Research on Teaching Reform of Multi-Agent Applications Based on the Digital-Intelligent Pharmacopoeia Large Language Model

Abstract

With the deepening advancement of the national strategies "Healthy China" and "Revitalization and Development of Traditional Chinese Medicine (TCM)", the TCM industry is ushering in a historic opportunity for digitalization and intellectualization. However, the current TCM education system suffers from a severe shortage of teaching resources integrating data science and artificial intelligence with medicine, making it difficult to meet the industry's urgent demand for interdisciplinary talents. This project, centered on the "Digital-Intelligent Pharmacopoeia" platform, constructs a teaching experimental platform for TCM data governance based on a multi-agent large language model. It aims to promote systematic reform in the teaching content, methods, and practical mechanisms of higher education in TCM through a deeply integrated "AI + Medicine" teaching model.

The platform's core technical feature is its multi-agent collaborative architecture. Through the synergistic workflow of agents such as Classifier, Extractor, Validator, and Matcher, it simulates the real-world data governance processes of the industry, providing students with comprehensive practical scenarios covering the entire workflow from data classification, information extraction, compliance validation, to data fusion. The project represents not only an innovation in technical tools but also a reform in educational philosophy. It is dedicated to cultivating interdisciplinary talents who possess both professional knowledge of TCM and mastery of AI technology, thereby providing intellectual support and talent assurance for the modernization of TCM.