to my understanding, fine tuning is slow and would be quite bad to update. embeddings seems to be the way to go. i don't understand it well enough, but it seems with the langchain framework you can create an embedding of your own data and submit it to the GPT API and i believe emeddings should be a similar principle in llama. at least i did it with diffusers in stablediffusion.