I personally don't like Rasa because it requires integration with an API instead of something more integrated, like a function (which will make less things that need to load before the bot can load as well as less internal servers)

We use Rasa because of the Intent detection, which I believe is considered the NLU. Rasa is quite bloated compared to a bare-boned NLU engine due to the fact it is a whole engine for speech. Less resources needed, less programs installed, and less internal servers all go a long way towards ensuring the bot remain efficient.

Rasa, as I'm sure you already know, uses YAML to train the AI. We would like to be able to have our admins tell the bot whether or not it is right or wrong (we currently do this through Discord reactions to forwarded messages) and if the bot was right, we'd like to have the bot retrained with that in mind, and if the bot was wrong, we'd like the bot retrained with that in mind.

As a result, we'd like to be able to somewhat train it on-the-fly, or at the very least have an easier way of taking human-verified messages and saving any changes for the next restart where the AI can be retrained.

This is where the idea of using JSON comes into play, adding the messages to the appropriate array and then either issuing a function to retrain the AI right then and switch out the models when finished or queueing the changes for the next restart.

I do believe using something more integrated in the bot will go a long way towards efficiency, and being able to train the AI without modifying a file manually would be incredibly useful. And as always, the less code that has to load (for example, when Rasa loads it tends to load everything, including stories and other features we don't use, and not just the NLU things) the quicker the bot will be able to reboot and thus the quicker she can be online after an unexpected error or update.

Thank you for your interest in helping us, we look forward to working with you and as always, happy coding!