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Use this tutorial when your metric depends on a sequence of structured input/output pairs rather than a single span or a fully serialized trace.

Current support

This is an advanced pattern in the current SDK. It is best treated as a custom workflow where you prepare the dataset into a stable multi-field representation before training.

Dataset schema

Typical columns:
  • input: one structured view of the conversation or trace history
  • output: the corresponding assistant response or action summary
  • label: the ground-truth class for the metric

Config shape

  • data_generation.metric.input_format: "tuple"
  • data_generation.source_data.dataset.columns.features: ["input", "output"]

Minimal config