Add feature to summarize a large schema

[mrseanryan]

take a list of tables, with their properties

output high level summary:

• classify tables - but grouping via associations could be more important.

• table summary

• class description

• higher level class of classes (top level category, then table category)

use LLM or just an embedding like sbert? (word2vec) then cluster - or dillibert no case but need name the cluster

• use llm for that. or better have categories and convert to embedding. pick the closest one:

dot prod of 2 normalised vectors = cos Angle cosine distance = 1 - v.w smaller then closer

• user can add categories. different views (sets of categories).

• stem entity names by their casing