Is there a way to do stable random search?

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1

My use case is that I wish to randomly present a feed to each refresh by user for items in a certain collection, for example photos.

Yet when user scroll down, this random generated feed should be stable and have no duplicates or few duplicates.

Each refresh could generate a random seed, then this seed can be used for this search.

I am not sure if it is an appropriate application of vector search. Any insight would be much appreciated.

Thanks.

2

Hi @homer_thompson , there are a couple of ways. If you know the _id list ahead of time you could randomly sample a document and then use that to search with. Alternatively, we have a context_vector that can be used for a random search. In this case, you would create a random vector and then search directly with that.

Here is an example;

res = client.search({query:0.0}, context={"tensor":[{"vector": context_vector, "weight": 1.0}]})

where context_vector is a random vector.