If I take advantage of this for allowing my customers to ask questions about our product documentation, how do I limit questions to questions about my product documentation? I don't want to be paying Open OPI for questions unrelated to my product.

One idea would be to use a much cheaper (and faster) classifier to come back with a "yes" or "no" if the question asked is about your product documentation.

Using Ada or Babbage is about 1% of the cost of Davinci (and Curie is 10% the cost of Davinci).

Without any real tuning, this responds quite promptly (and the various tests I've done, correctly):

    curl https://api.openai.com/v1/completions \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer $OPENAI_API_KEY" \
      -d '{
      "model": "text-ada-001",
      "prompt": "Identify if the following question is about the Olympic Games.  Answer with {yes}, {no}, {maybe}.\n\nWhat category is pole vaulting in?",
      "temperature": 0.7,
      "max_tokens": 38,
      "top_p": 1,
      "frequency_penalty": 0,
      "presence_penalty": 0
    }'

> What category is pole vaulting in?

>> Yes

Well, at least you can't say the documentation is out of date.

I was just after something simple in its training set to demonstrate the simple classification that could be used as a check before passing the request on to a more expensive fine tuned model.

Honestly the best comment I've read on here in a long time. Cheers.

It's way easier and cheaper to use embeddings for these sorts of use cases.

It probably is - I just haven't toyed with that part of the system yet.

This is really a good question. Could be interesting also which is the best method to provide to GPT a Product documentato and ask question inherents to that and nothing else.

I'm going to coin the cyber-security finding "Bill exhaustion via open ML prompts".. wonder how long till it's in the Owasp top X