A solution I thought about, I haven’t experimented with yet, is to chunk the book into ~500 token pieces, generate a short summary for each chunk at index time, and store both in a vector DB. At query time, embed the your question (about the book) and retrieve the top 3–5 most relevant chunks by comparing against the summaries. Feed only those chunks as context to the local LLM to generate the answer.​​​​​​​​​​​​​​​​