I have an existing bot running in Kubernetes with RedsTrackerStore, custom actions, components and channel. I understand how Rasa X can help manage conversations and improve models, but I wonder what is the recommended way to use its functionality on top of a running bot, which is also used by real users through the specified channel.
I think there are two options here:
a) Set up Rasa X es described in the docs with a “plain” rasa core container from Dockerhub, then connect it to the tracker store (via --endpoints option). Since there is only SQLTrackerStore supported at the moment, that means I would need to change to this tracker store or use the migration script on a regular basis. Pro: Easy to install (follow the docs) Con: SQLTrackerStore is required; how to push the improved models back to the live bot?
b) Instead of the rasa core container from Dockerhub, use the container that contains the live bot for “rasa-worker” and “rasa-production” services. Pro: Everything integrated into one application, i.e. improved models are used by the live bot, conversations from users should be visible in real-time Con: More complicated manual installation process
Please tell me in case I missed something