If you are interrested we can do that together in a video session. I could imagine a few more ways to solve that.
You could add some context to your prompts by getting the data from another system first e.g.
- a wordbubble/knowledge tree in a RDBMS
- a graph DB that stores relations between documents which is filled over time by crawlers
- a vector db
- maybe even live crawling and summarizing
- a combination of above
You can even build a database extension e.g. for postgresql that enables your database to understand SQL like this:
SELECT content from querypool WHERE prompt=‘…’
That would be like a stored procedure with access to different architectures (even a pool of local PDFs)…
… and of course utilizing other/own models. Although there is not much even slightly as good as the openai world 