  The demand for psychological counselling has grown significantly in recent
years, particularly with the global outbreak of COVID-19, which has heightened
the need for timely and professional mental health support. Online
psychological counselling has emerged as the predominant mode of providing
services in response to this demand. In this study, we propose the Psy-LLM
framework, an AI-based assistive tool leveraging Large Language Models (LLMs)
for question-answering in psychological consultation settings to ease the
demand for mental health professions. Our framework combines pre-trained LLMs
with real-world professional Q\&A from psychologists and extensively crawled
psychological articles. The Psy-LLM framework serves as a front-end tool for
healthcare professionals, allowing them to provide immediate responses and
mindfulness activities to alleviate patient stress. Additionally, it functions
as a screening tool to identify urgent cases requiring further assistance. We
evaluated the framework using intrinsic metrics, such as perplexity, and
extrinsic evaluation metrics, with human participant assessments of response
helpfulness, fluency, relevance, and logic. The results demonstrate the
effectiveness of the Psy-LLM framework in generating coherent and relevant
answers to psychological questions. This article discusses the potential and
limitations of using large language models to enhance mental health support
through AI technologies.
