Package-level declarations
Types
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Preset auto-run modes controlling candidate count, validation set size, and trial budget cap.
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class InstructionProposer
Generates instruction candidates for each optimizable module.
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data class InstructionProposerConfig(val useDatasetSummary: Boolean = true, val programAware: Boolean = true, val useTaskDemos: Boolean = true, val numDemosInContext: Int = 3, val useTip: Boolean = true, val setTipRandomly: Boolean = true, val useInstructHistory: Boolean = false, val setHistoryRandomly: Boolean = false)
Configuration for InstructionProposer, toggling which context the meta-LLM receives.
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class MIPROv2Optimizer<Input, Output, InputLabel>(metaModel: LLModel, autoMode: AutoRunMode = AutoRunMode.LIGHT, numCandidatesOverride: Int? = null, numTrialsOverride: Int? = null, maxBootstrappedDemos: Int = 4, maxTotalDemos: Int = 8, includeLabeledExamples: Boolean = true, proposerConfig: InstructionProposerConfig = InstructionProposerConfig(), val storagePath: ResilientPath, randomSeed: Long = 42, parallelism: Int = 1) : AgentOptimizer<Input, Output, InputLabel>
MIPRO v2 optimizer that tunes instructions and demonstrations via a 3-stage pipeline: