Hah! This was actually one of the main algorithmic challenges of adapting DiskANN to PostgreSQL. Yes, I think it's common for these algorithms to assume you know how many results to return ahead of time. But in PostgreSQL that's not how things work -- because of things like post-index-retrieval-filtering the right interface for Postgres is one that just keeps on returning more and more results until all possible matches are exhausted. We solved this by creating a "streaming" version of the search algorithm that keep state like which nodes in the graph have been visited, which have been returned etc.

That's all to say -- Yes we've solved this, there are no arbitrary limits on the number of results returned.

Hi, we've solved the problem you mentioned! Please take a look on our open source postgres vector extension https://github.com/tensorchord/pgvecto.rs.

Our index building process is significantly faster than pgvector on hnsw because we can utilize all the cores, whereas pgvector can only use one core. And for the filter support, we do support pre-filtering, which will guarantee enough results no matter the condition is.