Train Rasa NLU without having to restart the server

Hi, I’m using only RASA nlu and not the core part. Everytime I have to make a change in nlu.md file, I need to retrain and run the model which leads to downtime of server. Is it possible to train and create the model in the background and then execute the new model without having to restart the server?

I’m testing out a few things with our API to see what you might could accomplish there, HTTP API. Is there a need to use the Rasa Core piece? If so you could check out Rasa X and maybe install it and test it.

It would allow you to learn from conversations if you used the core piece and be able to update your training via the UI and then make the new model active.

Just something else to think about, I’ll let you know more about the API calls I just need to test a few things on it.

@Farheen-J I believe HTTP API should work for what you want. You would just supply it the new model file location on the server or from a remote location and update it that way.

@btotharye, I’m using only RASA NLU part and not the CORE one. also:

  1. I tried training the model using HTTP API using /model/train. In JSON body, the attributes like config, nlu, etc has to be passed in the form of string. They could not be loaded from a file. Also, the model is generated in .tar.gz format which doesn’t seem compatible with below replace API call
  2. I used /model/ to replace the current model, I got the response message as “An unexpected error occured, Error: File is not a Zip file”