Generative AI-Powered Conversational Assistant for Document, Web, and Repository Interaction and Retrieval

With continuously increasing digital content and resources, it has become even more essential to have simple, intuitive means of retrieving and understanding information. This paper develops a new AI-powered system that enables interactive learning by three different features: “Chat with PDF”, “Chat with Repository”, and “Chat with URL”. Based on state-of-the-art language models and retrieval-augmented generation techniques, it allows for the extraction, querying, and understanding of all the information that comes from the most varied sources with even less effort. Advanced vector stores, conversational retrieval chains and document embedding strategies form the architecture to ensure high-accuracy relevant responses. The paper emphasises system design, implementation challenges as well as its practical use in education, software development, and research. The results of evaluating this system show a substantial increase in user engagement as well as knowledge acquisition. Our work is meant to fill the gap between statically consumed content and the dynamically intelligent AI-driven interface-a new generation of very useful study aids.