Integrating LLMs and Chatbots Technologies - A Case Study on Brazilian Transit Law - Rocho, Rafael Selau M.; Perez, Anderson Luiz Fernandes; Farias, Giovani P.; Panisson, Alison R. (Anais do Encontro Nacional de Inteligência Artificial e Computacional (ENIAC); 2024: Anais do XXI Encontro Nacional de Inteligência Artificial e Computacional, 2024)
This paper proposes a hybrid integration of technologies for the development of chatbots. The proposed integration incorporates a framework for developing rule-based chatbots and Large Language Models (LLMs). As a case study of the proposed integration, an application was developed focused on Brazilian traffic legislation, specifically Law No. 9.503 of Sept. 23, 1997, Chapter XV - Infractions. The study demonstrates the technical feasibility of the proposed integration and addresses related challenges. It also identifies future research opportunities, such as adapting the chatbot to different laws and enhancing accessibility. In general, the study shows the potential of combining chatbot development frameworks with LLM to create sophisticated personalized chatbots.