Study Material Automator

A fully automated system that processes PDF class notes and lecture videos into structured study materials, complete with diagrams, flashcards, quizzes, and simplified explanations.

Features

Comprehensive Content Processing

• Extract and analyze text from PDF class notes
• Process and transcribe lecture videos (local files or URLs)
• Intelligent content analysis using AI

Structured Learning Modules

• Automatically organize content into digestible modules
• Break down complex concepts into simple explanations
• Create learning objectives for each module
• Estimate study time requirements

Visual Learning Materials

• Generate concept map diagrams
• Create flow diagrams for processes
• Build hierarchical relationship diagrams
• Export high-quality PNG images

Interactive Study Tools

• Generate flashcards with spaced repetition schedules
• Create comprehensive quizzes for each module
• Multiple question types (multiple choice, true/false, short answer)
• Automatic quiz grading functionality

AI-Powered Intelligence

• Uses GPT-4 for content analysis and generation
• Simplifies complex concepts with analogies
• Identifies relationships between concepts
• Creates context-aware study materials

Intuitive Web Interface

• Modern, responsive UI for easy access
• Drag & drop file upload
• Real-time progress tracking
• Interactive preview of generated materials
• Download materials with one click

User Authentication & Accounts

• Email/password registration and login
• OAuth 2.0 (Google, Microsoft, Apple Sign-In)
• JWT-based secure sessions
• Personal user accounts with data privacy

Progress Tracking & Analytics

• Module completion tracking
• Quiz score recording with performance analytics
• Flashcard review counting
• Study time tracking
• Overall completion percentage
• Personalized study dashboard

Multiple Topic Management

• Upload materials for different subjects
• Organize study content by topic
• Track progress separately for each topic
• Dashboard view of all your topics
• Topic-specific file management

Installation

1. Clone the repository:

git clone https://github.com/Zoe-life/study-material-automator.git
cd study-material-automator

2. Install dependencies:

pip install -r requirements.txt

3. Set up configuration:

cp .env.example .env
# Edit .env and add your configuration:
# - OPENAI_API_KEY (required)
# - DATABASE_URL (defaults to SQLite)
# - OAuth credentials (optional, for social login)

4. Initialize the database (for web interface with auth):

cd web
python -c "from app import app, db; app.app_context().push(); db.create_all()"

Usage

Web Interface (Recommended)

The easiest way to use the Study Material Automator is through the web interface:

cd web
python app.py

Then open your browser to http://localhost:5000

Features:

• Drag & drop PDF upload
• Video URL input
• Interactive results display
• Preview materials in-browser
• Download individual files

Command Line Interface

Process a PDF file:

python main.py --pdf path/to/notes.pdf

Process a video URL:

python main.py --video https://youtube.com/watch?v=example

Process both PDF and video together:

python main.py --pdf notes.pdf --video lecture.mp4

Advanced Options

Specify custom output directory:

python main.py --pdf notes.pdf --output my_study_materials

Use a custom configuration file:

python main.py --pdf notes.pdf --config custom.env

Python API

You can also use the library programmatically:

from src.study_material_automator import StudyMaterialAutomator
from src.utils import Config

# Initialize
config = Config()
automator = StudyMaterialAutomator(config)

# Process materials
results = automator.process_materials(
    pdf_path="notes.pdf",
    video_source="lecture.mp4",
    output_dir="output"
)

# Access generated materials
print(f"Modules: {results['modules']}")
print(f"Flashcards: {results['flashcards']}")
print(f"Quizzes: {results['quizzes']}")

Output Structure

The system generates the following materials in the output directory:

output/
├── module_1.txt              # Learning module 1
├── module_1_quiz.txt         # Quiz for module 1
├── module_2.txt              # Learning module 2
├── module_2_quiz.txt         # Quiz for module 2
├── diagram_Topic1.png        # Concept diagram
├── diagram_Topic2.png        # Concept diagram
├── flashcards.txt            # Study flashcards
├── comprehensive_quiz.txt    # Overall assessment
└── summary.json              # Summary of all materials

Configuration

Create a .env file with the following variables:

# Required
OPENAI_API_KEY=your_api_key_here

# Optional
OPENAI_MODEL=gpt-4                 # AI model to use
OPENAI_TEMPERATURE=0.7             # Creativity level (0-1)
OUTPUT_DIR=output                  # Output directory
TEMP_DIR=temp                      # Temporary files directory

Requirements

• Python 3.8+
• OpenAI API key
• FFmpeg (for video processing)

Architecture

The system is organized into modular components:

• Processors: Extract content from PDFs and videos
• Analyzers: Use AI to analyze and structure content
• Generators: Create study materials (modules, diagrams, flashcards, quizzes)
• CLI: Command-line interface for easy usage

Examples

See the examples/ directory for sample inputs and outputs.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is open source and available under the MIT License.

Acknowledgments

• Built with OpenAI's GPT-4 for intelligent content analysis
• Uses Whisper API for video transcription
• Matplotlib for diagram generation