[fergal_reid]

LLMs like GPT-4 'natively' speak certain syntaxes very well - e.g. Python, JSON. I'd suggest you want to take advantage of that, if at all possible, rather than embark on training or fine tuning your own LLM.

If you have a particular data structure you want to have the LLM generate or manipulate, which there aren't large quantities of in the training set, you might want to consider writing a translator that will translate it into a format the LLM natively 'speaks', using the LLM on that, and then translating back into your DSL.

Going this direction and also adding examples in some sort of vector store, as others have suggested, could be a good direction.