I have my RASA server interacting with an external API, which issues retraining and reloading commands for new models.
I keep my NLU data on a db in json format for the ease of modifying it. Unfortunately, it looks like the endpoint /model/train of the HTTP API of RASA doesn’t take NLU data as json and requires markdown. Am I wrong?
In any case, my temporary solution is to use load_data from from rasa.nlu.training_data in order to convert the json to markdown before sending it to the server [I have tried other markdown converter libs, they don’t seem to work with RASA].
What I don’t like about this is that I have to have the entirety of RASA installed on that external server and 100s of MBs is way too much overhead for using just a simple function.
I am wondering if there is a way I could separate this functionality and install only that part. I looked into the source code, everything seems deeply interconnected. Is there some way to go around this? What is the least amount of megabytes I have to have in order to use load_data?