Hi everyone. I can’t find complete documentation describing the objects and functions of the libraries rasa, rasa.core and rasa.nlu (the latter is most interested) for jupyter notebooks. The site has a dedicated page, but there is very little information (rasa.com/docs/rasa/1.1.6/api/jupyter-notebooks). I would like to know about all the possibilities: loading the finished model, additional training of the model and etc. Please tell me if there is such a finished publication.
Unfortunately not, you’d have to dive into the code. Maybe this page Agent could also help you. What do you want to do?
Thanck you for your answer. If I understand correctly, the Agent class builds interaction with the full core+nlu. I am interested specifically in NLU for recognition of input text information. Now I do:
import rasa.nlu
config = 'config.yml'
training_files = 'data/nlu_ru.md'
output = 'models/'
model = rasa.nlu.train(config, training_files, output)
model[1].parse('simple text with intents')
I want to study all available methods of the received object for understanding of the further opportunities. The immediate priority is to learn how to use an already trained model in jupiter.
