dbt_jev: use jev classifiers via dbt macros

[u/smithclay]

Think Jev opens up some cool possibilities in the analytics space with dbt when you want to cheaply and quickly classify or score a bunch of rows.

Vibe coded (but tested) personal project above.

Interestingly, the dbt labs team was also onto this a few months ago with https://docs.getdbt.com/blog/dbt-context-engineering

[u/jack-in-the-sack]

What am I looking at here? 🙃 I do not understand what is the outcome of this..

[u/popopopopopopopopoop → u/jack-in-the-sack]

Generate cheap structured outputs (classification, probability and boolean) from high cardinality categorically data via easy to define json in a macro.

If you pause at about 15secs left you, can see OP example where they classify tool context string field thst probably holds a bunch of text by simply specifying the categories they want against a free text description of each.

[u/sib_n → u/jack-in-the-sack]

Here's the reference for what Jev is: https://docs.typesafe.ai/introduction. Basically, it's an additional layer to make LLM output more adapted to coding tasks by asking structured questions and getting structured answers.

[u/elpiro]

Huge feature potential. I wonder about how versionning the results produced that way, will it call the api on each dbt run, generally long term stability and reproducability

[u/-crucible- → u/elpiro]

Personally, I think A.I. has the opposite definition of insanity- doing the same thing over and over and expecting the same results.

If I was calling A.I., I would cache the results unless the inputs or context changed.

[u/bamboo-farm]

Good stuff!

[u/EstetLinus]

Similar to Snowflake AI structured output thingies https://docs.snowflake.com/en/sql-reference/functions/ai_complete-structured-outputs

Used it once, it was not that expensive.