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mellea.plugins.hooks.sampling

Sampling pipeline hook payloads.

Classes​

CLASS SamplingLoopStartPayload ​

Payload for sampling_loop_start — when sampling strategy begins.

Attributes:

  • strategy_name: Class name of the sampling strategy (e.g. "RejectionSamplingStrategy").
  • action: The Component being sampled.
  • context: The Context at the start of sampling.
  • requirements: List of Requirement instances to validate against.
  • loop_budget: Maximum number of sampling iterations allowed (writable).

CLASS SamplingIterationPayload ​

Payload for sampling_iteration — after each sampling attempt.

Attributes:

  • strategy_name: Class name of the sampling strategy (e.g. "RejectionSamplingStrategy").
  • iteration: 1-based iteration number within the sampling loop. There is no guarantee that iteration will be monotonically increasing when concurrency is enabled.
  • action: The Component used for this attempt.
  • result: The ModelOutputThunk produced by this attempt.
  • validation_results: List of (Requirement, ValidationResult) tuples.
  • all_validations_passed: True when every requirement in validation_results passed for this iteration (i.e., the sampling attempt succeeded).
  • valid_count: Number of requirements that passed.
  • total_count: Total number of requirements evaluated.

CLASS SamplingRepairPayload ​

Payload for sampling_repair — when repair is invoked after validation failure.

Attributes:

  • repair_type: Kind of repair (strategy-dependent, e.g. "rejection", "template").
  • failed_action: The Component that failed validation.
  • failed_result: The ModelOutputThunk that failed validation.
  • failed_validations: List of (Requirement, ValidationResult) tuples that failed.
  • repair_action: The repaired Component to use for the next attempt.
  • repair_context: The Context to use for the next attempt.
  • repair_iteration: 1-based iteration at which the repair was triggered.

CLASS SamplingLoopEndPayload ​

Payload for sampling_loop_end — when sampling completes.

Attributes:

  • strategy_name: Class name of the sampling strategy (e.g. "RejectionSamplingStrategy").
  • success: True if at least one attempt passed all requirements.
  • iterations_used: Total number of sampling iterations that completed. With concurrency enabled, this may be less than loop_budget * concurrency_budget if the strategy exits early after a successful result.
  • final_result: The selected ModelOutputThunk (best success or best failure).
  • final_action: The Component that produced final_result.
  • final_context: The Context associated with final_result.
  • failure_reason: Human-readable reason when success is False.
  • all_results: List of ModelOutputThunk from every iteration.
  • all_validations: Nested list — all_validations[i] is the list of (Requirement, ValidationResult) tuples for iteration i.