Operating a Retrieval-Augmented Classifier

Consider a design: a query gets embedded, retrieval pulls the nearest labeled examples from a vector store, and an LLM assigns a label from a fixed set. Mechanically this is kNN classification with an LLM head: the store is the training set, retrieval finds the neighbors, and the LLM replaces