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.github | 2025-03-20 |
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[00bf8a] cf |
assets | 2025-03-21 |
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[faa9c2] Pages UPL |
.gitignore | 2025-03-21 |
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[0df713] Icon upload |
LICENSE | 2025-03-20 |
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[10f9dc] Initial commit |
README.md | 2025-03-20 |
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[4ed9dc] Update README |
index.html | 2025-03-21 |
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[a263d0] Minor Adjustment |
requirements.txt | 2025-03-20 |
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[21c8ab] Zylthra |
zylthra.ico | 2025-03-21 |
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[0df713] Icon upload |
zylthra.py | 2025-03-21 |
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[7195cb] Set icon |
Welcome to Zylthra, a powerful Python-based desktop application built with PyQt6, designed to generate synthetic datasets using the DataLLM API from data.mostly.ai. This tool allows users to create custom datasets by defining columns, configuring generation parameters, and saving setups for reuse, all within a sleek, dark-themed interface.
Zylthra is a Python application that runs on any platform with the proper dependencies. Follow these steps to set it up:
bash
git clone https://github.com/VoxDroid/Zylthra.git
cd Zylthra
bash
pip install -r requirements.txt
bash
python zylthra.py
Upon launching Zylthra, you’ll see a tabbed interface with three sections: Generator, Configurations, and Help. The Generator tab is for creating datasets, Configurations manages saved setups, and Help provides detailed guidance.
voxgen
directory in the working directory for configurations (database.db
) and outputs (Generated
folder).Here are previews of the main tabs in Zylthra:
![]() Generator Tab |
![]() Configurations Tab |
If you enjoy this project or want to support its development, consider these options:
Zylthra is open-source, and contributions are welcome! Here’s how to get involved:
1. Fork the repository: https://github.com/VoxDroid/Zylthra.
2. Create a branch for your feature or fix.
3. Submit a pull request with a clear description of your changes.
4. Adhere to coding standards (to be detailed in a future CONTRIBUTING.md
).
5. Test your changes thoroughly before submission.
This project is licensed under the MIT License. Use, modify, and distribute it freely per the license terms.
To build from source, install the following Python packages:
- PyQt6
(for the GUI)
- pandas
(for data handling)
- datallm
(for synthetic data generation)
- qtawesome
(for icons)
Create a requirements.txt
file with these dependencies and run pip install -r requirements.txt
.