Rasa shell - specify NLU and Core separately

I’m getting around to migrating to 1.x now finally. One thing I seem to be missing now is the ability to run a bot on the console and specify separately the NLU and Core models. This is quite inconvenient - consider the case where I have a lot of NLU training data and a complex NLU model that takes on the order of half an hour to train, and then I’m developing my Core stories. This makes for very slow iteration if I have to train a “combined NLU and Core” model every time I make a change to the stories, and want to check the outcome.

Am I missing something? Is it possible to use the “rasa shell” command and specify separately core and NLU models?

OK, by digging in the code a bit I’ve found out that the “rasa train” command will only retrain the NLU model if the NLU “fingerprint” (data+config) has changed, and same for core. Would have found that out if I had actually tried the command before complaining!

Hi @einarbmag. No worries :slight_smile: Happy to see you found a solution :slight_smile:

It would still be good to have the ability to specify the NLU and Core models separately when launching the rasa service. The reason being, I would like to train the NLU and Core models in parallel. With our models getting larger, and the scope of our bot expanding, training our bot is having a significant impact on developer productivity. Being able to train the models in parallel and selecting Core and NLU models when starting the service would save a lot of time.