Configure MLflow for Experiment Tracking and Model Versioning

evaluationChallenge

Prompt Content

Set up MLflow to track your DSPy experiments. Log the performance metrics (e.g., relevance, style scores) of different pipeline iterations, prompt variations, and Claude Opus 4.1 configurations. Use MLflow's Model Registry to version your best-performing DSPy pipelines and models, allowing for easy rollback or deployment of specific versions.

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