Normalised cosine similarity between a stored vector attribute and a query embedding, matching Neo4j's vector.similarity.cosine/2.

Returns a float in [0.0, 1.0] — 1.0 identical direction, 0.5 orthogonal, 0.0 opposite — i.e. (1 + raw_cosine) / 2. Higher is closer. Typically used in sort to rank results by relevance:

Item
|> Ash.Query.sort({calc(vector_similarity(embedding, ^q), type: :float), :desc})
|> Ash.read!()

Requires Cypher 25 (Neo4j ≥ 2025.06). The data layer pushes this down to vector.similarity.cosine(s.embedding, $q). evaluate/1 mirrors that exact normalisation in Elixir so the data layer's in-memory correctness re-filter agrees with the pushdown (and so filters/sorts also work without pushdown).