🧠 LLM-Powered Flashcard Generator

The LLM-Powered Flashcard Generator is a modern, intelligent study tool that allows students, educators, and content creators to generate question-answer flashcards automatically from educational text or PDF files. It uses advanced NLP models like T5 for question generation and BART for answer extraction, wrapped inside an intuitive Streamlit web app.

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💡 How It Works

🔧 Core Logic (main.py)

The core functionality involves:

1. Sentence Tokenization using NLTK to divide content into logical units.
2. Question Generation using the lmqg/t5-large-squad-qg model.
3. Relevance Ranking of questions via Sentence-BERT embeddings.
4. Answer Extraction using the valhalla/bart-large-finetuned-squadv1 model.
5. PDF support: Users can also upload educational PDFs — text is extracted using PyMuPDF.
6. Flashcard Packaging: Q&A pairs are combined and returned for display or download.

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🖥️ User Interface (streamlit_app.py)

• Paste educational content or upload a .pdf
• Choose how many flashcards to generate
• Optional: Select a subject type to guide the prompt
• View generated flashcards in a styled UI
• Export to CSV or JSON

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📦 Installation & Setup

🔁 Clone the Repository

git clone https://github.com/AmanYadav038/LLM-Powered-Flashcard-Generator.git
cd LLM-Powered-Flashcard-Generator

🐍 Set Up Environment

(Optional but recommended)

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

📥 Install Dependencies

pip install -r requirements.txt

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▶️ Running the Streamlit App

streamlit run streamlit_app.py

Then open the app in your browser at:
📍 http://localhost:8501

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📄 Example API Input/Output (Internally)

{
  "question": "What is the primary function of vehicles?",
  "answer": "To transport people or goods from one place to another."
}

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✨ Features

• 📄 Upload PDFs and extract text
• 📚 Paste raw educational content
• 🎯 Generate flashcards based on subject relevance
• 💾 Export to CSV or JSON
• 💬 Clean and interactive Streamlit interface

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🧪 Example Run

You can try it with examples/vehicles_500_words.pdf or paste your own text.

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🛣️ Future Improvements

• ✅ Add support for multi-language flashcards
• ✅ Fine-tune custom models on educational corpora
• 🔄 Feedback mechanism for students
• 🔖 Export flashcards to Anki/Quizlet formats
• ⚡ Add parallel processing to speed up generation

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📤 Exports

• flashcards.csv — for spreadsheets or sharing
• flashcards.json — for developer use or integration

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