The invention relates to a multi-agent-based personalized opera action teaching assistance method and
system. The method comprises the steps of inputting a student portrait into a planning agent to generate a
personalized learning plan; collecting student follow-up training videos in real time, extracting to obtain a key
point sequence, inputting the key
point sequence into the lightweight action matching model, calculating the similarity between student follow-up training actions and standard actions in real time, and outputting an action similarity
score; inputting key
point data obtained after the follow-up training is finished into an execution agent to obtain opera action characteristics, performing deviation judgment and reason analysis through a large
language model, generating correction suggestions, and realizing teaching assistance; and after a learning cycle is completed, inputting deviation judgment and reason analysis results into the reflection agent, carrying out statistics on a deviation trend and a skill improvement amplitude, outputting a portrait updating suggestion, updating the student portrait through an index
moving average algorithm, and triggering a new round of learning planning. Compared with the prior art, the intelligent level and effectiveness of Chinese opera action teaching assistance are remarkably improved.