I have a domain specific JSON object for which I want to store in a vector db. I would be using embedding models like sentence=transformer or openai's text-embedding-002.
Questions are: a) Can these models efficiently compute proper embeddings for these json objects? b) Even if they can compute embeddings how efficiently can an LLM reason through them later? LLMs can reason through text but would they from JSONs?
The domain specific data is not so much esoteric - mostly the keys and values are English.