Using GPT-3 to make regular expressions legible:

Aug 21, 2022 · 10:19 AM UTC

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A second example using a UUID regex:
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Also possible to make regexes from prose descriptions, but be careful! You can never fully trust GPT-3. Generate at low/zero temperature. Make sure output is verbose and easy for you to verify. GPT-3 often emits code that appears right but isn’t quite. Correct it via dialog.
Riley Goodside
 @goodside
10 Jul 2022
Writing code with GPT-3 is often best done incrementally through dialog, guided by human feedback. Here, GPT-3 infers the high-level intent of a regex specified only through test cases, and crafts a legible PCRE2 satisfying all of them:
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Note my example here is, technically, very subtly wrong: It doesn’t match leap seconds. GPT-3 is a poor substitute for real wisdom.
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Another quick demo, incrementally crafting a regex through instructional dialog. This is overkill for this one, obviously, but it illustrates how you can talk to it using examples, corrections, etc. Playground link: beta.openai.com/playground/p…
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These dialogs are often productive in themselves, similar to “rubber duck debugging”. You learn through GPT-3’s misunderstandings how much the task was actually underspecified in your head.
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See an extension of this prompt here too:
Riley Goodside
 @goodside
24 Aug 2022
Using GPT-3 to translate a shell/awk one-liner into both Python 3 and plain English with a single prompt:
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Replying to @goodside @jeremyphoward
There's @atr3gx which does this only using regexp
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Yup! That’s a cool project. I like having a place for examples and dialog though, especially for complicated generations that I can only do piece-by-piece.
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Replying to @goodside @__MLT__
Does it actually manage to somewhat parse/break down the regex… or rather just soft matches it against near-identical ones it found in its training data? 🤔 i.e.: will it do a decent job if you give it something that does not already exist many times in the wild?
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Good question! Here’s something that isn’t in any textbook, and it does a great job, I think. This particular task it’s unusually good at.
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