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🎓 LearnPro AI

A full-stack AI-powered learning platform built with the MERN stack and Tailwind CSS — helping students learn smarter through contextual AI chat, auto-generated flashcards, quizzes, and real-time progress tracking.

dashboardLearn documentLearn chatLearn SummaryLearn flashcardLearn quizzesLearn

📖 Table of Contents

🚀 Overview

LearnPro AI is a full-stack learning platform that lets students upload PDF documents and instantly unlock AI-powered study tools — contextual chat, automatic summaries, concept explanations, flashcard generation, and quizzes — all powered by Google Gemini API (gemini-2.5-flash-lite).

PDFs are stored on Cloudinary (up to 10MB), processed server-side via pdf-parse to extract text, which is then chunked and scored for relevance before being passed to Gemini for intelligent responses.

✨ Features

🤖 AI Learning Assistant (Google Gemini)

  • Contextual Chat — Ask questions about any uploaded document; relevant text chunks are retrieved and passed as context to Gemini
  • Auto Summary — Generate a concise document summary with one click
  • Concept Explanation — Enter any concept and get a detailed, document-grounded explanation
  • Persistent Chat History — Conversations are saved per document in MongoDB

📄 PDF Upload & Management

  • Upload PDFs up to 10MB via Multer + Cloudinary (multer-storage-cloudinary)
  • Embedded Google Docs in-browser viewer — no forced download
  • Background text extraction and chunking after upload (status: processing → ready → failed)

🧠 AI Flashcard Generator

  • Auto-generates 10–20 flashcards per document using Gemini
  • Each card includes question, answer, and difficulty (easy / medium / hard)
  • Flip animation, star/favourite toggle, and review count tracking
  • Multiple flashcard sets per document

📝 AI Quiz Generator

  • Generates multiple-choice quizzes (configurable question count) from document content
  • 4 options per question with correct answer mapping and explanation
  • Full submit flow with per-question result, score percentage, and detailed review page

📊 Progress Dashboard

  • Overview stats: total documents, flashcard sets, flashcards, and quizzes
  • Recent activity feed (last accessed documents + quiz attempts) with live timestamps
  • Per-set progress bars showing reviewed vs. total flashcard counts

🔐 JWT Authentication

  • Register / Login with bcrypt-hashed passwords
  • JWT stored in localStorage, attached via Axios request interceptor
  • Protected routes on both frontend (ProtectedRoute) and backend (protect middleware)
  • Profile page with password change support

🛠 Tech Stack

Backend (/backend)

Layer Technology
Runtime Node.js 20+
Framework Express.js 5
Database MongoDB + Mongoose 9
AI @google/genai (Gemini 2.5 Flash Lite)
Auth jsonwebtoken + bcryptjs
File Upload Multer 2 + multer-storage-cloudinary
File Storage Cloudinary
PDF Parsing pdf-parse (fetches from Cloudinary URL)
Validation express-validator

Frontend (/frontend)

Layer Technology
Framework React 19 + Vite 7
Styling Tailwind CSS 4
Routing React Router DOM 7
HTTP Axios (with JWT interceptors)
Markdown react-markdown + remark-gfm + react-syntax-highlighter
UI Icons Lucide React
Notifications react-hot-toast
Dates Moment.js

📁 Project Structure

learnpro-ai/
├── package.json                  # Root scripts (install-all, build, start)
│
├── backend/
│   ├── server.js                 # Express app, CORS, routes, production static serving
│   ├── package.json
│   ├── config/
│   │   ├── db.js                 # MongoDB connection
│   │   ├── cloudinary.js         # Cloudinary SDK config
│   │   └── multer.js             # Multer + CloudinaryStorage (10MB PDF limit)
│   ├── controllers/
│   │   ├── authController.js     # register, login, getProfile, updateProfile, changePassword
│   │   ├── documentController.js # upload, getDocuments, getDocument, deleteDocument
│   │   ├── aiController.js       # generateFlashcards, generateQuiz, generateSummary, Chat, explainConcept, getChatHistory
│   │   ├── flashcardController.js
│   │   ├── quizController.js
│   │   └── progressController.js # getDashboard (aggregated stats + recent activity)
│   ├── middleware/
│   │   ├── auth.js               # JWT protect middleware
│   │   └── errorHandler.js       # Centralised error handler (Mongoose, Multer, Cloudinary, JWT)
│   ├── models/
│   │   ├── User.js               # username, email, bcrypt password
│   │   ├── Document.js           # cloudinaryUrl, cloudinaryPublicId, chunks[], status
│   │   ├── Flashcard.js          # cards[]: question, answer, difficulty, reviewCount, isStarred
│   │   ├── Quiz.js               # questions[], userAnswers[], score, completedAt
│   │   └── ChatHistory.js        # messages[]: role, content, relevantChunks
│   ├── routes/
│   │   ├── authRoutes.js
│   │   ├── documentRoutes.js
│   │   ├── aiRoutes.js
│   │   ├── flashcardRoutes.js
│   │   ├── quizRoutes.js
│   │   └── progressRoutes.js
│   └── utils/
│       ├── geminiService.js      # Gemini API wrappers (flashcards, quiz, summary, chat, explain)
│       ├── pdfParser.js          # Fetches PDF from Cloudinary URL → extracts text via pdf-parse
│       └── textChunker.js        # chunkText() (500 words, 50 overlap) + findRelevantChunks() (keyword scoring)
│
└── frontend/
    ├── index.html
    ├── vite.config.js
    ├── package.json
    └── src/
        ├── App.jsx               # Routes + auth redirect guard
        ├── main.jsx              # AuthProvider + Toaster
        ├── index.css             # Tailwind 4 + Urbanist Google Font
        ├── context/
        │   └── AuthContext.jsx   # Global auth state synced with localStorage
        ├── services/             # Axios API call wrappers per domain
        │   ├── authService.js
        │   ├── documentService.js
        │   ├── aiService.js
        │   ├── flashcardService.js
        │   ├── quizeService.js
        │   └── progressService.js
        ├── utils/
        │   ├── apiPaths.js       # Centralised API route constants
        │   └── axiosInstance.js  # Axios instance with JWT + error interceptors
        ├── components/
        │   ├── auth/ProtectedRoute.jsx
        │   ├── layout/           # AppLayout, Sidebar (mobile + desktop), Header
        │   ├── common/           # Button, Modal, Spinner, Tabs, PageHeader, EmptyState, MarkdownRender
        │   ├── ai/AIActions.jsx  # Summary + Explain Concept UI
        │   ├── chat/ChatInterface.jsx
        │   ├── documents/DocumentCard.jsx
        │   ├── flashcards/       # Flashcard (flip), FlashcardManager, FlashcardSetCard
        │   └── quizzes/          # QuizCard, QuizManager
        └── pages/
            ├── Auth/             # LoginPage, RegisterPage
            ├── Dashboard/        # DashboardPage (stats + activity feed)
            ├── Documents/        # DocumentListPage, DocumentDetailPage (5-tab layout)
            ├── Flashcards/       # FlashcardsListPage, FlashcardPage
            ├── Quizzes/          # QuizTakePage, QuizResultPage
            └── Profile/          # ProfilePage (view info + change password)

🏁 Getting Started

Prerequisites

Installation

1. Clone the repository

git clone https://github.com/your-username/learnpro-ai.git
cd learnpro-ai

2. Install all dependencies

npm run install-all

Or install each separately:

cd backend && npm install
cd ../frontend && npm install

Environment Variables

Create a .env file inside /backend:

# Server
PORT=5000
NODE_ENV=development

# MongoDB
MONGODB_URI=your_mongodb_connection_string

# JWT
JWT_SECRET=your_super_secret_jwt_key
JWT_EXPIRE=7d

# Google Gemini
GEMINI_API_KEY=your_gemini_api_key

# Cloudinary
CLOUDINARY_CLOUD_NAME=your_cloud_name
CLOUDINARY_API_KEY=your_api_key
CLOUDINARY_API_SECRET=your_api_secret

# Frontend URL (for CORS)
CLIENT_URL=http://localhost:5173

Create a .env file inside /frontend:

VITE_SERVER_URL=http://localhost:5000

Running the App

Development — run both servers separately:

# Terminal 1 — Backend (nodemon)
cd backend
npm run dev

# Terminal 2 — Frontend (Vite HMR)
cd frontend
npm run dev

Production build:

# From the root directory
npm run build    # builds frontend/dist via Vite
npm run start    # starts backend; Express serves frontend/dist in production

The frontend runs at http://localhost:5173 and the API at http://localhost:5000.

In production, the Express server serves the built React app from ../frontend/dist and catches all non-API routes with a /{*splat} handler to support client-side navigation.

📡 API Endpoints

All routes are prefixed with /api. Protected routes require the header:

Authorization: Bearer <jwt_token>

Auth — /api/auth

Method Endpoint Access Description
POST /register Public Register new user (username, email, password)
POST /login Public Login, returns JWT + user object
GET /profile Protected Get current user profile
PUT /profile Protected Update username / email
POST /change-password Protected Change password (currentPassword, newPassword)

Documents — /api/documents

Method Endpoint Access Description
POST /upload Protected Upload PDF (multipart/form-data: file, title)
GET / Protected List all user documents with flashcard & quiz counts
GET /:id Protected Get single document; updates lastAccessed
DELETE /:id Protected Delete document + Cloudinary raw file

AI — /api/ai

Method Endpoint Access Description
POST /generate-flashcards Protected Generate flashcards (documentId, optional count)
POST /generate-quiz Protected Generate quiz (documentId, numQuestions, title)
POST /generate-summary Protected Summarise document (documentId)
POST /chat Protected Chat with document (documentId, question)
POST /explain-concept Protected Explain concept (documentId, concept)
GET /chat-history/:documentId Protected Retrieve saved chat messages for a document

Flashcards — /api/flashcards

Method Endpoint Access Description
GET / Protected Get all flashcard sets for current user
GET /:documentId Protected Get flashcard sets for a specific document
POST /:cardId/review Protected Increment reviewCount + update lastReviewed
PUT /:cardId/star Protected Toggle isStarred on a card
DELETE /:id Protected Delete an entire flashcard set

Quizzes — /api/quizzes

Method Endpoint Access Description
GET /:documentId Protected Get quizzes for a document
GET /quiz/:id Protected Get a single quiz by ID
POST /:id/submit Protected Submit answers array, calculates & saves score
GET /:id/results Protected Get detailed quiz results with explanations
DELETE /:id Protected Delete a quiz

Progress — /api/progress

Method Endpoint Access Description
GET /dashboard Protected Aggregated stats + recent 5 documents & quizzes

🏗 Architecture

┌──────────────────────────────────────────────────────────────┐
│                  FRONTEND  (React 19 + Vite 7)               │
│                                                              │
│  AuthContext → Axios Interceptor (JWT) → API Service Layer   │
│                                                              │
│  Pages: Dashboard | Documents | Flashcards | Quizzes | Profile│
│  Document Detail: Content | Chat | AI Actions | FC | Quiz    │
└───────────────────────┬──────────────────────────────────────┘
                        │ HTTP (REST)
┌───────────────────────▼──────────────────────────────────────┐
│               BACKEND  (Express.js 5, Node.js 20)            │
│                                                              │
│  protect (JWT) → Routes → Controllers → Utils / Services     │
│  Centralised errorHandler (Mongoose, Multer, JWT, Cloudinary) │
└───────────┬──────────────────────────┬───────────────────────┘
            │                          │
┌───────────▼──────────┐  ┌────────────▼────────────────────┐
│  MongoDB (Mongoose)  │  │  External Services               │
│                      │  │                                  │
│  Users               │  │  Cloudinary  (PDF raw storage)   │
│  Documents + Chunks  │  │  Google Gemini API               │
│  Flashcards          │  │    gemini-2.5-flash-lite         │
│  Quizzes             │  │  pdf-parse   (text extraction)   │
│  ChatHistory         │  │                                  │
└──────────────────────┘  └──────────────────────────────────┘

PDF Processing Pipeline

1. User uploads PDF (Multer → Cloudinary)
2. Document saved to MongoDB (status: "processing")
3. processPDF() runs async in background:
   a. fetch(cloudinaryUrl) → ArrayBuffer
   b. pdf-parse extracts raw text
   c. chunkText(text, 500 words, 50-word overlap) → chunks[]
   d. Document updated: extractedText, chunks, status: "ready"
4. AI requests use findRelevantChunks():
   - Keyword scoring with stop-word filtering
   - Exact match (+3) and partial match (+1.5) scoring
   - Position bias + multi-word bonus
   - Top 3 chunks passed as context to Gemini

🤝 Contributing

Contributions are welcome!

  1. Fork the repository
  2. Create a feature branch: git checkout -b feature/your-feature
  3. Commit your changes: git commit -m "feat: add your feature"
  4. Push to the branch: git push origin feature/your-feature
  5. Open a Pull Request

Built with ❤️ using the MERN Stack, Google Gemini AI & Cloudinary

⭐ Star this repo · 🐛 Report a Bug · 💡 Request a Feature

About

LearnPro AI is a full-stack learning platform that lets students upload PDF documents and instantly unlock AI-powered study tools — contextual chat, automatic summaries, concept explanations, flashcard generation, and quizzes — all powered by Google Gemini API.

learnpro-ai.onrender.com/login

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