🧠 StudyPal - AI-Powered Study Companion

An intelligent learning platform that transforms study materials into interactive flashcards and adaptive quizzes using natural language processing. StudyPal helps students learn more efficiently with AI-powered content analysis, spaced repetition algorithms, and personalized difficulty adjustment.

Key Features

Document Processing

• Multi-format Support - Upload PDF, DOCX, or TXT files
• Intelligent Text Extraction - Parses complex documents with high accuracy
• AI Content Analysis - Automatically identifies key concepts, topics, and difficulty level
• Smart Summarization - Generates concise summaries using extractive NLP

Flashcard System

• Auto-generation - Creates flashcards from uploaded documents using NLP
• Spaced Repetition (SM-2) - Optimizes review timing based on performance
• Manual Editing - Customize AI-generated cards to your preferences
• Progress Tracking - Monitor mastery levels for each card

Adaptive Quizzes

• Multiple Question Types - Multiple choice, true/false, fill-in-the-blank
• Difficulty Adaptation - Adjusts based on user performance
• Instant Feedback - Detailed explanations for each answer
• Performance Analytics - Identifies strengths and knowledge gaps

Learning Analytics

• Study Session Tracking - Records time, cards reviewed, and accuracy
• Streak Monitoring - Gamified daily study streaks
• Progress Dashboard - Visual insights into learning patterns
• AI Recommendations - Personalized study suggestions

Architecture

┌────────────────────────────────┐
│   React Frontend (TypeScript)  │
│  - Document Upload Interface   │
│  - Flashcard Review System     │
│  - Quiz Taking Platform        │
│  - Analytics Dashboard         │
└───────────┬────────────────────┘
            │ REST API
┌───────────▼────────────────────┐
│  Node.js + Express Backend     │
│  - Authentication (JWT)        │
│  - Document Management         │
│  - Spaced Repetition Logic     │
│  - Study Session Tracking      │
└──┬─────────────────────┬───────┘
   │                     │
   ▼                     ▼
┌──────────┐      ┌─────────────────────┐
│ MongoDB  │      │  Python NLP Service │
│          │      │    (FastAPI)        │
│ - Users  │      │  - PDF Parsing      │
│ - Docs   │      │  - Text Analysis    │
│ - Cards  │      │  - Summarization    │
│ - Quizzes│      │  - Flashcard Gen    │
│ - Sessions│     │  - Quiz Generation  │
└──────────┘      └─────────────────────┘

🛠️ Tech Stack

Frontend

• React 18 with TypeScript
• Tailwind CSS for styling
• Lucide React for icons
• Axios for API requests
• React Router for navigation

Backend

• Node.js with Express.js
• TypeScript for type safety
• MongoDB with Mongoose ODM
• JWT for authentication
• Multer for file uploads

NLP/AI Service

• Python 3.10+ with FastAPI
• spaCy for NLP tasks
• PyPDF2 for PDF parsing
• python-docx for Word documents
• scikit-learn for ML algorithms

Algorithms

• SM-2 Spaced Repetition - Optimizes flashcard review intervals
• Extractive Summarization - Sentence scoring and ranking
• Keyword Extraction - TF-IDF and noun phrase analysis
• Difficulty Estimation - Multi-factor text complexity analysis

Getting Started

Prerequisites

node >= 18.0.0
python >= 3.10
mongodb >= 5.0

Installation

1. Clone the repository

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

2. Backend Setup

cd backend
npm install
cp .env.example .env
# Configure MongoDB URI and NLP API URL
npm run dev

3. NLP Service Setup

cd nlp_service
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate
pip install -r requirements.txt
python -m spacy download en_core_web_sm
uvicorn main:app --reload

4. Frontend Setup

cd frontend
npm install
cp .env.example .env
npm start

Environment Variables

Backend (.env)

MONGODB_URI=mongodb://localhost:27017/studypal
JWT_SECRET=your-secret-key
NLP_API_URL=http://localhost:8000
PORT=3000

Frontend (.env)

REACT_APP_API_URL=http://localhost:3000/api

📚 API Documentation

Documents

• POST /api/documents/upload - Upload and process document
• GET /api/documents - List user's documents
• GET /api/documents/:id - Get document details
• DELETE /api/documents/:id - Delete document

Flashcards

• POST /api/flashcards/generate - Generate flashcards from document
• GET /api/flashcards/due - Get cards due for review
• POST /api/flashcards/:id/review - Submit flashcard review
• GET /api/flashcards - List all flashcards
• PUT /api/flashcards/:id - Update flashcard
• DELETE /api/flashcards/:id - Delete flashcard

Quizzes

• POST /api/quizzes/generate - Generate quiz from document
• GET /api/quizzes - List available quizzes
• GET /api/quizzes/:id - Get quiz details
• POST /api/quizzes/:id/start - Start quiz attempt
• POST /api/quizzes/attempts/:id/submit - Submit quiz answers

Study Analytics

• POST /api/study/session/start - Start study session
• POST /api/study/session/:id/end - End study session
• GET /api/study/analytics - Get study statistics

NLP Endpoints

• POST /nlp/parse-document - Extract text from file
• POST /nlp/analyze - Analyze content
• POST /nlp/generate-flashcards - Create flashcards
• POST /nlp/generate-quiz - Create quiz questions
• POST /nlp/summarize - Generate summary

Spaced Repetition Algorithm (SM-2)

StudyPal implements the SuperMemo 2 (SM-2) algorithm for optimal review scheduling:

# Quality rating: 0-5 (0=blackout, 5=perfect)
new_EF = EF + (0.1 - (5 - quality) * (0.08 + (5 - quality) * 0.02))

if quality < 3:  # Incorrect
    interval = 1 day
    repetitions = 0
else:  # Correct
    if repetitions == 0:
        interval = 1 day
    elif repetitions == 1:
        interval = 6 days
    else:
        interval = previous_interval * EF

Benefits:

• Cards you know well appear less frequently
• Struggling cards appear more often
• Review timing adapts to individual retention patterns
• Maximizes long-term memory retention

Screenshots

Dashboard

![Dashboard showing study stats, recent documents, and due flashcards]

Flashcard Review

![Interactive flashcard with flip animation and quality rating]

Quiz Interface

![Multiple choice quiz with instant feedback]

Document Upload

![Drag-and-drop upload with AI analysis progress]

NLP Features Explained

Text Extraction

• PDF: Uses PyPDF2 to extract text from all pages
• DOCX: Parses Word documents with python-docx
• TXT: Direct UTF-8 text reading

Content Analysis

1. Named Entity Recognition - Identifies people, places, concepts
2. Noun Phrase Extraction - Finds key terms and topics
3. Difficulty Estimation - Analyzes sentence complexity, vocabulary diversity
4. Topic Modeling - Extracts main themes using frequency analysis

Flashcard Generation Strategies

1. Definition Detection - Finds "X is Y" patterns
2. Important Sentence Selection - Scores based on keywords and length
3. Key Term Extraction - Creates term-definition pairs

Quiz Generation

• Multiple Choice: Blanks out key terms, generates distractors
• True/False: Modifies statements to create false versions
• Adaptive Difficulty: Adjusts question complexity based on user level

Database Schema Highlights

Flashcard Model

{
  front: String,
  back: String,
  spaced_repetition: {
    easiness_factor: Number,
    interval: Number,
    repetitions: Number,
    next_review_date: Date
  },
  review_history: [{
    quality: Number,
    response_time: Number
  }]
}

Quiz Attempt Model

{
  quiz_id: ObjectId,
  answers: [{
    question_id: ObjectId,
    user_answer: String,
    is_correct: Boolean
  }],
  score: Number,
  performance_analysis: {
    strengths: [String],
    weaknesses: [String]
  }
}

Development Roadmap

Phase 1: Core Features

• Document upload and parsing
• Flashcard generation
• Spaced repetition system
• Quiz generation
• Basic analytics

Phase 2: Enhanced Learning (4 weeks)

• Voice-to-text for flashcard answers
• Image occlusion for diagrams
• Collaborative study sets
• Mobile app (React Native)

Phase 3: Advanced AI (6 weeks)

• GPT integration for better content generation
• Personalized learning paths
• Predictive performance modeling
• Natural language quiz answers (not just multiple choice)

Phase 4: Social Features (4 weeks)

• Study groups and leaderboards
• Shared flashcard decks
• Peer tutoring matching
• Study challenges and competitions

Testing

# Backend tests
cd backend
npm test

# NLP service tests
cd nlp_service
pytest

# Frontend tests
cd frontend
npm test

# E2E tests
npm run test:e2e

📈 Performance Metrics

• Document Processing: <5 seconds for typical PDF
• Flashcard Generation: ~10 cards per second
• Spaced Repetition Calculation: <10ms per card
• Quiz Generation: <3 seconds for 10 questions
• API Response Time: <100ms for most endpoints

Security Features

• Authentication: JWT tokens with secure httpOnly cookies
• File Validation: Type and size checks before processing
• Input Sanitization: Prevents XSS and injection attacks
• Rate Limiting: Prevents API abuse
• Data Privacy: User data encrypted at rest

What I Learned

Through building StudyPal, I gained expertise in:

• Natural language processing with spaCy
• Complex algorithm implementation (SM-2)
• File parsing and text extraction
• MongoDB schema design for flexible data
• Microservices architecture
• Educational technology best practices

Contributing

Contributions welcome! Please read CONTRIBUTING.md for guidelines.

License

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

Author

Your Name

• LinkedIn: linkedin.com/in/yourprofile

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Built with ❤️ to help students learn more effectively through AI-powered study tools