ArcadeDB's HNSW indes is pretty powerful, but the lack of SQL support makes it hard to use via API.

We need some new function/method to expose the following methods from the index:

• findNeighborsFromVector(TVector vector, int k): find max K neighbors from a vector of embeddings
• findNeighborsFromId(TID id, int k): find max K neighbors starting from an id (indexed with the underlying LSMTree)
• findNeighborsFromVertex(Vertex start, int k): find max K neighbors starting from a vertex

The easiest way is to create 3 new SQL functions to be used from SQL. Example:

select findNeighborsFromVector( "Word[name,vector]", [1,2,3,4,5,6], 10 )

The Java API returns a List<Pair<Identifiable, ? extends Number>>, with the vertex rid as the first argument and a number (float, double or whatever you pick at index creation) with the proximity. Ordered by proximity, the closest first.

With SQL it must be wrapped in a Result with "vertex" and "proximity" properties:

+------------------+---------------------+
| VERTEX           |           PROXIMITY |
+------------------+---------------------+
| #13:4            |                0.12 |
| #19:10           |                0.19 |
+------------------+---------------------+

So you can also cross the graph starting with embeddings:

select expand( vertex ) from (
  select findNeighborsFromVector( "Word[name,vector]", [1,2,3,4,5,6], 10 )
) where proximity < 0.5

To return all the neighbors with proximity less than 0.5 from the vector.