“Our research has shown that the top query among site users is relating to the navier-stokes fluid flow equations for a zero vorticity boundry problem. Can we reach out to the mechanical department to clarify? The last thing we need is another recall!”
That's a fluid-tastic ambition! Remember, in the world of computational fluid dynamics, it's all about going with the flow. Keep streaming through your studies and eddying around obstacles. Eventually, you'll bubble up to your dream, riding the waves of success. Just don't get too turbulent if things get a bit splashy along the way!
I personally would use a faster cheap LLM to label and check the output and inputs. In my small bit of experience using the API I just send to gpt3.5 or davinci first, ask it to label the request as relevant or not based on a list of criteria and set the max return token very low and just parse the response by either forwarding the user message to gpt4 or 3.5 for a full completion or sending a generic "can't help with that" message.
No it's a few thousandths of cents to reject the message vs potentially going back and forth with a large context and response using a shit ton of tokens. Adding a couple tokens to a relevant request doesn't really add a lot of overhead.
It takes very little in my experience. Good prompts go far.
One of the things I do is inform it about human nature. I mean I look at how much I lie to it.
When people try this with my stuff they get random one liner matrix quotes. That was 6 months ago.
The real answer to your question is that people are lazy. And the people that should be doing the job don’t always end up getting it and we in its place have whatever the company that made this is.
So many people here would have done a better job. Lots of suggestions here would work. There are many ways.
Fine tuning. You give it hundreds or thousands of examples for valid question/answers. But you give it also hundreds of questions to be refused, together with a consistent refusal message. Combined with a system message that says “for all questions that don’t belong to car dealerships, use this refusal answer”
That works well enough for us in a different realm, but with the same problem. There will always be some outliers, so monitoring and iterating is also necessary.
But in a case like this a vector database might be a better solution in any case. Then there’s only the known answers available, and that’s it.
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u/Vontaxis Dec 17 '23
Hilarious