an effective "vectorless RAG" is to have an LLM write search queries against the documents. e.g. if you store your documents in postgres, allow the LLM to const

an effective "vectorless RAG" is to have an LLM write search queries against the documents. e.g. if you store your documents in postgres, allow the LLM to construct a regex string that will find relevant matches. If you were searching for “Martin Luther King Jr.”, it might write something like: SELECT id, body FROM docs WHERE body ~* E'(?x) -- x = allow whitespace/comments (?:\\m(?:dr|rev(?:erend)?)\\.?\\M[\\s.]+)? -- optional title: Dr., Rev., Reverend ( -- name forms (?:\\mmartin\\M[\\s.]+(?:\\mluther\\M[\\s.]+)?\\mking\\M) -- "Martin (Luther)? King" | (?:\\mm\\.?\\M[\\s.]+(?:\\ml\\.?\\M[\\s.]+)?\\mking\\M) -- "M. (L.)? King" / "M L King" | (?:\\mmlk\\M) -- "MLK" ) (?:[\\s.,-]*\\m(?:jr|junior)\\M\\.?)* -- optional suffix(es): Jr, Jr., Junior ';