VHumanize is a web-based tool for transforming AI-generated text into natural, human-like content and detecting AI-generated text. It provides advanced paraphrasing, rewriting, and AI detection features, leveraging state-of-the-art NLP models and a modern Svelte frontend.
- 🔍 AI Detection: Detects AI-generated content at line and sentence levels, with visual highlighting and detailed statistics
- 🔄 Humanization Pipeline: Two-step process (Paraphrasing + Rewriting) to convert AI text into more human-like writing
- 🤖 Multi-Model Support: Choose from multiple transformer-based models (T5, BART, Pegasus, etc.) for paraphrasing and rewriting
- ⚡ Enhanced Mode: Optionally use advanced prompts and NLP techniques for higher-quality rewriting
- 🔬 Combined Humanize & Verify: Instantly humanize text and check for AI traces in a single workflow
- 📋 Copy & Share: Easily copy results to clipboard
- 📱 Responsive UI: Clean, modern interface built with SvelteKit and Vite
- Python 3.11+
- Flask - Web framework
- NLTK, spaCy, TextBlob - NLP processing and advanced rewriting
- Transformers (HuggingFace) - Paraphrasing and rewriting models (T5, BART, Pegasus)
- SvelteKit - Modern, component-based UI framework
- Vite - Fast build tool and dev server
- Svelte Stores - Reactive state management
- Lucide Icons - UI icons
humanizer/
├── detector.py # AI detection backend logic
├── download_models.py # Script to download required models
├── main.py # Backend server entry point
├── paraphraser.py # Paraphrasing logic and model management
├── rewriter.py # Advanced rewriting and NLP enhancements
├── requirements.txt # Python dependencies
├── README.md
├── frontend/
│ ├── package.json
│ ├── vite.config.js
│ ├── svelte.config.js
│ ├── src/
│ │ ├── app.html
│ │ ├── lib/
│ │ │ ├── script.js # Frontend logic and API calls
│ │ │ └── style.css # Main CSS
│ │ └── routes/
│ │ └── +page.svelte # Main Svelte page
│ └── static/
│ └── favicon.png
└── __pycache__/
- Python 3.11+
- Node.js 16+
- Git
-
Clone the repository
git clone https://github.com/vardhin/vhumanize.git cd vhumanize
-
Backend Setup
# Install Python dependencies pip install -r requirements.txt # Download required models python download_models.py # Start the backend server python main.py
The API server will start at
http://localhost:8080
-
Frontend Setup
# Navigate to frontend directory cd frontend # Install Node.js dependencies npm install # Start the development server npm run dev
The frontend will be available at
http://localhost:5173
Endpoint | Description |
---|---|
/paraphrase_only |
Paraphrase text with selected model |
/rewrite_only |
Rewrite text for humanization |
/paraphrase_multi |
Paraphrase with multiple models |
/paraphrase_all |
Paraphrase with all available models |
/highlight_ai |
Highlight detected AI-generated sentences/lines |
/humanize_and_check |
Humanize and verify in one step |
/models |
List available models |
/health |
Backend health check |
- Model Selection: Choose or recommend models for paraphrasing/humanization
- Enhanced Mode: Toggle for higher-quality, slower rewriting
- Detection Threshold: Adjust sensitivity for AI detection
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the project
- Create your feature branch (
git checkout -b feature/AmazingFeature
) - Commit your changes (
git commit -m 'Add some AmazingFeature'
) - Push to the branch (
git push origin feature/AmazingFeature
) - Open a Pull Request
This project is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
You are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material
Under the following terms:
- Attribution — You must give appropriate credit to Vardhin, provide a link to the license, and indicate if changes were made
- NonCommercial — You may not use the material for commercial purposes
See the LICENSE file for details or visit Creative Commons for more information.
- Built with SvelteKit and HuggingFace Transformers
- Icons by Lucide
- Thanks to all contributors and the open-source community
If you encounter any issues or have questions, please open an issue on GitHub.