Don't use OpenAI's outdated tools. Also, don't rely on prompt engineering to force the output to conform. Instead, use a local LLM and something like jsonformer or parserllm which can provably output well-formed/parseable text.
I'll be informal to boost your intuition. You know how a parser can reject invalid inputs? Parsers can be generated from grammars, so we can think of the grammars themselves as rejecting invalid inputs too. When we use a grammar for generation, every generated output will be a valid input when parsed, because the grammar can't build any invalid sentences (by definition!)
For example, suppose we want to generate a JSON object. The grammar for JSON objects starts with an opening curly brace "{". This means that every parser which accepts JSON objects (and rejects everything else) must start by accepting "{". So, our generator must start by emitting a "{" as well. Since our language-modeling generators work over probability distributions, this can be accomplished by setting the probability of every token which doesn't start with "{" to zero.
While there are not actually any trailing commas in the dictionaries present and you are correct to say the ones present are part of a list, you can also have trailing commas in Python dictionaries. OP might have researched “Python trailing commas” and learned that part.
Trailing commas are fantastic to reduce changed lines in git diffs. Makes life much better. Same thing with leading commas in SQL queries.
Downside is that it includes your indentation whitespace, though I doubt chatgpt would care about that, as I'd imagine it gets discarded when it's tokenized, but it's still good to keep in mind when using " " ".