Hi all,

None my previous deployments of a keras model have been time critical – waiting a few seconds for the python script to load in all the libraries (like tensorflow, numpy), load up the model, etc etc. was fine.

However, I’m now dealing with a situation where I’m going to need to query my deployed model every 1 second or so – and get a response back as quickly as possible. This means that my usual method of calling a python script via a .bat file, passing in an argument with my csv filename(using Process() in my .net app) and reading the stdout will not suffice.

I need a way to keep a python session alive somehow, with the libraries and model loaded into ram – waiting for some sort of call that points towards my csv file(s) that need to be queried against the model. Note that I must initiate this call [and get a response back into] my C# code, as this is part of a bigger system that relies on other C# libraries.

Anyone have thoughts about how to go about this?