📚 Prepare — AI-Powered Educational Platform

Prepare is a full-stack educational SaaS platform that helps students learn smarter through AI-generated practice exams, conversational AI tutoring, and session-based note management — all in one place.

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✨ Features

🧪 AI Exam Generator

• Enter any topic (or upload a PDF) and get 10 auto-generated MCQ questions powered by Google Gemini
• 2-minute countdown timer with color warnings
• Visual question navigation panel (unanswered → marked → answered)
• Instant score + detailed answer explanations on submission

💬 Conversational AI Tutor

• Chat with an AI that explains topics interactively with examples
• Real-time streaming responses — no waiting for full replies
• Full chat history saved and accessible from your dashboard
• Markdown rendering for clean, structured answers

📝 Notes Manager

• Create, edit, and delete notes directly within a chat session
• Notes are auto-saved on page leave
• Organized per user and per session
• Soft-delete support (notes are recoverable)

👤 User Management

• Email verification on signup (account inactive until verified)
• Secure password reset via tokenized email links
• Daily usage quotas — 3 exam generations and 10 chat interactions per day (auto-reset every 24 hours)

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🛠️ Tech Stack

Layer	Technology
Backend	Django 5.2.5 (Python)
Relational DB	PostgreSQL via Neon, Render
Document DB	MongoDB Atlas (via MongoEngine ODM)
AI	Google Gemini 2.5 Flash API
Frontend	Django Templates + Tailwind CSS
JS	Vanilla JavaScript + Fetch API
Markdown	Marked.js
Email	Gmail SMTP
Static Files	Whitenoise
Containerization	Docker

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🏗️ Architecture Overview

Prepare uses a dual-database architecture:

• PostgreSQL — handles structured, relational data: users, sessions, usage quotas
• MongoDB — handles flexible document storage: chats, exams, notes

┌─────────────────────────────────────────────┐
│                   Client                    │
│     (Django Templates + Tailwind + JS)      │
└────────────────────┬────────────────────────┘
                     │
┌────────────────────▼────────────────────────┐
│               Django Backend                │
│  Auth │ Exam Module │ Chat Module │ Notes   │
└──────┬─────────────┬──────────────┬─────────┘
       │             │              │
  PostgreSQL      MongoDB       Gemini API
  (Users,        (Exams,        (AI responses,
   Sessions,      Chats,         Question gen,
   Quotas)        Notes)         Streaming)

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🔁 Data Flow

Exam Flow

User Input (Topic + Optional PDF)
        ↓
  opt1_view → File upload to temp folder
        ↓
  Gemini API → Parse JSON questions
        ↓
  Store in MongoDB → Set session['exam_id']
        ↓
  exam_view → User answers questions
        ↓
  update_exam → Save responses + calculate score

Chat Flow

create_chat → New MongoDB chat document
        ↓
  start_chat → Set session['chat_id']
        ↓
  ask_view → Stream response from Gemini
        ↓
  save_chat_history → Store in ChatHistory
        ↓
  Frontend renders Markdown response
        ↓
  create_note → Attach notes to session

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📡 API Endpoints

Endpoint	Method	Description
/api/get-gen-ques/	GET	Fetch generated exam questions
/api/update-exam/	POST	Save user answers & score
/api/create_chat/	POST	Create a new chat session
/api/ask/	POST	Send message (streaming response)
/api/get-chats/	GET	List all user chats
/api/get-chathis/	GET	Fetch chat message history
/api/create-note/	POST	Create a new note
/api/get-noteslist/	GET	List all notes
/api/update-note/	POST	Update note content
/api/delete-note/	DELETE	Delete a note (soft delete)

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⚙️ Getting Started

Prerequisites

• Python 3.x
• Node.js (for Tailwind CSS compilation)
• MongoDB Atlas account
• PostgreSQL database (Neon recommended)
• Google Gemini API key
• Gmail account (for SMTP)

1. Clone the repository

git clone https://github.com/lubaid-01/Prepare.git
cd prepare

2. Create and activate a virtual environment

python -m venv venv
source venv/bin/activate      # macOS/Linux
venv\Scripts\activate         # Windows

3. Install dependencies

pip install -r requirements.txt

4. Set up environment variables

Create a .env file in the project root:

DJANGO_SECRET_KEY=your_secret_key
DJANGO_DEBUG=True
DJANGO_ALLOWED_HOSTS=localhost,127.0.0.1

DATABASE_URL=your_postgresql_connection_string
MONGO_URI=your_mongodb_atlas_connection_string

GEMINI_API_KEY=your_google_gemini_api_key

EMAIL_HOST_USER=your_gmail_address
GMAIL_PASSWORD=your_gmail_app_password

5. Apply migrations

python manage.py migrate

6. Compile Tailwind CSS

npm install
npx tailwindcss -i ./static/css/input.css -o ./static/css/output.css --watch

7. Run the development server

python manage.py runserver

Visit http://127.0.0.1:8000 in your browser.

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🐳 Docker Setup

docker build -t prepare .
docker run -p 8000:8000 --env-file .env prepare

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🔐 Security

• CSRF protection on all POST requests
• @login_required enforced on all protected endpoints
• Users remain inactive until email is verified
• Token-based password reset
• Secrets managed via .env (never committed to version control)

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📁 Project Structure

prepare/
├── project/
│   ├── core/               # Main app (exam, chat, notes)
│   │   ├── views.py        # All core view logic
│   │   └── templates/core/ # HTML templates
│   ├── accounts/           # Auth, registration, verification
│   ├── static/
│   │   └── js/
│   │       ├── exam.js     # Timer, navigation, submission
│   │       ├── opt2.js     # Streaming chat, notes panel
│   │       └── profile.js  # Dashboard: history, results
│   └── settings.py
├── Dockerfile
├── requirements.txt
└── .env.example

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🚦 Usage Limits

Feature	Daily Limit	Reset
Exam Generation	3 per day	Every 24 hours
Chat Interactions	10 per day	Every 24 hours

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🤝 Contributing

Contributions are welcome! Please open an issue first to discuss any changes you'd like to make, then submit a pull request.

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📄 License

This project is licensed under the MIT License.

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Built with ❤️ using Django, MongoDB, and Google Gemini.