Hi,
I am looking to develop a question answering system to work on structured data. I have the option of either using the Embeddings endpoint to store the data as vectors and then use embeddings similar to embeddings of the query to select the top-k results to be returned and use a verification method to get the correct answer, or use fine-tuning to train the model to the data and then make use of the fine-tuned model.
Considering that the data could change with time, can someone please guide me how to decide which alternative would be best to use?
