Peer-Review Platform Documentation

Welcome to Peer-Review Platform

The Peer-Review Platform is a comprehensive documentation analysis and improvement tool that combines traditional style checking with AI-powered content enhancement. This system analyzes documents for style compliance, detects ambiguities, and provides intelligent suggestions for improvement.

Key Features

  • Multi-format Support: Analyze PDF, DOCX, Markdown, and AsciiDoc documents

  • 45+ Style Rules: Comprehensive rule system covering grammar, punctuation, structure, and formatting

  • AI-powered Rewriting: Two-pass improvement system using Ollama integration

  • Ambiguity Detection: Specialized detectors for fabrication risks, missing actors, and unclear references

  • Real-time Analysis: WebSocket-based communication for instant feedback

  • Extensible Architecture: Modular design for easy extension and customization

Getting Started

Technology Stack

  • Backend: Flask 3.0+, Python 3.8+

  • AI/ML: SpaCy 3.7+, Transformers 4.36+, Ollama 0.1+

  • Document Processing: PyPDF2, python-docx, python-markdown

  • Frontend: HTML5, JavaScript ES6+, WebSockets

  • Deployment: Docker, Docker Compose

Architecture Overview

The system follows a modular architecture with clear separation of concerns:

graph TD
    A[Document Input] --> B[Format Detection]
    B --> C[Document Parser]
    C --> D[Style Analyzer]
    D --> E[Rules Engine]
    D --> F[Ambiguity Detector]
    D --> G[AI Rewriter]
    E --> H[Analysis Results]
    F --> H
    G --> H
    H --> I[Client Interface]

Quick Start

  1. Installation

    git clone https://github.com/gtrivedi88/peer-lens.git
    cd peer-lens
    pip install -r requirements.txt
  2. Configuration

    cp config.example.py config.py
    # Edit config.py with your settings
  3. Run the Application

    python app.py
  4. Access the Interface

    Open your browser to http://localhost:5000

Support

For questions, issues, or contributions:

  • Documentation: Browse the architecture and how-to guides

  • Issues: Report bugs or request features on GitHub

  • Contributions: See the contribution guidelines for development setup

License

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