This application uses RAG (Retrieval-Augmented Generation) to generate multiple-choice questions and short answer questions from PDF documents. It leverages LangChain, FAISS, Azure OpenAI, and Streamlit to create an interactive question generation system.

• Upload PDF documents
• Extract and process content using LangChain
• Store document chunks in FAISS vector store
• Generate 5 MCQs with options and answers
• Generate 5 Short Answer Questions
• Interactive Streamlit interface

1. Create a .env file in the project root with your Azure OpenAI credentials:

AZURE_OPENAI_ENDPOINT=your_endpoint
AZURE_OPENAI_API_VERSION=your_api_version
AZURE_OPENAI_API_KEY=your_api_key
AZURE_OPENAI_DEPLOYMENT_NAME=your_deployment_name

2. Install the required dependencies:

pip install -r requirements.txt

3. Run the Streamlit application:

streamlit run APP.py

1. Open the application in your web browser
2. Upload a PDF document using the file uploader
3. Wait for the processing to complete
4. View the generated MCQs and Short Answer Questions

• Python 3.8+
• Azure OpenAI API access
• Internet connection for API calls