I’ve successfully deployed an app locally but when I run it in the cloud it crashes without error (there is one error in installing dependencies that the protobuf version is not compatible with streamlit/tensorflow but I’ve removed the tf import and the error still happens). From similar topics it seems this might be a memory issue but I’ve stripped the code right back and am still having the same error.
Any pointers or advice on how to reduce/profile memory usage or other ways to figure out the issue would be much appreciated.
I wondered that, but the error is at install time and I removed the tensorflow import which I thought meant it wouldn’t cause an issue at runtime.
As far as I can see this is the version of protobuf needed by streamlit and gets installed by an internal streamlit pip install which overwrites the version I specify in my install script. But I might be misunderstanding the installation workflow…
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