PROJECT_STATUS.md

Project Status - Ready for Submission

✅ Features Implemented

• ML Graph Classification - PyTorch model integration
• React Frontend - Interactive UI with classification button
• Flask Backend - API with ML endpoints
• Docker Services - Separate containers for frontend/backend
• CI/CD Pipeline - Automated testing and deployment

✅ Components Status

Frontend (React)

• GraphInput component with "Classify Graph" button
• ModelPrediction component for results display
• useGraphClassification hook for API calls
• Production Docker build ready

Backend (Python Flask)

• ML model loaded (graph_classifier_model.pth)
• Classification API endpoint (/classify)
• Health check endpoint (/health)
• CORS enabled for frontend communication

Docker Infrastructure

• Frontend Dockerfile (multi-stage build)
• Backend Dockerfile (Python ML dependencies)
• docker-compose.yml (orchestrated services)
• Health checks and restart policies

CI/CD Pipeline

• Separate frontend/backend testing
• Docker image builds for both services
• GitHub Actions workflow
• Automated deployment ready

🚀 Ready for Deployment

• Repository: https://github.com/ToWhiD073/NodeScape-Empty-Volume.git
• Frontend: http://localhost:3000
• Backend: http://localhost:5000
• All services containerized and production-ready