AgentOptimizationJobs
Estimate an agent optimization job
Estimates validation-set rows, per-stage model call volumes, and cost bands without submitting the job.
Parametri di query
api-version
string
necessario
The API version to use for this operation.
Corpo della richiesta
The inputs to estimate against.
target_configuration
foundry_agent
Base target configuration for an optimization job.
foundry_agent
AgentOptimizationFoundryAgentTargetConfiguration
Identifies the Foundry agent that owns the configuration being optimized.
type
enum
necessario
Foundry-agent target discriminator.
name
string
necessario
Registered Foundry agent name.
version
string
Pinned agent version. Omitted to resolve and pin the latest version.
optimization_model_configuration
AgentOptimizationModelConfiguration
necessario
Identifies a model used by an optimization or evaluation step.
model
string
necessario
A non-empty Foundry model name or existing deployment name.
optimization_configuration
AgentOptimizationConfiguration
necessario
Configuration for optimizing an agent for measured quality.
type
enum
necessario
Optimization type discriminator.
goal
string | enum
Goal for an agent-optimization job.
enum
evaluation_configuration
AgentOptimizationEvaluationConfiguration
necessario
Reusable quality-measurement configuration.
training_set
target_completion | user_conversation_simulation
necessario
Base discriminated model for an optimization evaluation set.
target_completion
AgentOptimizationTargetCompletionEvaluationSet
Evaluation set containing independent single-turn inputs.
type
enum
necessario
Target-completion set discriminator.
source
inline | dataset_reference
necessario
Base source for a target-completion optimization evaluation set.
inline
AgentOptimizationTargetCompletionInlineDataSource
Supplies single-turn rows directly in the optimization request.
type
enum
necessario
Inline source discriminator.
test_cases
AgentOptimizationTargetCompletionTestCase[]
necessario
Target-completion test cases.
dataset_reference
AgentOptimizationTargetCompletionDatasetReferenceDataSource
References an explicitly versioned registered Foundry dataset for target-completion evaluation.
type
enum
necessario
Registered dataset source discriminator.
name
string
necessario
Registered dataset name.
version
string
necessario
Registered dataset version.
user_conversation_simulation
AgentOptimizationUserConversationSimulationEvaluationSet
Evaluation set containing scenarios for simulated conversations.
type
enum
necessario
User-conversation-simulation set discriminator.
source
inline | dataset_reference
necessario
Base source for a user-conversation-simulation optimization evaluation set.
inline
AgentOptimizationUserConversationSimulationInlineDataSource
Supplies Evals user-conversation simulation test cases directly in the optimization request.
type
enum
necessario
Inline source discriminator.
test_cases
UserConversationSimulationTestCase[]
necessario
Conversation test scenarios.
dataset_reference
AgentOptimizationUserConversationSimulationDatasetReferenceDataSource
References an explicitly versioned registered Foundry dataset for user-conversation-simulation evaluation.
type
enum
necessario
Registered dataset source discriminator.
name
string
necessario
Registered dataset name.
version
string
necessario
Registered dataset version.
default_simulation_configuration
UserConversationSimulationConfiguration
Configures the number, length, audio effects, and simulated user behavior of conversations.
max_num_turns
integer
Hard limit on turns in each conversation. When omitted, the service defaults to 20.
conversation_repetitions
integer
Number of independent conversation repetitions for each test case. Defaults to 1 when not specified at either the data-source or test-case level.
desired_num_turns
integer
Target number of turns in each conversation. The effective value cannot exceed the effective max_num_turns. When omitted, no target is set and the simulation model determines the conversation length dynamically from the scenario.
audio_effects
UserConversationSimulationAudioEffectsConfiguration
Configures effects applied to simulated conversation audio.
effects
UserConversationSimulationAudioEffect[]
Effects to apply to simulated audio.
volume_percentage
integer
Volume of the configured audio effects, as a percentage from 1 through 100. When omitted, the service defaults to 15.
user_behavior
UserConversationSimulationUserBehaviorConfiguration
Configures conversation behavior for the simulated user.
interruption
default
Configuration for simulated user interruption behavior.
default
UserConversationSimulationDefaultInterruptionConfiguration
Configures the default interruption behavior for the simulated user.
type
enum
necessario
The interruption type, always default.
validation_set
target_completion | user_conversation_simulation
Base discriminated model for an optimization evaluation set.
target_completion
AgentOptimizationTargetCompletionEvaluationSet
Evaluation set containing independent single-turn inputs.
type
enum
necessario
Target-completion set discriminator.
source
inline | dataset_reference
necessario
Base source for a target-completion optimization evaluation set.
inline
AgentOptimizationTargetCompletionInlineDataSource
Supplies single-turn rows directly in the optimization request.
type
enum
necessario
Inline source discriminator.
test_cases
AgentOptimizationTargetCompletionTestCase[]
necessario
Target-completion test cases.
dataset_reference
AgentOptimizationTargetCompletionDatasetReferenceDataSource
References an explicitly versioned registered Foundry dataset for target-completion evaluation.
type
enum
necessario
Registered dataset source discriminator.
name
string
necessario
Registered dataset name.
version
string
necessario
Registered dataset version.
user_conversation_simulation
AgentOptimizationUserConversationSimulationEvaluationSet
Evaluation set containing scenarios for simulated conversations.
type
enum
necessario
User-conversation-simulation set discriminator.
source
inline | dataset_reference
necessario
Base source for a user-conversation-simulation optimization evaluation set.
inline
AgentOptimizationUserConversationSimulationInlineDataSource
Supplies Evals user-conversation simulation test cases directly in the optimization request.
type
enum
necessario
Inline source discriminator.
test_cases
UserConversationSimulationTestCase[]
necessario
Conversation test scenarios.
dataset_reference
AgentOptimizationUserConversationSimulationDatasetReferenceDataSource
References an explicitly versioned registered Foundry dataset for user-conversation-simulation evaluation.
type
enum
necessario
Registered dataset source discriminator.
name
string
necessario
Registered dataset name.
version
string
necessario
Registered dataset version.
default_simulation_configuration
UserConversationSimulationConfiguration
Configures the number, length, audio effects, and simulated user behavior of conversations.
max_num_turns
integer
Hard limit on turns in each conversation. When omitted, the service defaults to 20.
conversation_repetitions
integer
Number of independent conversation repetitions for each test case. Defaults to 1 when not specified at either the data-source or test-case level.
desired_num_turns
integer
Target number of turns in each conversation. The effective value cannot exceed the effective max_num_turns. When omitted, no target is set and the simulation model determines the conversation length dynamically from the scenario.
audio_effects
UserConversationSimulationAudioEffectsConfiguration
Configures effects applied to simulated conversation audio.
effects
UserConversationSimulationAudioEffect[]
Effects to apply to simulated audio.
volume_percentage
integer
Volume of the configured audio effects, as a percentage from 1 through 100. When omitted, the service defaults to 15.
user_behavior
UserConversationSimulationUserBehaviorConfiguration
Configures conversation behavior for the simulated user.
interruption
default
Configuration for simulated user interruption behavior.
default
UserConversationSimulationDefaultInterruptionConfiguration
Configures the default interruption behavior for the simulated user.
type
enum
necessario
The interruption type, always default.
evaluators
AgentOptimizationEvaluator[]
necessario
Evaluator references used to score candidate quality.
evaluation_model
EvaluationModelConfiguration
necessario
Configures the model that plays the simulated user. This model is separate from the evaluated target.
model
string
necessario
Model deployment that generates simulated user turns, in the format {connectionName}/modelDeploymentName.
sampling_params
ModelSamplingParams
Represents a set of parameters used to control the sampling behavior of a language model during text generation.
temperature
number
The temperature parameter for sampling. Defaults to 1.0.
top_p
number
The top-p parameter for nucleus sampling. Defaults to 1.0.
seed
integer
The random seed for reproducibility. Defaults to 42.
max_completion_tokens
integer
The maximum number of tokens allowed in the completion.
voice_model
azure-standard
Voice configuration used to convert text to speech for evaluation through the Voice Live endpoint.
azure-standard
EvaluationAzureStandardVoiceModelConfiguration
Configures an Azure standard neural voice used to convert text to speech for evaluation through the Voice Live endpoint.
type
enum
necessario
The voice kind. Always azure-standard.
name
string
necessario
The Azure neural voice name.
temperature
number
The synthesis temperature, from 0 to 1. When omitted, the service defaults to the underlying voice model's default temperature.
max_concurrent_agent_runs
integer
Maximum number of target-agent runs executed concurrently during each single-turn evaluation. If omitted, the service defaults to 1. Conversation evaluation supports only 1.
candidate_search_configuration
AgentOptimizationCandidateSearchConfiguration
necessario
Candidate search settings.
max_candidates
integer
Maximum number of non-baseline candidates to fully evaluate. If omitted, the service defaults to 1.
baseline_agent_configuration
AgentOptimizationBaselineAgentConfiguration
Caller-supplied baseline agent values that cannot be resolved from the target agent.
system_prompt
string
Caller-supplied baseline system prompt. Omitted to resolve the baseline from the target; a prompt agent's stored definition is authoritative.
current_model
string
A non-empty Foundry model name or existing deployment name.
skills
AgentOptimizationSkill[]
Skills available for optimization. Omitted when no manual skill surface is supplied.
tools
OpenAI.ChatCompletionTool[]
Function tools available for optimization. Omitted when no manual tool surface is supplied. The optimizer may change function and argument descriptions while preserving names and parameter JSON Schema.
agent_optimization_space
AgentOptimizationSpace
necessario
The agent attributes and alternative values available to an agent-optimization search.
target_attributes
TargetAttribute[]
Agent attributes the optimizer may change. If omitted, the service defaults to instructions.
model_search_space
AgentOptimizationModelName[]
Alternative model names or existing deployment names available when model is an optimization target.
Risposte
The request has succeeded.
Corpo
call_counts
AgentOptimizationStageEstimate
Estimated values grouped by optimization stage.
agent
AgentOptimizationEstimateBand
A low/typical/ceiling range for an estimated quantity. Cost values apply average per-call usage assumptions to each call-count scenario. Expected values may be fractional, including estimated model-call counts.
low
number
necessario
Lower estimate based on model calls required for every run.
typical
number
necessario
Expected estimate based on model calls consumed by a typical run.
ceiling
number
necessario
Upper bound calculated from the maximum number of model calls.
evaluation
AgentOptimizationEstimateBand
A low/typical/ceiling range for an estimated quantity. Cost values apply average per-call usage assumptions to each call-count scenario. Expected values may be fractional, including estimated model-call counts.
low
number
necessario
Lower estimate based on model calls required for every run.
typical
number
necessario
Expected estimate based on model calls consumed by a typical run.
ceiling
number
necessario
Upper bound calculated from the maximum number of model calls.
optimization
AgentOptimizationEstimateBand
A low/typical/ceiling range for an estimated quantity. Cost values apply average per-call usage assumptions to each call-count scenario. Expected values may be fractional, including estimated model-call counts.
low
number
necessario
Lower estimate based on model calls required for every run.
typical
number
necessario
Expected estimate based on model calls consumed by a typical run.
ceiling
number
necessario
Upper bound calculated from the maximum number of model calls.
cost
AgentOptimizationCostEstimate
Estimated monetary cost. Present only when at least one contributing model has pricing data.
currency
string
necessario
ISO 4217 currency code for all monetary values in this estimate.
total
AgentOptimizationEstimateBand
A low/typical/ceiling range for an estimated quantity. Cost values apply average per-call usage assumptions to each call-count scenario. Expected values may be fractional, including estimated model-call counts.
low
number
necessario
Lower estimate based on model calls required for every run.
typical
number
necessario
Expected estimate based on model calls consumed by a typical run.
ceiling
number
necessario
Upper bound calculated from the maximum number of model calls.
by_stage
AgentOptimizationStageEstimate
Estimated values grouped by optimization stage.
agent
AgentOptimizationEstimateBand
A low/typical/ceiling range for an estimated quantity. Cost values apply average per-call usage assumptions to each call-count scenario. Expected values may be fractional, including estimated model-call counts.
low
number
necessario
Lower estimate based on model calls required for every run.
typical
number
necessario
Expected estimate based on model calls consumed by a typical run.
ceiling
number
necessario
Upper bound calculated from the maximum number of model calls.
evaluation
AgentOptimizationEstimateBand
A low/typical/ceiling range for an estimated quantity. Cost values apply average per-call usage assumptions to each call-count scenario. Expected values may be fractional, including estimated model-call counts.
low
number
necessario
Lower estimate based on model calls required for every run.
typical
number
necessario
Expected estimate based on model calls consumed by a typical run.
ceiling
number
necessario
Upper bound calculated from the maximum number of model calls.
optimization
AgentOptimizationEstimateBand
A low/typical/ceiling range for an estimated quantity. Cost values apply average per-call usage assumptions to each call-count scenario. Expected values may be fractional, including estimated model-call counts.
low
number
necessario
Lower estimate based on model calls required for every run.
typical
number
necessario
Expected estimate based on model calls consumed by a typical run.
ceiling
number
necessario
Upper bound calculated from the maximum number of model calls.
unpriced_stages
AgentOptimizationStage[]
Stages excluded from the total because pricing was unavailable.
Richiedi
POST /agent_optimization_jobs:estimate HTTP/1.1
Response
Status: 200
Content-Type: application/json
Status: 4XX
Content-Type: application/json
Status: 5XX
Content-Type: application/json