MCP Tools Reference: aiplatform.googleapis.com

Tool: evaluate_instances

Evaluates instances based on a given metric. Use this to perform online evaluation of model responses using metrics like fluency, coherence, safety, and more.

The following sample demonstrate how to use curl to invoke the evaluate_instances MCP tool.

Curl Request
curl --location 'https://aiplatform.googleapis.com/mcp/generate' \ --header 'content-type: application/json' \ --header 'accept: application/json, text/event-stream' \ --data '{ "method": "tools/call", "params": { "name": "evaluate_instances", "arguments": { // provide these details according to the tool's MCP specification } }, "jsonrpc": "2.0", "id": 1 }'

Input Schema

Request message for EvaluationService.EvaluateInstances.

EvaluateInstancesRequest

JSON representation

{ "location": string, "autoraterConfig": { object (AutoraterConfig) }, // Union field metric_inputs can be only one of the following: "exactMatchInput": { object (ExactMatchInput) }, "bleuInput": { object (BleuInput) }, "rougeInput": { object (RougeInput) }, "fluencyInput": { object (FluencyInput) }, "coherenceInput": { object (CoherenceInput) }, "safetyInput": { object (SafetyInput) }, "groundednessInput": { object (GroundednessInput) }, "fulfillmentInput": { object (FulfillmentInput) }, "summarizationQualityInput": { object (SummarizationQualityInput) }, "pairwiseSummarizationQualityInput": { object (PairwiseSummarizationQualityInput) }, "summarizationHelpfulnessInput": { object (SummarizationHelpfulnessInput) }, "summarizationVerbosityInput": { object (SummarizationVerbosityInput) }, "questionAnsweringQualityInput": { object (QuestionAnsweringQualityInput) }, "pairwiseQuestionAnsweringQualityInput": { object (PairwiseQuestionAnsweringQualityInput) }, "questionAnsweringRelevanceInput": { object (QuestionAnsweringRelevanceInput) }, "questionAnsweringHelpfulnessInput": { object (QuestionAnsweringHelpfulnessInput) }, "questionAnsweringCorrectnessInput": { object (QuestionAnsweringCorrectnessInput) }, "pointwiseMetricInput": { object (PointwiseMetricInput) }, "pairwiseMetricInput": { object (PairwiseMetricInput) }, "toolCallValidInput": { object (ToolCallValidInput) }, "toolNameMatchInput": { object (ToolNameMatchInput) }, "toolParameterKeyMatchInput": { object (ToolParameterKeyMatchInput) }, "toolParameterKvMatchInput": { object (ToolParameterKVMatchInput) }, "cometInput": { object (CometInput) }, "metricxInput": { object (MetricxInput) }, "trajectoryExactMatchInput": { object (TrajectoryExactMatchInput) }, "trajectoryInOrderMatchInput": { object (TrajectoryInOrderMatchInput) }, "trajectoryAnyOrderMatchInput": { object (TrajectoryAnyOrderMatchInput) }, "trajectoryPrecisionInput": { object (TrajectoryPrecisionInput) }, "trajectoryRecallInput": { object (TrajectoryRecallInput) }, "trajectorySingleToolUseInput": { object (TrajectorySingleToolUseInput) }, "rubricBasedInstructionFollowingInput": { object (RubricBasedInstructionFollowingInput) } // End of list of possible types for union field metric_inputs. }

Fields
location	string Required. The resource name of the Location to evaluate the instances. Format: projects/{project}/locations/{location}
autoraterConfig	object (AutoraterConfig) Optional. Autorater config used for evaluation.
Union field metric_inputs. Instances and specs for evaluation metric_inputs can be only one of the following:
exactMatchInput	object (ExactMatchInput) Auto metric instances. Instances and metric spec for exact match metric.
bleuInput	object (BleuInput) Instances and metric spec for bleu metric.
rougeInput	object (RougeInput) Instances and metric spec for rouge metric.
fluencyInput	object (FluencyInput) LLM-based metric instance. General text generation metrics, applicable to other categories. Input for fluency metric.
coherenceInput	object (CoherenceInput) Input for coherence metric.
safetyInput	object (SafetyInput) Input for safety metric.
groundednessInput	object (GroundednessInput) Input for groundedness metric.
fulfillmentInput	object (FulfillmentInput) Input for fulfillment metric.
summarizationQualityInput	object (SummarizationQualityInput) Input for summarization quality metric.
pairwiseSummarizationQualityInput	object (PairwiseSummarizationQualityInput) Input for pairwise summarization quality metric.
summarizationHelpfulnessInput	object (SummarizationHelpfulnessInput) Input for summarization helpfulness metric.
summarizationVerbosityInput	object (SummarizationVerbosityInput) Input for summarization verbosity metric.
questionAnsweringQualityInput	object (QuestionAnsweringQualityInput) Input for question answering quality metric.
pairwiseQuestionAnsweringQualityInput	object (PairwiseQuestionAnsweringQualityInput) Input for pairwise question answering quality metric.
questionAnsweringRelevanceInput	object (QuestionAnsweringRelevanceInput) Input for question answering relevance metric.
questionAnsweringHelpfulnessInput	object (QuestionAnsweringHelpfulnessInput) Input for question answering helpfulness metric.
questionAnsweringCorrectnessInput	object (QuestionAnsweringCorrectnessInput) Input for question answering correctness metric.
pointwiseMetricInput	object (PointwiseMetricInput) Input for pointwise metric.
pairwiseMetricInput	object (PairwiseMetricInput) Input for pairwise metric.
toolCallValidInput	object (ToolCallValidInput) Tool call metric instances. Input for tool call valid metric.
toolNameMatchInput	object (ToolNameMatchInput) Input for tool name match metric.
toolParameterKeyMatchInput	object (ToolParameterKeyMatchInput) Input for tool parameter key match metric.
toolParameterKvMatchInput	object (ToolParameterKVMatchInput) Input for tool parameter key value match metric.
cometInput	object (CometInput) Translation metrics. Input for Comet metric.
metricxInput	object (MetricxInput) Input for Metricx metric.
trajectoryExactMatchInput	object (TrajectoryExactMatchInput) Input for trajectory exact match metric.
trajectoryInOrderMatchInput	object (TrajectoryInOrderMatchInput) Input for trajectory in order match metric.
trajectoryAnyOrderMatchInput	object (TrajectoryAnyOrderMatchInput) Input for trajectory match any order metric.
trajectoryPrecisionInput	object (TrajectoryPrecisionInput) Input for trajectory precision metric.
trajectoryRecallInput	object (TrajectoryRecallInput) Input for trajectory recall metric.
trajectorySingleToolUseInput	object (TrajectorySingleToolUseInput) Input for trajectory single tool use metric.
rubricBasedInstructionFollowingInput	object (RubricBasedInstructionFollowingInput) Rubric Based Instruction Following metric.

ExactMatchInput

JSON representation
{ "metricSpec": { object (ExactMatchSpec) }, "instances": [ { object (ExactMatchInstance) } ] }

Fields
metricSpec	object (ExactMatchSpec) Required. Spec for exact match metric.
instances[]	object (ExactMatchInstance) Required. Repeated exact match instances.

ExactMatchInstance

JSON representation
{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _reference can be only one of the following: "reference": string // End of list of possible types for union field _reference. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.
Union field _reference. _reference can be only one of the following:
reference	string Required. Ground truth used to compare against the prediction.

BleuInput

JSON representation
{ "metricSpec": { object (BleuSpec) }, "instances": [ { object (BleuInstance) } ] }

Fields
metricSpec	object (BleuSpec) Required. Spec for bleu score metric.
instances[]	object (BleuInstance) Required. Repeated bleu instances.

BleuSpec

JSON representation
{ "useEffectiveOrder": boolean }

Fields
useEffectiveOrder	boolean Optional. Whether to use_effective_order to compute bleu score.

BleuInstance

JSON representation
{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _reference can be only one of the following: "reference": string // End of list of possible types for union field _reference. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.
Union field _reference. _reference can be only one of the following:
reference	string Required. Ground truth used to compare against the prediction.

RougeInput

JSON representation
{ "metricSpec": { object (RougeSpec) }, "instances": [ { object (RougeInstance) } ] }

Fields
metricSpec	object (RougeSpec) Required. Spec for rouge score metric.
instances[]	object (RougeInstance) Required. Repeated rouge instances.

RougeSpec

JSON representation
{ "rougeType": string, "useStemmer": boolean, "splitSummaries": boolean }

Fields
rougeType	string Optional. Supported rouge types are rougen[1-9], rougeL, and rougeLsum.
useStemmer	boolean Optional. Whether to use stemmer to compute rouge score.
splitSummaries	boolean Optional. Whether to split summaries while using rougeLsum.

RougeInstance

JSON representation
{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _reference can be only one of the following: "reference": string // End of list of possible types for union field _reference. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.
Union field _reference. _reference can be only one of the following:
reference	string Required. Ground truth used to compare against the prediction.

FluencyInput

JSON representation
{ "metricSpec": { object (FluencySpec) }, "instance": { object (FluencyInstance) } }

Fields
metricSpec	object (FluencySpec) Required. Spec for fluency score metric.
instance	object (FluencyInstance) Required. Fluency instance.

FluencySpec

JSON representation
{ "version": integer }

Fields
version	integer Optional. Which version to use for evaluation.

FluencyInstance

JSON representation
{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.

CoherenceInput

JSON representation
{ "metricSpec": { object (CoherenceSpec) }, "instance": { object (CoherenceInstance) } }

Fields
metricSpec	object (CoherenceSpec) Required. Spec for coherence score metric.
instance	object (CoherenceInstance) Required. Coherence instance.

CoherenceSpec

JSON representation
{ "version": integer }

Fields
version	integer Optional. Which version to use for evaluation.

CoherenceInstance

JSON representation
{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.

SafetyInput

JSON representation
{ "metricSpec": { object (SafetySpec) }, "instance": { object (SafetyInstance) } }

Fields
metricSpec	object (SafetySpec) Required. Spec for safety metric.
instance	object (SafetyInstance) Required. Safety instance.

SafetySpec

JSON representation
{ "version": integer }

Fields
version	integer Optional. Which version to use for evaluation.

SafetyInstance

JSON representation
{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.

GroundednessInput

JSON representation
{ "metricSpec": { object (GroundednessSpec) }, "instance": { object (GroundednessInstance) } }

Fields
metricSpec	object (GroundednessSpec) Required. Spec for groundedness metric.
instance	object (GroundednessInstance) Required. Groundedness instance.

GroundednessSpec

JSON representation
{ "version": integer }

Fields
version	integer Optional. Which version to use for evaluation.

GroundednessInstance

JSON representation
{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _context can be only one of the following: "context": string // End of list of possible types for union field _context. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.
Union field _context. _context can be only one of the following:
context	string Required. Background information provided in context used to compare against the prediction.

FulfillmentInput

JSON representation
{ "metricSpec": { object (FulfillmentSpec) }, "instance": { object (FulfillmentInstance) } }

Fields
metricSpec	object (FulfillmentSpec) Required. Spec for fulfillment score metric.
instance	object (FulfillmentInstance) Required. Fulfillment instance.

FulfillmentSpec

JSON representation
{ "version": integer }

Fields
version	integer Optional. Which version to use for evaluation.

FulfillmentInstance

JSON representation
{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _instruction can be only one of the following: "instruction": string // End of list of possible types for union field _instruction. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.
Union field _instruction. _instruction can be only one of the following:
instruction	string Required. Inference instruction prompt to compare prediction with.

SummarizationQualityInput

JSON representation
{ "metricSpec": { object (SummarizationQualitySpec) }, "instance": { object (SummarizationQualityInstance) } }

Fields
metricSpec	object (SummarizationQualitySpec) Required. Spec for summarization quality score metric.
instance	object (SummarizationQualityInstance) Required. Summarization quality instance.

SummarizationQualitySpec

JSON representation
{ "useReference": boolean, "version": integer }

Fields
useReference	boolean Optional. Whether to use instance.reference to compute summarization quality.
version	integer Optional. Which version to use for evaluation.

SummarizationQualityInstance

JSON representation

{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _reference can be only one of the following: "reference": string // End of list of possible types for union field _reference. // Union field _context can be only one of the following: "context": string // End of list of possible types for union field _context. // Union field _instruction can be only one of the following: "instruction": string // End of list of possible types for union field _instruction. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.
Union field _reference. _reference can be only one of the following:
reference	string Optional. Ground truth used to compare against the prediction.
Union field _context. _context can be only one of the following:
context	string Required. Text to be summarized.
Union field _instruction. _instruction can be only one of the following:
instruction	string Required. Summarization prompt for LLM.

PairwiseSummarizationQualityInput

JSON representation
{ "metricSpec": { object (PairwiseSummarizationQualitySpec) }, "instance": { object (PairwiseSummarizationQualityInstance) } }

Fields
metricSpec	object (PairwiseSummarizationQualitySpec) Required. Spec for pairwise summarization quality score metric.
instance	object (PairwiseSummarizationQualityInstance) Required. Pairwise summarization quality instance.

PairwiseSummarizationQualitySpec

JSON representation
{ "useReference": boolean, "version": integer }

Fields
useReference	boolean Optional. Whether to use instance.reference to compute pairwise summarization quality.
version	integer Optional. Which version to use for evaluation.

PairwiseSummarizationQualityInstance

JSON representation

{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _baseline_prediction can be only one of the following: "baselinePrediction": string // End of list of possible types for union field _baseline_prediction. // Union field _reference can be only one of the following: "reference": string // End of list of possible types for union field _reference. // Union field _context can be only one of the following: "context": string // End of list of possible types for union field _context. // Union field _instruction can be only one of the following: "instruction": string // End of list of possible types for union field _instruction. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the candidate model.
Union field _baseline_prediction. _baseline_prediction can be only one of the following:
baselinePrediction	string Required. Output of the baseline model.
Union field _reference. _reference can be only one of the following:
reference	string Optional. Ground truth used to compare against the prediction.
Union field _context. _context can be only one of the following:
context	string Required. Text to be summarized.
Union field _instruction. _instruction can be only one of the following:
instruction	string Required. Summarization prompt for LLM.

SummarizationHelpfulnessInput

JSON representation
{ "metricSpec": { object (SummarizationHelpfulnessSpec) }, "instance": { object (SummarizationHelpfulnessInstance) } }

Fields
metricSpec	object (SummarizationHelpfulnessSpec) Required. Spec for summarization helpfulness score metric.
instance	object (SummarizationHelpfulnessInstance) Required. Summarization helpfulness instance.

SummarizationHelpfulnessSpec

JSON representation
{ "useReference": boolean, "version": integer }

Fields
useReference	boolean Optional. Whether to use instance.reference to compute summarization helpfulness.
version	integer Optional. Which version to use for evaluation.

SummarizationHelpfulnessInstance

JSON representation

{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _reference can be only one of the following: "reference": string // End of list of possible types for union field _reference. // Union field _context can be only one of the following: "context": string // End of list of possible types for union field _context. // Union field _instruction can be only one of the following: "instruction": string // End of list of possible types for union field _instruction. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.
Union field _reference. _reference can be only one of the following:
reference	string Optional. Ground truth used to compare against the prediction.
Union field _context. _context can be only one of the following:
context	string Required. Text to be summarized.
Union field _instruction. _instruction can be only one of the following:
instruction	string Optional. Summarization prompt for LLM.

SummarizationVerbosityInput

JSON representation
{ "metricSpec": { object (SummarizationVerbositySpec) }, "instance": { object (SummarizationVerbosityInstance) } }

Fields
metricSpec	object (SummarizationVerbositySpec) Required. Spec for summarization verbosity score metric.
instance	object (SummarizationVerbosityInstance) Required. Summarization verbosity instance.

SummarizationVerbositySpec

JSON representation
{ "useReference": boolean, "version": integer }

Fields
useReference	boolean Optional. Whether to use instance.reference to compute summarization verbosity.
version	integer Optional. Which version to use for evaluation.

SummarizationVerbosityInstance

JSON representation

{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _reference can be only one of the following: "reference": string // End of list of possible types for union field _reference. // Union field _context can be only one of the following: "context": string // End of list of possible types for union field _context. // Union field _instruction can be only one of the following: "instruction": string // End of list of possible types for union field _instruction. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.
Union field _reference. _reference can be only one of the following:
reference	string Optional. Ground truth used to compare against the prediction.
Union field _context. _context can be only one of the following:
context	string Required. Text to be summarized.
Union field _instruction. _instruction can be only one of the following:
instruction	string Optional. Summarization prompt for LLM.

QuestionAnsweringQualityInput

JSON representation
{ "metricSpec": { object (QuestionAnsweringQualitySpec) }, "instance": { object (QuestionAnsweringQualityInstance) } }

Fields
metricSpec	object (QuestionAnsweringQualitySpec) Required. Spec for question answering quality score metric.
instance	object (QuestionAnsweringQualityInstance) Required. Question answering quality instance.

QuestionAnsweringQualitySpec

JSON representation
{ "useReference": boolean, "version": integer }

Fields
useReference	boolean Optional. Whether to use instance.reference to compute question answering quality.
version	integer Optional. Which version to use for evaluation.

QuestionAnsweringQualityInstance

JSON representation

{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _reference can be only one of the following: "reference": string // End of list of possible types for union field _reference. // Union field _context can be only one of the following: "context": string // End of list of possible types for union field _context. // Union field _instruction can be only one of the following: "instruction": string // End of list of possible types for union field _instruction. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.
Union field _reference. _reference can be only one of the following:
reference	string Optional. Ground truth used to compare against the prediction.
Union field _context. _context can be only one of the following:
context	string Required. Text to answer the question.
Union field _instruction. _instruction can be only one of the following:
instruction	string Required. Question Answering prompt for LLM.

PairwiseQuestionAnsweringQualityInput

JSON representation
{ "metricSpec": { object (PairwiseQuestionAnsweringQualitySpec) }, "instance": { object (PairwiseQuestionAnsweringQualityInstance) } }

Fields
metricSpec	object (PairwiseQuestionAnsweringQualitySpec) Required. Spec for pairwise question answering quality score metric.
instance	object (PairwiseQuestionAnsweringQualityInstance) Required. Pairwise question answering quality instance.

PairwiseQuestionAnsweringQualitySpec

JSON representation
{ "useReference": boolean, "version": integer }

Fields
useReference	boolean Optional. Whether to use instance.reference to compute question answering quality.
version	integer Optional. Which version to use for evaluation.

PairwiseQuestionAnsweringQualityInstance

JSON representation

{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _baseline_prediction can be only one of the following: "baselinePrediction": string // End of list of possible types for union field _baseline_prediction. // Union field _reference can be only one of the following: "reference": string // End of list of possible types for union field _reference. // Union field _context can be only one of the following: "context": string // End of list of possible types for union field _context. // Union field _instruction can be only one of the following: "instruction": string // End of list of possible types for union field _instruction. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the candidate model.
Union field _baseline_prediction. _baseline_prediction can be only one of the following:
baselinePrediction	string Required. Output of the baseline model.
Union field _reference. _reference can be only one of the following:
reference	string Optional. Ground truth used to compare against the prediction.
Union field _context. _context can be only one of the following:
context	string Required. Text to answer the question.
Union field _instruction. _instruction can be only one of the following:
instruction	string Required. Question Answering prompt for LLM.

QuestionAnsweringRelevanceInput

JSON representation
{ "metricSpec": { object (QuestionAnsweringRelevanceSpec) }, "instance": { object (QuestionAnsweringRelevanceInstance) } }

Fields
metricSpec	object (QuestionAnsweringRelevanceSpec) Required. Spec for question answering relevance score metric.
instance	object (QuestionAnsweringRelevanceInstance) Required. Question answering relevance instance.

QuestionAnsweringRelevanceSpec

JSON representation
{ "useReference": boolean, "version": integer }

Fields
useReference	boolean Optional. Whether to use instance.reference to compute question answering relevance.
version	integer Optional. Which version to use for evaluation.

QuestionAnsweringRelevanceInstance

JSON representation

{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _reference can be only one of the following: "reference": string // End of list of possible types for union field _reference. // Union field _context can be only one of the following: "context": string // End of list of possible types for union field _context. // Union field _instruction can be only one of the following: "instruction": string // End of list of possible types for union field _instruction. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.
Union field _reference. _reference can be only one of the following:
reference	string Optional. Ground truth used to compare against the prediction.
Union field _context. _context can be only one of the following:
context	string Optional. Text provided as context to answer the question.
Union field _instruction. _instruction can be only one of the following:
instruction	string Required. The question asked and other instruction in the inference prompt.

QuestionAnsweringHelpfulnessInput

JSON representation
{ "metricSpec": { object (QuestionAnsweringHelpfulnessSpec) }, "instance": { object (QuestionAnsweringHelpfulnessInstance) } }

Fields
metricSpec	object (QuestionAnsweringHelpfulnessSpec) Required. Spec for question answering helpfulness score metric.
instance	object (QuestionAnsweringHelpfulnessInstance) Required. Question answering helpfulness instance.

QuestionAnsweringHelpfulnessSpec

JSON representation
{ "useReference": boolean, "version": integer }

Fields
useReference	boolean Optional. Whether to use instance.reference to compute question answering helpfulness.
version	integer Optional. Which version to use for evaluation.

QuestionAnsweringHelpfulnessInstance

JSON representation

{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _reference can be only one of the following: "reference": string // End of list of possible types for union field _reference. // Union field _context can be only one of the following: "context": string // End of list of possible types for union field _context. // Union field _instruction can be only one of the following: "instruction": string // End of list of possible types for union field _instruction. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.
Union field _reference. _reference can be only one of the following:
reference	string Optional. Ground truth used to compare against the prediction.
Union field _context. _context can be only one of the following:
context	string Optional. Text provided as context to answer the question.
Union field _instruction. _instruction can be only one of the following:
instruction	string Required. The question asked and other instruction in the inference prompt.

QuestionAnsweringCorrectnessInput

JSON representation
{ "metricSpec": { object (QuestionAnsweringCorrectnessSpec) }, "instance": { object (QuestionAnsweringCorrectnessInstance) } }

Fields
metricSpec	object (QuestionAnsweringCorrectnessSpec) Required. Spec for question answering correctness score metric.
instance	object (QuestionAnsweringCorrectnessInstance) Required. Question answering correctness instance.

QuestionAnsweringCorrectnessSpec

JSON representation
{ "useReference": boolean, "version": integer }

Fields
useReference	boolean Optional. Whether to use instance.reference to compute question answering correctness.
version	integer Optional. Which version to use for evaluation.

QuestionAnsweringCorrectnessInstance

JSON representation

{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _reference can be only one of the following: "reference": string // End of list of possible types for union field _reference. // Union field _context can be only one of the following: "context": string // End of list of possible types for union field _context. // Union field _instruction can be only one of the following: "instruction": string // End of list of possible types for union field _instruction. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.
Union field _reference. _reference can be only one of the following:
reference	string Optional. Ground truth used to compare against the prediction.
Union field _context. _context can be only one of the following:
context	string Optional. Text provided as context to answer the question.
Union field _instruction. _instruction can be only one of the following:
instruction	string Required. The question asked and other instruction in the inference prompt.

PointwiseMetricInput

JSON representation
{ "metricSpec": { object (PointwiseMetricSpec) }, "instance": { object (PointwiseMetricInstance) } }

Fields
metricSpec	object (PointwiseMetricSpec) Required. Spec for pointwise metric.
instance	object (PointwiseMetricInstance) Required. Pointwise metric instance.

PointwiseMetricSpec

JSON representation

{ "customOutputFormatConfig": { object (CustomOutputFormatConfig) }, // Union field _metric_prompt_template can be only one of the following: "metricPromptTemplate": string // End of list of possible types for union field _metric_prompt_template. // Union field _system_instruction can be only one of the following: "systemInstruction": string // End of list of possible types for union field _system_instruction. }

Fields
customOutputFormatConfig	object (CustomOutputFormatConfig) Optional. CustomOutputFormatConfig allows customization of metric output. By default, metrics return a score and explanation. When this config is set, the default output is replaced with either: - The raw output string. - A parsed output based on a user-defined schema. If a custom format is chosen, the score and explanation fields in the corresponding metric result will be empty.
Union field _metric_prompt_template. _metric_prompt_template can be only one of the following:
metricPromptTemplate	string Required. Metric prompt template for pointwise metric.
Union field _system_instruction. _system_instruction can be only one of the following:
systemInstruction	string Optional. System instructions for pointwise metric.

CustomOutputFormatConfig

JSON representation
{ // Union field custom_output_format_config can be only one of the following: "returnRawOutput": boolean // End of list of possible types for union field custom_output_format_config. }

Fields
Union field custom_output_format_config. Custom output format configuration. custom_output_format_config can be only one of the following:
returnRawOutput	boolean Optional. Whether to return raw output.

PointwiseMetricInstance

JSON representation
{ // Union field instance can be only one of the following: "jsonInstance": string, "contentMapInstance": { object (ContentMap) } // End of list of possible types for union field instance. }

Fields
Union field instance. Instance for pointwise metric. instance can be only one of the following:
jsonInstance	string Instance specified as a json string. String key-value pairs are expected in the json_instance to render PointwiseMetricSpec.instance_prompt_template.
contentMapInstance	object (ContentMap) Key-value contents for the mutlimodality input, including text, image, video, audio, and pdf, etc. The key is placeholder in metric prompt template, and the value is the multimodal content.

ContentMap

JSON representation
{ "values": { string: { object (Contents) }, ... } }

Fields
values	map (key: string, value: object (Contents)) Optional. Map of placeholder to contents. An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.

ValuesEntry

JSON representation
{ "key": string, "value": { object (Contents) } }

Fields
key	string
value	object (Contents)

Contents

JSON representation
{ "contents": [ { object (Content) } ] }

Fields
contents[]	object (Content) Optional. Repeated contents.

Content

JSON representation
{ "role": string, "parts": [ { object (Part) } ] }

Fields
role	string Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
parts[]	object (Part) Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.

Part

JSON representation

{ "thought": boolean, "thoughtSignature": string, "mediaResolution": { object (MediaResolution) }, // Union field data can be only one of the following: "text": string, "inlineData": { object (Blob) }, "fileData": { object (FileData) }, "functionCall": { object (FunctionCall) }, "functionResponse": { object (FunctionResponse) }, "executableCode": { object (ExecutableCode) }, "codeExecutionResult": { object (CodeExecutionResult) } // End of list of possible types for union field data. // Union field metadata can be only one of the following: "videoMetadata": { object (VideoMetadata) } // End of list of possible types for union field metadata. }

Fields
thought	boolean Optional. Indicates whether the part represents the model's thought process or reasoning.
thoughtSignature	string (bytes format) Optional. An opaque signature for the thought so it can be reused in subsequent requests. A base64-encoded string.
mediaResolution	object (MediaResolution) per part media resolution. Media resolution for the input media.
Union field data. data can be only one of the following:
text	string Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example @my-repo will be converted to and sent as **my-repo** by the IDE agent.
inlineData	object (Blob) Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
fileData	object (FileData) Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
functionCall	object (FunctionCall) Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
functionResponse	object (FunctionResponse) Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
executableCode	object (ExecutableCode) Optional. Code generated by the model that is intended to be executed.
codeExecutionResult	object (CodeExecutionResult) Optional. The result of executing the ExecutableCode.
Union field metadata. metadata can be only one of the following:
videoMetadata	object (VideoMetadata) Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.

Blob

JSON representation
{ "mimeType": string, "data": string, "displayName": string }

Fields
mimeType	string Required. The IANA standard MIME type of the source data.
data	string (bytes format) Required. The raw bytes of the data. A base64-encoded string.
displayName	string Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is used in the Gemini calls only when server-side tools (code_execution, google_search, and url_context) are enabled.

FileData

JSON representation
{ "mimeType": string, "fileUri": string, "displayName": string }

Fields
mimeType	string Required. The IANA standard MIME type of the source data.
fileUri	string Required. The URI of the file in Google Cloud Storage.
displayName	string Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in PromptMessage for prompt management. It is used in the Gemini calls only when server side tools (code_execution, google_search, and url_context) are enabled.

FunctionCall

JSON representation
{ "id": string, "name": string, "args": { object }, "partialArgs": [ { object (PartialArg) } ], "willContinue": boolean }

Fields
id	string Optional. The unique id of the function call. If populated, the client to execute the function_call and return the response with the matching id.
name	string Optional. The name of the function to call. Matches FunctionDeclaration.name.
args	object (Struct format) Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details.
partialArgs[]	object (PartialArg) Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
willContinue	boolean Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.

Struct

JSON representation
{ "fields": { string: value, ... } }

Fields
fields	map (key: string, value: value (Value format)) Unordered map of dynamically typed values. An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.

FieldsEntry

JSON representation
{ "key": string, "value": value }

Fields
key	string
value	value (Value format)

Value

JSON representation
{ // Union field kind can be only one of the following: "nullValue": null, "numberValue": number, "stringValue": string, "boolValue": boolean, "structValue": { object }, "listValue": array // End of list of possible types for union field kind. }

Fields
Union field kind. The kind of value. kind can be only one of the following:
nullValue	null Represents a JSON null.
numberValue	number Represents a JSON number. Must not be NaN, Infinity or -Infinity, since those are not supported in JSON. This also cannot represent large Int64 values, since JSON format generally does not support them in its number type.
stringValue	string Represents a JSON string.
boolValue	boolean Represents a JSON boolean (true or false literal in JSON).
structValue	object (Struct format) Represents a JSON object.
listValue	array (ListValue format) Represents a JSON array.

ListValue

JSON representation
{ "values": [ value ] }

Fields
values[]	value (Value format) Repeated field of dynamically typed values.

PartialArg

JSON representation
{ "jsonPath": string, "willContinue": boolean, // Union field delta can be only one of the following: "nullValue": null, "numberValue": number, "stringValue": string, "boolValue": boolean // End of list of possible types for union field delta. }

Fields
jsonPath	string Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
willContinue	boolean Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
Union field delta. The delta of field value being streamed. delta can be only one of the following:
nullValue	null Optional. Represents a null value.
numberValue	number Optional. Represents a double value.
stringValue	string Optional. Represents a string value.
boolValue	boolean Optional. Represents a boolean value.

FunctionResponse

JSON representation
{ "id": string, "name": string, "response": { object }, "parts": [ { object (FunctionResponsePart) } ] }

Fields
id	string Optional. The id of the function call this response is for. Populated by the client to match the corresponding function call id.
name	string Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.
response	object (Struct format) Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
parts[]	object (FunctionResponsePart) Optional. Ordered Parts that constitute a function response. Parts may have different IANA MIME types.

FunctionResponsePart

JSON representation
{ // Union field data can be only one of the following: "inlineData": { object (FunctionResponseBlob) }, "fileData": { object (FunctionResponseFileData) } // End of list of possible types for union field data. }

Fields
Union field data. The data of the function response part. data can be only one of the following:
inlineData	object (FunctionResponseBlob) Inline media bytes.
fileData	object (FunctionResponseFileData) URI based data.

FunctionResponseBlob

JSON representation
{ "mimeType": string, "data": string, "displayName": string }

Fields
mimeType	string Required. The IANA standard MIME type of the source data.
data	string (bytes format) Required. Raw bytes. A base64-encoded string.
displayName	string Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.

FunctionResponseFileData

JSON representation
{ "mimeType": string, "fileUri": string, "displayName": string }

Fields
mimeType	string Required. The IANA standard MIME type of the source data.
fileUri	string Required. URI.
displayName	string Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.

ExecutableCode

JSON representation
{ "language": enum (Language), "code": string }

Fields
language	enum (Language) Required. Programming language of the code.
code	string Required. The code to be executed.

CodeExecutionResult

JSON representation
{ "outcome": enum (Outcome), "output": string }

Fields
outcome	enum (Outcome) Required. Outcome of the code execution.
output	string Optional. Contains stdout when code execution is successful, stderr or other description otherwise.

VideoMetadata

JSON representation
{ "startOffset": string, "endOffset": string, "fps": number }

Fields
startOffset	string (Duration format) Optional. The start offset of the video. A duration in seconds with up to nine fractional digits, ending with 's'. Example: "3.5s".
endOffset	string (Duration format) Optional. The end offset of the video. A duration in seconds with up to nine fractional digits, ending with 's'. Example: "3.5s".
fps	number Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].

Duration

JSON representation
{ "seconds": string, "nanos": integer }

Fields
seconds	string (int64 format) Signed seconds of the span of time. Must be from -315,576,000,000 to +315,576,000,000 inclusive. Note: these bounds are computed from: 60 sec/min * 60 min/hr * 24 hr/day * 365.25 days/year * 10000 years
nanos	integer Signed fractions of a second at nanosecond resolution of the span of time. Durations less than one second are represented with a 0 seconds field and a positive or negative nanos field. For durations of one second or more, a non-zero value for the nanos field must be of the same sign as the seconds field. Must be from -999,999,999 to +999,999,999 inclusive.

MediaResolution

JSON representation
{ // Union field value can be only one of the following: "level": enum (Level) // End of list of possible types for union field value. }

Fields
Union field value. value can be only one of the following:
level	enum (Level) The tokenization quality used for given media.

PairwiseMetricInput

JSON representation
{ "metricSpec": { object (PairwiseMetricSpec) }, "instance": { object (PairwiseMetricInstance) } }

Fields
metricSpec	object (PairwiseMetricSpec) Required. Spec for pairwise metric.
instance	object (PairwiseMetricInstance) Required. Pairwise metric instance.

PairwiseMetricSpec

JSON representation

{ "candidateResponseFieldName": string, "baselineResponseFieldName": string, "customOutputFormatConfig": { object (CustomOutputFormatConfig) }, // Union field _metric_prompt_template can be only one of the following: "metricPromptTemplate": string // End of list of possible types for union field _metric_prompt_template. // Union field _system_instruction can be only one of the following: "systemInstruction": string // End of list of possible types for union field _system_instruction. }

Fields
candidateResponseFieldName	string Optional. The field name of the candidate response.
baselineResponseFieldName	string Optional. The field name of the baseline response.
customOutputFormatConfig	object (CustomOutputFormatConfig) Optional. CustomOutputFormatConfig allows customization of metric output. When this config is set, the default output is replaced with the raw output string. If a custom format is chosen, the pairwise_choice and explanation fields in the corresponding metric result will be empty.
Union field _metric_prompt_template. _metric_prompt_template can be only one of the following:
metricPromptTemplate	string Required. Metric prompt template for pairwise metric.
Union field _system_instruction. _system_instruction can be only one of the following:
systemInstruction	string Optional. System instructions for pairwise metric.

PairwiseMetricInstance

JSON representation
{ // Union field instance can be only one of the following: "jsonInstance": string, "contentMapInstance": { object (ContentMap) } // End of list of possible types for union field instance. }

Fields
Union field instance. Instance for pairwise metric. instance can be only one of the following:
jsonInstance	string Instance specified as a json string. String key-value pairs are expected in the json_instance to render PairwiseMetricSpec.instance_prompt_template.
contentMapInstance	object (ContentMap) Key-value contents for the mutlimodality input, including text, image, video, audio, and pdf, etc. The key is placeholder in metric prompt template, and the value is the multimodal content.

ToolCallValidInput

JSON representation
{ "metricSpec": { object (ToolCallValidSpec) }, "instances": [ { object (ToolCallValidInstance) } ] }

Fields
metricSpec	object (ToolCallValidSpec) Required. Spec for tool call valid metric.
instances[]	object (ToolCallValidInstance) Required. Repeated tool call valid instances.

ToolCallValidInstance

JSON representation
{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _reference can be only one of the following: "reference": string // End of list of possible types for union field _reference. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.
Union field _reference. _reference can be only one of the following:
reference	string Required. Ground truth used to compare against the prediction.

ToolNameMatchInput

JSON representation
{ "metricSpec": { object (ToolNameMatchSpec) }, "instances": [ { object (ToolNameMatchInstance) } ] }

Fields
metricSpec	object (ToolNameMatchSpec) Required. Spec for tool name match metric.
instances[]	object (ToolNameMatchInstance) Required. Repeated tool name match instances.

ToolNameMatchInstance

JSON representation
{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _reference can be only one of the following: "reference": string // End of list of possible types for union field _reference. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.
Union field _reference. _reference can be only one of the following:
reference	string Required. Ground truth used to compare against the prediction.

ToolParameterKeyMatchInput

JSON representation
{ "metricSpec": { object (ToolParameterKeyMatchSpec) }, "instances": [ { object (ToolParameterKeyMatchInstance) } ] }

Fields
metricSpec	object (ToolParameterKeyMatchSpec) Required. Spec for tool parameter key match metric.
instances[]	object (ToolParameterKeyMatchInstance) Required. Repeated tool parameter key match instances.

ToolParameterKeyMatchInstance

JSON representation
{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _reference can be only one of the following: "reference": string // End of list of possible types for union field _reference. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.
Union field _reference. _reference can be only one of the following:
reference	string Required. Ground truth used to compare against the prediction.

ToolParameterKVMatchInput

JSON representation
{ "metricSpec": { object (ToolParameterKVMatchSpec) }, "instances": [ { object (ToolParameterKVMatchInstance) } ] }

Fields
metricSpec	object (ToolParameterKVMatchSpec) Required. Spec for tool parameter key value match metric.
instances[]	object (ToolParameterKVMatchInstance) Required. Repeated tool parameter key value match instances.

ToolParameterKVMatchSpec

JSON representation
{ "useStrictStringMatch": boolean }

Fields
useStrictStringMatch	boolean Optional. Whether to use STRICT string match on parameter values.

ToolParameterKVMatchInstance

JSON representation
{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _reference can be only one of the following: "reference": string // End of list of possible types for union field _reference. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.
Union field _reference. _reference can be only one of the following:
reference	string Required. Ground truth used to compare against the prediction.

CometInput

JSON representation
{ "metricSpec": { object (CometSpec) }, "instance": { object (CometInstance) } }

Fields
metricSpec	object (CometSpec) Required. Spec for comet metric.
instance	object (CometInstance) Required. Comet instance.

CometSpec

JSON representation
{ "sourceLanguage": string, "targetLanguage": string, // Union field _version can be only one of the following: "version": enum (CometVersion) // End of list of possible types for union field _version. }

Fields
sourceLanguage	string Optional. Source language in BCP-47 format.
targetLanguage	string Optional. Target language in BCP-47 format. Covers both prediction and reference.
Union field _version. _version can be only one of the following:
version	enum (CometVersion) Required. Which version to use for evaluation.

CometInstance

JSON representation

{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _reference can be only one of the following: "reference": string // End of list of possible types for union field _reference. // Union field _source can be only one of the following: "source": string // End of list of possible types for union field _source. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.
Union field _reference. _reference can be only one of the following:
reference	string Optional. Ground truth used to compare against the prediction.
Union field _source. _source can be only one of the following:
source	string Optional. Source text in original language.

MetricxInput

JSON representation
{ "metricSpec": { object (MetricxSpec) }, "instance": { object (MetricxInstance) } }

Fields
metricSpec	object (MetricxSpec) Required. Spec for Metricx metric.
instance	object (MetricxInstance) Required. Metricx instance.

MetricxSpec

JSON representation
{ "sourceLanguage": string, "targetLanguage": string, // Union field _version can be only one of the following: "version": enum (MetricxVersion) // End of list of possible types for union field _version. }

Fields
sourceLanguage	string Optional. Source language in BCP-47 format.
targetLanguage	string Optional. Target language in BCP-47 format. Covers both prediction and reference.
Union field _version. _version can be only one of the following:
version	enum (MetricxVersion) Required. Which version to use for evaluation.

MetricxInstance

JSON representation

{ // Union field _prediction can be only one of the following: "prediction": string // End of list of possible types for union field _prediction. // Union field _reference can be only one of the following: "reference": string // End of list of possible types for union field _reference. // Union field _source can be only one of the following: "source": string // End of list of possible types for union field _source. }

Fields
Union field _prediction. _prediction can be only one of the following:
prediction	string Required. Output of the evaluated model.
Union field _reference. _reference can be only one of the following:
reference	string Optional. Ground truth used to compare against the prediction.
Union field _source. _source can be only one of the following:
source	string Optional. Source text in original language.

TrajectoryExactMatchInput

JSON representation
{ "metricSpec": { object (TrajectoryExactMatchSpec) }, "instances": [ { object (TrajectoryExactMatchInstance) } ] }

Fields
metricSpec	object (TrajectoryExactMatchSpec) Required. Spec for TrajectoryExactMatch metric.
instances[]	object (TrajectoryExactMatchInstance) Required. Repeated TrajectoryExactMatch instance.

TrajectoryExactMatchInstance

JSON representation
{ // Union field _predicted_trajectory can be only one of the following: "predictedTrajectory": { object (Trajectory) } // End of list of possible types for union field _predicted_trajectory. // Union field _reference_trajectory can be only one of the following: "referenceTrajectory": { object (Trajectory) } // End of list of possible types for union field _reference_trajectory. }

Fields
Union field _predicted_trajectory. _predicted_trajectory can be only one of the following:
predictedTrajectory	object (Trajectory) Required. Spec for predicted tool call trajectory.
Union field _reference_trajectory. _reference_trajectory can be only one of the following:
referenceTrajectory	object (Trajectory) Required. Spec for reference tool call trajectory.

Trajectory

JSON representation
{ "toolCalls": [ { object (ToolCall) } ] }

Fields
toolCalls[]	object (ToolCall) Required. Tool calls in the trajectory.

ToolCall

JSON representation
{ // Union field _tool_name can be only one of the following: "toolName": string // End of list of possible types for union field _tool_name. // Union field _tool_input can be only one of the following: "toolInput": string // End of list of possible types for union field _tool_input. }

Fields
Union field _tool_name. _tool_name can be only one of the following:
toolName	string Required. Spec for tool name
Union field _tool_input. _tool_input can be only one of the following:
toolInput	string Optional. Spec for tool input

TrajectoryInOrderMatchInput

JSON representation
{ "metricSpec": { object (TrajectoryInOrderMatchSpec) }, "instances": [ { object (TrajectoryInOrderMatchInstance) } ] }

Fields
metricSpec	object (TrajectoryInOrderMatchSpec) Required. Spec for TrajectoryInOrderMatch metric.
instances[]	object (TrajectoryInOrderMatchInstance) Required. Repeated TrajectoryInOrderMatch instance.

TrajectoryInOrderMatchInstance

JSON representation
{ // Union field _predicted_trajectory can be only one of the following: "predictedTrajectory": { object (Trajectory) } // End of list of possible types for union field _predicted_trajectory. // Union field _reference_trajectory can be only one of the following: "referenceTrajectory": { object (Trajectory) } // End of list of possible types for union field _reference_trajectory. }

Fields
Union field _predicted_trajectory. _predicted_trajectory can be only one of the following:
predictedTrajectory	object (Trajectory) Required. Spec for predicted tool call trajectory.
Union field _reference_trajectory. _reference_trajectory can be only one of the following:
referenceTrajectory	object (Trajectory) Required. Spec for reference tool call trajectory.

TrajectoryAnyOrderMatchInput

JSON representation
{ "metricSpec": { object (TrajectoryAnyOrderMatchSpec) }, "instances": [ { object (TrajectoryAnyOrderMatchInstance) } ] }

Fields
metricSpec	object (TrajectoryAnyOrderMatchSpec) Required. Spec for TrajectoryAnyOrderMatch metric.
instances[]	object (TrajectoryAnyOrderMatchInstance) Required. Repeated TrajectoryAnyOrderMatch instance.

TrajectoryAnyOrderMatchInstance

JSON representation
{ // Union field _predicted_trajectory can be only one of the following: "predictedTrajectory": { object (Trajectory) } // End of list of possible types for union field _predicted_trajectory. // Union field _reference_trajectory can be only one of the following: "referenceTrajectory": { object (Trajectory) } // End of list of possible types for union field _reference_trajectory. }

Fields
Union field _predicted_trajectory. _predicted_trajectory can be only one of the following:
predictedTrajectory	object (Trajectory) Required. Spec for predicted tool call trajectory.
Union field _reference_trajectory. _reference_trajectory can be only one of the following:
referenceTrajectory	object (Trajectory) Required. Spec for reference tool call trajectory.

TrajectoryPrecisionInput

JSON representation
{ "metricSpec": { object (TrajectoryPrecisionSpec) }, "instances": [ { object (TrajectoryPrecisionInstance) } ] }

Fields
metricSpec	object (TrajectoryPrecisionSpec) Required. Spec for TrajectoryPrecision metric.
instances[]	object (TrajectoryPrecisionInstance) Required. Repeated TrajectoryPrecision instance.

TrajectoryPrecisionInstance

JSON representation
{ // Union field _predicted_trajectory can be only one of the following: "predictedTrajectory": { object (Trajectory) } // End of list of possible types for union field _predicted_trajectory. // Union field _reference_trajectory can be only one of the following: "referenceTrajectory": { object (Trajectory) } // End of list of possible types for union field _reference_trajectory. }

Fields
Union field _predicted_trajectory. _predicted_trajectory can be only one of the following:
predictedTrajectory	object (Trajectory) Required. Spec for predicted tool call trajectory.
Union field _reference_trajectory. _reference_trajectory can be only one of the following:
referenceTrajectory	object (Trajectory) Required. Spec for reference tool call trajectory.

TrajectoryRecallInput

JSON representation
{ "metricSpec": { object (TrajectoryRecallSpec) }, "instances": [ { object (TrajectoryRecallInstance) } ] }

Fields
metricSpec	object (TrajectoryRecallSpec) Required. Spec for TrajectoryRecall metric.
instances[]	object (TrajectoryRecallInstance) Required. Repeated TrajectoryRecall instance.

TrajectoryRecallInstance

JSON representation
{ // Union field _predicted_trajectory can be only one of the following: "predictedTrajectory": { object (Trajectory) } // End of list of possible types for union field _predicted_trajectory. // Union field _reference_trajectory can be only one of the following: "referenceTrajectory": { object (Trajectory) } // End of list of possible types for union field _reference_trajectory. }

Fields
Union field _predicted_trajectory. _predicted_trajectory can be only one of the following:
predictedTrajectory	object (Trajectory) Required. Spec for predicted tool call trajectory.
Union field _reference_trajectory. _reference_trajectory can be only one of the following:
referenceTrajectory	object (Trajectory) Required. Spec for reference tool call trajectory.

TrajectorySingleToolUseInput

JSON representation
{ "metricSpec": { object (TrajectorySingleToolUseSpec) }, "instances": [ { object (TrajectorySingleToolUseInstance) } ] }

Fields
metricSpec	object (TrajectorySingleToolUseSpec) Required. Spec for TrajectorySingleToolUse metric.
instances[]	object (TrajectorySingleToolUseInstance) Required. Repeated TrajectorySingleToolUse instance.

TrajectorySingleToolUseSpec

JSON representation
{ // Union field _tool_name can be only one of the following: "toolName": string // End of list of possible types for union field _tool_name. }

Fields
Union field _tool_name. _tool_name can be only one of the following:
toolName	string Required. Spec for tool name to be checked for in the predicted trajectory.

TrajectorySingleToolUseInstance

JSON representation
{ // Union field _predicted_trajectory can be only one of the following: "predictedTrajectory": { object (Trajectory) } // End of list of possible types for union field _predicted_trajectory. }

Fields
Union field _predicted_trajectory. _predicted_trajectory can be only one of the following:
predictedTrajectory	object (Trajectory) Required. Spec for predicted tool call trajectory.

RubricBasedInstructionFollowingInput

JSON representation
{ "metricSpec": { object (RubricBasedInstructionFollowingSpec) }, "instance": { object (RubricBasedInstructionFollowingInstance) } }

Fields
metricSpec	object (RubricBasedInstructionFollowingSpec) Required. Spec for RubricBasedInstructionFollowing metric.
instance	object (RubricBasedInstructionFollowingInstance) Required. Instance for RubricBasedInstructionFollowing metric.

RubricBasedInstructionFollowingInstance

JSON representation
{ // Union field instance can be only one of the following: "jsonInstance": string // End of list of possible types for union field instance. }

Fields
Union field instance. Instance for RubricBasedInstructionFollowing metric. instance can be only one of the following:
jsonInstance	string Required. Instance specified as a json string. String key-value pairs are expected in the json_instance to render RubricBasedInstructionFollowing prompt templates.

AutoraterConfig

JSON representation
{ "autoraterModel": string, "generationConfig": { object (GenerationConfig) }, // Union field _sampling_count can be only one of the following: "samplingCount": integer // End of list of possible types for union field _sampling_count. // Union field _flip_enabled can be only one of the following: "flipEnabled": boolean // End of list of possible types for union field _flip_enabled. }

Fields
autoraterModel	string Optional. The fully qualified name of the publisher model or tuned autorater endpoint to use. Publisher model format: projects/{project}/locations/{location}/publishers/*/models/* Tuned model endpoint format: projects/{project}/locations/{location}/endpoints/{endpoint}
generationConfig	object (GenerationConfig) Optional. Configuration options for model generation and outputs.
Union field _sampling_count. _sampling_count can be only one of the following:
samplingCount	integer Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.
Union field _flip_enabled. _flip_enabled can be only one of the following:
flipEnabled	boolean Optional. Default is true. Whether to flip the candidate and baseline responses. This is only applicable to the pairwise metric. If enabled, also provide PairwiseMetricSpec.candidate_response_field_name and PairwiseMetricSpec.baseline_response_field_name. When rendering PairwiseMetricSpec.metric_prompt_template, the candidate and baseline fields will be flipped for half of the samples to reduce bias.

GenerationConfig

JSON representation

{ "stopSequences": [ string ], "responseMimeType": string, "responseModalities": [ enum (Modality) ], "thinkingConfig": { object (ThinkingConfig) }, "modelConfig": { object (ModelConfig) }, // Union field _temperature can be only one of the following: "temperature": number // End of list of possible types for union field _temperature. // Union field _top_p can be only one of the following: "topP": number // End of list of possible types for union field _top_p. // Union field _top_k can be only one of the following: "topK": number // End of list of possible types for union field _top_k. // Union field _candidate_count can be only one of the following: "candidateCount": integer // End of list of possible types for union field _candidate_count. // Union field _max_output_tokens can be only one of the following: "maxOutputTokens": integer // End of list of possible types for union field _max_output_tokens. // Union field _response_logprobs can be only one of the following: "responseLogprobs": boolean // End of list of possible types for union field _response_logprobs. // Union field _logprobs can be only one of the following: "logprobs": integer // End of list of possible types for union field _logprobs. // Union field _presence_penalty can be only one of the following: "presencePenalty": number // End of list of possible types for union field _presence_penalty. // Union field _frequency_penalty can be only one of the following: "frequencyPenalty": number // End of list of possible types for union field _frequency_penalty. // Union field _seed can be only one of the following: "seed": integer // End of list of possible types for union field _seed. // Union field _response_schema can be only one of the following: "responseSchema": { object (Schema) } // End of list of possible types for union field _response_schema. // Union field _response_json_schema can be only one of the following: "responseJsonSchema": value // End of list of possible types for union field _response_json_schema. // Union field _routing_config can be only one of the following: "routingConfig": { object (RoutingConfig) } // End of list of possible types for union field _routing_config. // Union field _audio_timestamp can be only one of the following: "audioTimestamp": boolean // End of list of possible types for union field _audio_timestamp. // Union field _media_resolution can be only one of the following: "mediaResolution": enum (MediaResolution) // End of list of possible types for union field _media_resolution. // Union field _speech_config can be only one of the following: "speechConfig": { object (SpeechConfig) } // End of list of possible types for union field _speech_config. // Union field _enable_affective_dialog can be only one of the following: "enableAffectiveDialog": boolean // End of list of possible types for union field _enable_affective_dialog. // Union field _image_config can be only one of the following: "imageConfig": { object (ImageConfig) } // End of list of possible types for union field _image_config. }

Fields
stopSequences[]	string Optional. A list of character sequences that will stop the model from generating further tokens. If a stop sequence is generated, the output will end at that point. This is useful for controlling the length and structure of the output. For example, you can use ["\n", "###"] to stop generation at a new line or a specific marker.
responseMimeType	string Optional. The IANA standard MIME type of the response. The model will generate output that conforms to this MIME type. Supported values include 'text/plain' (default) and 'application/json'. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined.
responseModalities[]	enum (Modality) Optional. The modalities of the response. The model will generate a response that includes all the specified modalities. For example, if this is set to [TEXT, IMAGE], the response will include both text and an image.
thinkingConfig	object (ThinkingConfig) Optional. Configuration for thinking features. An error will be returned if this field is set for models that don't support thinking.
modelConfig (deprecated)	object (ModelConfig) Optional. The model_config field is deprecated and is not supported anymore. Use routing_config instead. Optional. Config for model selection.
Union field _temperature. _temperature can be only one of the following:
temperature	number Optional. Controls the randomness of the output. A higher temperature results in more creative and diverse responses, while a lower temperature makes the output more predictable and focused. The valid range is (0.0, 2.0].
Union field _top_p. _top_p can be only one of the following:
topP	number Optional. Specifies the nucleus sampling threshold. The model considers only the smallest set of tokens whose cumulative probability is at least top_p. This helps generate more diverse and less repetitive responses. For example, a top_p of 0.9 means the model considers tokens until the cumulative probability of the tokens to select from reaches 0.9. It's recommended to adjust either temperature or top_p, but not both.
Union field _top_k. _top_k can be only one of the following:
topK	number Optional. Specifies the top-k sampling threshold. The model considers only the top k most probable tokens for the next token. This can be useful for generating more coherent and less random text. For example, a top_k of 40 means the model will choose the next word from the 40 most likely words.
Union field _candidate_count. _candidate_count can be only one of the following:
candidateCount	integer Optional. The number of candidate responses to generate. A higher candidate_count can provide more options to choose from, but it also consumes more resources. This can be useful for generating a variety of responses and selecting the best one.
Union field _max_output_tokens. _max_output_tokens can be only one of the following:
maxOutputTokens	integer Optional. The maximum number of tokens to generate in the response. A token is approximately four characters. The default value varies by model. This parameter can be used to control the length of the generated text and prevent overly long responses.
Union field _response_logprobs. _response_logprobs can be only one of the following:
responseLogprobs	boolean Optional. If set to true, the log probabilities of the output tokens are returned. Log probabilities are the logarithm of the probability of a token appearing in the output. A higher log probability means the token is more likely to be generated. This can be useful for analyzing the model's confidence in its own output and for debugging.
Union field _logprobs. _logprobs can be only one of the following:
logprobs	integer Optional. The number of top log probabilities to return for each token. This can be used to see which other tokens were considered likely candidates for a given position. A higher value will return more options, but it will also increase the size of the response.
Union field _presence_penalty. _presence_penalty can be only one of the following:
presencePenalty	number Optional. Penalizes tokens that have already appeared in the generated text. A positive value encourages the model to generate more diverse and less repetitive text. Valid values can range from [-2.0, 2.0].
Union field _frequency_penalty. _frequency_penalty can be only one of the following:
frequencyPenalty	number Optional. Penalizes tokens based on their frequency in the generated text. A positive value helps to reduce the repetition of words and phrases. Valid values can range from [-2.0, 2.0].
Union field _seed. _seed can be only one of the following:
seed	integer Optional. A seed for the random number generator. By setting a seed, you can make the model's output mostly deterministic. For a given prompt and parameters (like temperature, top_p, etc.), the model will produce the same response every time. However, it's not a guaranteed absolute deterministic behavior. This is different from parameters like temperature, which control the level of randomness. seed ensures that the "random" choices the model makes are the same on every run, making it essential for testing and ensuring reproducible results.
Union field _response_schema. _response_schema can be only one of the following:
responseSchema	object (Schema) Optional. Lets you to specify a schema for the model's response, ensuring that the output conforms to a particular structure. This is useful for generating structured data such as JSON. The schema is a subset of the OpenAPI 3.0 schema object object. When this field is set, you must also set the response_mime_type to application/json.
Union field _response_json_schema. _response_json_schema can be only one of the following:
responseJsonSchema	value (Value format) Optional. When this field is set, response_schema must be omitted and response_mime_type must be set to application/json.
Union field _routing_config. _routing_config can be only one of the following:
routingConfig	object (RoutingConfig) Optional. Routing configuration.
Union field _audio_timestamp. _audio_timestamp can be only one of the following:
audioTimestamp	boolean Optional. If enabled, audio timestamps will be included in the request to the model. This can be useful for synchronizing audio with other modalities in the response.
Union field _media_resolution. _media_resolution can be only one of the following:
mediaResolution	enum (MediaResolution) Optional. The token resolution at which input media content is sampled. This is used to control the trade-off between the quality of the response and the number of tokens used to represent the media. A higher resolution allows the model to perceive more detail, which can lead to a more nuanced response, but it will also use more tokens. This does not affect the image dimensions sent to the model.
Union field _speech_config. _speech_config can be only one of the following:
speechConfig	object (SpeechConfig) Optional. The speech generation config.
Union field _enable_affective_dialog. _enable_affective_dialog can be only one of the following:
enableAffectiveDialog	boolean Optional. If enabled, the model will detect emotions and adapt its responses accordingly. For example, if the model detects that the user is frustrated, it may provide a more empathetic response.
Union field _image_config. _image_config can be only one of the following:
imageConfig	object (ImageConfig) Optional. Config for image generation features.

Schema

JSON representation

{ "type": enum (Type), "format": string, "title": string, "description": string, "nullable": boolean, "default": value, "items": { object (Schema) }, "minItems": string, "maxItems": string, "enum": [ string ], "properties": { string: { object (Schema) }, ... }, "propertyOrdering": [ string ], "required": [ string ], "minProperties": string, "maxProperties": string, "minimum": number, "maximum": number, "minLength": string, "maxLength": string, "pattern": string, "example": value, "anyOf": [ { object (Schema) } ], "additionalProperties": value, "ref": string, "defs": { string: { object (Schema) }, ... } }

Fields
type	enum (Type) Optional. Data type of the schema field.
format	string Optional. The format of the data. For NUMBER type, format can be float or double. For INTEGER type, format can be int32 or int64. For STRING type, format can be email, byte, date, date-time, password, and other formats to further refine the data type.
title	string Optional. Title for the schema.
description	string Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
nullable	boolean Optional. Indicates if the value of this field can be null.
default	value (Value format) Optional. Default value to use if the field is not specified.
items	object (Schema) Optional. If type is ARRAY, items specifies the schema of elements in the array.
minItems	string (int64 format) Optional. If type is ARRAY, min_items specifies the minimum number of items in an array.
maxItems	string (int64 format) Optional. If type is ARRAY, max_items specifies the maximum number of items in an array.
enum[]	string Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set format to enum and provide the list of possible values in enum. For example: 1. To define directions: {type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]} 2. To define apartment numbers: {type:INTEGER, format:enum, enum:["101", "201", "301"]}
properties	map (key: string, value: object (Schema)) Optional. If type is OBJECT, properties is a map of property names to schema definitions for each property of the object. An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.
propertyOrdering[]	string Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
required[]	string Optional. If type is OBJECT, required lists the names of properties that must be present.
minProperties	string (int64 format) Optional. If type is OBJECT, min_properties specifies the minimum number of properties that can be provided.
maxProperties	string (int64 format) Optional. If type is OBJECT, max_properties specifies the maximum number of properties that can be provided.
minimum	number Optional. If type is INTEGER or NUMBER, minimum specifies the minimum allowed value.
maximum	number Optional. If type is INTEGER or NUMBER, maximum specifies the maximum allowed value.
minLength	string (int64 format) Optional. If type is STRING, min_length specifies the minimum length of the string.
maxLength	string (int64 format) Optional. If type is STRING, max_length specifies the maximum length of the string.
pattern	string Optional. If type is STRING, pattern specifies a regular expression that the string must match.
example	value (Value format) Optional. Example of an instance of this schema.
anyOf[]	object (Schema) Optional. The instance must be valid against any (one or more) of the subschemas listed in any_of.
additionalProperties	value (Value format) Optional. If type is OBJECT, specifies how to handle properties not defined in properties. If it is a boolean false, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
ref	string Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in defs. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
defs	map (key: string, value: object (Schema)) Optional. defs provides a map of schema definitions that can be reused by ref elsewhere in the schema. Only allowed at root level of the schema. An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.

PropertiesEntry

JSON representation
{ "key": string, "value": { object (Schema) } }

Fields
key	string
value	object (Schema)

DefsEntry

JSON representation
{ "key": string, "value": { object (Schema) } }

Fields
key	string
value	object (Schema)

RoutingConfig

JSON representation
{ // Union field routing_config can be only one of the following: "autoMode": { object (AutoRoutingMode) }, "manualMode": { object (ManualRoutingMode) } // End of list of possible types for union field routing_config. }

Fields
Union field routing_config. The routing mode for the request. routing_config can be only one of the following:
autoMode	object (AutoRoutingMode) In this mode, the model is selected automatically based on the content of the request.
manualMode	object (ManualRoutingMode) In this mode, the model is specified manually.

AutoRoutingMode

JSON representation
{ // Union field _model_routing_preference can be only one of the following: "modelRoutingPreference": enum (ModelRoutingPreference) // End of list of possible types for union field _model_routing_preference. }

Fields
Union field _model_routing_preference. _model_routing_preference can be only one of the following:
modelRoutingPreference	enum (ModelRoutingPreference) The model routing preference.

ManualRoutingMode

JSON representation
{ // Union field _model_name can be only one of the following: "modelName": string // End of list of possible types for union field _model_name. }

Fields
Union field _model_name. _model_name can be only one of the following:
modelName	string The name of the model to use. Only public LLM models are accepted.

SpeechConfig

JSON representation
{ "voiceConfig": { object (VoiceConfig) }, "languageCode": string, "multiSpeakerVoiceConfig": { object (MultiSpeakerVoiceConfig) } }

Fields
voiceConfig	object (VoiceConfig) The configuration for the voice to use.
languageCode	string Optional. The language code (ISO 639-1) for the speech synthesis.
multiSpeakerVoiceConfig	object (MultiSpeakerVoiceConfig) The configuration for a multi-speaker text-to-speech request. This field is mutually exclusive with voice_config.

VoiceConfig

JSON representation
{ // Union field voice_config can be only one of the following: "prebuiltVoiceConfig": { object (PrebuiltVoiceConfig) }, "replicatedVoiceConfig": { object (ReplicatedVoiceConfig) } // End of list of possible types for union field voice_config. }

Fields
Union field voice_config. The configuration for the speaker to use. voice_config can be only one of the following:
prebuiltVoiceConfig	object (PrebuiltVoiceConfig) The configuration for a prebuilt voice.
replicatedVoiceConfig	object (ReplicatedVoiceConfig) Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.

PrebuiltVoiceConfig

JSON representation
{ // Union field _voice_name can be only one of the following: "voiceName": string // End of list of possible types for union field _voice_name. }

Fields
Union field _voice_name. _voice_name can be only one of the following:
voiceName	string The name of the prebuilt voice to use.

ReplicatedVoiceConfig

JSON representation
{ "mimeType": string, "voiceSampleAudio": string }

Fields
mimeType	string Optional. The mimetype of the voice sample. The only currently supported value is audio/wav. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. mime_type will default to audio/wav if not set.
voiceSampleAudio	string (bytes format) Optional. The sample of the custom voice. A base64-encoded string.

MultiSpeakerVoiceConfig

JSON representation
{ "speakerVoiceConfigs": [ { object (SpeakerVoiceConfig) } ] }

Fields
speakerVoiceConfigs[]	object (SpeakerVoiceConfig) Required. A list of configurations for the voices of the speakers. Exactly two speaker voice configurations must be provided.

SpeakerVoiceConfig

JSON representation
{ "speaker": string, "voiceConfig": { object (VoiceConfig) } }

Fields
speaker	string Required. The name of the speaker. This should be the same as the speaker name used in the prompt.
voiceConfig	object (VoiceConfig) Required. The configuration for the voice of this speaker.

ThinkingConfig

JSON representation

{ // Union field _include_thoughts can be only one of the following: "includeThoughts": boolean // End of list of possible types for union field _include_thoughts. // Union field _thinking_budget can be only one of the following: "thinkingBudget": integer // End of list of possible types for union field _thinking_budget. // Union field _thinking_level can be only one of the following: "thinkingLevel": enum (ThinkingLevel) // End of list of possible types for union field _thinking_level. }

Fields
Union field _include_thoughts. _include_thoughts can be only one of the following:
includeThoughts	boolean Optional. If true, the model will include its thoughts in the response. "Thoughts" are the intermediate steps the model takes to arrive at the final response. They can provide insights into the model's reasoning process and help with debugging. If this is true, thoughts are returned only when available.
Union field _thinking_budget. _thinking_budget can be only one of the following:
thinkingBudget	integer Optional. The token budget for the model's thinking process. The model will make a best effort to stay within this budget. This can be used to control the trade-off between response quality and latency.
Union field _thinking_level. _thinking_level can be only one of the following:
thinkingLevel	enum (ThinkingLevel) Optional. The number of thoughts tokens that the model should generate.

ModelConfig

JSON representation
{ "featureSelectionPreference": enum (FeatureSelectionPreference) }

Fields
featureSelectionPreference	enum (FeatureSelectionPreference) Required. Feature selection preference.

ImageConfig

JSON representation

{ // Union field _image_output_options can be only one of the following: "imageOutputOptions": { object (ImageOutputOptions) } // End of list of possible types for union field _image_output_options. // Union field _aspect_ratio can be only one of the following: "aspectRatio": string // End of list of possible types for union field _aspect_ratio. // Union field _person_generation can be only one of the following: "personGeneration": enum (PersonGeneration) // End of list of possible types for union field _person_generation. // Union field _image_size can be only one of the following: "imageSize": string // End of list of possible types for union field _image_size. }

Fields
Union field _image_output_options. _image_output_options can be only one of the following:
imageOutputOptions	object (ImageOutputOptions) Optional. The image output format for generated images.
Union field _aspect_ratio. _aspect_ratio can be only one of the following:
aspectRatio	string Optional. The desired aspect ratio for the generated images. The following aspect ratios are supported: "1:1" "2:3", "3:2" "3:4", "4:3" "4:5", "5:4" "9:16", "16:9" "21:9"
Union field _person_generation. _person_generation can be only one of the following:
personGeneration	enum (PersonGeneration) Optional. Controls whether the model can generate people.
Union field _image_size. _image_size can be only one of the following:
imageSize	string Optional. Specifies the size of generated images. Supported values are 1K, 2K, 4K. If not specified, the model will use default value 1K.

ImageOutputOptions

JSON representation
{ // Union field _mime_type can be only one of the following: "mimeType": string // End of list of possible types for union field _mime_type. // Union field _compression_quality can be only one of the following: "compressionQuality": integer // End of list of possible types for union field _compression_quality. }

Fields
Union field _mime_type. _mime_type can be only one of the following:
mimeType	string Optional. The image format that the output should be saved as.
Union field _compression_quality. _compression_quality can be only one of the following:
compressionQuality	integer Optional. The compression quality of the output image.

Output Schema

Response message for EvaluationService.EvaluateInstances.

EvaluateInstancesResponse

JSON representation

{ // Union field evaluation_results can be only one of the following: "exactMatchResults": { object (ExactMatchResults) }, "bleuResults": { object (BleuResults) }, "rougeResults": { object (RougeResults) }, "fluencyResult": { object (FluencyResult) }, "coherenceResult": { object (CoherenceResult) }, "safetyResult": { object (SafetyResult) }, "groundednessResult": { object (GroundednessResult) }, "fulfillmentResult": { object (FulfillmentResult) }, "summarizationQualityResult": { object (SummarizationQualityResult) }, "pairwiseSummarizationQualityResult": { object (PairwiseSummarizationQualityResult) }, "summarizationHelpfulnessResult": { object (SummarizationHelpfulnessResult) }, "summarizationVerbosityResult": { object (SummarizationVerbosityResult) }, "questionAnsweringQualityResult": { object (QuestionAnsweringQualityResult) }, "pairwiseQuestionAnsweringQualityResult": { object (PairwiseQuestionAnsweringQualityResult) }, "questionAnsweringRelevanceResult": { object (QuestionAnsweringRelevanceResult) }, "questionAnsweringHelpfulnessResult": { object (QuestionAnsweringHelpfulnessResult) }, "questionAnsweringCorrectnessResult": { object (QuestionAnsweringCorrectnessResult) }, "pointwiseMetricResult": { object (PointwiseMetricResult) }, "pairwiseMetricResult": { object (PairwiseMetricResult) }, "toolCallValidResults": { object (ToolCallValidResults) }, "toolNameMatchResults": { object (ToolNameMatchResults) }, "toolParameterKeyMatchResults": { object (ToolParameterKeyMatchResults) }, "toolParameterKvMatchResults": { object (ToolParameterKVMatchResults) }, "cometResult": { object (CometResult) }, "metricxResult": { object (MetricxResult) }, "trajectoryExactMatchResults": { object (TrajectoryExactMatchResults) }, "trajectoryInOrderMatchResults": { object (TrajectoryInOrderMatchResults) }, "trajectoryAnyOrderMatchResults": { object (TrajectoryAnyOrderMatchResults) }, "trajectoryPrecisionResults": { object (TrajectoryPrecisionResults) }, "trajectoryRecallResults": { object (TrajectoryRecallResults) }, "trajectorySingleToolUseResults": { object (TrajectorySingleToolUseResults) }, "rubricBasedInstructionFollowingResult": { object (RubricBasedInstructionFollowingResult) } // End of list of possible types for union field evaluation_results. }

Fields
Union field evaluation_results. Evaluation results will be served in the same order as presented in EvaluationRequest.instances. evaluation_results can be only one of the following:
exactMatchResults	object (ExactMatchResults) Auto metric evaluation results. Results for exact match metric.
bleuResults	object (BleuResults) Results for bleu metric.
rougeResults	object (RougeResults) Results for rouge metric.
fluencyResult	object (FluencyResult) LLM-based metric evaluation result. General text generation metrics, applicable to other categories. Result for fluency metric.
coherenceResult	object (CoherenceResult) Result for coherence metric.
safetyResult	object (SafetyResult) Result for safety metric.
groundednessResult	object (GroundednessResult) Result for groundedness metric.
fulfillmentResult	object (FulfillmentResult) Result for fulfillment metric.
summarizationQualityResult	object (SummarizationQualityResult) Summarization only metrics. Result for summarization quality metric.
pairwiseSummarizationQualityResult	object (PairwiseSummarizationQualityResult) Result for pairwise summarization quality metric.
summarizationHelpfulnessResult	object (SummarizationHelpfulnessResult) Result for summarization helpfulness metric.
summarizationVerbosityResult	object (SummarizationVerbosityResult) Result for summarization verbosity metric.
questionAnsweringQualityResult	object (QuestionAnsweringQualityResult) Question answering only metrics. Result for question answering quality metric.
pairwiseQuestionAnsweringQualityResult	object (PairwiseQuestionAnsweringQualityResult) Result for pairwise question answering quality metric.
questionAnsweringRelevanceResult	object (QuestionAnsweringRelevanceResult) Result for question answering relevance metric.
questionAnsweringHelpfulnessResult	object (QuestionAnsweringHelpfulnessResult) Result for question answering helpfulness metric.
questionAnsweringCorrectnessResult	object (QuestionAnsweringCorrectnessResult) Result for question answering correctness metric.
pointwiseMetricResult	object (PointwiseMetricResult) Generic metrics. Result for pointwise metric.
pairwiseMetricResult	object (PairwiseMetricResult) Result for pairwise metric.
toolCallValidResults	object (ToolCallValidResults) Tool call metrics. Results for tool call valid metric.
toolNameMatchResults	object (ToolNameMatchResults) Results for tool name match metric.
toolParameterKeyMatchResults	object (ToolParameterKeyMatchResults) Results for tool parameter key match metric.
toolParameterKvMatchResults	object (ToolParameterKVMatchResults) Results for tool parameter key value match metric.
cometResult	object (CometResult) Translation metrics. Result for Comet metric.
metricxResult	object (MetricxResult) Result for Metricx metric.
trajectoryExactMatchResults	object (TrajectoryExactMatchResults) Result for trajectory exact match metric.
trajectoryInOrderMatchResults	object (TrajectoryInOrderMatchResults) Result for trajectory in order match metric.
trajectoryAnyOrderMatchResults	object (TrajectoryAnyOrderMatchResults) Result for trajectory any order match metric.
trajectoryPrecisionResults	object (TrajectoryPrecisionResults) Result for trajectory precision metric.
trajectoryRecallResults	object (TrajectoryRecallResults) Results for trajectory recall metric.
trajectorySingleToolUseResults	object (TrajectorySingleToolUseResults) Results for trajectory single tool use metric.
rubricBasedInstructionFollowingResult	object (RubricBasedInstructionFollowingResult) Result for rubric based instruction following metric.

ExactMatchResults

JSON representation
{ "exactMatchMetricValues": [ { object (ExactMatchMetricValue) } ] }

Fields
exactMatchMetricValues[]	object (ExactMatchMetricValue) Output only. Exact match metric values.

ExactMatchMetricValue

JSON representation
{ // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. }

Fields
Union field _score. _score can be only one of the following:
score	number Output only. Exact match score.

BleuResults

JSON representation
{ "bleuMetricValues": [ { object (BleuMetricValue) } ] }

Fields
bleuMetricValues[]	object (BleuMetricValue) Output only. Bleu metric values.

BleuMetricValue

JSON representation
{ // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. }

Fields
Union field _score. _score can be only one of the following:
score	number Output only. Bleu score.

RougeResults

JSON representation
{ "rougeMetricValues": [ { object (RougeMetricValue) } ] }

Fields
rougeMetricValues[]	object (RougeMetricValue) Output only. Rouge metric values.

RougeMetricValue

JSON representation
{ // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. }

Fields
Union field _score. _score can be only one of the following:
score	number Output only. Rouge score.

FluencyResult

JSON representation
{ "explanation": string, // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. // Union field _confidence can be only one of the following: "confidence": number // End of list of possible types for union field _confidence. }

Fields
explanation	string Output only. Explanation for fluency score.
Union field _score. _score can be only one of the following:
score	number Output only. Fluency score.
Union field _confidence. _confidence can be only one of the following:
confidence	number Output only. Confidence for fluency score.

CoherenceResult

JSON representation
{ "explanation": string, // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. // Union field _confidence can be only one of the following: "confidence": number // End of list of possible types for union field _confidence. }

Fields
explanation	string Output only. Explanation for coherence score.
Union field _score. _score can be only one of the following:
score	number Output only. Coherence score.
Union field _confidence. _confidence can be only one of the following:
confidence	number Output only. Confidence for coherence score.

SafetyResult

JSON representation
{ "explanation": string, // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. // Union field _confidence can be only one of the following: "confidence": number // End of list of possible types for union field _confidence. }

Fields
explanation	string Output only. Explanation for safety score.
Union field _score. _score can be only one of the following:
score	number Output only. Safety score.
Union field _confidence. _confidence can be only one of the following:
confidence	number Output only. Confidence for safety score.

GroundednessResult

JSON representation
{ "explanation": string, // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. // Union field _confidence can be only one of the following: "confidence": number // End of list of possible types for union field _confidence. }

Fields
explanation	string Output only. Explanation for groundedness score.
Union field _score. _score can be only one of the following:
score	number Output only. Groundedness score.
Union field _confidence. _confidence can be only one of the following:
confidence	number Output only. Confidence for groundedness score.

FulfillmentResult

JSON representation
{ "explanation": string, // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. // Union field _confidence can be only one of the following: "confidence": number // End of list of possible types for union field _confidence. }

Fields
explanation	string Output only. Explanation for fulfillment score.
Union field _score. _score can be only one of the following:
score	number Output only. Fulfillment score.
Union field _confidence. _confidence can be only one of the following:
confidence	number Output only. Confidence for fulfillment score.

SummarizationQualityResult

JSON representation
{ "explanation": string, // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. // Union field _confidence can be only one of the following: "confidence": number // End of list of possible types for union field _confidence. }

Fields
explanation	string Output only. Explanation for summarization quality score.
Union field _score. _score can be only one of the following:
score	number Output only. Summarization Quality score.
Union field _confidence. _confidence can be only one of the following:
confidence	number Output only. Confidence for summarization quality score.

PairwiseSummarizationQualityResult

JSON representation
{ "pairwiseChoice": enum (PairwiseChoice), "explanation": string, // Union field _confidence can be only one of the following: "confidence": number // End of list of possible types for union field _confidence. }

Fields
pairwiseChoice	enum (PairwiseChoice) Output only. Pairwise summarization prediction choice.
explanation	string Output only. Explanation for summarization quality score.
Union field _confidence. _confidence can be only one of the following:
confidence	number Output only. Confidence for summarization quality score.

SummarizationHelpfulnessResult

JSON representation
{ "explanation": string, // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. // Union field _confidence can be only one of the following: "confidence": number // End of list of possible types for union field _confidence. }

Fields
explanation	string Output only. Explanation for summarization helpfulness score.
Union field _score. _score can be only one of the following:
score	number Output only. Summarization Helpfulness score.
Union field _confidence. _confidence can be only one of the following:
confidence	number Output only. Confidence for summarization helpfulness score.

SummarizationVerbosityResult

JSON representation
{ "explanation": string, // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. // Union field _confidence can be only one of the following: "confidence": number // End of list of possible types for union field _confidence. }

Fields
explanation	string Output only. Explanation for summarization verbosity score.
Union field _score. _score can be only one of the following:
score	number Output only. Summarization Verbosity score.
Union field _confidence. _confidence can be only one of the following:
confidence	number Output only. Confidence for summarization verbosity score.

QuestionAnsweringQualityResult

JSON representation
{ "explanation": string, // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. // Union field _confidence can be only one of the following: "confidence": number // End of list of possible types for union field _confidence. }

Fields
explanation	string Output only. Explanation for question answering quality score.
Union field _score. _score can be only one of the following:
score	number Output only. Question Answering Quality score.
Union field _confidence. _confidence can be only one of the following:
confidence	number Output only. Confidence for question answering quality score.

PairwiseQuestionAnsweringQualityResult

JSON representation
{ "pairwiseChoice": enum (PairwiseChoice), "explanation": string, // Union field _confidence can be only one of the following: "confidence": number // End of list of possible types for union field _confidence. }

Fields
pairwiseChoice	enum (PairwiseChoice) Output only. Pairwise question answering prediction choice.
explanation	string Output only. Explanation for question answering quality score.
Union field _confidence. _confidence can be only one of the following:
confidence	number Output only. Confidence for question answering quality score.

QuestionAnsweringRelevanceResult

JSON representation
{ "explanation": string, // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. // Union field _confidence can be only one of the following: "confidence": number // End of list of possible types for union field _confidence. }

Fields
explanation	string Output only. Explanation for question answering relevance score.
Union field _score. _score can be only one of the following:
score	number Output only. Question Answering Relevance score.
Union field _confidence. _confidence can be only one of the following:
confidence	number Output only. Confidence for question answering relevance score.

QuestionAnsweringHelpfulnessResult

JSON representation
{ "explanation": string, // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. // Union field _confidence can be only one of the following: "confidence": number // End of list of possible types for union field _confidence. }

Fields
explanation	string Output only. Explanation for question answering helpfulness score.
Union field _score. _score can be only one of the following:
score	number Output only. Question Answering Helpfulness score.
Union field _confidence. _confidence can be only one of the following:
confidence	number Output only. Confidence for question answering helpfulness score.

QuestionAnsweringCorrectnessResult

JSON representation
{ "explanation": string, // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. // Union field _confidence can be only one of the following: "confidence": number // End of list of possible types for union field _confidence. }

Fields
explanation	string Output only. Explanation for question answering correctness score.
Union field _score. _score can be only one of the following:
score	number Output only. Question Answering Correctness score.
Union field _confidence. _confidence can be only one of the following:
confidence	number Output only. Confidence for question answering correctness score.

PointwiseMetricResult

JSON representation
{ "explanation": string, "customOutput": { object (CustomOutput) }, // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. }

Fields
explanation	string Output only. Explanation for pointwise metric score.
customOutput	object (CustomOutput) Output only. Spec for custom output.
Union field _score. _score can be only one of the following:
score	number Output only. Pointwise metric score.

CustomOutput

JSON representation
{ // Union field custom_output can be only one of the following: "rawOutputs": { object (RawOutput) } // End of list of possible types for union field custom_output. }

Fields
Union field custom_output. Custom output. custom_output can be only one of the following:
rawOutputs	object (RawOutput) Output only. List of raw output strings.

RawOutput

JSON representation
{ "rawOutput": [ string ] }

Fields
rawOutput[]	string Output only. Raw output string.

PairwiseMetricResult

JSON representation
{ "pairwiseChoice": enum (PairwiseChoice), "explanation": string, "customOutput": { object (CustomOutput) } }

Fields
pairwiseChoice	enum (PairwiseChoice) Output only. Pairwise metric choice.
explanation	string Output only. Explanation for pairwise metric score.
customOutput	object (CustomOutput) Output only. Spec for custom output.

ToolCallValidResults

JSON representation
{ "toolCallValidMetricValues": [ { object (ToolCallValidMetricValue) } ] }

Fields
toolCallValidMetricValues[]	object (ToolCallValidMetricValue) Output only. Tool call valid metric values.

ToolCallValidMetricValue

JSON representation
{ // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. }

Fields
Union field _score. _score can be only one of the following:
score	number Output only. Tool call valid score.

ToolNameMatchResults

JSON representation
{ "toolNameMatchMetricValues": [ { object (ToolNameMatchMetricValue) } ] }

Fields
toolNameMatchMetricValues[]	object (ToolNameMatchMetricValue) Output only. Tool name match metric values.

ToolNameMatchMetricValue

JSON representation
{ // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. }

Fields
Union field _score. _score can be only one of the following:
score	number Output only. Tool name match score.

ToolParameterKeyMatchResults

JSON representation
{ "toolParameterKeyMatchMetricValues": [ { object (ToolParameterKeyMatchMetricValue) } ] }

Fields
toolParameterKeyMatchMetricValues[]	object (ToolParameterKeyMatchMetricValue) Output only. Tool parameter key match metric values.

ToolParameterKeyMatchMetricValue

JSON representation
{ // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. }

Fields
Union field _score. _score can be only one of the following:
score	number Output only. Tool parameter key match score.

ToolParameterKVMatchResults

JSON representation
{ "toolParameterKvMatchMetricValues": [ { object (ToolParameterKVMatchMetricValue) } ] }

Fields
toolParameterKvMatchMetricValues[]	object (ToolParameterKVMatchMetricValue) Output only. Tool parameter key value match metric values.

ToolParameterKVMatchMetricValue

JSON representation
{ // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. }

Fields
Union field _score. _score can be only one of the following:
score	number Output only. Tool parameter key value match score.

CometResult

JSON representation
{ // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. }

Fields
Union field _score. _score can be only one of the following:
score	number Output only. Comet score. Range depends on version.

MetricxResult

JSON representation
{ // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. }

Fields
Union field _score. _score can be only one of the following:
score	number Output only. MetricX score. Range depends on version.

TrajectoryExactMatchResults

JSON representation
{ "trajectoryExactMatchMetricValues": [ { object (TrajectoryExactMatchMetricValue) } ] }

Fields
trajectoryExactMatchMetricValues[]	object (TrajectoryExactMatchMetricValue) Output only. TrajectoryExactMatch metric values.

TrajectoryExactMatchMetricValue

JSON representation
{ // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. }

Fields
Union field _score. _score can be only one of the following:
score	number Output only. TrajectoryExactMatch score.

TrajectoryInOrderMatchResults

JSON representation
{ "trajectoryInOrderMatchMetricValues": [ { object (TrajectoryInOrderMatchMetricValue) } ] }

Fields
trajectoryInOrderMatchMetricValues[]	object (TrajectoryInOrderMatchMetricValue) Output only. TrajectoryInOrderMatch metric values.

TrajectoryInOrderMatchMetricValue

JSON representation
{ // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. }

Fields
Union field _score. _score can be only one of the following:
score	number Output only. TrajectoryInOrderMatch score.

TrajectoryAnyOrderMatchResults

JSON representation
{ "trajectoryAnyOrderMatchMetricValues": [ { object (TrajectoryAnyOrderMatchMetricValue) } ] }

Fields
trajectoryAnyOrderMatchMetricValues[]	object (TrajectoryAnyOrderMatchMetricValue) Output only. TrajectoryAnyOrderMatch metric values.

TrajectoryAnyOrderMatchMetricValue

JSON representation
{ // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. }

Fields
Union field _score. _score can be only one of the following:
score	number Output only. TrajectoryAnyOrderMatch score.

TrajectoryPrecisionResults

JSON representation
{ "trajectoryPrecisionMetricValues": [ { object (TrajectoryPrecisionMetricValue) } ] }

Fields
trajectoryPrecisionMetricValues[]	object (TrajectoryPrecisionMetricValue) Output only. TrajectoryPrecision metric values.

TrajectoryPrecisionMetricValue

JSON representation
{ // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. }

Fields
Union field _score. _score can be only one of the following:
score	number Output only. TrajectoryPrecision score.

TrajectoryRecallResults

JSON representation
{ "trajectoryRecallMetricValues": [ { object (TrajectoryRecallMetricValue) } ] }

Fields
trajectoryRecallMetricValues[]	object (TrajectoryRecallMetricValue) Output only. TrajectoryRecall metric values.

TrajectoryRecallMetricValue

JSON representation
{ // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. }

Fields
Union field _score. _score can be only one of the following:
score	number Output only. TrajectoryRecall score.

TrajectorySingleToolUseResults

JSON representation
{ "trajectorySingleToolUseMetricValues": [ { object (TrajectorySingleToolUseMetricValue) } ] }

Fields
trajectorySingleToolUseMetricValues[]	object (TrajectorySingleToolUseMetricValue) Output only. TrajectorySingleToolUse metric values.

TrajectorySingleToolUseMetricValue

JSON representation
{ // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. }

Fields
Union field _score. _score can be only one of the following:
score	number Output only. TrajectorySingleToolUse score.

RubricBasedInstructionFollowingResult

JSON representation
{ "rubricCritiqueResults": [ { object (RubricCritiqueResult) } ], // Union field _score can be only one of the following: "score": number // End of list of possible types for union field _score. }

Fields
rubricCritiqueResults[]	object (RubricCritiqueResult) Output only. List of per rubric critique results.
Union field _score. _score can be only one of the following:
score	number Output only. Overall score for the instruction following.

RubricCritiqueResult

JSON representation
{ "rubric": string, "verdict": boolean }

Fields
rubric	string Output only. Rubric to be evaluated.
verdict	boolean Output only. Verdict for the rubric - true if the rubric is met, false otherwise.

Tool Annotations

Destructive Hint: ❌ | Idempotent Hint: ❌ | Read Only Hint: ❌ | Open World Hint: ❌