In this case I think such a system makes even more sense, as it is essentially using the LLM to fetch the correct docs based on a natural language query instead of relying on potentially outdated training data (you’d have to continuously re-train the model; making it forget past training isn’t really a thing, and it still is likely to mangle some output).
From a tinkerers perspective I’m all for fine-tuning a model to see where it leads us, I definitely see the allure!
And yes, very curious about what the community builds around the core teams’ advancements! 
