  With the ever-increasing utilization of natural language processing (NLP), we
started to witness over the past few years a significant transformation in our
interaction with legal texts. This technology has advanced the analysis and
enhanced the understanding of complex legal terminology and contexts. The
development of recent large language models (LLMs), particularly ChatGPT, has
also introduced a revolutionary contribution to the way that legal texts can be
processed and comprehended. In this paper, we present our work on a
cooperative-legal question-answering LLM-based chatbot, where we developed a
set of legal questions about Palestinian cooperatives, associated with their
regulations and compared the auto-generated answers by the chatbot to their
correspondences that are designed by a legal expert. To evaluate the proposed
chatbot, we have used 50 queries generated by the legal expert and compared the
answers produced by the chart to their relevance judgments. Finding
demonstrated that an overall accuracy rate of 82% has been achieved when
answering the queries, while exhibiting an F1 score equivalent to 79%.
