Kunal AI - Multi-Feature AI Assistant

A full-stack AI-powered application featuring three intelligent tools: Q&A Bot, Text Summarizer, and Expense Tracker. Built with React, TypeScript, Flask, and Google Gemini AI.

▶️ Demo Video

You can watch the project demo directly from this repository. GitHub READMEs don't allow iframes, so click the thumbnail below to open a playable preview of the demo page.

Or open the video on YouTube: https://youtu.be/RztUMrw_sJ4

🌟 Features

1. Q&A Bot

• Interactive question-answering system powered by Google Gemini
• Real-time streaming responses with character-by-character display
• Natural language understanding for diverse queries

2. Text Summarizer

• Intelligent text summarization using AI
• Extracts key points from long documents
• Clean, concise summaries

3. Expense Tracker

• AI-powered expense management
• Natural language input (e.g., "add $20 for coffee")
• Track spending with conversational commands

🏗️ Tech Stack

Frontend

• Framework: React 18.3.1 with TypeScript
• Build Tool: Vite 5.4.19
• UI Components: Shadcn UI (Radix UI primitives)
• Styling: Tailwind CSS
• Routing: React Router DOM
• State Management: TanStack Query
• Deployment: Vercel

Backend

• Framework: Flask 3.0.3
• AI Integration: LangChain + Google Gemini AI
• CORS: Flask-CORS
• Server: Gunicorn
• Deployment: Railway

📋 Prerequisites

Before you begin, ensure you have the following installed:

• Node.js (v18 or higher)
• Python (v3.11 or higher)
• pip (Python package manager)
• npm or yarn (Node package manager)
• Google Gemini API Key (Get one here)

🚀 Local Setup

1. Clone the Repository

git clone https://github.com/Hiteshydv001/Internship-assesment.git
cd Internship-assesment

2. Backend Setup

Navigate to backend directory

cd backend

Create virtual environment (recommended)

# Windows
python -m venv venv
venv\Scripts\activate

# macOS/Linux
python3 -m venv venv
source venv/bin/activate

Install dependencies

pip install -r requirements.txt

Create .env file

Create a .env file in the backend directory:

GEMINI_API_KEY=your_gemini_api_key_here

Replace your_gemini_api_key_here with your actual Google Gemini API key.

Run the backend server

# Development mode
python main.py

# Production mode with Gunicorn
gunicorn main:app --bind 0.0.0.0:5001 --workers 2

The backend server will start at http://localhost:5001

3. Frontend Setup

Navigate to frontend directory (from root)

cd frontend

Install dependencies

npm install
# or
yarn install

Create .env file (optional)

Create a .env file in the frontend directory:

VITE_API_URL=http://localhost:5001/api

Run the development server

npm run dev
# or
yarn dev

The frontend will start at http://localhost:5173

📂 Project Structure

Internship-assign/
├── backend/
│   ├── app/
│   │   ├── __init__.py          # Flask app factory with CORS config
│   │   ├── api/
│   │   │   ├── qna.py           # Q&A endpoint with streaming
│   │   │   ├── summarizer.py    # Summarization endpoint
│   │   │   └── tracker.py       # Expense tracker endpoint
│   │   └── core/
│   │       └── agents.py        # LangChain agent configurations
│   ├── config.py                # Configuration management
│   ├── main.py                  # Flask application entry point
│   └── requirements.txt         # Python dependencies
├── frontend/
│   ├── src/
│   │   ├── components/
│   │   │   ├── features/        # Feature-specific components
│   │   │   ├── layout/          # Layout components (Navbar, Footer)
│   │   │   └── ui/              # Shadcn UI components
│   │   ├── pages/               # Route pages
│   │   ├── lib/
│   │   │   ├── api.ts           # API client functions
│   │   │   └── utils.ts         # Utility functions
│   │   ├── App.tsx              # Main app component
│   │   └── main.tsx             # Entry point
│   ├── package.json             # Node dependencies
│   └── vite.config.ts           # Vite configuration
├── Dockerfile                   # Docker configuration for backend
└── README.md                    # This file

🔧 Environment Variables

Backend (backend/.env)

Variable	Description	Required
GEMINI_API_KEY	Google Gemini API key	Yes

Frontend (frontend/.env)

Variable	Description	Default
VITE_API_URL	Backend API URL	http://localhost:5001/api

🐳 Docker Deployment

Build Docker Image

docker build -t kunal-ai-backend .

Run Docker Container

docker run -p 8080:8080 -e GEMINI_API_KEY=your_api_key kunal-ai-backend

🌐 Production Deployment

Backend (Railway)

1. Push your code to GitHub
2. Connect your repository to Railway
3. Add GEMINI_API_KEY environment variable
4. Railway will automatically deploy using the Dockerfile

Live Backend URL: https://internship-assesment-production.up.railway.app

Frontend (Vercel)

1. Push your code to GitHub
2. Import project to Vercel
3. Set environment variable:
   • VITE_API_URL=https://internship-assesment-production.up.railway.app/api
4. Deploy

Live Frontend URL: https://internship-assesment-git-main-hitesh-kumars-projects-788f775a.vercel.app

🔌 API Endpoints

Health Check

GET /api/health

Returns API status

Q&A Bot

POST /api/qna
Content-Type: application/json

{
  "question": "What is machine learning?"
}

Returns streaming text response

Summarizer

POST /api/summarize
Content-Type: application/json

{
  "text": "Long text to summarize..."
}

Returns JSON with summary

Expense Tracker

POST /api/tracker
Content-Type: application/json

{
  "prompt": "add $50 for groceries"
}

Returns JSON with tracker response

🛠️ Development

Run Tests

# Backend
cd backend
python -m pytest

# Frontend
cd frontend
npm run test

Lint Code

# Frontend
cd frontend
npm run lint

Build for Production

# Frontend
cd frontend
npm run build

🐛 Troubleshooting

CORS Issues

If you encounter CORS errors:

1. Ensure VITE_API_URL includes /api suffix
2. Check that backend CORS is configured for your frontend origin
3. Verify the API endpoints are correct (/api/qna, not /qna)

API Key Errors

If you get API key errors:

1. Verify your .env file exists in the backend directory
2. Ensure GEMINI_API_KEY is set correctly
3. Restart the backend server after adding the key

Port Conflicts

If ports are already in use:

• Backend: Change port in main.py (default: 5001)
• Frontend: Change port in vite.config.ts or use --port flag

📝 License

This project is created as part of an internship assessment.

👤 Author

Hitesh Kumar

• GitHub: @Hiteshydv001
• Repository: Internship-assesment

🙏 Acknowledgments

• Google Gemini AI for powering the AI features
• Shadcn UI for beautiful components
• LangChain for AI agent orchestration
• Flask and React communities

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Made with ❤️ for Kunal AI Internship Assessment