🎓 CSM Query System

Experience Data at Fingertips 📊

An AI-powered query system designed exclusively for CSM students to access instant insights and answers about academic information.

📋 Table of Contents

✨ Features
🏛️ Architecture
🛠️ Installation
⚙️ Configuration
🚀 Usage
📁 Project Structure
🔧 API Endpoints
🎨 UI/UX
🧪 Testing
🤝 Contributing
📜 License
👨‍💻 Author

✨ Features

🤖 AI-Powered Query Processing

NVIDIA NIM Integration: Leverages cutting-edge NVIDIA AI models for natural language understanding
RAG Architecture: Retrieval-Augmented Generation for accurate, context-aware responses
Smart Document Processing: Automatic parsing and indexing of academic documents

🎓 Academic Information Access

📚 Current Syllabus: Instant access to CSE 3-2 semester curriculum
👨‍🏫 Faculty Information: Faculty schedules and timetable details
📅 Academic Calendar: Semester dates and important deadlines
📊 Student Data: Marks, performance analytics, and student details
🎯 Project Information: 3-2 project guidelines, timelines, and requirements

🔐 Security & Authentication

Email-Based Registration: Secure signup with OTP verification
College Email Restriction: Limited to @vvit.net domain for exclusivity
Session Management: Secure user sessions with MongoDB storage
Query Limits: Fair usage policy with daily query restrictions

🎨 Modern UI/UX

Responsive Design: Optimized for desktop, tablet, and mobile devices
Dark/Light Mode: Seamless theme switching with user preference persistence
Glassmorphism UI: Modern, elegant interface with backdrop blur effects
Real-time Feedback: Loading states, progress indicators, and toast notifications
Markdown Support: Rich text rendering for formatted responses

📊 Advanced Features

Vector Search: Qdrant-powered semantic search for document retrieval
Chat History: Track and review previous queries
Error Handling: Comprehensive error management with user-friendly messages
Performance Monitoring: Query count tracking and usage analytics

🏛️ Architecture

graph TD
    A[User Interface] --> B[Flask Web Server]
    B --> C[Authentication System]
    B --> D[RAG Pipeline]
    
    C --> E[MongoDB]
    C --> F[Email Service]
    
    D --> G[Document Loader]
    D --> H[Text Splitter]
    D --> I[NVIDIA Embeddings]
    D --> J[Qdrant Vector Store]
    D --> K[NVIDIA LLM]
    
    G --> L[Source Documents]
    J --> M[Vector Database]
    
    style A fill:#e1f5fe
    style B fill:#f3e5f5
    style D fill:#e8f5e8
    style E fill:#fff3e0
    style J fill:#fce4ec

Technology Stack

Backend

🐍 Python 3.8+: Core programming language
🌶️ Flask: Lightweight web framework
🗄️ MongoDB: NoSQL database for user management
🔍 Qdrant: Vector database for semantic search
📧 SMTP: Email service for notifications

AI/ML Components

🚀 NVIDIA NIM: AI model serving platform
🦜 LangChain: LLM application framework
📄 LlamaIndex: Document indexing and retrieval
🔢 Vector Embeddings: Semantic text representation

Frontend

📱 HTML5/CSS3: Modern web standards
⚡ JavaScript: Interactive functionality
🎨 Custom CSS: Responsive design system
📝 Markdown: Rich text rendering

🛠️ Installation

Prerequisites

Python 3.8 or higher
MongoDB instance
NVIDIA API access
Qdrant Cloud account (or local instance)
SMTP email service

1. Clone Repository

git clone https://github.com/Epik-Whale463/College_Query_System.git
cd College_Query_System

2. Create Virtual Environment

python -m venv venv

# On Windows
venv\Scripts\activate

# On macOS/Linux
source venv/bin/activate

3. Install Dependencies

pip install -r requirements.txt

4. Environment Configuration

Create a .env file in the root directory:

# MongoDB Configuration
MONGODB_URI=mongodb://localhost:27017/
MONGODB_DATABASE=csm_query_system

# NVIDIA API
NVIDIA_API_KEY=your_nvidia_api_key_here

# Qdrant Configuration
QDRANT_URL=https://your-qdrant-cluster.qdrant.io:6333
QDRANT_API_KEY=your_qdrant_api_key_here

# Email Configuration
SMTP_SERVER=smtp.gmail.com
SMTP_PORT=587
SMTP_EMAIL=your_email@gmail.com
SMTP_PASSWORD=your_app_password

# Flask Configuration
FLASK_SECRET_KEY=your_secret_key_here
FLASK_ENV=development

5. Initialize Database

python -c "from app import initialize_rag; initialize_rag()"

6. Run Application

python app.py

The application will be available at http://localhost:5000

⚙️ Configuration

Document Sources

Place your academic documents in the source_documents/ directory:

about_vvit.txt - College information
cur_syllabus.txt - Current syllabus
faculty_schedule.txt - Faculty timetables
project_details.txt - Project information
semester_calender.txt - Academic calendar
student_marks.txt - Student performance data
students_details.txt - Student information

Customization

Query Limits: Modify MAX_QUERIES_PER_DAY in app.py
UI Theme: Customize CSS variables in static/style.css
Email Templates: Edit templates in python_modules/generate_send_mail.py

🚀 Usage

User Registration

Visit the registration page
Enter your college email (@vvit.net)
Verify your email with the OTP sent
Complete registration process

Querying the System

Login to your account
Type your question in natural language
Get instant AI-powered responses with relevant information
Use demo topics for quick queries

Example Queries

"What is the syllabus for Machine Learning?"
"When is the next semester exam?"
"Show me faculty schedule for CSE department"
"What are the project submission deadlines?"

📁 Project Structure

College_Query_System/
├── 📁 source_documents/        # Academic documents
│   ├── about_vvit.txt
│   ├── cur_syllabus.txt
│   ├── faculty_schedule.txt
│   ├── project_details.txt
│   ├── semester_calender.txt
│   ├── student_marks.txt
│   └── students_details.txt
├── 📁 python_modules/          # Core Python modules
│   ├── add_user.py            # User management
│   ├── generate_send_mail.py   # Email services
│   ├── rag_functions.py       # RAG pipeline
│   └── users.txt             # User data
├── 📁 static/                 # Static assets
│   ├── style.css             # Main stylesheet
│   └── favicon.ico           # Site icon
├── 📁 templates/              # HTML templates
│   ├── home.html             # Landing page
│   ├── index.html            # Main query interface
│   ├── login.html            # Login page
│   ├── register.html         # Registration page
│   ├── verify_otp.html       # OTP verification
│   ├── 404.html              # Error pages
│   └── 500.html
├── 📄 app.py                  # Main Flask application
├── 📄 requirements.txt        # Python dependencies
├── 📄 Dockerfile             # Docker configuration
├── 📄 .gitignore             # Git ignore rules
└── 📄 README.md              # This file

🔧 API Endpoints

Endpoint	Method	Description	Authentication
`/`	GET	Home page	❌
`/register`	GET/POST	User registration	❌
`/verify-otp`	GET/POST	OTP verification	❌
`/login`	GET/POST	User login	❌
`/logout`	GET	User logout	✅
`/dashboard`	GET	Main query interface	✅
`/query`	POST	Process user queries	✅
`/query-count`	GET	Get user query statistics	✅

🎨 UI/UX

Design System

🎨 Color Palette: Modern blue gradient theme
📱 Responsive Design: Mobile-first approach
✨ Animations: Smooth transitions and micro-interactions
🌓 Theme Support: Dark and light mode toggle
♿ Accessibility: WCAG compliant design

Key Components

Glassmorphism Cards: Modern translucent design
Interactive Elements: Hover effects and feedback
Loading States: Progress indicators and spinners
Toast Notifications: User feedback system
Markdown Rendering: Rich text support

🧪 Testing

Manual Testing

# Test user registration
curl -X POST http://localhost:5000/register \
  -H "Content-Type: application/json" \
  -d '{"email":"test@vvit.net","password":"password123"}'

# Test query endpoint
curl -X POST http://localhost:5000/query \
  -H "Content-Type: application/json" \
  -d '{"query":"What is the current syllabus?"}'

Load Testing

Test query processing performance
Verify concurrent user handling
Monitor database response times

🤝 Contributing

We welcome contributions to improve the CSM Query System! Here's how you can help:

Development Setup

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Make your changes
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

Contribution Guidelines

Follow Python PEP 8 style guidelines
Add comments for complex functionality
Update documentation for new features
Test your changes thoroughly

Issues

🐛 Bug Reports: Use the bug report template
💡 Feature Requests: Describe the proposed functionality
📖 Documentation: Help improve our docs

📜 License

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

👨‍💻 Author

Rama Charan

🎓 Affiliation: CSM Department, VVIT
📧 Email: your-email@vvit.net
🔗 GitHub: @Epik-Whale463

🌟 Show your support

Give a ⭐️ if this project helped you!

Made with ❤️ for CSM Students

📊 Project Statistics

🚀 Status: Active Development
📅 Created: January 2025
🔄 Last Updated: June 2025
👥 Contributors: 1
🌟 Stars: Be the first!
🍴 Forks: 0

🔮 Future Enhancements

Multi-language Support: Add regional language support
Voice Queries: Voice-to-text query input
Advanced Analytics: Detailed usage analytics dashboard
Mobile App: Native mobile application
API Integration: RESTful API for third-party integration
Real-time Chat: Live chat support system
Document Upload: User document upload functionality
Export Features: Export responses to PDF/Word

This README was last updated on June 19, 2025

Name		Name	Last commit message	Last commit date
Latest commit History 8 Commits
python_modules		python_modules
source_documents		source_documents
static		static
templates		templates
.gitignore		.gitignore
Dockerfile		Dockerfile
README.md		README.md
app.py		app.py
requirements.txt		requirements.txt

Epik-Whale463/College_Query_System

Folders and files

Latest commit

History

Repository files navigation