real

AI ops

Purpose

ask, classify, extract, embed/retrieve, tools, and abstain heads.

ask fixture-only
classify fixture-only
extract fixture-only
embed fixture-only
retrieve fixture-only

Example

model code
model train dataset "examples/fixtures/train/dataset.jsonl" base "fixture-base" out "out/train/job-dry-001" backend "http" method "spark_distill_cpu" -> job
model status "job-dry-001" -> status
expect contains job fixture "examples/fixtures/train/want_accepted.txt"
expect contains status fixture "examples/fixtures/train/want_succeeded.txt"

Dry-run vs live

Mode	Behavior
dry-run	Fixtures only. No GPU. No network.
live	Needs keys / trainer URL. Fail-loud on miss.

Exit codes

Exit	Meaning
0	success / expect pass
1	expect fail or language fail
2	usage / unknown method / missing program
4	credential unavailable or CAP miss

What it does not do

Does not invent Bifrost task aliases from prompt text.