It feels crazy to me that we are building "tool search" instead of building real tool with interface, state and available actions.
Think how would you define a Calculator, a Browser, a Car...?
I think, notably, one of the errors has been to name functions calls "tools"...
I'm trying to understand what does it got to do with LLM size?
Imho, right tools allow small models to perform better than undirected tool like bash to do everything.
But I understand that this code is to show people how function calling is just a template for LLM.
Why do humans need a IDE when we could do anything in a shell?
Interface give you the informations you need at a given moment and the actions you can take.
> I wish you luck in refining your differentiation.
Can't agree more with you. It's about distribution (which Snowflake/Databricks/... have) or differentiation.
Still, chatting with your data is already working and useful for lots.
> Do you need an expert to verify if the answer from AI is correct?
If the underling data has a quality issue that is not obvious to a human, the AI will miss it too. Otherwise, the AI will correct it for you.
But I would argue that it's highly probable that your expert would have missed it too...
So, no, it's not a silver bullet yet, and the AI model often lacks enough context that humans have, and the capacity to take a step back.
> How is it time saved refining prompts instead of SQL?
I wouldn't call that "prompting". It's just a chat. I'm at least ~10x faster (for reasonable complex & interesting queries).
Awesome.
Using Vue/Tailwind, I'm definitely interested in this.
Maybe you could try to add examples of integrations with others frameworks?
I'll play with it and give you my 2 cents.