🎓 JECRC Campus Assistant

Smart India Hackathon 2025 Project
Multilingual AI-powered campus chatbot for JECRC University

🌟 Features

• 🌐 Multilingual Support: Hindi, English, and regional languages
• 📱 Responsive Design: Works perfectly on mobile and desktop
• 🤖 Smart Intent Recognition: Understands student queries naturally
• ⚡ Real-time Responses: Instant answers to common questions
• 🎨 Beautiful UI: Modern, accessible design with animations
• 🔧 Easy Maintenance: Simple JSON-based knowledge base
• 📊 Analytics Ready: Built-in interaction logging
• ♿ Accessible: Screen reader friendly with ARIA labels

🎯 Problem Statement

ID: 25104
Title: Language Agnostic Chatbot
Organization: Government of Rajasthan - Directorate of Technical Education (DTE)

Campus offices handle hundreds of repetitive queries daily. This chatbot:

• ✅ Reduces administrative workload
• ✅ Provides 24/7 student support
• ✅ Breaks language barriers
• ✅ Integrates with existing systems
• ✅ Maintains conversation logs for improvement

🚀 Quick Start

Prerequisites

• Python 3.11+ installed
• Git installed
• Modern web browser

Installation

1. Clone the repository

git clone https://github.com/yourusername/campus-chatbot.git
cd campus-chatbot

2. Create virtual environment

python -m venv chatbot_env

# Windows
chatbot_env\Scripts\activate

# macOS/Linux
source chatbot_env/bin/activate

3. Install dependencies

pip install -r requirements.txt

4. Run the application

python app.py

5. Open browser

http://localhost:5000

🧪 Testing

Test the chatbot with these queries:

• fees → Fee information
• फीस → Hindi fee information
• admission → Admission details
• hostel → Hostel information
• placement → Placement statistics

Run automated tests:

python -m pytest tests/ -v

🌐 Deployment

Option 1: Heroku (Free Tier Available)

1. Install Heroku CLI

# Download from: https://devcenter.heroku.com/articles/heroku-cli

2. Deploy to Heroku

# Login to Heroku
heroku login

# Create app
heroku create jecrc-campus-assistant

# Deploy
git add .
git commit -m "Deploy to Heroku"
git push heroku main

# Open app
heroku open

Option 2: Railway

1. Connect to Railway

# Install Railway CLI
npm install -g @railway/cli

# Login and deploy
railway login
railway create
railway up

Option 3: Render

1. Fork this repository
2. Connect to Render.com
3. Create new Web Service
4. Connect your GitHub repo
5. Deploy automatically

Option 4: Local Network Deployment

# Run on local network (accessible to all devices on WiFi)
python app.py

# Access from other devices using your IP:
# http://YOUR_IP_ADDRESS:5000

📚 API Documentation

Endpoints

POST /chat

Send a message to the chatbot

Request:

{
  "message": "fees kya hai?"
}

Response:

{
  "response": "💰 Fee Information:\n• B.Tech Fee: ₹1,25,000/year...",
  "intent": "fees",
  "language": "hi",
  "status": "success"
}

GET /health

Check server health

Response:

{
  "status": "healthy",
  "intents": 12,
  "version": "1.0.0"
}

🎛️ Configuration

Adding New Responses

Edit knowledge_base.json:

{
  "new_topic": {
    "keywords": ["keyword1", "keyword2", "हिंदी_keyword"],
    "responses": {
      "hi": "Hindi response here",
      "en": "English response here"
    }
  }
}

Customizing UI

• Colors: Edit static/css/styles.css
• Content: Edit templates/index.html
• Behavior: Edit static/js/script.js

🏗️ Architecture

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   Frontend      │    │    Flask App     │    │  Knowledge      │
│   (HTML/CSS/JS) │◄──►│   (Python)       │◄──►│  Base (JSON)    │
└─────────────────┘    └──────────────────┘    └─────────────────┘
        │                        │                        │
        ▼                        ▼                        ▼
┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   User Interface│    │ Intent Detection │    │   Responses     │
│   • Chat Widget │    │ • Language Detect│    │   • Hindi       │
│   • Animations  │    │ • Keyword Match  │    │   • English     │
│   • Responsive  │    │ • Context Handle │    │   • Multilingual│
└─────────────────┘    └──────────────────┘    └─────────────────┘

🎯 Hackathon Demo Script

1. Problem Introduction (1 minute)

"Campus offices are overwhelmed with repetitive queries. Students struggle with language barriers. Our solution provides 24/7 multilingual support."

2. Live Demo (3 minutes)

• Show beautiful UI loading
• Demonstrate English query: "fees"
• Demonstrate Hindi query: "फीस"
• Show language switching
• Test mobile responsiveness
• Show admin panel (knowledge base editing)

3. Technical Highlights (1 minute)

• "Built with Flask, modern JavaScript"
• "JSON-based knowledge system for easy updates"
• "Production-ready with proper error handling"
• "Deployable in minutes"

📊 Impact & Metrics

Expected Benefits

• 80% reduction in repetitive queries to admin staff
• 24/7 availability for student support
• Multi-language accessibility for diverse student body
• Instant responses instead of long queues
• Easy maintenance by student volunteers

Success Metrics

• Query resolution rate: >90%
• Response time: <2 seconds
• User satisfaction: >4.5/5
• Admin time saved: >20 hours/week

🛠️ Development

Adding New Features

1. New Intent Recognition

# Add to detect_intent() function in app.py
if 'new_keyword' in message_lower:
    return 'new_intent'

2. New UI Components

/* Add to static/css/styles.css */
.new-component {
    /* Your styles here */
}

3. New Interactions

// Add to static/js/script.js
function newFeature() {
    // Your code here
}

🤝 Contributing

1. Fork the repository
2. Create feature branch (git checkout -b feature/AmazingFeature)
3. Commit changes (git commit -m 'Add AmazingFeature')
4. Push to branch (git push origin feature/AmazingFeature)
5. Open Pull Request

🏆 Team Credits

JECRC Foundation - SIH 2025 Team

• Team Leader: [Your Name]
• Frontend Developer: [Name]
• Backend Developer: [Name]
• UI/UX Designer: [Name]
• Data Analyst: [Name]
• Tester: [Name]

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🆘 Support

Common Issues

Q: Chatbot not responding?
A: Check if server is running and visit http://localhost:5000/health

Q: Hindi text not displaying properly?
A: Ensure UTF-8 encoding in your browser

Q: Mobile layout issues?
A: Clear browser cache and refresh

Q: Deployment failed?
A: Check all files are committed and requirements.txt is complete

Getting Help

• 📧 Email: [your-email@jecrc.edu]
• 💬 Discord: [Your Discord Server]
• 🐛 Issues: GitHub Issues

🎉 Acknowledgments

• SIH 2025 for the opportunity
• JECRC University for support
• Government of Rajasthan for the problem statement
• Flask Community for the excellent framework
• Open Source Contributors for inspiration

---

Made with ❤️ for Smart India Hackathon 2025
Empowering students through technology

Windows Setup Commands Step 1: Open Command Prompt or PowerShell cmd# Open Command Prompt as Administrator (recommended)

Navigate to your desired project directory

cd C:\your-projects-folder Step 2: Create Project Directory cmdmkdir campus-chatbot cd campus-chatbot Step 3: Create Virtual Environment cmdpython -m venv venv Step 4: Activate Virtual Environment cmd# For Command Prompt venv\Scripts\activate

For PowerShell (if above doesn't work)

venv\Scripts\Activate.ps1 Step 5: Upgrade pip cmdpython -m pip install --upgrade pip Step 6: Install All Dependencies cmdpip install flask==2.3.3 pip install flask-cors==4.0.0 pip install chromadb==0.4.15 pip install sentence-transformers==2.2.2 pip install transformers==4.35.0 pip install torch==2.1.0 pip install PyPDF2==3.0.1 pip install pandas==2.1.3 pip install openpyxl==3.1.2 pip install python-docx==1.1.0 pip install nltk==3.8.1 pip install scikit-learn==1.3.2 pip install numpy==1.24.4 Step 7: Create Project Files cmd# Create main directories mkdir documents mkdir templates mkdir static

Create the main Python file

echo. > smart_rag_app.py

Create reset utility

echo. > reset_database.py

Create requirements file

pip freeze > requirements.txt

macOS/Linux Setup Commands Step 1: Open Terminal bash# Navigate to your desired project directory cd ~/your-projects-folder Step 2: Create Project Directory bashmkdir campus-chatbot cd campus-chatbot Step 3: Create Virtual Environment bashpython3 -m venv venv Step 4: Activate Virtual Environment bashsource venv/bin/activate Step 5: Upgrade pip bashpython -m pip install --upgrade pip Step 6: Install All Dependencies bashpip install flask==2.3.3 pip install flask-cors==4.0.0 pip install chromadb==0.4.15 pip install sentence-transformers==2.2.2 pip install transformers==4.35.0 pip install torch==2.1.0 pip install PyPDF2==3.0.1 pip install pandas==2.1.3 pip install openpyxl==3.1.2 pip install python-docx==1.1.0 pip install nltk==3.8.1 pip install scikit-learn==1.3.2 pip install numpy==1.24.4 Step 7: Create Project Structure bash# Create directories mkdir documents templates static

Create main files

touch smart_rag_app.py touch reset_database.py

Create requirements file

pip freeze > requirements.txt

Setting Up the Code Step 8: Add Your Code Files cmd# Copy your smart_rag_app.py content into the file

Use any text editor like notepad, VSCode, or vim

For Windows

notepad smart_rag_app.py

For macOS

open -a TextEdit smart_rag_app.py

For Linux

nano smart_rag_app.py Step 9: Create Reset Database Script Create reset_database.py with this content: cmd# For Windows notepad reset_database.py Add this code: pythonimport shutil import os

def reset_rag_system(): if os.path.exists("./advanced_jecrc_vectordb"): shutil.rmtree("./advanced_jecrc_vectordb") print("✅ Removed vector database")

if os.path.exists("document_cache.pkl"):
    os.remove("document_cache.pkl")
    print("✅ Removed document cache")

print("🔄 Database reset complete!")

if name == "main": reset_rag_system() Step 10: Add Your Documents cmd# Copy your PDF and Excel files to the documents folder

Windows

copy "C:\path\to\your\documents*" documents\

macOS/Linux

cp /path/to/your/documents/* documents/

First Run Commands Step 11: Initial Setup Run cmd# Make sure virtual environment is activated

Windows

venv\Scripts\activate

macOS/Linux

source venv/bin/activate

Run the application for first time

python smart_rag_app.py You should see output like: 🚀 Initializing Advanced Smart RAG System... 📥 Loading advanced embedding model... 🧠 Loading free QA model... ✅ QA model loaded successfully 📚 Loading enhanced JECRC documents... ✅ Successfully loaded documents

• Running on http://127.0.0.1:5000 Step 12: Test the Application Open your browser and go to: http://localhost:5000

Troubleshooting Commands If Models Don't Download: cmd# Check internet connection ping google.com

Clear pip cache

pip cache purge

Reinstall sentence-transformers

pip uninstall sentence-transformers pip install sentence-transformers If Database Issues Occur: cmd# Stop the application (Ctrl+C)

Reset database

python reset_database.py

Restart application

python smart_rag_app.py If Import Errors: cmd# Check what's installed pip list

Reinstall specific package

pip uninstall package-name pip install package-name If Port Already in Use: cmd# Windows - Find process using port 5000 netstat -ano | findstr :5000

Kill the process (replace PID with actual number)

taskkill /PID 1234 /F

macOS/Linux - Find and kill process

lsof -ti:5000 | xargs kill -9

Daily Operation Commands Starting the Application: cmd# Navigate to project cd campus-chatbot

Activate environment

Windows

venv\Scripts\activate

macOS/Linux

source venv/bin/activate

Run application

python smart_rag_app.py Stopping the Application: cmd# Press Ctrl+C in the terminal running the app Adding New Documents: cmd# Copy new documents to folder

Windows

copy "C:\new\documents*" documents\

Restart application to load new documents

python smart_rag_app.py Updating Dependencies: cmdpip install --upgrade flask chromadb sentence-transformers

Complete Setup Verification Run these commands to verify everything works: cmd# 1. Check Python version python --version

2. Check if virtual environment is active

(you should see (venv) in your command prompt)

3. Test imports

python -c "import flask, chromadb, sentence_transformers; print('All imports successful')"

4. Check documents folder

Windows

dir documents

macOS/Linux

ls -la documents/

5. Run application

python smart_rag_app.py Expected Final Output: 📁 Found X documents to process... ✅ 📌 Loaded PDF: CURRENT_Syllabus-CSE-5-6.pdf (12 chunks, Priority: high) ✅ 📊 Loaded Excel: CURRENT_2023-2024.xlsx (6 chunks, Priority: high) ✅ Successfully loaded X documents from Y files

• Serving Flask app 'smart_rag_app'
• Running on http://127.0.0.1:5000