Conversational AI agents often require extensive datasets for training that
are not publicly released, are limited to social chit-chat or handling a
specific domain, and may not be easily extended to accommodate the latest
advances in AI technologies. This paper introduces Jill Watson, a
conversational Virtual Teaching Assistant (VTA) leveraging the capabilities of
ChatGPT. Jill Watson based on ChatGPT requires no prior training and uses a
modular design to allow the integration of new APIs using a skill-based
architecture inspired by XiaoIce. Jill Watson is also well-suited for
intelligent textbooks as it can process and converse using multiple large
documents. We exclusively utilize publicly available resources for
reproducibility and extensibility. Comparative analysis shows that our system
outperforms the legacy knowledge-based Jill Watson as well as the OpenAI
Assistants service. We employ many safety measures that reduce instances of
hallucinations and toxicity. The paper also includes real-world examples from a
classroom setting that demonstrate different features of Jill Watson and its
effectiveness