Ah, maybe we should disambiguate a little.
If you mean Assistants API retrieval - who knows 
(I don’t). However, it might still be hackable into a prototype, but I’m not sure how reliable you can get it.
In general, when we talk about retrieval in the LLM context, we mean embedding vector search, but it can be anything. FAQ is one of the trivial usecases for vector search, but it can be used for so much more. It’s essentially meaning encoded as a coordinate, a coordinate you can compute a distance with.
My guess is that you might want your tool to figure out what the user means, find relevant information, inject it into the prompt, and then allow the LLM to generate a response. Retrieval Augmented Generation.
What I meant by “user input” is the query that GPT-4 will have to answer. I doubt you’d want users to manually enter JSON code (unless it’s a copy-paste situation, or if your user is actually a machine 
).
But if indeed your input is a json object - what would be the retrieval criteria? a matching function signature? 
I’m wondering if you may not even need a language model at all, but I might be misunderstanding - you suggested that the code might need to be rewritten…
Sorry if I’m slow to understand your problem or if I’m explaining stuff you already know 