AUTOMATIC QUESTION AND ANSWER GENERATION BY USING NLP AND FLASK FRAMEWORK

In the evolving landscape of Natural Language Processing (NLP), the demand for automated systems capable of generating relevant questions from textual data has grown substantially. This research introduces an innovative approach leveraging advanced NLP techniques combined with the Flask framework to develop a dynamic question and answer generation system. The proposed system demonstrates promising results in generating coherent and contextually relevant questions based on the input text, thereby enhancing the accessibility and comprehension of textual content.