Vector search places queries and documents in one vector space and ranks candidates by distance or similarity. Approximate nearest-neighbor indexes can reduce work on large collections.
The demo lights the closest candidates to a query point. Distance depends on the embedding model and metric, so task relevance needs separate evaluation.
When to use
Use it to retrieve related material when exact words may differ.