastAPI Python

Txtify is a free open-source wep application that transcribes and translates audio from YouTube videos or uploaded media files. It now runs on Docker for easier deployment and includes monitoring capabilities.

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About

Txtify is designed to simplify the process of converting audio and video content into text. Whether you're looking to transcribe a YouTube video or your own audio/video files, Txtify offers an easy-to-use interface and powerful AI models to ensure accuracy and speed. The application supports multiple output formats including .txt, .pdf, .srt, .vtt, and .sbv.

Demo

Txtify Demo Video
Check out the demo video to see Txtify in action.

Prerequisites

Before you begin, ensure you have met the following requirements:

  • Python 3.10 installed on your machine
  • Docker (containerized deployment)
  • An API key for DeepL if you want to enable translation (in case you need to use this tool for translation)

Installation

To install and run Txtify using Docker, follow these steps:

  1. Clone the repository:
git clone https://github.com/lkmeta/txtify.git
cd txtify
  1. Set Up Environment Variables
cp .env.example .env

Edit the .env file and add your DeepL API key for translation, and any other necessary environment variables.

  1. Build the Docker Image
docker build -t txtify .
  1. Run the Docker Container
docker run -d -p 8010:8010 --env-file .env --name txtify_container txtify

Note: The --env-file option passes your environment variables to the container.
Note: The -d flag runs the container in detached mode.

Usage

Access the Application

Open your web browser and navigate to http://localhost:8010 to access Txtify.

Monitoring

To monitor the application and the transcription processes:

  1. Ensure you have completed the installation steps above.

  2. You can view the logs of the running Docker container to monitor the application output.

docker logs -f txtify_container

Note: The -f option follows the log output in real-time.

Online Simulation Demo

To understand how Txtify works, you can use the online simulation demo. Visit Txtify Website and follow the instructions to upload your media or enter a YouTube URL for a simulated transcription process.

Roadmap

  • Basic transcription functionality
  • Support for multiple output formats
  • Integration with DeepL for translations
  • Improved UI/UX
  • Containerized the application
  • Enhance performance and scalability
  • Web browser Whisper option

Report Issues

If you encounter any issues, bugs, or have suggestions for improvements, please report them using one of the following methods:

  • Contact Form: Visit our Contact Page and submit your feedback or issue.
  • GitHub Issues: Open an issue on the repository's issue tracker. Please provide detailed information to help us address the problem effectively.

Your feedback is valuable and helps us improve Txtify!

Contributing

Feel free to contribute by opening issues, suggesting improvements, or submitting pull requests. Your feedback is highly appreciated!

License

This project is licensed under Apache 2.0.

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Web application that converts audio and video to text using AI, supporting various formats and self-hosting.

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  • Python 40.2%
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