koog-agents-optimization/ai.koog.agents.optimization.training/CapturingPromptExecutor

CapturingPromptExecutor

abstract class CapturingPromptExecutor : PromptExecutor

A PromptExecutor that accumulates the LLMConsumption of the calls it intercepts and hands it back via collectAndClear. The training infrastructure creates one per leaf prompt call (via the session's capturingExecutorFactory) and reads its consumption between retry attempts; the concrete provider-aware extraction lives in the app.

Inheritors

ConsumptionCapturingPromptExecutor

Constructors

CapturingPromptExecutor

constructor()

Functions

abstract fun close()

collectAndClear

abstract fun collectAndClear(): LLMConsumption?

Returns the consumption accumulated since the previous call (or since construction), then resets the accumulator. Returns null when nothing was captured.

execute

open suspend fun execute(prompt: Prompt, model: ResolvedModel, tools: List<ToolDescriptor>): Message.Assistant

abstract suspend fun execute(prompt: Prompt, model: LLModel, tools: List<ToolDescriptor>): Message.Assistant

executeBlocking

fun executeBlocking(prompt: Prompt, resolvedModel: ResolvedModel, tools: List<ToolDescriptor>): Message.Assistant

fun executeBlocking(prompt: Prompt, model: LLModel, tools: List<ToolDescriptor>): Message.Assistant

executeMultipleChoices

open suspend fun executeMultipleChoices(prompt: Prompt, resolvedModel: ResolvedModel, tools: List<ToolDescriptor>): LLMChoice

open suspend fun executeMultipleChoices(prompt: Prompt, model: LLModel, tools: List<ToolDescriptor>): LLMChoice

executeMultipleChoicesBlocking

fun executeMultipleChoicesBlocking(prompt: Prompt, resolvedModel: ResolvedModel, tools: List<ToolDescriptor>): LLMChoice

fun executeMultipleChoicesBlocking(prompt: Prompt, model: LLModel, tools: List<ToolDescriptor>): LLMChoice

executeStreaming

open fun executeStreaming(prompt: Prompt, resolvedModel: ResolvedModel, tools: List<ToolDescriptor>): Flow<StreamFrame>

abstract fun executeStreaming(prompt: Prompt, model: LLModel, tools: List<ToolDescriptor>): Flow<StreamFrame>

executeStreamingBlocking

fun executeStreamingBlocking(prompt: Prompt, resolvedModel: ResolvedModel, tools: List<ToolDescriptor>): Flow.Publisher<StreamFrame>

fun executeStreamingBlocking(prompt: Prompt, model: LLModel, tools: List<ToolDescriptor>): Flow.Publisher<StreamFrame>

executeStructuredOrThrow

inline suspend fun <OutputStructT> PromptExecutor.executeStructuredOrThrow(prompt: Prompt, model: LLModel): OutputStructT

Executes prompt against model, requesting a structured response of type OutputStructT, and returns the parsed data.

getBasicJsonSchemaGenerator

open fun getBasicJsonSchemaGenerator(model: LLModel): BasicJsonSchemaGenerator

getStandardJsonSchemaGenerator

open fun getStandardJsonSchemaGenerator(model: LLModel): StandardJsonSchemaGenerator

models

open suspend fun models(): List<LLModel>

modelsBlocking

fun modelsBlocking(): List<LLModel>

moderate

open suspend fun moderate(prompt: Prompt, model: ResolvedModel): ModerationResult

abstract suspend fun moderate(prompt: Prompt, model: LLModel): ModerationResult

moderateBlocking

fun moderateBlocking(prompt: Prompt, resolvedModel: ResolvedModel): ModerationResult

fun moderateBlocking(prompt: Prompt, model: LLModel): ModerationResult

resolveModel

open suspend fun resolveModel(model: LLModel, promptExecutorOperation: PromptExecutorOperation): ResolvedModel

resolveModelBlocking

fun resolveModelBlocking(requestedModel: LLModel, promptExecutorOperation: PromptExecutorOperation): ResolvedModel