The GitHub Actions job "Tests (AMD)" on airflow.git/common-ai-cost-limit has 
failed.
Run started by GitHub user Lee-W (triggered by Lee-W).

Head commit for run:
86101b27053fe34ef7c3eb1186d8856f9449f3b6 / Wei Lee <[email protected]>
Support per-run cost limits in common.ai LLM and Agent operators

Dag authors had no way to cap what a single LLM or Agent task is allowed to
spend, and no way to see what one cost after the fact. pydantic-ai made both
first-class in 2.23.0 via RunUsage.cost and UsageLimits.cost_limit, but this
provider's floor was >=2.0.0, so neither existed for users here.

Raising the floor is what unlocks the enforcement path — the operators already
forward usage_limits untouched to run_sync, so cost_limit takes effect with no
interception logic of our own. The max_cost parameter exists for the one thing
usage_limits structurally cannot do: a UsageLimits object cannot be templated,
so a budget that follows the environment had to be expressible as a scalar.

The docs deliberately spell out where the cap stops being a guarantee, since
each of these reads as a broken promise to anyone who assumed otherwise: the
request that crosses the limit still completes and still bills, self-hosted or
unpriced models report no cost at all and the limit silently does nothing, and
a durable replay re-counts the cached spend against a fresh attempt's budget.

Report URL: https://github.com/apache/airflow/actions/runs/31571143208

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