Package org.mlflow.api.proto

Interface PromptOptimization.PromptOptimizationJobConfigOrBuilder

    • Method Summary

      All Methods Instance Methods Abstract Methods 
      Modifier and Type Method Description
      java.lang.String getDatasetId()
      ID of the EvaluationDataset containing training data.
      com.google.protobuf.ByteString getDatasetIdBytes()
      ID of the EvaluationDataset containing training data.
      java.lang.String getOptimizerConfigJson()
      JSON-serialized optimizer-specific configuration.
      com.google.protobuf.ByteString getOptimizerConfigJsonBytes()
      JSON-serialized optimizer-specific configuration.
      PromptOptimization.OptimizerType getOptimizerType()
      The optimizer type to use.
      java.lang.String getScorers​(int index)
      List of scorer names.
      com.google.protobuf.ByteString getScorersBytes​(int index)
      List of scorer names.
      int getScorersCount()
      List of scorer names.
      java.util.List<java.lang.String> getScorersList()
      List of scorer names.
      boolean hasDatasetId()
      ID of the EvaluationDataset containing training data.
      boolean hasOptimizerConfigJson()
      JSON-serialized optimizer-specific configuration.
      boolean hasOptimizerType()
      The optimizer type to use.

      • Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

        isInitialized

      • Methods inherited from interface com.google.protobuf.MessageOrBuilder

        findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

    • Method Detail

      • hasOptimizerType

        boolean hasOptimizerType()
         The optimizer type to use.
        optional .mlflow.OptimizerType optimizer_type = 1;
        Returns:
        Whether the optimizerType field is set.

      • getOptimizerType

        PromptOptimization.OptimizerType getOptimizerType()
         The optimizer type to use.
        optional .mlflow.OptimizerType optimizer_type = 1;
        Returns:
        The optimizerType.

      • hasDatasetId

        boolean hasDatasetId()
         ID of the EvaluationDataset containing training data.
        optional string dataset_id = 2;
        Returns:
        Whether the datasetId field is set.

      • getDatasetId

        java.lang.String getDatasetId()
         ID of the EvaluationDataset containing training data.
        optional string dataset_id = 2;
        Returns:
        The datasetId.

      • getDatasetIdBytes

        com.google.protobuf.ByteString getDatasetIdBytes()
         ID of the EvaluationDataset containing training data.
        optional string dataset_id = 2;
        Returns:
        The bytes for datasetId.

      • getScorersList

        java.util.List<java.lang.String> getScorersList()
         List of scorer names. Can be built-in scorer class names
 (e.g., "Correctness", "Safety") or registered scorer names.
        repeated string scorers = 3;
        Returns:
        A list containing the scorers.

      • getScorersCount

        int getScorersCount()
         List of scorer names. Can be built-in scorer class names
 (e.g., "Correctness", "Safety") or registered scorer names.
        repeated string scorers = 3;
        Returns:
        The count of scorers.

      • getScorers

        java.lang.String getScorers​(int index)
         List of scorer names. Can be built-in scorer class names
 (e.g., "Correctness", "Safety") or registered scorer names.
        repeated string scorers = 3;
        Parameters:
        index - The index of the element to return.
        Returns:
        The scorers at the given index.

      • getScorersBytes

        com.google.protobuf.ByteString getScorersBytes​(int index)
         List of scorer names. Can be built-in scorer class names
 (e.g., "Correctness", "Safety") or registered scorer names.
        repeated string scorers = 3;
        Parameters:
        index - The index of the value to return.
        Returns:
        The bytes of the scorers at the given index.

      • hasOptimizerConfigJson

        boolean hasOptimizerConfigJson()
         JSON-serialized optimizer-specific configuration.
 Different optimizers accept different parameters:
 - GEPA: {"reflection_model": "openai:/gpt-5", "max_metric_calls": 300}
 - MetaPrompt: {"reflection_model": "openai:/gpt-5", "guidelines": "...", "lm_kwargs": {...}}
        optional string optimizer_config_json = 4;
        Returns:
        Whether the optimizerConfigJson field is set.

      • getOptimizerConfigJson

        java.lang.String getOptimizerConfigJson()
         JSON-serialized optimizer-specific configuration.
 Different optimizers accept different parameters:
 - GEPA: {"reflection_model": "openai:/gpt-5", "max_metric_calls": 300}
 - MetaPrompt: {"reflection_model": "openai:/gpt-5", "guidelines": "...", "lm_kwargs": {...}}
        optional string optimizer_config_json = 4;
        Returns:
        The optimizerConfigJson.

      • getOptimizerConfigJsonBytes

        com.google.protobuf.ByteString getOptimizerConfigJsonBytes()
         JSON-serialized optimizer-specific configuration.
 Different optimizers accept different parameters:
 - GEPA: {"reflection_model": "openai:/gpt-5", "max_metric_calls": 300}
 - MetaPrompt: {"reflection_model": "openai:/gpt-5", "guidelines": "...", "lm_kwargs": {...}}
        optional string optimizer_config_json = 4;
        Returns:
        The bytes for optimizerConfigJson.