📘 QuizifyAI

An interactive Streamlit app powered by LangChain and Groq LLMs that helps students learn faster by turning PDF study material into:

• Q&A (Question–Answer pairs)
• MCQs (Multiple-Choice Questions)
• Flashcards
• Summaries

Upload your PDF, select a mode, and generate high-quality study content instantly.

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🚀 Features

• 📂 Upload PDFs and automatically split them into manageable chunks.

• 🤖 LLM-powered generation using Groq’s llama-3.3-70b-versatile model.

• 📝 Modes Available:

  • Q&A pairs
  • MCQs with answers
  • Flashcards (concise one-line answers)
  • Summaries

• 🎚️ Difficulty Levels: Easy, Medium, Hard

• ⏱️ Fast & Accurate generation with duplicate removal and consolidation.

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🛠️ Installation & Running

🔑 Setting up Groq API Key

For this project, you need a Groq API key.

1. Sign up at Groq and get your API key.
2. Create a .env file in the root folder and add:

echo "GROQ_API_KEY=your_api_key_here" > .env

1. Clone the repo

git clone https://github.com/fns12/quizify-ai.git
cd quizify-ai

2. Create virtual environment & install dependencies

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

pip install -r requirements.txt

3. Run the app with Streamlit:

streamlit run main.py

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🚀 Using the Live Demo

You can try the deployed app here: Live Demo

When running the demo, you need to provide your GROQ API Key:

1. Go to manage app,click the three dots (⋮) → Settings → Secrets.

2. Add your key in the following format:

   GROQ_API_KEY="your_api_key_here"
   

3. Save and restart the app.

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▶️ Usage

1. Upload a PDF file.
2. Choose a mode (QNA, MCQs, Flashcards, or Summary).
3. Select difficulty and number of questions.
4. Click Generate 🚀.
5. View and copy results directly.

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📂 Project Structure

quizify-ai/
│── main.py              # Main Streamlit app
│── requirements.txt    # Python dependencies
│── .env.example        # Example env file (ignored in git)
│── README.md           # Project documentation

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📸 Screenshots (Optional)

Add screenshots here of the interface and output.

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📌 Example Outputs

Q&A

Q.1: What is machine learning?  
A: Machine learning is a field of AI focused on training algorithms to learn patterns from data.  

Q.2: Define supervised learning.  
A: Supervised learning is a type of ML where models are trained on labeled data.  

MCQ

1. Which of the following is a supervised algorithm?  
   A) K-Means  
   B) Linear Regression ✅  
   C) PCA  
   D) Autoencoder  

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🤝 Contributing

Pull requests are welcome! For major changes, please open an issue first to discuss what you’d like to change.

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📜 License

MIT License