StudentWhisperer

A modern educational platform that combines student information management with AI-powered assistance.

Student_Whisperer_Demo_vid.mp4

Overview

StudentWhisperer is an integrated platform designed to enhance the educational experience for students through:

• AI Chatbot Support: Get answers to questions about courses, assignments, and academic concepts
• Student Profile Management: Track academic progress, grades, and course information
• Secure Authentication: Multiple login options including traditional credentials and Microsoft SSO
• Responsive UI: Modern interface that works across desktop and mobile devices

Features

• AI Chatbot

  • Natural language processing to answer student questions
  • Context-aware responses based on your academic profile
  • Ability to provide academic guidance and explain concepts

• Student Information System

  • View course enrollments and grades
  • Track progress toward degree completion
  • Access academic records and feedback

• User Management

  • Secure authentication with JWT tokens
  • Profile management (update email, password)
  • Microsoft Azure AD Single Sign-On integration

• Administrative Tools

  • Usage metrics and analytics
  • User management capabilities

Technology Stack

• Frontend: React, TypeScript, Tailwind CSS
• Backend: Python, Flask
• AI Integration: Azure OpenAI Services
• Search: Azure Cognitive Search
• Database: SQL Server, Azure SQL
• Authentication: JWT tokens, Azure AD integration
• Deployment: Docker, Docker Compose, Azure Container Apps

Getting Started

Prerequisites

• Docker and Docker Compose
• Node.js (for local frontend development)
• Python 3.8+ (for local backend development)

Running with Docker

1. Clone the repository

git clone git@github.com:DevOps2025Group1/v4-StudentWhisperer.git
cd v4-StudentWhisperer

2. Start the application using Docker Compose

docker-compose up

3. Access the application at http://localhost

Local Development Setup

Frontend

1. Navigate to the frontend directory

cd frontend

2. Install dependencies

npm install

3. Start the development server

npm run dev

Backend

1. Navigate to the backend directory

cd backend

2. Create a Python virtual environment

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies

pip install -r requirements.txt

4. Set up environment variables (create a .env file based on .env.sample)

cp .env.sample .env
# Edit the .env file with your configurations

5. Start the Flask server

python app.py

Configuration

Environment Variables

The backend requires several environment variables to be set. Create a .env file in the backend directory based on the .env.sample provided:

# Azure OpenAI Configuration
azure-openai-api-key=""
azure-openai-endpoint=""
azure-openai-embedding-deployment-id=""
azure-openai-gpt-model-deployment-id=""
azure-openai-api-version=""

# Azure Search Configuration
azure-search-service-endpoint=""
azure-search-index=""
azure-search-datasource=""
azure-search-skillset=""
azure-search-indexer=""
azure-search-admin-key=""
azure-search-semantic-config=""

# SQL Database Configuration
sql-server=""
sql-db=""
sql-user=""
sql-password=""

These environment variables are used for:

• Connecting to Azure OpenAI for the chatbot functionality
• Setting up Azure Cognitive Search for information retrieval
• Connecting to the SQL database for student information

API Documentation

The backend provides several API endpoints:

• Authentication: /api/auth/login, /api/auth/register, /api/auth/azure-token
• Profile: /api/me, /api/student/courses
• Chat: /api/chat
• Account Management: /api/student/update-email, /api/student/update-password

For a complete list of endpoints and their documentation, see the backend code or run the application and explore the API.

Contributing

We welcome contributions to StudentWhisperer! Please feel free to submit issues or pull requests.

License

This project is licensed under the Apache License 2.0.