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RoadMap
This roadmap outlines the step-by-step development plan for the Chatter Box Application, a full-stack chat platform with AI integration. The project uses React (Frontend) and Spring Boot (Backend) with support for GPT, Grok, Bedrock, Claude, etc.
✅ Initialize React project using Vite or Create React App (CRA).
✅ Install dependencies:
npm install react-router-dom axios socket.io-client tailwindcss✅ Set up project structure with components, services, and WebSocket handling.
✅ Create a Spring Boot project using Maven.
✅ Set up Spring WebSockets, Spring Security, and Spring Data JPA (PostgreSQL/MongoDB).
✅ Configure CORS, WebSocket, and API routes.
✅ Configure PostgreSQL / MongoDB for storing user data & messages.
✅ Implement JWT-based authentication (Spring Security + OAuth2 support).
✅ Create User API:
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/register– User Signup -
/login– User Login -
/logout– User Logout -
/profile– Get user details
✅ Store users in PostgreSQL/MongoDB.
✅ Create Signup/Login UI.
✅ Integrate JWT-based authentication using Axios.
✅ Store tokens securely (localStorage / HttpOnly Cookies).
✅ Configure Spring WebSocket (STOMP protocol) for real-time messaging.
✅ Create ChatController to handle WebSocket communication.
✅ Save chat messages to the database.
✅ Implement WebSocket client in React (websocket.js).
✅ Build Chat UI (chat box, message list, typing indicators).
✅ Handle message sending & receiving in real-time.
✅ Implement AIController to support multiple AI models.
✅ Create API to send user queries to selected AI models.
✅ Implement AI response caching (Redis for fast access).
✅ Add AI model selection UI (Dropdown for GPT, Grok, Bedrock, Claude).
✅ Display AI responses dynamically.
✅ Add message history retrieval API.
✅ Enable file sharing (AWS S3 / Firebase Storage).
✅ Implement sentiment analysis & language translation.
✅ Implement message history UI.
✅ Add file upload & preview support.
✅ Optimize performance (lazy loading, WebSocket reconnections).
✅ Deploy React frontend on Vercel / Netlify.
✅ Deploy Spring Boot backend on AWS EC2 / DigitalOcean / Heroku.
✅ Host PostgreSQL/MongoDB on AWS RDS / MongoDB Atlas.
✅ Set up Docker & Kubernetes (optional).
✅ Configure GitHub Actions / Jenkins for CI/CD.
✅ Implement logging & monitoring (Prometheus, Grafana, ELK Stack).
✅ Write unit tests (JUnit for backend, Jest for frontend).
✅ Perform integration tests for WebSockets & AI APIs.
✅ Conduct user testing & bug fixes.
✅ Add push notifications for new messages.
✅ Improve UI/UX with animations & themes.
✅ Implement end-to-end encryption for messages.
Once core features are complete, focus on:
🔹 Scalability: Load balancing, horizontal scaling.
🔹 AI Fine-Tuning: Custom AI response tuning.
🔹 Advanced Features: Voice & video chat integration.