I’ve started developing a chatbot but so far I’m only training/testing it locally on my machine. Since in the end it should be running on a server in order for users to interact with it I was wondering about the following question: Is there a built-in feature in rasa stack that allows to collect new input from users in order to increase the size of the training datasets for both the NLU and core unit in the Rasa stack over time? (Of course there would be a lot of manual (“hand-labelling”) work once the data is collected.)
I think it should be realizable with a custom action: e.g. whenever the fallback policy is needed some custom code could store all data of interest. However, since I am quite new to chatBots, APIs and databases I’m sure I don’t see the “correct” way of doing this.
Could someone please point me to the right direction? Specifically, how would I trigger the task of collecting a given conversation and how/where would I then store it?
Is all this offered in the data API of Rasa platform?
Thank you so much!