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ask finds notes by meaning, not exact wording — it never generates text; it only ever returns lines you already wrote, verbatim. As your file grows, ask will return more alternate results (max 10).

Each note is embedded (turned into a vector) by a small local model. Your question gets embedded the same way, and llote ranks every note by cosine similarity to it — closest meaning wins, not closest spelling.

Everything runs locally once the model's on disk. llote setup downloads it ahead of time; otherwise the first ask or browse search does it for you, which needs internet access once.

Embeddings are cached. Each note's embedding is stored in an index file in app data, keyed by a hash of its timestamp and text, which cuts down on ask times.