The invention discloses a self-adaptive retrieval enhancement generation method and
system based on multi-dimensional semantic routing and a medium. The method comprises the following steps: receiving a user query, identifying
data dependency and cognitive complexity of the query through a semantic
routing model, and carrying out bottom classification in combination with a regular matching mechanism; a dynamic routing instruction is generated according to an identification result, and corresponding
processing capacity is activated in a self-adaptive mode from an intuitive generation module, a retrieval enhancement module, an
algorithm thinking reasoning module and the like; wherein the retrieval enhancement module has a result correlation self-checking function and an internet search bottom-taking function, and the
algorithm thinking reasoning (AoT) module adopts a context example to guide a
large model to simulate an
algorithm search and a
backtracking path in single generation; and finally, carrying out validity detection and closed-loop repair on the answers through the quality evaluation model. The problems that a traditional RAG
system is rigid in process, complex, insufficient in reasoning capacity and lack of a fault-tolerant mechanism are solved, and the
resource efficiency, the logic depth and the answer robustness of the question-answering
system are remarkably improved.