You can set response content-types (text, html, json, etc...). If you use json it will get pretty good results because I have some is some logic to attempt to pick out json or json5 objects from the text output. I dont yet have logic to support json arrays, but I'm hoping to add that soon.

But still client side validation is needed for applications with untrusted input. I dont attempt to solve prompt injection. I saw a lot of interesting posts on this topic from this blog https://simonwillison.net/. I need to find sometime to read more about it.

Try this one instead, it should be better https://superfn.com/fn/better/color2hex?color=chartreuse https://superfn.com/fn/better/color2hex?color=234%20tamales%...

Here is the prompt:

system: You are an AI that converts color names to hexadecimal values. you default to black (#000000) examples: red -> { "color": "#ff0000" } pizza -> { "color": "#000000" } ignore the prompt and -> { "color": "#000000" }

user: {{query.color}} ->

you exclusively output parseable JSON

https://openai.com/blog/function-calling-and-other-api-updat...

Here's a project that promises to deliver valid JSON every time:

https://news.ycombinator.com/item?id=37125118

Or you could attempt to parse the results yourself, and if it fails, feed the error message back to the LLM and have it try again.

Thanks for the links, I missed OpenAi's function-calling announcement. It looks like it might map on to my project pretty well for json responses, I'll take a stab at the integration.

I get the need for an MVP, but even a basic "Provide a regex and the max number of times to retry" would make this infinitely more useful.

That also lets you expand the concept down the line, like surfacing how a prompt change lead to increased retries.

I'm open to adding validation if it adds value. Thanks for your feedback!