OpenAI-to-SQLite
I'm trying to wrap my head around embeddings and am not sure I understand how "realtime" embeddings will be in a real world application.For example, if you use embeddings, do you need to know "a priori" what you want to search for? In other words, if you don't know your search queries up front, you have to generate the embeddings, store them inside the database, and then use them. The first step requires an API call to a commercial company (OpenAI here), running against a private model, via a service (which could have downtime, etc). (I imagine there are other embedding technologies but then I would need to manage the hardware costs of training and all the things that come with running ML models on my own.)Compare that to a regular LIKE search inside my database: I can do that with just a term that a user provides without preparing my database beforehand; the database has native support for finding that term in whatever column I choose. Embedding seem much more powerful in that you can search for something in a much fuzzier way using the cosine distance of the embedding vector, but requires me to generate and store those embeddings first.Am I wrong about my assumptions here?