Comment by pampa

The name of the solution is RAG - retreival augumented generation. It is pretty easy to whip up your own over a corpus of material. I built one for myself within a week over a corpus of my favorite cook and homebrewing books. All you need is source material, postgress (pgvect) and some compute (llama.cpp with a decent chat model for chunking and labeling, an embedding and a rerank model. or some $ to use those via a router). When the corpus is indexed, you use your favorite coding agent and a system prompt that forces the model to answer only from search results.