StudyBot
AI-Powered Chat Application
Project Overview
StudyBot is a full-stack web application that delivers an intelligent conversational AI experience using Azure OpenAI's Assistant API. The application provides a modern chat interface with secure user authentication, real-time message delivery, and persistent conversation history.
Real-Time Communication
Bidirectional WebSocket connections using Socket.io for instant messaging
AI-Powered Responses
Azure OpenAI Assistant API for intelligent, context-aware conversations
Secure Authentication
JWT-based authentication with bcrypt password hashing
Persistent Storage
MongoDB for maintaining conversation continuity across sessions
Technical Specifications
Key Features
Secure Authentication System
Comprehensive JWT-based authentication with bcrypt password hashing, providing secure user registration, login, and session management. All user credentials are protected with industry-standard encryption.
- JWT tokens with 24-hour expiration
- bcrypt hashing with 10 salt rounds
- Custom authentication middleware for route protection
- Token storage in localStorage with Axios interceptors
Real-Time WebSocket Communication
Bidirectional communication using Socket.io for instant message delivery. Messages are broadcast to all connected clients in real-time, creating a seamless chat experience with connection state management.
- WebSocket connections with Socket.io
- User-specific socket management
- Real-time message broadcasting
- Automatic reconnection handling
AI-Powered Conversations
Integration with Azure OpenAI Assistant API for intelligent, context-aware responses. Thread management maintains conversation continuity with run status polling, timeout handling, and rate limit detection.
- Azure OpenAI Assistant API integration
- Thread creation for conversation context
- Message queueing and processing
- Rate limit detection (HTTP 429 handling)
Persistent Chat History
MongoDB storage for maintaining conversation continuity across sessions. All messages and chat sessions are persistently stored with timestamps, allowing users to access their conversation history anytime.
- MongoDB with Mongoose ODM
- Chat and message schema validation
- User-specific chat organization
- Automatic timestamp tracking
Modern UI/UX Design
Material Design components with responsive layout and markdown support. Built with Material-UI v7 and Framer Motion for smooth transitions, providing an intuitive and visually appealing user experience.
- Material-UI v7 component library
- Responsive Grid system
- react-markdown for formatted responses
- Framer Motion animations
Production-Ready Logging
Structured logging with Winston for comprehensive monitoring and debugging. Request logging with IP tracking, error logging with stack traces, and environment-aware configuration for production insights.
- Winston production-grade logging
- Request logging with IP tracking
- Error logging with stack traces
- Structured log format for parsing
Technical Architecture
Frontend Layer
Backend Layer
External Services
Architecture Highlights
User credentials are hashed with bcrypt and stored in MongoDB. On login, JWT tokens are generated with 24-hour expiration. Auth middleware validates tokens on protected routes.
Messages are sent via REST API, Azure OpenAI threads are created with conversation history for context, assistant runs are monitored with polling, and responses are saved to MongoDB.
Socket.io connections are established on client mount, server broadcasts new messages to all connected clients, and frontend listens for message events to update the UI.
User model with username, email, and hashed password. Chat model with userId reference, title, and embedded messages array containing role, content, and timestamps.
API Endpoints
Authentication
/api/auth/register
Create new user account
/api/auth/login
Authenticate and receive JWT token
Chat Management
/api/chat
Fetch all chats for authenticated user
/api/chat
Create new chat session
/api/chat/:chatId
Retrieve specific chat with message history
/api/chat/:chatId/messages
Send message and receive AI response
/api/chat/:chatId
Update chat title
All chat endpoints require JWT authentication via Authorization header.
Development Challenges & Solutions
Error Handling & Resilience
Challenge: Ensuring robust error handling across all system components, including AI API failures and database connection issues.
Solution: Implemented rate limit detection with user-friendly error messages, retry logic with exponential backoff, comprehensive try-catch blocks with structured logging, and graceful MongoDB connection failure handling.
Security Best Practices
Challenge: Protecting user data and preventing common security vulnerabilities in a real-time chat application.
Solution: Implemented password hashing with bcrypt, JWT token expiration, CORS configuration for specific origins, MongoDB injection prevention via Mongoose, and environment variable usage for sensitive data.
Real-Time Synchronization
Challenge: Managing bidirectional real-time communication while maintaining data consistency across clients.
Solution: Implemented Socket.io connection pooling, user-specific socket management, and automatic reconnection logic to ensure reliable message delivery and state synchronization.
AI Response Management
Challenge: Handling long-running AI requests with unpredictable response times and potential rate limits.
Solution: Implemented run status polling with 1-second intervals and 30-second timeouts, HTTP 429 rate limit detection, and structured error logging for monitoring and debugging.
Skills Demonstrated
Full-Stack Development
- Full-stack JavaScript development (Node.js + React)
- RESTful API design and implementation
- Modern React patterns and hooks
- Async/await and Promise management
Cloud & DevOps
- Azure cloud services integration
- Production logging and monitoring
- DevOps and cloud deployment
- Environment configuration management
Data Management
- NoSQL database design and modeling
- MongoDB with Mongoose ODM
- Query optimization with indexing
- Schema validation and data integrity
Real-Time Systems
- Real-time communication with WebSockets
- Socket.io implementation
- Connection state management
- Error handling and resilience patterns
AI Integration
- Azure OpenAI API integration
- Assistant API and thread management
- Context-aware AI responses
- Rate limiting and error handling
Security & Auth
- Authentication and authorization
- JWT token management
- Password hashing with bcrypt
- CORS and security headers
Project Resources
This project demonstrates full-stack development capabilities with real-time communication and AI integration. For inquiries about similar projects or consultation, please get in touch.