I did the same for the FDA drug label database and 100% believe that this the future for search. Semantic search layer for context then the large language layer for human answers.
Tip - you don’t actually need GPT-3 level embedding for a decent semantic search. Sentence transformers paired with one of their models is good enough.
Tip - you don’t actually need GPT-3 level embedding for a decent semantic search. Sentence transformers paired with one of their models is good enough.
I like this: https://huggingface.co/sentence-transformers/multi-qa-MiniLM... - since it’s very light.
Also, perhaps I am an idiot but I just used Postgres array field to store my embeddings array to keep things simple and free.