Studify

Studify is an end-to-end AI learning platform that helps learners go from zero to mastery in any subject through structured courses, AI-generated lessons, adaptive quizzes, and an optional interactive AI tutor — all secured with Microsoft Entra ID External (CIAM) authentication.

It is designed to feel like a personalised digital classroom: you define what you want to learn, and the platform builds, teaches, tests, and guides you step-by-step.

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🧭 How It Works (End-to-End Experience)

🔐 Secure Login with Microsoft Entra ID

Users sign in using Microsoft Entra External ID (CIAM). Authentication is handled via OAuth 2.0 / OpenID Connect, ensuring enterprise-grade security from the very first interaction.

📚 Create AI-Generated Courses in Seconds

Users can create a new course by specifying:

• Subject
• Subtopics
• Difficulty level

After login, users land on their dashboard, where they can view all existing courses or start a new one.

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🧠 AI-Generated Lessons with an Interactive Tutor

Studify uses AI to generate a structured curriculum tailored to the learner's intent and skill level.

Learners can optionally enable an AI Tutor, which opens in a split-screen layout. The tutor can:

• Answer questions about the lesson
• Clarify confusing concepts
• Accept text and image input

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📝 Adaptive Quizzes to Test Understanding

After completing a lesson, users can generate a quiz to test their understanding.
Questions are dynamically created based on lesson content and learning objectives.

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✅ AI Grading with Actionable Feedback

Once submitted, quizzes are:

• Automatically graded by AI
• Evaluated for correctness and reasoning
• Annotated with helpful feedback and improvement advice

For incorrect answers, Studify explains:

• Why the answer is wrong
• What the correct approach is
• How to avoid similar mistakes in the future

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✨ Features

• AI-generated lesson plans and structured curricula
• Dynamic lesson generation and section expansion
• Adaptive quizzes with AI grading
• Progress tracking
• Optional AI Tutor chat (text + image input)
• Secure authentication & authorisation with Microsoft Entra External ID

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📁 Repository Structure

.
├── backend/
│   ├── api.py                     # FastAPI entry point
│   ├── learning_platform.py       # Core orchestration layer
│   ├── requirements.txt
│   ├── documentation/
│   │   └── postman.md              # API collection notes
│   ├── lesson_plans/
│   │   └── lesson_plan_service.py
│   ├── lessons/
│   │   └── lesson_service.py
│   ├── quizzes/
│   │   └── quiz_service.py
│   ├── progress/
│   │   └── progress_service.py
│   ├── users/
│   │   ├── auth.py                 # Entra ID JWT validation
│   │   └── user_creation.py
│   └── shared/
│       ├── models.py               # Pydantic models
│       ├── cosmos_client.py        # Azure Cosmos DB client
│       ├── openai_client.py        # OpenAI wrapper
│       └── cosmos-rbac-guide.md
│
├── frontend/
│   ├── README.md
│   ├── next.config.ts
│   ├── next-env.d.ts
│   ├── public/
│   └── src/
│       ├── app/
│       │   ├── api/tutor-chat/route.ts
│       │   ├── layout.tsx
│       │   ├── ClientLayout.tsx
│       │   └── page.tsx
│       ├── components/
│       │   ├── Platform.tsx        # Main app UI
│       │   ├── AITutorChat.tsx
│       │   ├── LoginPage.tsx
│       │   └── views/
│       │       ├── CreateCourseView.tsx
│       │       ├── LessonView.tsx
│       │       ├── QuizView.tsx
│       │       └── QuizResultView.tsx
│       ├── lib/
│       │   ├── authConfig.ts        # MSAL configuration
│       │   └── msalInstance.ts
│       └── types/
│           └── api.ts
│
└── README.md

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🧠 Architecture Overview

The system consists of a FastAPI backend and a Next.js (App Router) frontend, secured using Microsoft Entra ID External (CIAM).

• Frontend: Next.js (React, App Router) using @azure/msal-react
• Backend: FastAPI with JWT validation via Microsoft Entra External ID
• Auth: OAuth2 / OpenID Connect (Authorisation Code + PKCE)
• Storage: Azure Cosmos DB
• AI: Azure OpenAI APIs for content generation and grading

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Environment Variables (Backend)

COSMOS_DB_ENDPOINT=<endpoint-name>
AZURE_OPENAI_ENDPOINT=https://<endpoint-name>.cognitiveservices.azure.com/
AZURE_OPENAI_KEY=<api-key>
DEPLOYMENT_NAME=<deployment-name>

TENANT_ID=<your-tenant-id>
CLIENT_ID=<backend-app-client-id>

Environment Variables (Frontend)

NEXT_PUBLIC_AZURE_CLIENT_ID=<frontend-client-id>
NEXT_PUBLIC_AZURE_AUTHORITY=https://<TENANT_ID>.ciamlogin.com/<TENANT_ID>
NEXT_PUBLIC_AZURE_KNOWN_AUTHORITY=<TENANT_ID>.ciamlogin.com
NEXT_PUBLIC_AZURE_REDIRECT_URI=http://localhost:3000
NEXT_PUBLIC_API_SCOPE=api://<BACKEND_CLIENT_ID>/access_as_user
AZURE_OPENAI_ENDPOINT=<openai-api-endpoint>
AZURE_OPENAI_KEY=<api-key>
DEPLOYMENT_NAME=<deployment-name>

🚀 Local Development Setup

Prerequisites

• Node.js 18+
• Python 3.14+
• Azure Entra External ID tenant
• Azure Cosmos DB
• OpenAI API key

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Backend Setup

cd backend
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
uvicorn api:app --reload --port 8000

API will be available at:

http://localhost:8000
http://localhost:8000/docs

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Frontend Setup

cd frontend
npm install
npm run dev

Frontend will be available at:

http://localhost:3000

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🧪 API Testing

• Swagger UI: /docs
• Postman notes: backend/documentation/postman.md

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⚠️ Production Notes

• Restrict CORS origins
• Cache JWKS keys with rotation support
• Use HTTPS everywhere
• Store secrets in Azure Key Vault
• Enable conditional access policies in Entra ID

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📜 Licence

This project is licensed under the terms of the MIT Licence.