Demo Website | Demo Video

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Txtify is a free open-source web 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. Leveraging the stable-ts library and the whisper models, Txtify offers enhanced transcription accuracy and performance.

Table of Contents

• About
• Demo
• Prerequisites
• Installation
• Usage
• Roadmap
• Report Issues
• Contributing
• License

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, .srt, .vtt, and .sbv.

Demo

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

2. 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.}

3. Run the Docker

docker-compose up --build -d

_{Note: The -d flag runs the container in detached mode.}

4. Stop the Docker Container

docker-compose down

Installation with Pre-Built Docker Image

If you want to use the pre-built Docker image available on Docker Hub, follow these steps:

1. Pull the Docker Imgae:

   docker pull lkmeta/txtify:latest

2. Run the Docker Container

    docker run -d -p 8010:8010 lkmeta/txtify:latest

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.