This folder contains all the documentation for the WebTrace AI project - an AI-powered website generation detection system.

• SIMPLIFIED_SETUP.md - Quick setup guide for the project

• CODEBASE_EXPLANATION.md - Complete explanation of the codebase structure and data flow
• FRONTEND_MODEL_INTEGRATION_FLOW.md - Detailed flow of how frontend input processes through the custom tree model

• MODEL_IMPROVEMENT_GUIDE.md - Guide for improving model performance
• MODEL_ANALYSIS_SUMMARY.md - Analysis of model performance and issues
• MODEL_IMPROVEMENT_RESULTS.md - Results from model improvement attempts

• CUSTOM_TREE_MODEL_RESULTS.md - Performance and insights from the custom decision tree model
• CUSTOM_TREE_INTEGRATION_SUCCESS.md - Success story of integrating the custom tree model with frontend endpoints

1. Start with SIMPLIFIED_SETUP.md to get the project running
2. Read CODEBASE_EXPLANATION.md to understand the system architecture

1. FRONTEND_MODEL_INTEGRATION_FLOW.md - Understand the complete data flow
2. CUSTOM_TREE_INTEGRATION_SUCCESS.md - See how the custom model was integrated

1. MODEL_IMPROVEMENT_GUIDE.md - Learn about model improvement strategies
2. CUSTOM_TREE_MODEL_RESULTS.md - Understand the custom tree model performance

• Custom Decision Tree: 96.15% accuracy
• Key Features: height (59%), gradient_magnitude (30%), avg_saturation (11%)
• Model Type: Custom implementation from scratch
• Status: ✅ Production ready

• Frontend: React/Vite application
• Backend: FastAPI with custom ML pipeline
• Model: Custom decision tree classifier
• Features: 19 visual + 6 HTML features

This documentation reflects the current state of the project as of the latest development phase. The system is now using the custom tree model for all frontend predictions with 96.15% accuracy.

Last Updated: Current development phase
Model Status: ✅ Custom tree model integrated and operational
Frontend Integration: ✅ Complete and functional