ExamGenie

This paper introduces ExamGenie, a next-generation automated exam paper generation system designed to streamline the creation of examination papers for educators. ExamGenie integrates advanced technologies for text extraction, including PyMuPDF, pdfplumber, python-pptx, Tesseract, and Google Cloud Vision (OCR), allowing the system to handle various document formats. Text search is powered by NLTK, regex, and spaCy, while large language models (LLMs) such as OpenAI GPT and Hugging Face Transformers are used for question generation and categorization based on difficulty. Built on robust web frameworks like Flask and Django, and supported by vector databases, ExamGenie offers a flexible and efficient tool for crafting customized, balanced exam papers. This system reduces manual effort, improves accuracy, and ensures alignment with academic standards, providing a significant improvement in the educational examination process.