Text Based Question Answering System

The “Question Answering System Based on Paragraph” is a Python-based web application designed to provide users with a seamless experience in extracting answers from textual content. Built with Flask, the application allows users to securely log in, paste a paragraph of text into an input field, and ask questions about the content. By leveraging the Gemini/OpenAI API, the system comprehends the provided paragraph’s context, enabling it to generate accurate and context-aware answers to user queries. This application is particularly useful for students, researchers, and professionals who need quick insights from large texts without manually searching for information. The project also includes basic user authentication through login and registration features, ensuring a personalized experience. This innovative approach combines natural language processing with advanced AI capabilities to offer an efficient and user- friendly solution for text-based question answering.

Python, Flask, web application, login, registration, paragraph input, question answering, OpenAI API, natural language processing, text comprehension, user authentication

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