GenAI Engineer Evaluation and monitoring HARD
PRODUCTION SCENARIO
A Generative AI Engineer wrote a class-based MLflow Scorer subclass that checks whether each response contains a ticket number. It runs correctly in mlflow.genai.evaluate, but registering it for production monitoring of live traces is rejected.

What should the engineer change?

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Answer: Rewrite the check as a function decorated with @scorer, then register it

Production monitoring accepts only @scorer decorator-based scorers, so the same deterministic logic must be expressed as a decorated function, registered with the experiment, and started with a sampling configuration. An LLM judge adds cost for a deterministic format check, and sampling or storage changes do not affect registration.
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