OrthoBot AI – Virtual Healthcare Assistant for Post-Op Care

OrthoBot AI is a virtual healthcare assistant built with React (frontend) and Node.js (backend). It provides AI-powered recovery guidance, rehab routines, diet plans, and real-time chat support for patients after orthopedic surgery.

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📑 Table of Contents

1. Features
2. Tech Stack
   • Frontend
   • Backend
3. Project Structure
4. Prerequisites
5. Quick Start
   • Clone and Install
   • Backend Setup
   • Start Development Servers
6. Configuration
   • Environment Variables
7. MongoDB Atlas Setup Guide
   • Step-by-Step MongoDB Atlas Configuration
   • 8. Database Structure
   • Security Best Practices
8. Troubleshooting
9. License
10. Contributing
11. Support

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🚀 Features

• AI-Powered Chatbot: Provides instant answers to patient queries
• Knowledge Base Integration: Delivers accurate rehab routines, diet plans, and post-op care guidance
• Voice & Translation Support: Enables voice-enabled conversations with real-time language translation
• User Authentication: Secure login/signup powered by Clerk
• Responsive Design: React-based frontend designed for smooth, mobile-friendly patient experience

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🛠️ Tech Stack

Frontend

• React 19 with Vite
• Clerk for secure login/signup with session management
• Conversational UI optimized for patient–bot interactions
• Built-in speech-to-text and text-to-speech for natural communication
• Built-in speech-to-text and text-to-speech for natural communication

Backend

• Node.js with Express for API handling
• CORS enabled for secure frontend-backend communication
• JSON-based knowledge base for structured post-op orthopedic data
• Keyword search for relevant knowledge retrieval
• Groq API integration for AI-driven patient-friendly answers
• Environment variables for secure API key management
• Error logging and reliable response handling
• MongoDB Atlas (cloud database)

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📂 Project Structure

orthobot-ai/
├── frontend/       # React + Vite (UI, Clerk auth, voice features)
├── backend/        # Node.js + Express (APIs, MongoDB, Groq AI)
├── README.md       # Project documentation
└── package.json    # Root config for scripts

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📋 Prerequisites

• Node.js (v16 or higher)
• npm or yarn
• Groq API key → Get one here
• MongoDB Atlas account → Sign up here

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🚀 Quick Start

1. Clone and Install

git clone <repository-url>
cd orthobot-ai
npm run install:all

2. Backend Setup

cd backend

# Copy example file
cp .env.example .env

# Edit .env with your API key
# GROQ_API_KEY=your_actual_groq_api_key_here
# PORT=3000

Or use the Windows setup script:

npm run setup:env

3. Start Development Servers

# Run both frontend and backend simultaneously
npm run dev:full

# Or run separately:
# Terminal 1: npm run dev (frontend on :5173)
# Terminal 2: npm run backend (backend on :3000)

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🔧 Configuration

Environment Variables

Create a .env file inside the backend/ folder:

GROQ_API_KEY=your_actual_groq_api_key_here
MONGODB_URI=mongodb+srv://<username>:<password>@<cluster>.mongodb.net/orthobot
PORT=3000

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🍃 MongoDB Atlas Setup Guide

Step-by-Step MongoDB Atlas Configuration

1. Create an Atlas account → cloud.mongodb.com
2. Create free cluster (M0, AWS recommended)
3. Configure Database User + Network Access
4. Copy connection string (Node.js driver)
5. Add to .env as MONGODB_URI

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8. Database Structure

SharedChats Collection

{
  shareId: "uuid-string",
  shareType: "full_chat" | "single_message",
  title: "Chat title",
  messages: [...],
  singleMessage: {...},
  createdAt: Date,
  viewCount: Number,
  expiresAt: Date
}

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Security Best Practices

• Never commit .env to GitHub
• Restrict IPs in production
• Use strong DB passwords & rotate regularly

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🐛 Troubleshooting

• Backend not starting: Check Node.js version and dependencies
• File upload fails: Verify file size and format
• AI processing errors: Check Groq API key and quota
• CORS issues: Ensure backend is running on port 3000
• Missing .env file: Create .env file in backend folder with your API key

📄 License

This project is licensed under the MIT License © 2025 Krishna Singh

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Open a Pull Request

📞 Support

For issues and questions, please check the troubleshooting section or create an issue in the repository.