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Getting AI to write good SQL

(cloud.google.com)
476 points richards | 1 comments | | HN request time: 0.256s | source
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mritchie712 ◴[] No.44010031[source]
the short answer: use a semantic layer.

It's the cleanest way to give the right context and the best place to pull a human in the loop.

A human can validate and create all important metrics (e.g. what does "monthly active users" really mean) then an LLM can use that metric definition whenever asked for MAU.

With a semantic layer, you get the added benefit of writing queries in JSON instead of raw SQL. LLM's are much more consistent at writing a small JSON vs. hundreds of lines of SQL.

We[0] use cube[1] for this. It's the best open source semantic layer, but there's a couple closed source options too.

My last company wrote a post on this in 2021[2]. Looks like the acquirer stopped paying for the blog hosting, but the HN post is still up.

0 - https://www.definite.app/

1 - https://cube.dev/

2 - https://news.ycombinator.com/item?id=25930190

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1. galenmarchetti ◴[] No.44011108[source]
still need someone to build the semantic layer, why not use text2sql or something similar for that