Research Companion App

This paper introduces the Research Companion App, designed to assist students in comprehending research papers through interactive features. Utilising Retrieval Augmented Generation (RAG) and prompt engineering, the app enhances response accuracy, scalability, and flexibility. The app, built with Streamlit and Hugging Face, and leveraging Microsoft Azure OpenAI models, includes functionalities such as summarisation, visual aids generation, quizzes, and a chatbot. Evaluation of the chatbot's performance across different temperature settings reveals that higher temperatures generally yield more consistent and reliable outputs. However, the quality of responses is contingent on the retrieval process. Future improvements aim to refine summary generation and explore better QA evaluators.