The Logic Behind Checking The Type of The First Element only in the embedding_retrieval Function in the InMemoryDocumentStore

[TaMaN2031A]

Hello,
Whenever you have time, I have a small question regarding the type checking in the embedding_retrieval Function in the InMemoryDocumentStore.
Here is the code snippet:

        if len(query_embedding) == 0 or not isinstance(query_embedding[0], float):
            raise ValueError("query_embedding should be a non-empty list of floats.")

If we are interested in making sure that the query_embedding list is float from start to end, why are we checking the type of the first element only?

Thanks!

[anakin87]

My impression is that this a trade-off: it quickly checks the type without scanning the whole vector.
It's not a perfect but helps catch basic errors early.

I also checked other document stores in https://github.com/deepset-ai/haystack-core-integrations and most of them don't perform this check at all: they just let type errors surface later.

[TaMaN2031A]

Understood, thanks alot!