I think OP means to filter the user input through an LLM with “convert this question into a keyword list” and then calculating the embedding of the LLM’s output (instead of calculating the embedding of the user input directly). The “search the embedding” is the normal vector DB part.
"Query expansion"[0] has been an information retrieval technique for a while, but using LLMs to help with query expansion is fairly new and promising, e.g. "Query Expansion by Prompting Large Language Models"[1], and "Query2doc: Query Expansion with Large Language Models"[2].
