RAG architecture (Tabular answer question)

Hi . I am trying to make a chatbot for our tabular database . In this case I want to make a chatbot that knows the database data and answer base on them to the costumer . I think RAG is good for this case . is there any better architecture?
I have another problem with this architecture ; My database is updating every hour and the embedding must be update every hour is there any way to reduce the cost ?
And more one question ; how can i embed database ? I export the DB to CSV and embed this CSV . Is there any better solution ?

It really depends on what the contents of the database is, if it’s photograph bitimages, then it’s not going to work very well, assuming your database contains text in human readable form, and not just a large collection of numbers then you could embed it, but updating every hour is going to become costly regardless of if you use a paid API or you run a local embedding model, compute costs money, so that needs to be factored in, not knowing the nature of the data, it’s hard to advise further.

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Thanks for your response .
My data is something like stock market statistics for each month .
For example the user may ask something like “What was the net profit of X at 2022 ?”
and in my database there is that , but my RAG application should filter on Vectorized DB like chroma to find for example :
Company_name == X
Year == 2022
Query == net_profit

Do you have any idea to accomplish this :slight_smile: ??