How does someone take structured data from a database and turn it into unstructured data for an LLM? I know RAG is a thing but they talk in terms of documents not tables and fields.
Could the LLM derive that same California sales answer from just knowing the dataset, but not by writing sql?
I’m not sure if this is the same as pg queues but I just started using pg_notify with channels, and it’s so good.
Row update occurs as normal express api, but at the end I call pg_notify on some channel name. I pickup the message in a new thread via polling, and perform aggregate queries to a agg table. It’s like materialized views, but with no wasteful refreshes. Then I push the updates aggs back to the frontend via websockets.
What’s the right way to manage npm installs and deploy it to an AWS ec2 instance from github? Kubernetes? GitOps? EKS? I roll my own solution now with cron and bash because everything seems so bloated.