🧠 CramAI – Study Smarter, Not Harder

A comprehensive web application that uses RAG (Retrieval-Augmented Generation) to help students upload PDFs, organize by subject/topic, and instantly generate summaries, quizzes, and intelligent Q&A content for fast, effective last-minute studying.

🚀 Features

✅ Upload & Organize

• Upload PDFs or notes
• Tag them by subject, topic, and chapter
• Automatically extracted text and structured using NLP

📚 AI Study Tools

1. Summary Generator

   • Auto-generates short summaries per section
   • Choose between "Quick Recap," "Deep Dive," or "Flashcard Format"

2. Question Generator

   • AI-generated questions:
     • MCQs
     • Objective
     • Detailed Q&A
     • Numerical/Problem-solving
   • Categorized by Bloom's taxonomy (recall, analysis, application)

3. Quiz Mode

   • Select topic → choose difficulty level → start quiz
   • "Show Answer" button only reveals answers on click (promotes active recall)
   • Option to enable timed mode for mock exams

4. Ask a Question (Chat Interface)

   • Ask questions directly (like "Explain Newton's Laws" or "Give me 5 MCQs on Thermodynamics")
   • AI retrieves relevant sections + provides tailored response

5. Flashcards

   • Auto-generate flashcards from key points and definitions
   • Supports spaced repetition algorithm

6. Progress Tracking

   • Visual dashboard for completed topics, quiz scores, and weak areas

🛠️ Installation

1. Clone the repository

   git clone <repository-url>
   cd cram-ai

2. Install dependencies

   pip install -r requirements.txt

3. Set up environment variables

   • Create a .env file in the root directory
   • Add your OpenAI API key:

     OPENAI_API_KEY=your_openai_api_key_here
     

4. Run the application

   streamlit run app.py

📋 Requirements

• Python 3.8+
• OpenAI API key
• Streamlit
• LangChain
• PyPDF2
• FAISS
• Other dependencies listed in requirements.txt

🎯 Usage

1. Upload Documents: Go to "Upload & Organize" and upload your PDF study materials
2. Organize Content: Tag each document with subject, topic, and chapter
3. Generate Summaries: Use "Study Tools" to create summaries in different formats
4. Create Quizzes: Generate practice questions and take interactive quizzes
5. Ask Questions: Use the chat interface to ask specific questions about your materials
6. Study with Flashcards: Generate and study with AI-created flashcards
7. Track Progress: Monitor your quiz performance and study statistics

🏗️ Architecture

• Frontend: Streamlit web interface
• Backend: Python with LangChain for AI processing
• Vector Store: FAISS for document embeddings and similarity search
• AI Models: OpenAI GPT models for content generation
• PDF Processing: PyPDF2 for text extraction

📁 Project Structure

cram-ai/
├── app.py                 # Main Streamlit application
├── config.py             # Configuration settings
├── requirements.txt      # Python dependencies
├── utils/
│   ├── __init__.py
│   ├── pdf_processor.py  # PDF text extraction
│   ├── vector_store.py   # Vector store management
│   └── ai_helpers.py     # AI content generation
└── README.md

🔧 Configuration

Edit config.py to customize:

• Default subjects and topics
• Chunk sizes for text processing
• Quiz difficulty levels
• Summary types

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request

📄 License

This project is licensed under the MIT License.

🆘 Support

If you encounter any issues or have questions, please open an issue on GitHub.

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Built with ❤️ using Streamlit and LangChain