[iamflimflam1]

Very interesting paper!

It's something that I've been wondering about with ChatGPT plugins - they've kind of left it up to the user to enable/disable plugins. But there's definitely going to come a point where plugins conflict and the LLM is going to have to choose the most appropriate plugin to use.

I have been very impressed at how good it is at turning random commands into concrete API calls. You are right though, pretty much any command can be interpreted as an instruction to use a plugin.

[evmaki]

Thanks! That is part of the challenge as this idea scales imo - once you've increased the number of plugins or "levers" available to the model, you start to increase the likelihood that it will pull some of them indiscriminately.

To your point about turning random commands into API calls: if you give it the raw JSON from a Philips Hue bridge and ask it to manipulate it in response to commands, it can even do oddly specific things like triggering Hue-specific lighting effects [0] without any description in the plugin yaml. I'm assuming some part of the corpus contains info about the Hue API.

[0] https://evanking.io/posts/homegpt/