> simple chart specs can be reliable, but generated charts are often of low quality due to reliance on system defaults; - complex chart specs with explicit details can produce good-looking charts, but they are verbose and agents can struggle with reliability
N of only a few of us working on an analytics agent, I don't think we've been finding this to be the case. We've been impressed with just how good LLMs (even smaller open weight models) are at using Python and R for visualization. Often any shortcomings go away if we iterate a bit to about ambiguity. Are there any threads of research that could better support this claim or highlight where issues might be?
we are considering also reliability, interactivity besides expressiveness. Simpler spec with good expressiveness comes handy when you want the agent to be reliably for non-expert users and with small models.
A simpler spec can be used by a simpler agent. So, maybe that's the use-case here... use by smaller/cheaper agents that run in parallel as opposed to large models running one visualization at a time.
Or at least, maybe that's the idea?
IME, Claude and ChatGPT do just fine generating ggplot models, but extensive customization can get a bit hairy.