AMUqBot Documentation

Table of Contents

1. Introduction
2. System Architecture
3. Installation Guide
4. Configuration
5. User Guide
6. Developer Guide
7. Techinical Architecture
8. Troubleshooting

Introduction

AMUqBot is a comprehensive query management system designed specifically for Aligarh Muslim University (AMU). It provides a modern, efficient platform for handling academic queries, document management, and real-time discussions.

Key Features

• User Authentication: Secure login system with role-based access control
• Document Management: Upload, store, and manage academic documents
• Query System: Submit, track, and manage academic queries
• Real-time Communication: WebSocket-based discussion system
• Responsive Design: Mobile-friendly interface using Tailwind CSS

System Architecture

Technology Stack

• Backend Framework: Django 5.2
• Frontend: Tailwind CSS
• Database: SQLite3
• Real-time Communication: Django Channels
• Server: Daphne (ASGI server)
• Template Engine: Jinja2

Project Structure

AMUqBot/
├── amu_query_bot/         # Main Django project
│   ├── core/             # Core application
│   │   ├── models.py     # Database models
│   │   ├── views.py      # View logic
│   │   └── urls.py       # URL routing
│   ├── documents/        # Document management
│   ├── users/           # User management
│   ├── templates/       # HTML templates
│   └── static/          # Static files
├── docs/                # Documentation
└── requirements.txt     # Python dependencies

Installation Guide

Prerequisites

• Python 3.x
• Node.js and npm
• Git

Step-by-Step Installation

1. Clone the Repository

   git clone https://github.com/yourusername/AMUqBot.git
   cd AMUqBot

2. Set Up Virtual Environment

   python -m venv .venv
   # Windows
   .venv\Scripts\activate
   # Unix/MacOS
   source .venv/bin/activate

3. Install Dependencies

   pip install -r requirements.txt
   npm install

4. Database Setup

   cd amu_query_bot
   python manage.py migrate
   python manage.py createsuperuser

5. Run Development Server

   python manage.py runserver

Configuration

Environment Variables

Create a .env file in the project root with the following variables:

DEBUG=True
SECRET_KEY=your-secret-key
DATABASE_URL=sqlite:///db.sqlite3

Database Configuration

The project uses SQLite by default. For production, configure your preferred database in settings.py.

User Guide

User Roles

1. Student

   • Submit queries
   • Upload documents
   • Participate in discussions

2. Faculty

   • Respond to queries
   • Manage documents
   • Moderate discussions

3. Admin

   • Manage users
   • System configuration
   • Access all features

Using the System

Submitting a Query

1. Log in to your account
2. Navigate to "New Query"
3. Fill in the query details
4. Attach relevant documents
5. Submit

Document Management

1. Access the document section
2. Upload new documents
3. Organize in folders
4. Share with relevant users

Real-time Discussion

1. Join a discussion room
2. Send messages in real-time
3. Share files and links
4. Use @mentions for specific users

Developer Guide

Setting Up Development Environment

1. Fork the repository
2. Create a feature branch
3. Set up pre-commit hooks
4. Follow coding standards

Code Style

• Follow PEP 8 guidelines
• Use meaningful variable names
• Write docstrings for functions
• Include type hints

Testing

python manage.py test

Technical Architecture

System Overview

AMUqBot is built using a modern web architecture that emphasizes scalability, maintainability, and real-time capabilities.

Architecture Diagram

┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐
│   Client Layer  │     │  Application    │     │   Data Layer    │
│  (Frontend)     │◄───►│  Layer (Django) │◄───►│  (Database)     │
└─────────────────┘     └─────────────────┘     └─────────────────┘
        ▲                        ▲                        ▲
        │                        │                        │
        ▼                        ▼                        ▼
┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐
│  WebSockets     │     │  Task Queue     │     │  File Storage   │
│  (Channels)     │     │  (Celery)       │     │  (Media)        │
└─────────────────┘     └─────────────────┘     └─────────────────┘

Component Details

1. Frontend Architecture

• Framework: Tailwind CSS
• State Management: Alpine.js
• Real-time Updates: WebSocket client
• Build System: Webpack

2. Backend Architecture

• Framework: Django 5.2
• ASGI Server: Daphne
• Task Queue: Celery
• Caching: Redis
• WebSockets: Django Channels

3. Database Architecture

• Primary Database: SQLite3 (Development)
• Production Database: PostgreSQL
• Caching Layer: Redis
• Search Engine: Elasticsearch (Optional)

4. Security Architecture

• Authentication: Django Authentication System
• Authorization: Role-Based Access Control (RBAC)
• Data Encryption: AES-256
• HTTPS: TLS 1.3

5. Deployment Architecture

• Web Server: Nginx
• Application Server: Daphne
• Process Manager: Supervisor
• Containerization: Docker
• CI/CD: GitHub Actions

Data Flow

Query Submission Flow

1. User submits query through frontend
2. Request validated by Django middleware
3. Query stored in database
4. Notification sent through WebSocket
5. Email notification sent (optional)

Real-time Communication Flow

1. WebSocket connection established
2. Messages routed through Django Channels
3. Redis backend for message persistence
4. Real-time updates to connected clients

Performance Considerations

Caching Strategy

• Page Caching: 5 minutes
• API Response Caching: 1 minute
• Static Asset Caching: 1 week
• Database Query Caching: 15 minutes

Database Optimization

• Indexed fields
• Query optimization
• Connection pooling
• Regular maintenance

Load Balancing

• Horizontal scaling
• Round-robin distribution
• Health checks
• Failover configuration

Monitoring and Logging

Monitoring Tools

• Application: New Relic
• Server: Prometheus
• Logging: ELK Stack
• Error Tracking: Sentry

Key Metrics

• Response time
• Error rates
• User sessions
• Resource utilization
• Database performance

Backup and Recovery

Backup Strategy

• Daily database backups
• Weekly full system backups
• Real-time file replication
• Off-site storage

Recovery Procedures

• Point-in-time recovery
• Database restoration
• File system recovery
• Service restoration

Development Workflow

Version Control

• Git flow branching model
• Feature branches
• Release branches
• Hotfix branches

Code Quality

• PEP 8 compliance
• Type checking
• Unit testing
• Integration testing
• Code review process

Security Measures

Application Security

• CSRF protection
• XSS prevention
• SQL injection protection
• Rate limiting
• Input validation

Infrastructure Security

• Firewall configuration
• SSL/TLS encryption
• Regular security audits
• Vulnerability scanning
• Access control lists

Troubleshooting

Common Issues

1. Database Migration Errors

   python manage.py makemigrations
   python manage.py migrate --run-syncdb

2. Static Files Not Loading

   python manage.py collectstatic

3. WebSocket Connection Issues

   • Check Daphne server status
   • Verify ASGI configuration
   • Check firewall settings

Getting Help

• Check the GitHub Issues
• Contact the development team
• Join the community forum

Screenshot

Contributing

Please read PR practices for details on our code of conduct and the process for submitting pull requests.

License

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

📫 Let's Connect

• GitHub: SuhelKhanCA
• LinkedIn: Suhel Khan
• Twitter: Suhel Khan
• Email: [email protected]