emem_find_similar

io.github.Vortx-AI/emem · Verify this server

k-NN over the corpus by cell embedding or inline vector. Returns `neighbours` ordered nearest-first, each with `cell64`, `score` and the `band` scanned, plus a signed receipt over the vectors read. Scoring is `mode`: cosine is exact fp32; hamming is a sign-bit popcount that scans far more cells for the same budget; hamming_then_rerank does both. `k` is 1..1000, default 10. It ranks what the corpus already holds and materialises nothing, so an empty result means nobody has attested a vector nearby, not that nowhere resembles the key. When to use: Call when the user asks 'find places like X', 'where else looks like this', or hands an embedding to find neighbours. `key` is either a cell64 or `inline:[x,y,...]`. Default band is `geotessera` (128-D Tessera foundation embedding); pass `band: "geotessera.multi_year"` for the 1152-D 9-vintage (2017–2025) fusion. Example arguments: {"key":"damO.zb000.xUti.zde78","k":10}