REALSCORE - Automated Text Scoring System

REALSCORE is a privacy-focused, browser-based automated text scoring system that provides real-time feedback on writing quality. Using TensorFlow.js, it analyzes text directly in your browser without sending data to any server.

🚀 Features

• Real-time Analysis: Get instant feedback as you write
• Complete Privacy: All processing happens in your browser
• Multiple Scoring Dimensions:
  • Grammar and syntax
  • Content coherence
  • Vocabulary richness
  • Topic relevance
  • Overall quality score
• Rich Text Editor: Full formatting capabilities
• Data Persistence: Auto-save and local storage
• Export Options: Save your work in multiple formats
• Responsive Design: Works on desktop and mobile
• Offline Support: Continue working without internet

🛠️ Technology Stack

• Frontend: React 18, TypeScript, Tailwind CSS
• Text Processing: TensorFlow.js, Universal Sentence Encoder
• State Management: React Context API
• Storage: LocalForage
• Text Editor: React Quill
• Visualization: Chart.js with React Chartjs 2
• Icons: Lucide React
• Build Tool: Vite

📋 Requirements

• Node.js 18.0.0 or higher
• Modern web browser (Chrome, Firefox, Safari, Edge)
• 4GB RAM minimum (8GB recommended)
• 500MB free disk space for model storage

🚀 Getting Started

1. Clone the repository:

   git clone https://github.com/divuzki/realscore.git
   cd realscore

2. Install dependencies:

   npm install

3. Start the development server:

   npm run dev

4. Open your browser and navigate to http://localhost:5173

📝 Usage

1. Create a New Document:

   • Click the "Create New Document" button
   • Start typing in the rich text editor

2. View Analysis:

   • See real-time scores in the sidebar
   • Review detailed breakdowns for each metric
   • Get suggestions for improvement

3. Save and Export:

   • Documents auto-save to local storage
   • Export to PDF, DOCX, or TXT formats
   • Access previous documents from the dropdown menu

🔍 Scoring Metrics

Grammar & Style (0-10)

• Sentence structure
• Punctuation
• Subject-verb agreement
• Writing mechanics

Coherence & Organization (0-10)

• Logical flow
• Paragraph structure
• Transitions
• Overall organization

Vocabulary Usage (0-10)

• Word choice
• Vocabulary diversity
• Language sophistication
• Context appropriateness

Topic Relevance (0-10)

• Content focus
• Main idea development
• Supporting details
• Topic consistency

🔒 Privacy Features

• All text analysis happens client-side
• No data sent to external servers
• Local storage encryption
• Optional data purging
• No analytics or tracking

🛠️ Development

Project Structure

src/
├── components/     # React components
├── hooks/         # Custom React hooks
├── types/         # TypeScript definitions
├── utils/         # Utility functions
└── main.tsx       # Application entry point

Key Components

• TextEditor: Rich text editing interface
• ScoreSidebar: Real-time scoring display
• ScoreRadarChart: Score visualization
• ModelLoader: ML model initialization

Custom Hooks

• useTensorflowModels: ML model management
• useDocumentStorage: Local storage operations

🤝 Contributing

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

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• TensorFlow.js team for browser ML capabilities
• React team for the excellent framework
• Open source community for various tools and libraries

⚠️ Known Limitations

• Initial model loading may take time
• Heavy CPU usage during analysis
• Limited to modern browsers
• Requires JavaScript enabled

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Built with ❤️ using React and TensorFlow.js