Is selection really the issue?
You'd still need to figure out what payload to give to the tool based on your context.
But I guess depending on your business case it might be worth it. It's not something I'd do from the beginning, though.
You'd still need to figure out what payload to give to the tool based on your context.
But I guess depending on your business case it might be worth it. It's not something I'd do from the beginning, though.
in my mind the biggest difference is llms that are invoked during a workflow, and llms that are invoked when _creating_ code (codegen).
for the former, tools could be well defined till they are small in number, but at some point, the system needs to examine a library of tools, understand how to call it and integrate it, and at its peak, even create new tools to talk to systems not already present in that library (codegen).
this gets worse when you’re chaining 3–4+ tools. context gets noisy, priors stay frozen and there's prompt soup..
my intuition here is: you can learn the tool routing and the llm prompts before and after the call. (can always swap out the rnn for a more expressive encoder model and backprop through the whole thing).
super useful when you’re building complex workflows -- it gives you a way to learn the full pipeline, not just guess and hope.