Last year, I tried to use Rasa for a project that needed to do open-ended chitchat across a few dozen topics but incorporate a bit of conversational memory. It ended up not working so well and I understand that’s not really what Rasa is for. So I recently started working on a different approach using neural conversation models (initially I’m using GPT-2 fine-tuned with a topic-oriented conversation corpus). Some of the responses are magic, but some are garbage because of the lack of any real conversational memory/entities. I’m thinking of ways to start introducing some notions of abstracting training data to start working with slots instead of entity instances, but it seems like someone has to be working on this already.
If only I could jam together a generative model that doesn’t require so much handcrafting with Rasa that can actually do things that make sense. It’s like trying to get the functionality of Google Duplex with Google Meena.
So the question is whether these will always be separate worlds or are there efforts to try to bring the two together somehow - either incorporating a generative chitchat model into Rasa or adding Rasa-type capabilities into generative models. Trying to build on what’s already being worked on if possible.