🔬 LabInsight AI

LabInsight AI-Powered Lab Report Analysis Platform

A full-stack healthcare web application that uses artificial intelligence to analyze lab reports, provide personalized health insights, and connect patients with doctors for professional medical guidance.

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📋 Table of Contents

• Overview
• Features
• Technology Stack
• Architecture
• Installation
• Configuration
• Running the Application
• API Documentation
• User Roles & Flows
• Project Structure
• Team Members
• Screenshots
• License

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🎯 Overview

LabInsight AI is a comprehensive healthcare platform designed to:

• Allow users to upload lab reports (PDF/images) and receive AI-generated analysis
• Provide an intelligent chatbot powered by RAG (Retrieval Augmented Generation) for health queries
• Connect patients with doctors for professional medical consultation
• Enable doctors to manage patients, view reports, and add professional comments
• Give administrators full control over users, doctors, and system reports

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✨ Features

👤 For Users (Patients)

• Secure Authentication - Email/password login with Google OAuth 2.0
• Report Upload - Upload lab reports (PDF, JPEG, PNG) with 10MB limit
• AI Analysis - Get instant AI-generated insights including:
  • Overall health summary
  • Key findings & recommendations
  • Severity assessment (low/medium/high)
  • Individual test interpretations
• AI Chat Assistant - Ask health questions and get context-aware answers based on your reports
• Trends Visualization - Track health metrics over time with charts
• Doctor Connection - Send requests to connect with available doctors
• Profile Management - Manage personal and medical information

👨‍⚕️ For Doctors

• Patient Management - View all connected patients
• Report Review - Access patient lab reports and AI analysis
• Professional Comments - Add medical comments and recommendations
• Connection Requests - Accept or reject patient connection requests
• Dashboard - Overview of patients, pending requests, and recent activity

🔐 For Administrators

• User Management - View, edit, suspend, or delete user accounts
• Doctor Management - Create and manage doctor accounts
• Report Oversight - View all reports across the platform
• System Dashboard - Statistics and analytics overview

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🛠 Technology Stack

Frontend

Technology	Purpose
React 18	UI Framework
TypeScript	Type Safety
Vite	Build Tool
Tailwind CSS	Styling
Radix UI / shadcn	Component Library
React Router DOM	Routing
Recharts	Data Visualization
React Markdown	Markdown Rendering
Firebase Auth	Google OAuth 2.0
Lucide React	Icons

Backend (Node.js)

Technology	Purpose
Node.js	Runtime Environment
Express.js	Web Framework
MongoDB	Database
Mongoose	ODM
JWT	Authentication Tokens
bcrypt	Password Hashing
Multer	File Upload
Swagger UI	API Documentation
CORS	Cross-Origin Requests

AI Service (Python)

Technology	Purpose
Flask	Microservice Framework
Groq API	LLM (Llama 3.3 70B)
SentenceTransformers	Text Embeddings
LangChain	PDF Processing
PyMongo	MongoDB Connection
NumPy	Vector Operations

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🏗 Architecture

┌─────────────────────────────────────────────────────────────────┐
│                         CLIENT (Browser)                         │
│                     React + TypeScript + Vite                    │
└─────────────────────────────┬───────────────────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────────┐
│                    BACKEND (Node.js + Express)                   │
│                         Port: 5000                               │
│  ┌──────────┐  ┌──────────┐  ┌──────────┐  ┌──────────────────┐ │
│  │   Auth   │  │  Upload  │  │  Admin   │  │     Doctor       │ │
│  │  Routes  │  │  Routes  │  │  Routes  │  │     Routes       │ │
│  └──────────┘  └──────────┘  └──────────┘  └──────────────────┘ │
│                         │                                        │
│                    Swagger UI (/api-docs)                        │
└─────────────────────────────┬───────────────────────────────────┘
                              │
              ┌───────────────┼───────────────┐
              ▼               ▼               ▼
┌─────────────────┐  ┌───────────────┐  ┌─────────────────────────┐
│    MongoDB      │  │  File Storage │  │   AI Service (Python)   │
│   (Database)    │  │   (uploads/)  │  │       Port: 5001        │
│                 │  │               │  │  ┌───────────────────┐  │
│  - Users        │  │  - PDFs       │  │  │  Groq LLM API     │  │
│  - Profiles     │  │  - Images     │  │  │  (Llama 3.3 70B)  │  │
│  - Reports      │  │               │  │  └───────────────────┘  │
│  - Doctors      │  │               │  │  ┌───────────────────┐  │
│  - Requests     │  │               │  │  │  Embeddings       │  │
│                 │  │               │  │  │  (RAG System)     │  │
└─────────────────┘  └───────────────┘  │  └───────────────────┘  │
                                        └─────────────────────────┘

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📥 Installation

Prerequisites

• Node.js v18+ (Download)
• Python 3.9+ (Download)
• MongoDB (Local or MongoDB Atlas)
• Git (Download)

Step 1: Clone the Repository

git clone https://github.com/your-username/labinsight-ai.git
cd labinsight-ai

Step 2: Install Frontend Dependencies

# From project root
npm install

Step 3: Install Backend Dependencies

cd Backend-Node
npm install
cd ..

Step 4: Install AI Service Dependencies

cd AI-Service
pip install -r requirements.txt
cd ..

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⚙️ Configuration

Backend Environment Variables

Create Backend-Node/.env:

# MongoDB Connection
MONGODB_URI=mongodb://localhost:27017/LabInsight

# JWT Configuration
JWT_SECRET=your-super-secret-jwt-key-change-this
JWT_EXPIRES_IN=7d

# Server Port
PORT=5000

# AI Service URL
AI_SERVICE_URL=http://localhost:5001

AI Service Environment Variables

Create AI-Service/.env:

# Groq API Key (Get from https://console.groq.com/)
GROQ_API_KEY=your-groq-api-key

# MongoDB Connection
MONGO_URI=mongodb://localhost:27017/LabInsight

Firebase Configuration (Google OAuth)

The Firebase configuration is already set up in src/components/firebase.ts. If you want to use your own Firebase project:

1. Go to Firebase Console
2. Create a new project
3. Enable Google Authentication
4. Update the config in firebase.ts

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🚀 Running the Application

Option 1: Run All Services

Open 3 terminal windows:

Terminal 1 - Frontend:

npm run dev

Frontend runs at: http://localhost:5173

Terminal 2 - Backend:

cd Backend-Node
node server.js

Backend runs at: http://localhost:5000

Terminal 3 - AI Service:

cd AI-Service
python ai_service.py

AI Service runs at: http://localhost:5001

Option 2: Using Concurrent Scripts (Optional)

You can set up a script to run all services together. Add to root package.json:

{
  "scripts": {
    "dev": "vite",
    "backend": "cd Backend-Node && node server.js",
    "ai": "cd AI-Service && python ai_service.py"
  }
}

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📚 API Documentation

Swagger UI

Once the backend is running, access the interactive API documentation at:

http://localhost:5000/api-docs

Key API Endpoints

Authentication

Method	Endpoint	Description
POST	/auth/signup	Register new user
POST	/auth/login	User login
POST	/auth/doctor-login	Doctor login
POST	/auth/change-password	Change password

User Profile & Reports

Method	Endpoint	Description
GET	/profile/:email	Get user profile
PUT	/profile/:email	Update profile
POST	/upload-report	Upload lab report
GET	/reports?email=	Get user's reports
GET	/report/:id	Get single report
DELETE	/delete-report/:id	Delete report

Doctor Routes

Method	Endpoint	Description
GET	/doctors	List all doctors
POST	/send-request	Send connection request
GET	/doctor/patients/:email	Get doctor's patients
PUT	/doctor/request/update/:id	Accept/reject request
POST	/doctor/add-comment	Add comment to report

Admin Routes

Method	Endpoint	Description
GET	/admin/users	Get all users
PUT	/admin/users/:email/status	Update user status
DELETE	/admin/users/:email	Delete user
POST	/admin/create-doctor	Create doctor account

AI Service

Method	Endpoint	Description
POST	/analyze	Analyze PDF report
GET	/chat/latest-report?email=	Get latest report info
POST	/chat/ask	Ask AI a question

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👥 User Roles & Flows

Flow 1: User Registration & Report Analysis

Sign Up → Login → Upload Report → View AI Analysis → Chat with AI

Flow 2: Patient-Doctor Connection

Login → Browse Doctors → Send Request → (Doctor Accepts) → View Assigned Doctor

Flow 3: Doctor Workflow

Login → View Dashboard → Check Requests → Accept/Reject → View Patients → Add Comments

Flow 4: Admin Management

Login → Dashboard → Manage Users → Manage Doctors → View Reports

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📁 Project Structure

Final_Web/
├── 📂 AI-Service/                 # Python AI Microservice
│   ├── ai_service.py              # Main Flask application
│   ├── requirements.txt           # Python dependencies
│   ├── Embeddings/                # Generated embeddings (.pkl)
│   └── .env.example
│
├── 📂 Backend-Node/               # Node.js Backend
│   ├── server.js                  # Express entry point
│   ├── swagger.js                 # Swagger configuration
│   ├── config/
│   │   └── db.js                  # MongoDB connection
│   ├── middleware/
│   │   └── auth.js                # JWT middleware
│   ├── models/                    # Mongoose schemas
│   │   ├── User.js
│   │   ├── Profile.js
│   │   ├── Report.js
│   │   ├── DoctorProfile.js
│   │   ├── AssignedDoctor.js
│   │   └── ConnectionRequest.js
│   ├── routes/                    # API routes
│   │   ├── auth.js
│   │   ├── profile.js
│   │   ├── upload.js
│   │   ├── admin.js
│   │   ├── doctorRoutes.js
│   │   └── ...
│   └── uploads/                   # Uploaded files
│
├── 📂 src/                        # React Frontend
│   ├── App.tsx                    # Main app with routes
│   ├── main.tsx                   # Entry point
│   ├── index.css                  # Global styles
│   ├── components/
│   │   ├── admin/                 # Admin components
│   │   ├── doctor/                # Doctor components
│   │   ├── ui/                    # Shared UI components
│   │   ├── Home.tsx
│   │   ├── SignIn.tsx
│   │   ├── Profile.tsx
│   │   ├── Chat.tsx
│   │   ├── ViewReports.tsx
│   │   └── ...
│   └── styles/
│
├── 📄 package.json                # Frontend dependencies
├── 📄 vite.config.ts              # Vite configuration
├── 📄 index.html                  # HTML entry point
├── 📄 README.md                   # This file
├── 📄 TEAM_WORKFLOW.md            # Team collaboration guide
└── 📄 .gitignore

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👨‍💻 Team Members

Name	Role	Responsibilities
Anushika Balamurugan	Frontend - User Module	User authentication, dashboard, reports UI
Venkata Sriya Kamarsu	Frontend - Admin/Doctor	Admin panel, doctor portal
Akshay Madavalappil Ramesh	Backend Developer	Node.js APIs, database, authentication
Amrin Bushra Taj	AI & Documentation	AI service, chatbot, documentation

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📸 Screenshots

Landing Page

User Dashboard

AI Chat Assistant

Admin Dashboard

Doctor Portal

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🔒 Security Features

• Password Hashing - bcrypt with salt rounds
• JWT Authentication - Secure token-based auth
• Role-Based Access Control - Admin, Doctor, User roles
• File Validation - Type and size restrictions
• Protected Routes - Middleware-based authorization
• Google OAuth 2.0 - Secure social login

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📄 License

This project is created for educational purposes as part of INFO 6150 - Fall 2025.

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🙏 Acknowledgments

• Groq for LLM API
• Firebase for Authentication
• shadcn/ui for UI Components
• Tailwind CSS for Styling

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⚠️ Disclaimer

This application is for educational purposes only. The AI-generated health insights should not replace professional medical advice. Always consult with healthcare providers for medical decisions.