LLM-Aided Museum Guide: Personalized Tours Based on User Preferences

Iva Vasic, Hans-Georg Fill, Ramona Quattrini, Roberto Pierdicca

Abstract: The quick development of generative artificial intelligence (GenAI) techniques is a promising step toward automated processes in the field of cultural heritage (CH). The recent rise of powerful Large Language Models (LLMs) like ChatGPT has made them a commonly utilized tool for a wide range of tasks across various fields. In this paper, we introduce LLMs as a guide in the three-dimensional (3D) panoramic virtual tour of the Civic Art Gallery of Ascoli to enable visitors to express their interest and show them the requested content. The input to our algorithm is a user request in natural language. The processing tasks are performed with the OpenAI’s Generative Pre-trained Transformer (GPT) 4o model. Requests are handled through the OpenAI’s API. We demonstrate all the functionalities within a developed local web-based application. This novel approach is capable of solving the problem of generic guided tours in the museum and offers a solution for the more automatized and personalized ones.