Receiving files, copying them within a file system, and transmitting the contents? Clearly not looking.
Computing a hash for each file? Doesn’t seem like looking either.
Parsing the contents, or tokenizing them for a ML model? That’s looking IMO.
I think the defining factor is the size and nature of the derived state update on the server. Copying and transmitting retains only metadata about the file. Computing a hash produces only a handful of bytes of state about the file, and there’s nothing that can be inferred about the file’s contents from the hash. But if you start storing something like word frequencies, that’s not neutral anymore, it’s a “look” into the contents.