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# π€β‘οΈπ¨ AI Text Humanizer & Detector Pro
<div align="center">




[](https://huggingface.co/spaces)
[](https://railway.app)
[](https://render.com)
**π Deploy your AI humanizer to the cloud with one click**
[π Quick Deploy](#-deployment-options) β’
[π Documentation](#-features) β’
[π§ Setup Guide](#-installation) β’
[π‘ Examples](#-usage-examples) β’
[π Support](#-support)
</div>
---
A comprehensive web application for transforming AI-generated text into natural, human-like writing while providing advanced AI detection capabilities.
## β¨ Features
<div align="center">



</div>
<table>
<tr>
<td width="33%">
### π **Text Humanizer**
- π **Advanced Vocabulary Enhancement**
- π **Sentence Flow Optimization**
- ποΈ **Structure Diversification**
- π **Academic Tone Preservation**
- β‘ **Multi-level Processing**

</td>
<td width="33%">
### π΅οΈ **AI Detector**
- π― **7-Point Analysis System**
- π **Detailed Scoring Breakdown**
- π **Confidence Level Assessment**
- π€ **Pattern Recognition Engine**
- β‘ **Real-time Analysis**

</td>
<td width="33%">
### π **Combined Processing**
- π **One-Click Workflow**
- π **Optimization Loop**
- β
**Quality Validation**
- π **Performance Metrics**
- π― **Result Verification**

</td>
</tr>
</table>
## π Live Demo
Visit the live application: [Hugging Face Spaces](https://huggingface.co/spaces/YOUR_USERNAME/ai-text-humanizer)
## π¦ Installation
<div align="center">

</div>
### π§ **Local Development Setup**
<details>
<summary>π <strong>System Requirements</strong></summary>
| Component | Requirement | Recommended |
|-----------|-------------|-------------|
|  | 3.8+ | 3.9+ |
|  | 4GB+ | 8GB+ |
|  | 2GB+ | 5GB+ |
|  | For models | Stable connection |
</details>
### π **Quick Start**
```bash
# π₯ 1. Clone Repository
git clone https://github.com/SidddhantJain/Humaniser-Sid.git
cd Humaniser-Sid
# π 2. Setup Environment
python -m venv .venv
.venv\Scripts\activate # Windows
source .venv/bin/activate # Linux/Mac
# π¦ 3. Install Dependencies
pip install -r requirements.txt
# π 4. Launch Application
python app.py
```
<div align="center">

</div>
### π **Dependencies**
<table>
<tr>
<td width="50%">
#### π― **Core Dependencies**
```
gradio==4.44.0 # Web interface
transformers==4.35.0 # AI models
torch==2.1.0 # Deep learning
nltk==3.8.1 # Language processing
```
</td>
<td width="50%">
#### π§ **Supporting Libraries**
```
textstat==0.7.3 # Text analysis
numpy==1.24.3 # Numerical computing
pandas==2.0.3 # Data manipulation
protobuf # Model serialization
```
</td>
</tr>
</table>
## π οΈ Technical Details
### Humanization Algorithms
- **Vocabulary Diversification**: WordNet-based synonym replacement
- **Structural Variation**: Sentence pattern modification
- **Natural Flow Enhancement**: Academic connector and hedge phrase insertion
- **Linguistic Pattern Breaking**: AI-specific phrase elimination
### AI Detection Metrics
1. **AI Phrase Detection**: Identifies common AI-generated expressions
2. **Vocabulary Repetition**: Analyzes overuse of academic terms
3. **Structure Patterns**: Detects repetitive sentence starters
4. **Transition Overuse**: Measures excessive formal connectors
5. **Formal Pattern Recognition**: Identifies robotic phrasing
6. **Sentence Consistency**: Analyzes unnatural uniformity
7. **Readability Assessment**: Evaluates writing naturalness
## π Usage Examples
### Input (AI-Generated):
```
The implementation of artificial intelligence algorithms demonstrates significant improvements in computational efficiency and accuracy metrics across various benchmark datasets.
```
### Output (Humanized):
```
AI algorithms show notable improvements in both computational efficiency and accuracy when tested across different benchmark datasets. These results indicate considerable advances in performance.
```
## π§ Configuration
### Humanization Levels:
- **Light**: Basic vocabulary substitution
- **Medium**: Vocabulary + natural flow enhancement
- **Heavy**: All techniques including structure modification
### AI Detection Thresholds:
- **0-20%**: Likely human-written
- **21-40%**: Possibly AI-generated
- **41-60%**: Probably AI-generated
- **61-80%**: Likely AI-generated
- **81-100%**: Very likely AI-generated
## π Deployment Options
<div align="center">

</div>
<table>
<tr>
<td width="33%">
### π€ **Hugging Face Spaces**
#### β RECOMMENDED - FREE

**β
Benefits:**
- π Completely FREE forever
- β‘ Auto-deployment from files
- π Global CDN (fast worldwide)
- π SSL certificate included
- π οΈ No coding required
- π± Mobile-friendly interface
**π Deploy Steps:**
1. Go to [huggingface.co/spaces](https://huggingface.co/spaces)
2. Click "Create new Space"
3. Choose Gradio SDK
4. Upload `app.py` & `requirements.txt`
5. β¨ Auto-deploy in 2-3 minutes!
</td>
<td width="33%">
### π **Railway**
#### π° FREE TIER AVAILABLE

**β
Benefits:**
- π― GitHub integration
- π Auto-deploy on push
- πΎ Persistent storage
- π Built-in monitoring
- π§ Environment variables
- π³ Credit card not required
**π Deploy Steps:**
1. Push code to GitHub
2. Go to [railway.app](https://railway.app)
3. "Deploy from GitHub repo"
4. Select your repository
5. π Railway auto-detects & deploys
</td>
<td width="33%">
### π¨ **Render**
#### π° FREE TIER AVAILABLE

**β
Benefits:**
- π GitHub integration
- π Free SSL certificates
- π Automatic deploys
- π Scalable infrastructure
- π» Custom domains
- π Real-time logs
**π Deploy Steps:**
1. Push to GitHub
2. Go to [render.com](https://render.com)
3. "New Web Service"
4. Connect GitHub repo
5. Set build: `pip install -r requirements.txt`
6. Set start: `python app.py`
</td>
</tr>
</table>
---
### π₯ **Recommended: Hugging Face Spaces**
<div align="center">

</div>
| Feature | Hugging Face | Railway | Render |
|---------|-------------|---------|---------|
| π° **Cost** |  |  |  |
| β‘ **Setup Time** |  |  |  |
| π οΈ **Configuration** |  |  |  |
| π **Global CDN** |  |  |  |
| π± **Mobile Optimized** |  |  |  |
## βοΈ Ethical Usage
This tool is designed for:
- β
Improving writing quality and naturalness
- β
Educational purposes and learning
- β
Understanding AI detection mechanisms
- β
Research and development
**Important Guidelines:**
- π« Do not use for plagiarism or academic dishonesty
- π« Do not violate institutional policies
- π« Do not misrepresent authorship
- β
Maintain transparency about AI assistance
- β
Follow academic integrity guidelines
## π€ Contributing
Contributions are welcome! Please feel free to submit pull requests or open issues for:
- Bug fixes
- Feature enhancements
- Algorithm improvements
- Documentation updates
## π License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## π Acknowledgments
- NLTK team for natural language processing tools
- Hugging Face for hosting and deployment platform
- Gradio team for the web interface framework
- Open source community for various libraries and tools
## π Support
For questions, issues, or suggestions:
- Open an issue on GitHub
- Contact: [mishrikotkar.siddhant@gmail.com]
---
**Disclaimer**: This tool is for educational and research purposes. Users are responsible for ensuring compliance with their institution's policies and maintaining academic integrity.
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