Research Paper Paraphraser

A tool for paraphrasing research papers and academic documents while preserving their structure, citations, equations, and technical terminology.

Features

• Supports multiple document formats (DOCX, PDF, TXT)
• Preserves document structure and formatting
• Handles special content:
  • Citations and references
  • Mathematical equations
  • Technical terminology
  • Section-specific formatting
• Parallel processing for better performance
• User-friendly web interface
• Progress tracking
• Multiple language model support

Installation

1. Clone the repository:

git clone https://github.com/Mr-vero/ParaphraseDoctor
cd ParaphraseDoctor

2. Install the required dependencies:

pip install numpy tqdm python-docx pypdf transformers torch gradio

Usage

1. Run the application:

python main.py

2. Access the web interface:

   • The application will start a local server
   • Open your web browser and go to http://localhost:7860
   • A public URL will also be provided for temporary access

3. Using the interface:

   • Upload your document (supported formats: .docx, .pdf, .txt)
   • Configure preservation options:
     • Preserve Citations: Keep citation formatting and references
     • Preserve Equations: Maintain mathematical formulas
   • Click "Submit" to start processing
   • Monitor progress through the progress bar
   • Download the paraphrased document when complete

How It Works

Document Processing Pipeline

1. Document Reading

   • Parses different document formats
   • Extracts text while maintaining structure
   • Identifies special content (citations, equations, etc.)

2. Content Analysis

   • Identifies different sections (abstract, methodology, etc.)
   • Detects technical terms and special notation
   • Preserves document hierarchy

3. Paraphrasing

   • Uses specialized models for different content types:
     • Main content: IndoT5-base-paraphrase
     • Technical sections: MT5-small
   • Processes content in parallel for better performance
   • Maintains context and coherence

4. Structure Preservation

   • Keeps original formatting
   • Maintains citations and references
   • Preserves equations and technical terms
   • Retains document layout

Configuration

The tool can be configured through the following parameters in document_paraphraser.py:

self.models = {
    'main': {
        'name': "Wikidepia/IndoT5-base-paraphrase",
        'max_length': 128,
        'batch_size': 4
    },
    'technical': {
        'name': "google/mt5-small",
        'max_length': 64,
        'batch_size': 8
    }
}

System Requirements

• Python 3.7 or higher
• Minimum 4GB RAM (8GB recommended)
• CUDA-capable GPU (optional, for better performance)
• Internet connection for initial model download
• Supported operating systems:
  • Windows 10/11
  • macOS 10.15 or later
  • Linux (Ubuntu 18.04 or later)

Limitations

1. Processing Speed

   • Large documents may take significant time
   • Performance depends on hardware capabilities
   • GPU recommended for faster processing

2. Content Handling

   • Complex mathematical equations might need manual review
   • Some technical terminology may require verification
   • Document formatting might need minor adjustments

3. Model Limitations

   • Initial model loading takes time
   • Internet required for first run
   • Memory usage increases with document size

Troubleshooting

Common issues and solutions:

1. Memory Error

   • Reduce batch size in configuration
   • Close other applications
   • Use smaller document chunks

2. Slow Processing

   • Enable GPU if available
   • Reduce document size
   • Adjust batch processing parameters

3. Format Issues

   • Ensure document is properly formatted
   • Check for supported file types
   • Verify document encoding

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

License

This project is licensed under the MIT License. See LICENSE for details.

Acknowledgments

• HuggingFace Transformers for NLP models
• Gradio for the web interface
• Python-docx for document processing
• PyPDF for PDF handling

Support

For issues and feature requests:

1. Check existing issues on GitHub
2. Create a new issue with:
   • Clear description
   • Steps to reproduce
   • System information
   • Error messages if any

Future Improvements

Planned features:

• Additional language model support
• Enhanced formatting preservation
• Batch processing capabilities
• Custom model training options
• API integration support