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Viewing docs for AWS v7.41.0
published on Friday, Aug 7, 2026 by Pulumi
Schema (JSON)
pulumi/pulumi-aws

aws.bedrock.EvaluationJob

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Viewing docs for AWS v7.41.0
published on Friday, Aug 7, 2026 by Pulumi
Schema (JSON)
pulumi/pulumi-aws

    Manages an Amazon Bedrock evaluation job. An evaluation job assesses model or knowledge base performance using either automated metrics or human workers.

    Amazon Bedrock does not support permanently deleting an evaluation job. Destroying this resource stops the job (if it is still running) using the StopEvaluationJob API, then removes it from Terraform state. Set skipDestroy to leave the job in its current state instead.

    Example Usage

    Automated Model Evaluation

    import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";

const example = new aws.bedrock.EvaluationJob("example", {
    jobName: "example-job",
    roleArn: exampleAwsIamRole.arn,
    evaluationConfig: {
        automated: {
            datasetMetricConfigs: [{
                taskType: "Generation",
                dataset: {
                    name: "Builtin.Bold",
                },
                metricNames: ["Builtin.Robustness"],
            }],
        },
    },
    inferenceConfig: {
        models: [{
            bedrockModel: {
                modelIdentifier: "amazon.nova-micro-v1:0",
            },
        }],
    },
    outputDataConfig: {
        s3Uri: `s3://${exampleAwsS3Bucket.id}/output/`,
    },
});

    import pulumi
import pulumi_aws as aws

example = aws.bedrock.EvaluationJob("example",
    job_name="example-job",
    role_arn=example_aws_iam_role["arn"],
    evaluation_config={
        "automated": {
            "dataset_metric_configs": [{
                "task_type": "Generation",
                "dataset": {
                    "name": "Builtin.Bold",
                },
                "metric_names": ["Builtin.Robustness"],
            }],
        },
    },
    inference_config={
        "models": [{
            "bedrock_model": {
                "model_identifier": "amazon.nova-micro-v1:0",
            },
        }],
    },
    output_data_config={
        "s3_uri": f"s3://{example_aws_s3_bucket['id']}/output/",
    })

    package main

import (
	"github.com/pulumi/pulumi-aws/sdk/v7/go/aws/bedrock"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := bedrock.NewEvaluationJob(ctx, "example", &bedrock.EvaluationJobArgs{
			JobName: pulumi.String("example-job"),
			RoleArn: pulumi.Any(exampleAwsIamRole.Arn),
			EvaluationConfig: &bedrock.EvaluationJobEvaluationConfigArgs{
				Automated: &bedrock.EvaluationJobEvaluationConfigAutomatedArgs{
					DatasetMetricConfigs: bedrock.EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigArray{
						&bedrock.EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigArgs{
							TaskType: pulumi.String("Generation"),
							Dataset: &bedrock.EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDatasetArgs{
								Name: pulumi.String("Builtin.Bold"),
							},
							MetricNames: pulumi.StringArray{
								pulumi.String("Builtin.Robustness"),
							},
						},
					},
				},
			},
			InferenceConfig: &bedrock.EvaluationJobInferenceConfigArgs{
				Models: bedrock.EvaluationJobInferenceConfigModelArray{
					&bedrock.EvaluationJobInferenceConfigModelArgs{
						BedrockModel: &bedrock.EvaluationJobInferenceConfigModelBedrockModelArgs{
							ModelIdentifier: pulumi.String("amazon.nova-micro-v1:0"),
						},
					},
				},
			},
			OutputDataConfig: &bedrock.EvaluationJobOutputDataConfigArgs{
				S3Uri: pulumi.Sprintf("s3://%v/output/", exampleAwsS3Bucket.Id),
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

    using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Aws = Pulumi.Aws;

return await Deployment.RunAsync(() => 
{
    var example = new Aws.Bedrock.EvaluationJob("example", new()
    {
        JobName = "example-job",
        RoleArn = exampleAwsIamRole.Arn,
        EvaluationConfig = new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigArgs
        {
            Automated = new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigAutomatedArgs
            {
                DatasetMetricConfigs = new[]
                {
                    new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigArgs
                    {
                        TaskType = "Generation",
                        Dataset = new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDatasetArgs
                        {
                            Name = "Builtin.Bold",
                        },
                        MetricNames = new[]
                        {
                            "Builtin.Robustness",
                        },
                    },
                },
            },
        },
        InferenceConfig = new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigArgs
        {
            Models = new[]
            {
                new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigModelArgs
                {
                    BedrockModel = new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigModelBedrockModelArgs
                    {
                        ModelIdentifier = "amazon.nova-micro-v1:0",
                    },
                },
            },
        },
        OutputDataConfig = new Aws.Bedrock.Inputs.EvaluationJobOutputDataConfigArgs
        {
            S3Uri = $"s3://{exampleAwsS3Bucket.Id}/output/",
        },
    });

});

    package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.aws.bedrock.EvaluationJob;
import com.pulumi.aws.bedrock.EvaluationJobArgs;
import com.pulumi.aws.bedrock.inputs.EvaluationJobEvaluationConfigArgs;
import com.pulumi.aws.bedrock.inputs.EvaluationJobEvaluationConfigAutomatedArgs;
import com.pulumi.aws.bedrock.inputs.EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigArgs;
import com.pulumi.aws.bedrock.inputs.EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDatasetArgs;
import com.pulumi.aws.bedrock.inputs.EvaluationJobInferenceConfigArgs;
import com.pulumi.aws.bedrock.inputs.EvaluationJobInferenceConfigModelArgs;
import com.pulumi.aws.bedrock.inputs.EvaluationJobInferenceConfigModelBedrockModelArgs;
import com.pulumi.aws.bedrock.inputs.EvaluationJobOutputDataConfigArgs;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var example = new EvaluationJob("example", EvaluationJobArgs.builder()
            .jobName("example-job")
            .roleArn(exampleAwsIamRole.arn())
            .evaluationConfig(EvaluationJobEvaluationConfigArgs.builder()
                .automated(EvaluationJobEvaluationConfigAutomatedArgs.builder()
                    .datasetMetricConfigs(EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigArgs.builder()
                        .taskType("Generation")
                        .dataset(EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDatasetArgs.builder()
                            .name("Builtin.Bold")
                            .build())
                        .metricNames("Builtin.Robustness")
                        .build())
                    .build())
                .build())
            .inferenceConfig(EvaluationJobInferenceConfigArgs.builder()
                .models(EvaluationJobInferenceConfigModelArgs.builder()
                    .bedrockModel(EvaluationJobInferenceConfigModelBedrockModelArgs.builder()
                        .modelIdentifier("amazon.nova-micro-v1:0")
                        .build())
                    .build())
                .build())
            .outputDataConfig(EvaluationJobOutputDataConfigArgs.builder()
                .s3Uri(String.format("s3://%s/output/", exampleAwsS3Bucket.id()))
                .build())
            .build());

    }
}

    resources:
  example:
    type: aws:bedrock:EvaluationJob
    properties:
      jobName: example-job
      roleArn: ${exampleAwsIamRole.arn}
      evaluationConfig:
        automated:
          datasetMetricConfigs:
            - taskType: Generation
              dataset:
                name: Builtin.Bold
              metricNames:
                - Builtin.Robustness
      inferenceConfig:
        models:
          - bedrockModel:
              modelIdentifier: amazon.nova-micro-v1:0
      outputDataConfig:
        s3Uri: s3://${exampleAwsS3Bucket.id}/output/

    pulumi {
  required_providers {
    aws = {
      source = "pulumi/aws"
    }
  }
}

resource "aws_bedrock_evaluationjob" "example" {
  job_name = "example-job"
  role_arn = exampleAwsIamRole.arn
  evaluation_config = {
    automated = {
      dataset_metric_configs = [{
        "taskType" = "Generation"
        "dataset" = {
          "name" = "Builtin.Bold"
        }
        "metricNames" = ["Builtin.Robustness"]
      }]
    }
  }
  inference_config = {
    models = [{
      "bedrockModel" = {
        "modelIdentifier" = "amazon.nova-micro-v1:0"
      }
    }]
  }
  output_data_config = {
    s3_uri ="s3://${exampleAwsS3Bucket.id}/output/"
  }
}

    Create EvaluationJob Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new EvaluationJob(name: string, args: EvaluationJobArgs, opts?: CustomResourceOptions);
    @overload
def EvaluationJob(resource_name: str,
                  args: EvaluationJobArgs,
                  opts: Optional[ResourceOptions] = None)

@overload
def EvaluationJob(resource_name: str,
                  opts: Optional[ResourceOptions] = None,
                  evaluation_config: Optional[EvaluationJobEvaluationConfigArgs] = None,
                  inference_config: Optional[EvaluationJobInferenceConfigArgs] = None,
                  job_name: Optional[str] = None,
                  output_data_config: Optional[EvaluationJobOutputDataConfigArgs] = None,
                  role_arn: Optional[str] = None,
                  application_type: Optional[str] = None,
                  customer_encryption_key_id: Optional[str] = None,
                  job_description: Optional[str] = None,
                  region: Optional[str] = None,
                  skip_destroy: Optional[bool] = None,
                  tags: Optional[Mapping[str, str]] = None,
                  timeouts: Optional[EvaluationJobTimeoutsArgs] = None)
    func NewEvaluationJob(ctx *Context, name string, args EvaluationJobArgs, opts ...ResourceOption) (*EvaluationJob, error)
    public EvaluationJob(string name, EvaluationJobArgs args, CustomResourceOptions? opts = null)
    public EvaluationJob(String name, EvaluationJobArgs args)
public EvaluationJob(String name, EvaluationJobArgs args, CustomResourceOptions options)

    type: aws:bedrock:EvaluationJob
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.


    resource "aws_bedrock_evaluation_job" "name" {
    # resource properties
}

    Parameters

    name string
    The unique name of the resource.
    args EvaluationJobArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    resource_name str
    The unique name of the resource.
    args EvaluationJobArgs
    The arguments to resource properties.
    opts ResourceOptions
    Bag of options to control resource's behavior.
    ctx Context
    Context object for the current deployment.
    name string
    The unique name of the resource.
    args EvaluationJobArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args EvaluationJobArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args EvaluationJobArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    Constructor example

    The following reference example uses placeholder values for all input properties.

    var evaluationJobResource = new Aws.Bedrock.EvaluationJob("evaluationJobResource", new()
{
    EvaluationConfig = new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigArgs
    {
        Automated = new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigAutomatedArgs
        {
            DatasetMetricConfigs = new[]
            {
                new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigArgs
                {
                    Dataset = new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDatasetArgs
                    {
                        Name = "string",
                        DatasetLocation = new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDatasetDatasetLocationArgs
                        {
                            S3Uri = "string",
                        },
                    },
                    MetricNames = new[]
                    {
                        "string",
                    },
                    TaskType = "string",
                },
            },
            CustomMetricConfig = new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigAutomatedCustomMetricConfigArgs
            {
                CustomMetrics = new[]
                {
                    new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricArgs
                    {
                        CustomMetricDefinition = new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionArgs
                        {
                            Instructions = "string",
                            Name = "string",
                            RatingScales = new[]
                            {
                                new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScaleArgs
                                {
                                    Definition = "string",
                                    Value = new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScaleValueArgs
                                    {
                                        FloatValue = 0,
                                        StringValue = "string",
                                    },
                                },
                            },
                        },
                    },
                },
                EvaluatorModelConfig = new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigAutomatedCustomMetricConfigEvaluatorModelConfigArgs
                {
                    BedrockEvaluatorModel = new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigAutomatedCustomMetricConfigEvaluatorModelConfigBedrockEvaluatorModelArgs
                    {
                        ModelIdentifier = "string",
                    },
                },
            },
            EvaluatorModelConfig = new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigAutomatedEvaluatorModelConfigArgs
            {
                BedrockEvaluatorModel = new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigAutomatedEvaluatorModelConfigBedrockEvaluatorModelArgs
                {
                    ModelIdentifier = "string",
                },
            },
        },
        Human = new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigHumanArgs
        {
            DatasetMetricConfigs = new[]
            {
                new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigHumanDatasetMetricConfigArgs
                {
                    Dataset = new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigHumanDatasetMetricConfigDatasetArgs
                    {
                        Name = "string",
                        DatasetLocation = new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigHumanDatasetMetricConfigDatasetDatasetLocationArgs
                        {
                            S3Uri = "string",
                        },
                    },
                    MetricNames = new[]
                    {
                        "string",
                    },
                    TaskType = "string",
                },
            },
            CustomMetrics = new[]
            {
                new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigHumanCustomMetricArgs
                {
                    Name = "string",
                    RatingMethod = "string",
                    Description = "string",
                },
            },
            HumanWorkflowConfig = new Aws.Bedrock.Inputs.EvaluationJobEvaluationConfigHumanHumanWorkflowConfigArgs
            {
                FlowDefinitionArn = "string",
                Instructions = "string",
            },
        },
    },
    InferenceConfig = new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigArgs
    {
        Models = new[]
        {
            new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigModelArgs
            {
                BedrockModel = new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigModelBedrockModelArgs
                {
                    ModelIdentifier = "string",
                    InferenceParams = "string",
                    PerformanceConfig = new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigModelBedrockModelPerformanceConfigArgs
                    {
                        Latency = "string",
                    },
                },
                PrecomputedInferenceSource = new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigModelPrecomputedInferenceSourceArgs
                {
                    InferenceSourceIdentifier = "string",
                },
            },
        },
        RagConfig = new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigRagConfigArgs
        {
            KnowledgeBaseConfig = new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigArgs
            {
                RetrieveAndGenerateConfig = new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigArgs
                {
                    KnowledgeBaseId = "string",
                    ModelArn = "string",
                    RetrievalConfiguration = new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigRetrievalConfigurationArgs
                    {
                        VectorSearchConfiguration = new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigRetrievalConfigurationVectorSearchConfigurationArgs
                        {
                            NumberOfResults = 0,
                        },
                    },
                },
                RetrieveConfig = new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigArgs
                {
                    KnowledgeBaseId = "string",
                    KnowledgeBaseRetrievalConfiguration = new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigKnowledgeBaseRetrievalConfigurationArgs
                    {
                        VectorSearchConfiguration = new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigKnowledgeBaseRetrievalConfigurationVectorSearchConfigurationArgs
                        {
                            NumberOfResults = 0,
                        },
                    },
                },
            },
            PrecomputedRagSourceConfig = new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigArgs
            {
                RetrieveAndGenerateSourceConfig = new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveAndGenerateSourceConfigArgs
                {
                    RagSourceIdentifier = "string",
                },
                RetrieveSourceConfig = new Aws.Bedrock.Inputs.EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveSourceConfigArgs
                {
                    RagSourceIdentifier = "string",
                },
            },
        },
    },
    JobName = "string",
    OutputDataConfig = new Aws.Bedrock.Inputs.EvaluationJobOutputDataConfigArgs
    {
        S3Uri = "string",
    },
    RoleArn = "string",
    ApplicationType = "string",
    CustomerEncryptionKeyId = "string",
    JobDescription = "string",
    Region = "string",
    SkipDestroy = false,
    Tags = 
    {
        { "string", "string" },
    },
    Timeouts = new Aws.Bedrock.Inputs.EvaluationJobTimeoutsArgs
    {
        Create = "string",
        Delete = "string",
    },
});

    example, err := bedrock.NewEvaluationJob(ctx, "evaluationJobResource", &bedrock.EvaluationJobArgs{
	EvaluationConfig: &bedrock.EvaluationJobEvaluationConfigArgs{
		Automated: &bedrock.EvaluationJobEvaluationConfigAutomatedArgs{
			DatasetMetricConfigs: bedrock.EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigArray{
				&bedrock.EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigArgs{
					Dataset: &bedrock.EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDatasetArgs{
						Name: pulumi.String("string"),
						DatasetLocation: &bedrock.EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDatasetDatasetLocationArgs{
							S3Uri: pulumi.String("string"),
						},
					},
					MetricNames: pulumi.StringArray{
						pulumi.String("string"),
					},
					TaskType: pulumi.String("string"),
				},
			},
			CustomMetricConfig: &bedrock.EvaluationJobEvaluationConfigAutomatedCustomMetricConfigArgs{
				CustomMetrics: bedrock.EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricArray{
					&bedrock.EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricArgs{
						CustomMetricDefinition: &bedrock.EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionArgs{
							Instructions: pulumi.String("string"),
							Name:         pulumi.String("string"),
							RatingScales: bedrock.EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScaleArray{
								&bedrock.EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScaleArgs{
									Definition: pulumi.String("string"),
									Value: &bedrock.EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScaleValueArgs{
										FloatValue:  pulumi.Float64(0),
										StringValue: pulumi.String("string"),
									},
								},
							},
						},
					},
				},
				EvaluatorModelConfig: &bedrock.EvaluationJobEvaluationConfigAutomatedCustomMetricConfigEvaluatorModelConfigArgs{
					BedrockEvaluatorModel: &bedrock.EvaluationJobEvaluationConfigAutomatedCustomMetricConfigEvaluatorModelConfigBedrockEvaluatorModelArgs{
						ModelIdentifier: pulumi.String("string"),
					},
				},
			},
			EvaluatorModelConfig: &bedrock.EvaluationJobEvaluationConfigAutomatedEvaluatorModelConfigArgs{
				BedrockEvaluatorModel: &bedrock.EvaluationJobEvaluationConfigAutomatedEvaluatorModelConfigBedrockEvaluatorModelArgs{
					ModelIdentifier: pulumi.String("string"),
				},
			},
		},
		Human: &bedrock.EvaluationJobEvaluationConfigHumanArgs{
			DatasetMetricConfigs: bedrock.EvaluationJobEvaluationConfigHumanDatasetMetricConfigArray{
				&bedrock.EvaluationJobEvaluationConfigHumanDatasetMetricConfigArgs{
					Dataset: &bedrock.EvaluationJobEvaluationConfigHumanDatasetMetricConfigDatasetArgs{
						Name: pulumi.String("string"),
						DatasetLocation: &bedrock.EvaluationJobEvaluationConfigHumanDatasetMetricConfigDatasetDatasetLocationArgs{
							S3Uri: pulumi.String("string"),
						},
					},
					MetricNames: pulumi.StringArray{
						pulumi.String("string"),
					},
					TaskType: pulumi.String("string"),
				},
			},
			CustomMetrics: bedrock.EvaluationJobEvaluationConfigHumanCustomMetricArray{
				&bedrock.EvaluationJobEvaluationConfigHumanCustomMetricArgs{
					Name:         pulumi.String("string"),
					RatingMethod: pulumi.String("string"),
					Description:  pulumi.String("string"),
				},
			},
			HumanWorkflowConfig: &bedrock.EvaluationJobEvaluationConfigHumanHumanWorkflowConfigArgs{
				FlowDefinitionArn: pulumi.String("string"),
				Instructions:      pulumi.String("string"),
			},
		},
	},
	InferenceConfig: &bedrock.EvaluationJobInferenceConfigArgs{
		Models: bedrock.EvaluationJobInferenceConfigModelArray{
			&bedrock.EvaluationJobInferenceConfigModelArgs{
				BedrockModel: &bedrock.EvaluationJobInferenceConfigModelBedrockModelArgs{
					ModelIdentifier: pulumi.String("string"),
					InferenceParams: pulumi.String("string"),
					PerformanceConfig: &bedrock.EvaluationJobInferenceConfigModelBedrockModelPerformanceConfigArgs{
						Latency: pulumi.String("string"),
					},
				},
				PrecomputedInferenceSource: &bedrock.EvaluationJobInferenceConfigModelPrecomputedInferenceSourceArgs{
					InferenceSourceIdentifier: pulumi.String("string"),
				},
			},
		},
		RagConfig: &bedrock.EvaluationJobInferenceConfigRagConfigArgs{
			KnowledgeBaseConfig: &bedrock.EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigArgs{
				RetrieveAndGenerateConfig: &bedrock.EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigArgs{
					KnowledgeBaseId: pulumi.String("string"),
					ModelArn:        pulumi.String("string"),
					RetrievalConfiguration: &bedrock.EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigRetrievalConfigurationArgs{
						VectorSearchConfiguration: &bedrock.EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigRetrievalConfigurationVectorSearchConfigurationArgs{
							NumberOfResults: pulumi.Int(0),
						},
					},
				},
				RetrieveConfig: &bedrock.EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigArgs{
					KnowledgeBaseId: pulumi.String("string"),
					KnowledgeBaseRetrievalConfiguration: &bedrock.EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigKnowledgeBaseRetrievalConfigurationArgs{
						VectorSearchConfiguration: &bedrock.EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigKnowledgeBaseRetrievalConfigurationVectorSearchConfigurationArgs{
							NumberOfResults: pulumi.Int(0),
						},
					},
				},
			},
			PrecomputedRagSourceConfig: &bedrock.EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigArgs{
				RetrieveAndGenerateSourceConfig: &bedrock.EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveAndGenerateSourceConfigArgs{
					RagSourceIdentifier: pulumi.String("string"),
				},
				RetrieveSourceConfig: &bedrock.EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveSourceConfigArgs{
					RagSourceIdentifier: pulumi.String("string"),
				},
			},
		},
	},
	JobName: pulumi.String("string"),
	OutputDataConfig: &bedrock.EvaluationJobOutputDataConfigArgs{
		S3Uri: pulumi.String("string"),
	},
	RoleArn:                 pulumi.String("string"),
	ApplicationType:         pulumi.String("string"),
	CustomerEncryptionKeyId: pulumi.String("string"),
	JobDescription:          pulumi.String("string"),
	Region:                  pulumi.String("string"),
	SkipDestroy:             pulumi.Bool(false),
	Tags: pulumi.StringMap{
		"string": pulumi.String("string"),
	},
	Timeouts: &bedrock.EvaluationJobTimeoutsArgs{
		Create: pulumi.String("string"),
		Delete: pulumi.String("string"),
	},
})

    resource "aws_bedrock_evaluation_job" "evaluationJobResource" {
  lifecycle {
    create_before_destroy = true
  }
  evaluation_config = {
    automated = {
      dataset_metric_configs = [{
        dataset = {
          name = "string"
          dataset_location = {
            s3_uri = "string"
          }
        }
        metric_names = ["string"]
        task_type    = "string"
      }]
      custom_metric_config = {
        custom_metrics = [{
          custom_metric_definition = {
            instructions = "string"
            name         = "string"
            rating_scales = [{
              definition = "string"
              value = {
                float_value  = 0
                string_value = "string"
              }
            }]
          }
        }]
        evaluator_model_config = {
          bedrock_evaluator_model = {
            model_identifier = "string"
          }
        }
      }
      evaluator_model_config = {
        bedrock_evaluator_model = {
          model_identifier = "string"
        }
      }
    }
    human = {
      dataset_metric_configs = [{
        dataset = {
          name = "string"
          dataset_location = {
            s3_uri = "string"
          }
        }
        metric_names = ["string"]
        task_type    = "string"
      }]
      custom_metrics = [{
        name          = "string"
        rating_method = "string"
        description   = "string"
      }]
      human_workflow_config = {
        flow_definition_arn = "string"
        instructions        = "string"
      }
    }
  }
  inference_config = {
    models = [{
      bedrock_model = {
        model_identifier = "string"
        inference_params = "string"
        performance_config = {
          latency = "string"
        }
      }
      precomputed_inference_source = {
        inference_source_identifier = "string"
      }
    }]
    rag_config = {
      knowledge_base_config = {
        retrieve_and_generate_config = {
          knowledge_base_id = "string"
          model_arn         = "string"
          retrieval_configuration = {
            vector_search_configuration = {
              number_of_results = 0
            }
          }
        }
        retrieve_config = {
          knowledge_base_id = "string"
          knowledge_base_retrieval_configuration = {
            vector_search_configuration = {
              number_of_results = 0
            }
          }
        }
      }
      precomputed_rag_source_config = {
        retrieve_and_generate_source_config = {
          rag_source_identifier = "string"
        }
        retrieve_source_config = {
          rag_source_identifier = "string"
        }
      }
    }
  }
  job_name = "string"
  output_data_config = {
    s3_uri = "string"
  }
  role_arn                   = "string"
  application_type           = "string"
  customer_encryption_key_id = "string"
  job_description            = "string"
  region                     = "string"
  skip_destroy               = false
  tags = {
    "string" = "string"
  }
  timeouts = {
    create = "string"
    delete = "string"
  }
}

    var evaluationJobResource = new EvaluationJob("evaluationJobResource", EvaluationJobArgs.builder()
    .evaluationConfig(EvaluationJobEvaluationConfigArgs.builder()
        .automated(EvaluationJobEvaluationConfigAutomatedArgs.builder()
            .datasetMetricConfigs(EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigArgs.builder()
                .dataset(EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDatasetArgs.builder()
                    .name("string")
                    .datasetLocation(EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDatasetDatasetLocationArgs.builder()
                        .s3Uri("string")
                        .build())
                    .build())
                .metricNames("string")
                .taskType("string")
                .build())
            .customMetricConfig(EvaluationJobEvaluationConfigAutomatedCustomMetricConfigArgs.builder()
                .customMetrics(EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricArgs.builder()
                    .customMetricDefinition(EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionArgs.builder()
                        .instructions("string")
                        .name("string")
                        .ratingScales(EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScaleArgs.builder()
                            .definition("string")
                            .value(EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScaleValueArgs.builder()
                                .floatValue(0.0)
                                .stringValue("string")
                                .build())
                            .build())
                        .build())
                    .build())
                .evaluatorModelConfig(EvaluationJobEvaluationConfigAutomatedCustomMetricConfigEvaluatorModelConfigArgs.builder()
                    .bedrockEvaluatorModel(EvaluationJobEvaluationConfigAutomatedCustomMetricConfigEvaluatorModelConfigBedrockEvaluatorModelArgs.builder()
                        .modelIdentifier("string")
                        .build())
                    .build())
                .build())
            .evaluatorModelConfig(EvaluationJobEvaluationConfigAutomatedEvaluatorModelConfigArgs.builder()
                .bedrockEvaluatorModel(EvaluationJobEvaluationConfigAutomatedEvaluatorModelConfigBedrockEvaluatorModelArgs.builder()
                    .modelIdentifier("string")
                    .build())
                .build())
            .build())
        .human(EvaluationJobEvaluationConfigHumanArgs.builder()
            .datasetMetricConfigs(EvaluationJobEvaluationConfigHumanDatasetMetricConfigArgs.builder()
                .dataset(EvaluationJobEvaluationConfigHumanDatasetMetricConfigDatasetArgs.builder()
                    .name("string")
                    .datasetLocation(EvaluationJobEvaluationConfigHumanDatasetMetricConfigDatasetDatasetLocationArgs.builder()
                        .s3Uri("string")
                        .build())
                    .build())
                .metricNames("string")
                .taskType("string")
                .build())
            .customMetrics(EvaluationJobEvaluationConfigHumanCustomMetricArgs.builder()
                .name("string")
                .ratingMethod("string")
                .description("string")
                .build())
            .humanWorkflowConfig(EvaluationJobEvaluationConfigHumanHumanWorkflowConfigArgs.builder()
                .flowDefinitionArn("string")
                .instructions("string")
                .build())
            .build())
        .build())
    .inferenceConfig(EvaluationJobInferenceConfigArgs.builder()
        .models(EvaluationJobInferenceConfigModelArgs.builder()
            .bedrockModel(EvaluationJobInferenceConfigModelBedrockModelArgs.builder()
                .modelIdentifier("string")
                .inferenceParams("string")
                .performanceConfig(EvaluationJobInferenceConfigModelBedrockModelPerformanceConfigArgs.builder()
                    .latency("string")
                    .build())
                .build())
            .precomputedInferenceSource(EvaluationJobInferenceConfigModelPrecomputedInferenceSourceArgs.builder()
                .inferenceSourceIdentifier("string")
                .build())
            .build())
        .ragConfig(EvaluationJobInferenceConfigRagConfigArgs.builder()
            .knowledgeBaseConfig(EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigArgs.builder()
                .retrieveAndGenerateConfig(EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigArgs.builder()
                    .knowledgeBaseId("string")
                    .modelArn("string")
                    .retrievalConfiguration(EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigRetrievalConfigurationArgs.builder()
                        .vectorSearchConfiguration(EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigRetrievalConfigurationVectorSearchConfigurationArgs.builder()
                            .numberOfResults(0)
                            .build())
                        .build())
                    .build())
                .retrieveConfig(EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigArgs.builder()
                    .knowledgeBaseId("string")
                    .knowledgeBaseRetrievalConfiguration(EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigKnowledgeBaseRetrievalConfigurationArgs.builder()
                        .vectorSearchConfiguration(EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigKnowledgeBaseRetrievalConfigurationVectorSearchConfigurationArgs.builder()
                            .numberOfResults(0)
                            .build())
                        .build())
                    .build())
                .build())
            .precomputedRagSourceConfig(EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigArgs.builder()
                .retrieveAndGenerateSourceConfig(EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveAndGenerateSourceConfigArgs.builder()
                    .ragSourceIdentifier("string")
                    .build())
                .retrieveSourceConfig(EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveSourceConfigArgs.builder()
                    .ragSourceIdentifier("string")
                    .build())
                .build())
            .build())
        .build())
    .jobName("string")
    .outputDataConfig(EvaluationJobOutputDataConfigArgs.builder()
        .s3Uri("string")
        .build())
    .roleArn("string")
    .applicationType("string")
    .customerEncryptionKeyId("string")
    .jobDescription("string")
    .region("string")
    .skipDestroy(false)
    .tags(Map.of("string", "string"))
    .timeouts(EvaluationJobTimeoutsArgs.builder()
        .create("string")
        .delete("string")
        .build())
    .build());

    evaluation_job_resource = aws.bedrock.EvaluationJob("evaluationJobResource",
    evaluation_config={
        "automated": {
            "dataset_metric_configs": [{
                "dataset": {
                    "name": "string",
                    "dataset_location": {
                        "s3_uri": "string",
                    },
                },
                "metric_names": ["string"],
                "task_type": "string",
            }],
            "custom_metric_config": {
                "custom_metrics": [{
                    "custom_metric_definition": {
                        "instructions": "string",
                        "name": "string",
                        "rating_scales": [{
                            "definition": "string",
                            "value": {
                                "float_value": float(0),
                                "string_value": "string",
                            },
                        }],
                    },
                }],
                "evaluator_model_config": {
                    "bedrock_evaluator_model": {
                        "model_identifier": "string",
                    },
                },
            },
            "evaluator_model_config": {
                "bedrock_evaluator_model": {
                    "model_identifier": "string",
                },
            },
        },
        "human": {
            "dataset_metric_configs": [{
                "dataset": {
                    "name": "string",
                    "dataset_location": {
                        "s3_uri": "string",
                    },
                },
                "metric_names": ["string"],
                "task_type": "string",
            }],
            "custom_metrics": [{
                "name": "string",
                "rating_method": "string",
                "description": "string",
            }],
            "human_workflow_config": {
                "flow_definition_arn": "string",
                "instructions": "string",
            },
        },
    },
    inference_config={
        "models": [{
            "bedrock_model": {
                "model_identifier": "string",
                "inference_params": "string",
                "performance_config": {
                    "latency": "string",
                },
            },
            "precomputed_inference_source": {
                "inference_source_identifier": "string",
            },
        }],
        "rag_config": {
            "knowledge_base_config": {
                "retrieve_and_generate_config": {
                    "knowledge_base_id": "string",
                    "model_arn": "string",
                    "retrieval_configuration": {
                        "vector_search_configuration": {
                            "number_of_results": 0,
                        },
                    },
                },
                "retrieve_config": {
                    "knowledge_base_id": "string",
                    "knowledge_base_retrieval_configuration": {
                        "vector_search_configuration": {
                            "number_of_results": 0,
                        },
                    },
                },
            },
            "precomputed_rag_source_config": {
                "retrieve_and_generate_source_config": {
                    "rag_source_identifier": "string",
                },
                "retrieve_source_config": {
                    "rag_source_identifier": "string",
                },
            },
        },
    },
    job_name="string",
    output_data_config={
        "s3_uri": "string",
    },
    role_arn="string",
    application_type="string",
    customer_encryption_key_id="string",
    job_description="string",
    region="string",
    skip_destroy=False,
    tags={
        "string": "string",
    },
    timeouts={
        "create": "string",
        "delete": "string",
    })

    const evaluationJobResource = new aws.bedrock.EvaluationJob("evaluationJobResource", {
    evaluationConfig: {
        automated: {
            datasetMetricConfigs: [{
                dataset: {
                    name: "string",
                    datasetLocation: {
                        s3Uri: "string",
                    },
                },
                metricNames: ["string"],
                taskType: "string",
            }],
            customMetricConfig: {
                customMetrics: [{
                    customMetricDefinition: {
                        instructions: "string",
                        name: "string",
                        ratingScales: [{
                            definition: "string",
                            value: {
                                floatValue: 0,
                                stringValue: "string",
                            },
                        }],
                    },
                }],
                evaluatorModelConfig: {
                    bedrockEvaluatorModel: {
                        modelIdentifier: "string",
                    },
                },
            },
            evaluatorModelConfig: {
                bedrockEvaluatorModel: {
                    modelIdentifier: "string",
                },
            },
        },
        human: {
            datasetMetricConfigs: [{
                dataset: {
                    name: "string",
                    datasetLocation: {
                        s3Uri: "string",
                    },
                },
                metricNames: ["string"],
                taskType: "string",
            }],
            customMetrics: [{
                name: "string",
                ratingMethod: "string",
                description: "string",
            }],
            humanWorkflowConfig: {
                flowDefinitionArn: "string",
                instructions: "string",
            },
        },
    },
    inferenceConfig: {
        models: [{
            bedrockModel: {
                modelIdentifier: "string",
                inferenceParams: "string",
                performanceConfig: {
                    latency: "string",
                },
            },
            precomputedInferenceSource: {
                inferenceSourceIdentifier: "string",
            },
        }],
        ragConfig: {
            knowledgeBaseConfig: {
                retrieveAndGenerateConfig: {
                    knowledgeBaseId: "string",
                    modelArn: "string",
                    retrievalConfiguration: {
                        vectorSearchConfiguration: {
                            numberOfResults: 0,
                        },
                    },
                },
                retrieveConfig: {
                    knowledgeBaseId: "string",
                    knowledgeBaseRetrievalConfiguration: {
                        vectorSearchConfiguration: {
                            numberOfResults: 0,
                        },
                    },
                },
            },
            precomputedRagSourceConfig: {
                retrieveAndGenerateSourceConfig: {
                    ragSourceIdentifier: "string",
                },
                retrieveSourceConfig: {
                    ragSourceIdentifier: "string",
                },
            },
        },
    },
    jobName: "string",
    outputDataConfig: {
        s3Uri: "string",
    },
    roleArn: "string",
    applicationType: "string",
    customerEncryptionKeyId: "string",
    jobDescription: "string",
    region: "string",
    skipDestroy: false,
    tags: {
        string: "string",
    },
    timeouts: {
        create: "string",
        "delete": "string",
    },
});

    type: aws:bedrock:EvaluationJob
properties:
    applicationType: string
    customerEncryptionKeyId: string
    evaluationConfig:
        automated:
            customMetricConfig:
                customMetrics:
                    - customMetricDefinition:
                        instructions: string
                        name: string
                        ratingScales:
                            - definition: string
                              value:
                                floatValue: 0
                                stringValue: string
                evaluatorModelConfig:
                    bedrockEvaluatorModel:
                        modelIdentifier: string
            datasetMetricConfigs:
                - dataset:
                    datasetLocation:
                        s3Uri: string
                    name: string
                  metricNames:
                    - string
                  taskType: string
            evaluatorModelConfig:
                bedrockEvaluatorModel:
                    modelIdentifier: string
        human:
            customMetrics:
                - description: string
                  name: string
                  ratingMethod: string
            datasetMetricConfigs:
                - dataset:
                    datasetLocation:
                        s3Uri: string
                    name: string
                  metricNames:
                    - string
                  taskType: string
            humanWorkflowConfig:
                flowDefinitionArn: string
                instructions: string
    inferenceConfig:
        models:
            - bedrockModel:
                inferenceParams: string
                modelIdentifier: string
                performanceConfig:
                    latency: string
              precomputedInferenceSource:
                inferenceSourceIdentifier: string
        ragConfig:
            knowledgeBaseConfig:
                retrieveAndGenerateConfig:
                    knowledgeBaseId: string
                    modelArn: string
                    retrievalConfiguration:
                        vectorSearchConfiguration:
                            numberOfResults: 0
                retrieveConfig:
                    knowledgeBaseId: string
                    knowledgeBaseRetrievalConfiguration:
                        vectorSearchConfiguration:
                            numberOfResults: 0
            precomputedRagSourceConfig:
                retrieveAndGenerateSourceConfig:
                    ragSourceIdentifier: string
                retrieveSourceConfig:
                    ragSourceIdentifier: string
    jobDescription: string
    jobName: string
    outputDataConfig:
        s3Uri: string
    region: string
    roleArn: string
    skipDestroy: false
    tags:
        string: string
    timeouts:
        create: string
        delete: string

    EvaluationJob Resource Properties

    To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

    Inputs

    In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

    The EvaluationJob resource accepts the following input properties:

    EvaluationConfig EvaluationJobEvaluationConfig
    Configuration for either an automated or human-based evaluation job. See evaluationConfig Block below.
    InferenceConfig EvaluationJobInferenceConfig
    Configuration for the inference model, or models, used for the evaluation job. See inferenceConfig Block below.
    JobName string
    Name for the evaluation job. Must be unique within your AWS account and Region, and consist of lowercase letters, numbers, and hyphens.
    OutputDataConfig EvaluationJobOutputDataConfig
    Configuration for the Amazon S3 location where the results of the evaluation job are stored. See outputDataConfig Block below.
    RoleArn string

    ARN of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. See Required permissions for model evaluations.

    The following arguments are optional:

    ApplicationType string
    Whether the evaluation job evaluates a model or a knowledge base. Valid values: ModelEvaluation, RagEvaluation.
    CustomerEncryptionKeyId string
    ARN of the customer managed KMS key to use to encrypt the evaluation job.
    JobDescription string
    Description of the evaluation job.
    Region string
    Region where this resource will be managed. Defaults to the Region set in the provider configuration.
    SkipDestroy bool
    Whether to leave the evaluation job in its current state when destroying the resource, instead of stopping it.
    Tags Dictionary<string, string>
    Map of tags to assign to the evaluation job. If configured with a provider defaultTags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    Timeouts EvaluationJobTimeouts
    EvaluationConfig EvaluationJobEvaluationConfigArgs
    Configuration for either an automated or human-based evaluation job. See evaluationConfig Block below.
    InferenceConfig EvaluationJobInferenceConfigArgs
    Configuration for the inference model, or models, used for the evaluation job. See inferenceConfig Block below.
    JobName string
    Name for the evaluation job. Must be unique within your AWS account and Region, and consist of lowercase letters, numbers, and hyphens.
    OutputDataConfig EvaluationJobOutputDataConfigArgs
    Configuration for the Amazon S3 location where the results of the evaluation job are stored. See outputDataConfig Block below.
    RoleArn string

    ARN of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. See Required permissions for model evaluations.

    The following arguments are optional:

    ApplicationType string
    Whether the evaluation job evaluates a model or a knowledge base. Valid values: ModelEvaluation, RagEvaluation.
    CustomerEncryptionKeyId string
    ARN of the customer managed KMS key to use to encrypt the evaluation job.
    JobDescription string
    Description of the evaluation job.
    Region string
    Region where this resource will be managed. Defaults to the Region set in the provider configuration.
    SkipDestroy bool
    Whether to leave the evaluation job in its current state when destroying the resource, instead of stopping it.
    Tags map[string]string
    Map of tags to assign to the evaluation job. If configured with a provider defaultTags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    Timeouts EvaluationJobTimeoutsArgs
    evaluation_config object
    Configuration for either an automated or human-based evaluation job. See evaluationConfig Block below.
    inference_config object
    Configuration for the inference model, or models, used for the evaluation job. See inferenceConfig Block below.
    job_name string
    Name for the evaluation job. Must be unique within your AWS account and Region, and consist of lowercase letters, numbers, and hyphens.
    output_data_config object
    Configuration for the Amazon S3 location where the results of the evaluation job are stored. See outputDataConfig Block below.
    role_arn string

    ARN of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. See Required permissions for model evaluations.

    The following arguments are optional:

    application_type string
    Whether the evaluation job evaluates a model or a knowledge base. Valid values: ModelEvaluation, RagEvaluation.
    customer_encryption_key_id string
    ARN of the customer managed KMS key to use to encrypt the evaluation job.
    job_description string
    Description of the evaluation job.
    region string
    Region where this resource will be managed. Defaults to the Region set in the provider configuration.
    skip_destroy bool
    Whether to leave the evaluation job in its current state when destroying the resource, instead of stopping it.
    tags map(string)
    Map of tags to assign to the evaluation job. If configured with a provider defaultTags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    timeouts object
    evaluationConfig EvaluationJobEvaluationConfig
    Configuration for either an automated or human-based evaluation job. See evaluationConfig Block below.
    inferenceConfig EvaluationJobInferenceConfig
    Configuration for the inference model, or models, used for the evaluation job. See inferenceConfig Block below.
    jobName String
    Name for the evaluation job. Must be unique within your AWS account and Region, and consist of lowercase letters, numbers, and hyphens.
    outputDataConfig EvaluationJobOutputDataConfig
    Configuration for the Amazon S3 location where the results of the evaluation job are stored. See outputDataConfig Block below.
    roleArn String

    ARN of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. See Required permissions for model evaluations.

    The following arguments are optional:

    applicationType String
    Whether the evaluation job evaluates a model or a knowledge base. Valid values: ModelEvaluation, RagEvaluation.
    customerEncryptionKeyId String
    ARN of the customer managed KMS key to use to encrypt the evaluation job.
    jobDescription String
    Description of the evaluation job.
    region String
    Region where this resource will be managed. Defaults to the Region set in the provider configuration.
    skipDestroy Boolean
    Whether to leave the evaluation job in its current state when destroying the resource, instead of stopping it.
    tags Map<String,String>
    Map of tags to assign to the evaluation job. If configured with a provider defaultTags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    timeouts EvaluationJobTimeouts
    evaluationConfig EvaluationJobEvaluationConfig
    Configuration for either an automated or human-based evaluation job. See evaluationConfig Block below.
    inferenceConfig EvaluationJobInferenceConfig
    Configuration for the inference model, or models, used for the evaluation job. See inferenceConfig Block below.
    jobName string
    Name for the evaluation job. Must be unique within your AWS account and Region, and consist of lowercase letters, numbers, and hyphens.
    outputDataConfig EvaluationJobOutputDataConfig
    Configuration for the Amazon S3 location where the results of the evaluation job are stored. See outputDataConfig Block below.
    roleArn string

    ARN of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. See Required permissions for model evaluations.

    The following arguments are optional:

    applicationType string
    Whether the evaluation job evaluates a model or a knowledge base. Valid values: ModelEvaluation, RagEvaluation.
    customerEncryptionKeyId string
    ARN of the customer managed KMS key to use to encrypt the evaluation job.
    jobDescription string
    Description of the evaluation job.
    region string
    Region where this resource will be managed. Defaults to the Region set in the provider configuration.
    skipDestroy boolean
    Whether to leave the evaluation job in its current state when destroying the resource, instead of stopping it.
    tags {[key: string]: string}
    Map of tags to assign to the evaluation job. If configured with a provider defaultTags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    timeouts EvaluationJobTimeouts
    evaluation_config EvaluationJobEvaluationConfigArgs
    Configuration for either an automated or human-based evaluation job. See evaluationConfig Block below.
    inference_config EvaluationJobInferenceConfigArgs
    Configuration for the inference model, or models, used for the evaluation job. See inferenceConfig Block below.
    job_name str
    Name for the evaluation job. Must be unique within your AWS account and Region, and consist of lowercase letters, numbers, and hyphens.
    output_data_config EvaluationJobOutputDataConfigArgs
    Configuration for the Amazon S3 location where the results of the evaluation job are stored. See outputDataConfig Block below.
    role_arn str

    ARN of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. See Required permissions for model evaluations.

    The following arguments are optional:

    application_type str
    Whether the evaluation job evaluates a model or a knowledge base. Valid values: ModelEvaluation, RagEvaluation.
    customer_encryption_key_id str
    ARN of the customer managed KMS key to use to encrypt the evaluation job.
    job_description str
    Description of the evaluation job.
    region str
    Region where this resource will be managed. Defaults to the Region set in the provider configuration.
    skip_destroy bool
    Whether to leave the evaluation job in its current state when destroying the resource, instead of stopping it.
    tags Mapping[str, str]
    Map of tags to assign to the evaluation job. If configured with a provider defaultTags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    timeouts EvaluationJobTimeoutsArgs
    evaluationConfig Property Map
    Configuration for either an automated or human-based evaluation job. See evaluationConfig Block below.
    inferenceConfig Property Map
    Configuration for the inference model, or models, used for the evaluation job. See inferenceConfig Block below.
    jobName String
    Name for the evaluation job. Must be unique within your AWS account and Region, and consist of lowercase letters, numbers, and hyphens.
    outputDataConfig Property Map
    Configuration for the Amazon S3 location where the results of the evaluation job are stored. See outputDataConfig Block below.
    roleArn String

    ARN of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. See Required permissions for model evaluations.

    The following arguments are optional:

    applicationType String
    Whether the evaluation job evaluates a model or a knowledge base. Valid values: ModelEvaluation, RagEvaluation.
    customerEncryptionKeyId String
    ARN of the customer managed KMS key to use to encrypt the evaluation job.
    jobDescription String
    Description of the evaluation job.
    region String
    Region where this resource will be managed. Defaults to the Region set in the provider configuration.
    skipDestroy Boolean
    Whether to leave the evaluation job in its current state when destroying the resource, instead of stopping it.
    tags Map<String>
    Map of tags to assign to the evaluation job. If configured with a provider defaultTags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    timeouts Property Map

    Outputs

    All input properties are implicitly available as output properties. Additionally, the EvaluationJob resource produces the following output properties:

    CreatedAt string
    Date and time the evaluation job was created.
    FailureMessages List<string>
    List of reasons the evaluation job failed to create, if applicable.
    Id string
    The provider-assigned unique ID for this managed resource.
    JobArn string
    ARN of the evaluation job.
    JobType string
    Whether the evaluation job is automated or human-based.
    LastModifiedTime string
    Date and time the evaluation job was last modified.
    Status string
    Current status of the evaluation job.
    TagsAll Dictionary<string, string>
    CreatedAt string
    Date and time the evaluation job was created.
    FailureMessages []string
    List of reasons the evaluation job failed to create, if applicable.
    Id string
    The provider-assigned unique ID for this managed resource.
    JobArn string
    ARN of the evaluation job.
    JobType string
    Whether the evaluation job is automated or human-based.
    LastModifiedTime string
    Date and time the evaluation job was last modified.
    Status string
    Current status of the evaluation job.
    TagsAll map[string]string
    created_at string
    Date and time the evaluation job was created.
    failure_messages list(string)
    List of reasons the evaluation job failed to create, if applicable.
    id string
    The provider-assigned unique ID for this managed resource.
    job_arn string
    ARN of the evaluation job.
    job_type string
    Whether the evaluation job is automated or human-based.
    last_modified_time string
    Date and time the evaluation job was last modified.
    status string
    Current status of the evaluation job.
    tags_all map(string)
    createdAt String
    Date and time the evaluation job was created.
    failureMessages List<String>
    List of reasons the evaluation job failed to create, if applicable.
    id String
    The provider-assigned unique ID for this managed resource.
    jobArn String
    ARN of the evaluation job.
    jobType String
    Whether the evaluation job is automated or human-based.
    lastModifiedTime String
    Date and time the evaluation job was last modified.
    status String
    Current status of the evaluation job.
    tagsAll Map<String,String>
    createdAt string
    Date and time the evaluation job was created.
    failureMessages string[]
    List of reasons the evaluation job failed to create, if applicable.
    id string
    The provider-assigned unique ID for this managed resource.
    jobArn string
    ARN of the evaluation job.
    jobType string
    Whether the evaluation job is automated or human-based.
    lastModifiedTime string
    Date and time the evaluation job was last modified.
    status string
    Current status of the evaluation job.
    tagsAll {[key: string]: string}
    created_at str
    Date and time the evaluation job was created.
    failure_messages Sequence[str]
    List of reasons the evaluation job failed to create, if applicable.
    id str
    The provider-assigned unique ID for this managed resource.
    job_arn str
    ARN of the evaluation job.
    job_type str
    Whether the evaluation job is automated or human-based.
    last_modified_time str
    Date and time the evaluation job was last modified.
    status str
    Current status of the evaluation job.
    tags_all Mapping[str, str]
    createdAt String
    Date and time the evaluation job was created.
    failureMessages List<String>
    List of reasons the evaluation job failed to create, if applicable.
    id String
    The provider-assigned unique ID for this managed resource.
    jobArn String
    ARN of the evaluation job.
    jobType String
    Whether the evaluation job is automated or human-based.
    lastModifiedTime String
    Date and time the evaluation job was last modified.
    status String
    Current status of the evaluation job.
    tagsAll Map<String>

    Look up Existing EvaluationJob Resource

    Get an existing EvaluationJob resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.

    public static get(name: string, id: Input<ID>, state?: EvaluationJobState, opts?: CustomResourceOptions): EvaluationJob
    @staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        application_type: Optional[str] = None,
        created_at: Optional[str] = None,
        customer_encryption_key_id: Optional[str] = None,
        evaluation_config: Optional[EvaluationJobEvaluationConfigArgs] = None,
        failure_messages: Optional[Sequence[str]] = None,
        inference_config: Optional[EvaluationJobInferenceConfigArgs] = None,
        job_arn: Optional[str] = None,
        job_description: Optional[str] = None,
        job_name: Optional[str] = None,
        job_type: Optional[str] = None,
        last_modified_time: Optional[str] = None,
        output_data_config: Optional[EvaluationJobOutputDataConfigArgs] = None,
        region: Optional[str] = None,
        role_arn: Optional[str] = None,
        skip_destroy: Optional[bool] = None,
        status: Optional[str] = None,
        tags: Optional[Mapping[str, str]] = None,
        tags_all: Optional[Mapping[str, str]] = None,
        timeouts: Optional[EvaluationJobTimeoutsArgs] = None) -> EvaluationJob
    func GetEvaluationJob(ctx *Context, name string, id IDInput, state *EvaluationJobState, opts ...ResourceOption) (*EvaluationJob, error)
    public static EvaluationJob Get(string name, Input<string> id, EvaluationJobState? state, CustomResourceOptions? opts = null)
    public static EvaluationJob get(String name, Output<String> id, EvaluationJobState state, CustomResourceOptions options)
    resources:  _:    type: aws:bedrock:EvaluationJob    get:      id: ${id}
    import {
  to = aws_bedrock_evaluation_job.example
  id = "${id}"
}
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    resource_name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    The following state arguments are supported:
    ApplicationType string
    Whether the evaluation job evaluates a model or a knowledge base. Valid values: ModelEvaluation, RagEvaluation.
    CreatedAt string
    Date and time the evaluation job was created.
    CustomerEncryptionKeyId string
    ARN of the customer managed KMS key to use to encrypt the evaluation job.
    EvaluationConfig EvaluationJobEvaluationConfig
    Configuration for either an automated or human-based evaluation job. See evaluationConfig Block below.
    FailureMessages List<string>
    List of reasons the evaluation job failed to create, if applicable.
    InferenceConfig EvaluationJobInferenceConfig
    Configuration for the inference model, or models, used for the evaluation job. See inferenceConfig Block below.
    JobArn string
    ARN of the evaluation job.
    JobDescription string
    Description of the evaluation job.
    JobName string
    Name for the evaluation job. Must be unique within your AWS account and Region, and consist of lowercase letters, numbers, and hyphens.
    JobType string
    Whether the evaluation job is automated or human-based.
    LastModifiedTime string
    Date and time the evaluation job was last modified.
    OutputDataConfig EvaluationJobOutputDataConfig
    Configuration for the Amazon S3 location where the results of the evaluation job are stored. See outputDataConfig Block below.
    Region string
    Region where this resource will be managed. Defaults to the Region set in the provider configuration.
    RoleArn string

    ARN of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. See Required permissions for model evaluations.

    The following arguments are optional:

    SkipDestroy bool
    Whether to leave the evaluation job in its current state when destroying the resource, instead of stopping it.
    Status string
    Current status of the evaluation job.
    Tags Dictionary<string, string>
    Map of tags to assign to the evaluation job. If configured with a provider defaultTags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    TagsAll Dictionary<string, string>
    Timeouts EvaluationJobTimeouts
    ApplicationType string
    Whether the evaluation job evaluates a model or a knowledge base. Valid values: ModelEvaluation, RagEvaluation.
    CreatedAt string
    Date and time the evaluation job was created.
    CustomerEncryptionKeyId string
    ARN of the customer managed KMS key to use to encrypt the evaluation job.
    EvaluationConfig EvaluationJobEvaluationConfigArgs
    Configuration for either an automated or human-based evaluation job. See evaluationConfig Block below.
    FailureMessages []string
    List of reasons the evaluation job failed to create, if applicable.
    InferenceConfig EvaluationJobInferenceConfigArgs
    Configuration for the inference model, or models, used for the evaluation job. See inferenceConfig Block below.
    JobArn string
    ARN of the evaluation job.
    JobDescription string
    Description of the evaluation job.
    JobName string
    Name for the evaluation job. Must be unique within your AWS account and Region, and consist of lowercase letters, numbers, and hyphens.
    JobType string
    Whether the evaluation job is automated or human-based.
    LastModifiedTime string
    Date and time the evaluation job was last modified.
    OutputDataConfig EvaluationJobOutputDataConfigArgs
    Configuration for the Amazon S3 location where the results of the evaluation job are stored. See outputDataConfig Block below.
    Region string
    Region where this resource will be managed. Defaults to the Region set in the provider configuration.
    RoleArn string

    ARN of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. See Required permissions for model evaluations.

    The following arguments are optional:

    SkipDestroy bool
    Whether to leave the evaluation job in its current state when destroying the resource, instead of stopping it.
    Status string
    Current status of the evaluation job.
    Tags map[string]string
    Map of tags to assign to the evaluation job. If configured with a provider defaultTags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    TagsAll map[string]string
    Timeouts EvaluationJobTimeoutsArgs
    application_type string
    Whether the evaluation job evaluates a model or a knowledge base. Valid values: ModelEvaluation, RagEvaluation.
    created_at string
    Date and time the evaluation job was created.
    customer_encryption_key_id string
    ARN of the customer managed KMS key to use to encrypt the evaluation job.
    evaluation_config object
    Configuration for either an automated or human-based evaluation job. See evaluationConfig Block below.
    failure_messages list(string)
    List of reasons the evaluation job failed to create, if applicable.
    inference_config object
    Configuration for the inference model, or models, used for the evaluation job. See inferenceConfig Block below.
    job_arn string
    ARN of the evaluation job.
    job_description string
    Description of the evaluation job.
    job_name string
    Name for the evaluation job. Must be unique within your AWS account and Region, and consist of lowercase letters, numbers, and hyphens.
    job_type string
    Whether the evaluation job is automated or human-based.
    last_modified_time string
    Date and time the evaluation job was last modified.
    output_data_config object
    Configuration for the Amazon S3 location where the results of the evaluation job are stored. See outputDataConfig Block below.
    region string
    Region where this resource will be managed. Defaults to the Region set in the provider configuration.
    role_arn string

    ARN of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. See Required permissions for model evaluations.

    The following arguments are optional:

    skip_destroy bool
    Whether to leave the evaluation job in its current state when destroying the resource, instead of stopping it.
    status string
    Current status of the evaluation job.
    tags map(string)
    Map of tags to assign to the evaluation job. If configured with a provider defaultTags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    tags_all map(string)
    timeouts object
    applicationType String
    Whether the evaluation job evaluates a model or a knowledge base. Valid values: ModelEvaluation, RagEvaluation.
    createdAt String
    Date and time the evaluation job was created.
    customerEncryptionKeyId String
    ARN of the customer managed KMS key to use to encrypt the evaluation job.
    evaluationConfig EvaluationJobEvaluationConfig
    Configuration for either an automated or human-based evaluation job. See evaluationConfig Block below.
    failureMessages List<String>
    List of reasons the evaluation job failed to create, if applicable.
    inferenceConfig EvaluationJobInferenceConfig
    Configuration for the inference model, or models, used for the evaluation job. See inferenceConfig Block below.
    jobArn String
    ARN of the evaluation job.
    jobDescription String
    Description of the evaluation job.
    jobName String
    Name for the evaluation job. Must be unique within your AWS account and Region, and consist of lowercase letters, numbers, and hyphens.
    jobType String
    Whether the evaluation job is automated or human-based.
    lastModifiedTime String
    Date and time the evaluation job was last modified.
    outputDataConfig EvaluationJobOutputDataConfig
    Configuration for the Amazon S3 location where the results of the evaluation job are stored. See outputDataConfig Block below.
    region String
    Region where this resource will be managed. Defaults to the Region set in the provider configuration.
    roleArn String

    ARN of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. See Required permissions for model evaluations.

    The following arguments are optional:

    skipDestroy Boolean
    Whether to leave the evaluation job in its current state when destroying the resource, instead of stopping it.
    status String
    Current status of the evaluation job.
    tags Map<String,String>
    Map of tags to assign to the evaluation job. If configured with a provider defaultTags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    tagsAll Map<String,String>
    timeouts EvaluationJobTimeouts
    applicationType string
    Whether the evaluation job evaluates a model or a knowledge base. Valid values: ModelEvaluation, RagEvaluation.
    createdAt string
    Date and time the evaluation job was created.
    customerEncryptionKeyId string
    ARN of the customer managed KMS key to use to encrypt the evaluation job.
    evaluationConfig EvaluationJobEvaluationConfig
    Configuration for either an automated or human-based evaluation job. See evaluationConfig Block below.
    failureMessages string[]
    List of reasons the evaluation job failed to create, if applicable.
    inferenceConfig EvaluationJobInferenceConfig
    Configuration for the inference model, or models, used for the evaluation job. See inferenceConfig Block below.
    jobArn string
    ARN of the evaluation job.
    jobDescription string
    Description of the evaluation job.
    jobName string
    Name for the evaluation job. Must be unique within your AWS account and Region, and consist of lowercase letters, numbers, and hyphens.
    jobType string
    Whether the evaluation job is automated or human-based.
    lastModifiedTime string
    Date and time the evaluation job was last modified.
    outputDataConfig EvaluationJobOutputDataConfig
    Configuration for the Amazon S3 location where the results of the evaluation job are stored. See outputDataConfig Block below.
    region string
    Region where this resource will be managed. Defaults to the Region set in the provider configuration.
    roleArn string

    ARN of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. See Required permissions for model evaluations.

    The following arguments are optional:

    skipDestroy boolean
    Whether to leave the evaluation job in its current state when destroying the resource, instead of stopping it.
    status string
    Current status of the evaluation job.
    tags {[key: string]: string}
    Map of tags to assign to the evaluation job. If configured with a provider defaultTags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    tagsAll {[key: string]: string}
    timeouts EvaluationJobTimeouts
    application_type str
    Whether the evaluation job evaluates a model or a knowledge base. Valid values: ModelEvaluation, RagEvaluation.
    created_at str
    Date and time the evaluation job was created.
    customer_encryption_key_id str
    ARN of the customer managed KMS key to use to encrypt the evaluation job.
    evaluation_config EvaluationJobEvaluationConfigArgs
    Configuration for either an automated or human-based evaluation job. See evaluationConfig Block below.
    failure_messages Sequence[str]
    List of reasons the evaluation job failed to create, if applicable.
    inference_config EvaluationJobInferenceConfigArgs
    Configuration for the inference model, or models, used for the evaluation job. See inferenceConfig Block below.
    job_arn str
    ARN of the evaluation job.
    job_description str
    Description of the evaluation job.
    job_name str
    Name for the evaluation job. Must be unique within your AWS account and Region, and consist of lowercase letters, numbers, and hyphens.
    job_type str
    Whether the evaluation job is automated or human-based.
    last_modified_time str
    Date and time the evaluation job was last modified.
    output_data_config EvaluationJobOutputDataConfigArgs
    Configuration for the Amazon S3 location where the results of the evaluation job are stored. See outputDataConfig Block below.
    region str
    Region where this resource will be managed. Defaults to the Region set in the provider configuration.
    role_arn str

    ARN of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. See Required permissions for model evaluations.

    The following arguments are optional:

    skip_destroy bool
    Whether to leave the evaluation job in its current state when destroying the resource, instead of stopping it.
    status str
    Current status of the evaluation job.
    tags Mapping[str, str]
    Map of tags to assign to the evaluation job. If configured with a provider defaultTags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    tags_all Mapping[str, str]
    timeouts EvaluationJobTimeoutsArgs
    applicationType String
    Whether the evaluation job evaluates a model or a knowledge base. Valid values: ModelEvaluation, RagEvaluation.
    createdAt String
    Date and time the evaluation job was created.
    customerEncryptionKeyId String
    ARN of the customer managed KMS key to use to encrypt the evaluation job.
    evaluationConfig Property Map
    Configuration for either an automated or human-based evaluation job. See evaluationConfig Block below.
    failureMessages List<String>
    List of reasons the evaluation job failed to create, if applicable.
    inferenceConfig Property Map
    Configuration for the inference model, or models, used for the evaluation job. See inferenceConfig Block below.
    jobArn String
    ARN of the evaluation job.
    jobDescription String
    Description of the evaluation job.
    jobName String
    Name for the evaluation job. Must be unique within your AWS account and Region, and consist of lowercase letters, numbers, and hyphens.
    jobType String
    Whether the evaluation job is automated or human-based.
    lastModifiedTime String
    Date and time the evaluation job was last modified.
    outputDataConfig Property Map
    Configuration for the Amazon S3 location where the results of the evaluation job are stored. See outputDataConfig Block below.
    region String
    Region where this resource will be managed. Defaults to the Region set in the provider configuration.
    roleArn String

    ARN of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. See Required permissions for model evaluations.

    The following arguments are optional:

    skipDestroy Boolean
    Whether to leave the evaluation job in its current state when destroying the resource, instead of stopping it.
    status String
    Current status of the evaluation job.
    tags Map<String>
    Map of tags to assign to the evaluation job. If configured with a provider defaultTags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    tagsAll Map<String>
    timeouts Property Map

    Supporting Types

    EvaluationJobEvaluationConfig, EvaluationJobEvaluationConfigArgs

    Automated EvaluationJobEvaluationConfigAutomated
    Configuration for an automated evaluation job that computes metrics. See automated Block below.
    Human EvaluationJobEvaluationConfigHuman
    Configuration for an evaluation job that uses human workers. See human Block below.
    Automated EvaluationJobEvaluationConfigAutomated
    Configuration for an automated evaluation job that computes metrics. See automated Block below.
    Human EvaluationJobEvaluationConfigHuman
    Configuration for an evaluation job that uses human workers. See human Block below.
    automated object
    Configuration for an automated evaluation job that computes metrics. See automated Block below.
    human object
    Configuration for an evaluation job that uses human workers. See human Block below.
    automated EvaluationJobEvaluationConfigAutomated
    Configuration for an automated evaluation job that computes metrics. See automated Block below.
    human EvaluationJobEvaluationConfigHuman
    Configuration for an evaluation job that uses human workers. See human Block below.
    automated EvaluationJobEvaluationConfigAutomated
    Configuration for an automated evaluation job that computes metrics. See automated Block below.
    human EvaluationJobEvaluationConfigHuman
    Configuration for an evaluation job that uses human workers. See human Block below.
    automated EvaluationJobEvaluationConfigAutomated
    Configuration for an automated evaluation job that computes metrics. See automated Block below.
    human EvaluationJobEvaluationConfigHuman
    Configuration for an evaluation job that uses human workers. See human Block below.
    automated Property Map
    Configuration for an automated evaluation job that computes metrics. See automated Block below.
    human Property Map
    Configuration for an evaluation job that uses human workers. See human Block below.

    EvaluationJobEvaluationConfigAutomated, EvaluationJobEvaluationConfigAutomatedArgs

    DatasetMetricConfigs List<EvaluationJobEvaluationConfigAutomatedDatasetMetricConfig>
    One or more configurations for the prompt datasets and metrics to use. See evaluation_config.automated.dataset_metric_config Block below.
    CustomMetricConfig EvaluationJobEvaluationConfigAutomatedCustomMetricConfig
    Configuration for custom metrics to compute for the evaluation job. See customMetricConfig Block below.
    EvaluatorModelConfig EvaluationJobEvaluationConfigAutomatedEvaluatorModelConfig
    Configuration for the evaluator (judge) model. Required for automated jobs that use an LLM-as-judge metric, or that evaluate a knowledge base. See evaluatorModelConfig Block below.
    DatasetMetricConfigs []EvaluationJobEvaluationConfigAutomatedDatasetMetricConfig
    One or more configurations for the prompt datasets and metrics to use. See evaluation_config.automated.dataset_metric_config Block below.
    CustomMetricConfig EvaluationJobEvaluationConfigAutomatedCustomMetricConfig
    Configuration for custom metrics to compute for the evaluation job. See customMetricConfig Block below.
    EvaluatorModelConfig EvaluationJobEvaluationConfigAutomatedEvaluatorModelConfig
    Configuration for the evaluator (judge) model. Required for automated jobs that use an LLM-as-judge metric, or that evaluate a knowledge base. See evaluatorModelConfig Block below.
    dataset_metric_configs list(object)
    One or more configurations for the prompt datasets and metrics to use. See evaluation_config.automated.dataset_metric_config Block below.
    custom_metric_config object
    Configuration for custom metrics to compute for the evaluation job. See customMetricConfig Block below.
    evaluator_model_config object
    Configuration for the evaluator (judge) model. Required for automated jobs that use an LLM-as-judge metric, or that evaluate a knowledge base. See evaluatorModelConfig Block below.
    datasetMetricConfigs List<EvaluationJobEvaluationConfigAutomatedDatasetMetricConfig>
    One or more configurations for the prompt datasets and metrics to use. See evaluation_config.automated.dataset_metric_config Block below.
    customMetricConfig EvaluationJobEvaluationConfigAutomatedCustomMetricConfig
    Configuration for custom metrics to compute for the evaluation job. See customMetricConfig Block below.
    evaluatorModelConfig EvaluationJobEvaluationConfigAutomatedEvaluatorModelConfig
    Configuration for the evaluator (judge) model. Required for automated jobs that use an LLM-as-judge metric, or that evaluate a knowledge base. See evaluatorModelConfig Block below.
    datasetMetricConfigs EvaluationJobEvaluationConfigAutomatedDatasetMetricConfig[]
    One or more configurations for the prompt datasets and metrics to use. See evaluation_config.automated.dataset_metric_config Block below.
    customMetricConfig EvaluationJobEvaluationConfigAutomatedCustomMetricConfig
    Configuration for custom metrics to compute for the evaluation job. See customMetricConfig Block below.
    evaluatorModelConfig EvaluationJobEvaluationConfigAutomatedEvaluatorModelConfig
    Configuration for the evaluator (judge) model. Required for automated jobs that use an LLM-as-judge metric, or that evaluate a knowledge base. See evaluatorModelConfig Block below.
    dataset_metric_configs Sequence[EvaluationJobEvaluationConfigAutomatedDatasetMetricConfig]
    One or more configurations for the prompt datasets and metrics to use. See evaluation_config.automated.dataset_metric_config Block below.
    custom_metric_config EvaluationJobEvaluationConfigAutomatedCustomMetricConfig
    Configuration for custom metrics to compute for the evaluation job. See customMetricConfig Block below.
    evaluator_model_config EvaluationJobEvaluationConfigAutomatedEvaluatorModelConfig
    Configuration for the evaluator (judge) model. Required for automated jobs that use an LLM-as-judge metric, or that evaluate a knowledge base. See evaluatorModelConfig Block below.
    datasetMetricConfigs List<Property Map>
    One or more configurations for the prompt datasets and metrics to use. See evaluation_config.automated.dataset_metric_config Block below.
    customMetricConfig Property Map
    Configuration for custom metrics to compute for the evaluation job. See customMetricConfig Block below.
    evaluatorModelConfig Property Map
    Configuration for the evaluator (judge) model. Required for automated jobs that use an LLM-as-judge metric, or that evaluate a knowledge base. See evaluatorModelConfig Block below.

    EvaluationJobEvaluationConfigAutomatedCustomMetricConfig, EvaluationJobEvaluationConfigAutomatedCustomMetricConfigArgs

    CustomMetrics List<EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetric>
    One or more custom metric definitions. See evaluation_config.automated.custom_metric_config.custom_metric Block below.
    EvaluatorModelConfig EvaluationJobEvaluationConfigAutomatedCustomMetricConfigEvaluatorModelConfig
    Configuration for the evaluator model used to compute the custom metrics. See evaluatorModelConfig Block above.
    CustomMetrics []EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetric
    One or more custom metric definitions. See evaluation_config.automated.custom_metric_config.custom_metric Block below.
    EvaluatorModelConfig EvaluationJobEvaluationConfigAutomatedCustomMetricConfigEvaluatorModelConfig
    Configuration for the evaluator model used to compute the custom metrics. See evaluatorModelConfig Block above.
    custom_metrics list(object)
    One or more custom metric definitions. See evaluation_config.automated.custom_metric_config.custom_metric Block below.
    evaluator_model_config object
    Configuration for the evaluator model used to compute the custom metrics. See evaluatorModelConfig Block above.
    customMetrics List<EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetric>
    One or more custom metric definitions. See evaluation_config.automated.custom_metric_config.custom_metric Block below.
    evaluatorModelConfig EvaluationJobEvaluationConfigAutomatedCustomMetricConfigEvaluatorModelConfig
    Configuration for the evaluator model used to compute the custom metrics. See evaluatorModelConfig Block above.
    customMetrics EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetric[]
    One or more custom metric definitions. See evaluation_config.automated.custom_metric_config.custom_metric Block below.
    evaluatorModelConfig EvaluationJobEvaluationConfigAutomatedCustomMetricConfigEvaluatorModelConfig
    Configuration for the evaluator model used to compute the custom metrics. See evaluatorModelConfig Block above.
    custom_metrics Sequence[EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetric]
    One or more custom metric definitions. See evaluation_config.automated.custom_metric_config.custom_metric Block below.
    evaluator_model_config EvaluationJobEvaluationConfigAutomatedCustomMetricConfigEvaluatorModelConfig
    Configuration for the evaluator model used to compute the custom metrics. See evaluatorModelConfig Block above.
    customMetrics List<Property Map>
    One or more custom metric definitions. See evaluation_config.automated.custom_metric_config.custom_metric Block below.
    evaluatorModelConfig Property Map
    Configuration for the evaluator model used to compute the custom metrics. See evaluatorModelConfig Block above.

    EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetric, EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricArgs

    custom_metric_definition object
    Definition of the custom metric. See customMetricDefinition Block below.
    customMetricDefinition Property Map
    Definition of the custom metric. See customMetricDefinition Block below.

    EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinition, EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionArgs

    Instructions string
    Prompt that instructs the evaluator model how to rate the model or RAG source under evaluation.
    Name string
    Name for the custom metric. Must be unique in your AWS Region.
    RatingScales List<EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScale>
    One or more items defining the rating scale for the custom metric. See ratingScale Block below.
    Instructions string
    Prompt that instructs the evaluator model how to rate the model or RAG source under evaluation.
    Name string
    Name for the custom metric. Must be unique in your AWS Region.
    RatingScales []EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScale
    One or more items defining the rating scale for the custom metric. See ratingScale Block below.
    instructions string
    Prompt that instructs the evaluator model how to rate the model or RAG source under evaluation.
    name string
    Name for the custom metric. Must be unique in your AWS Region.
    rating_scales list(object)
    One or more items defining the rating scale for the custom metric. See ratingScale Block below.
    instructions String
    Prompt that instructs the evaluator model how to rate the model or RAG source under evaluation.
    name String
    Name for the custom metric. Must be unique in your AWS Region.
    ratingScales List<EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScale>
    One or more items defining the rating scale for the custom metric. See ratingScale Block below.
    instructions string
    Prompt that instructs the evaluator model how to rate the model or RAG source under evaluation.
    name string
    Name for the custom metric. Must be unique in your AWS Region.
    ratingScales EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScale[]
    One or more items defining the rating scale for the custom metric. See ratingScale Block below.
    instructions str
    Prompt that instructs the evaluator model how to rate the model or RAG source under evaluation.
    name str
    Name for the custom metric. Must be unique in your AWS Region.
    rating_scales Sequence[EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScale]
    One or more items defining the rating scale for the custom metric. See ratingScale Block below.
    instructions String
    Prompt that instructs the evaluator model how to rate the model or RAG source under evaluation.
    name String
    Name for the custom metric. Must be unique in your AWS Region.
    ratingScales List<Property Map>
    One or more items defining the rating scale for the custom metric. See ratingScale Block below.

    EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScale, EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScaleArgs

    Definition string
    Definition for one rating in the custom metric rating scale.
    Value EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScaleValue
    Value for one rating in the custom metric rating scale. See value Block below.
    Definition string
    Definition for one rating in the custom metric rating scale.
    Value EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScaleValue
    Value for one rating in the custom metric rating scale. See value Block below.
    definition string
    Definition for one rating in the custom metric rating scale.
    value object
    Value for one rating in the custom metric rating scale. See value Block below.
    definition String
    Definition for one rating in the custom metric rating scale.
    value EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScaleValue
    Value for one rating in the custom metric rating scale. See value Block below.
    definition string
    Definition for one rating in the custom metric rating scale.
    value EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScaleValue
    Value for one rating in the custom metric rating scale. See value Block below.
    definition str
    Definition for one rating in the custom metric rating scale.
    value EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScaleValue
    Value for one rating in the custom metric rating scale. See value Block below.
    definition String
    Definition for one rating in the custom metric rating scale.
    value Property Map
    Value for one rating in the custom metric rating scale. See value Block below.

    EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScaleValue, EvaluationJobEvaluationConfigAutomatedCustomMetricConfigCustomMetricCustomMetricDefinitionRatingScaleValueArgs

    FloatValue double
    Floating point number representing the rating value.
    StringValue string
    String representing the rating value.
    FloatValue float64
    Floating point number representing the rating value.
    StringValue string
    String representing the rating value.
    float_value number
    Floating point number representing the rating value.
    string_value string
    String representing the rating value.
    floatValue Double
    Floating point number representing the rating value.
    stringValue String
    String representing the rating value.
    floatValue number
    Floating point number representing the rating value.
    stringValue string
    String representing the rating value.
    float_value float
    Floating point number representing the rating value.
    string_value str
    String representing the rating value.
    floatValue Number
    Floating point number representing the rating value.
    stringValue String
    String representing the rating value.

    EvaluationJobEvaluationConfigAutomatedCustomMetricConfigEvaluatorModelConfig, EvaluationJobEvaluationConfigAutomatedCustomMetricConfigEvaluatorModelConfigArgs

    bedrock_evaluator_model object
    Evaluator model. See bedrockEvaluatorModel Block below.
    bedrockEvaluatorModel Property Map
    Evaluator model. See bedrockEvaluatorModel Block below.

    EvaluationJobEvaluationConfigAutomatedCustomMetricConfigEvaluatorModelConfigBedrockEvaluatorModel, EvaluationJobEvaluationConfigAutomatedCustomMetricConfigEvaluatorModelConfigBedrockEvaluatorModelArgs

    ModelIdentifier string
    Identifier of the Amazon Bedrock model, or inference profile, used to compute the metrics.
    ModelIdentifier string
    Identifier of the Amazon Bedrock model, or inference profile, used to compute the metrics.
    model_identifier string
    Identifier of the Amazon Bedrock model, or inference profile, used to compute the metrics.
    modelIdentifier String
    Identifier of the Amazon Bedrock model, or inference profile, used to compute the metrics.
    modelIdentifier string
    Identifier of the Amazon Bedrock model, or inference profile, used to compute the metrics.
    model_identifier str
    Identifier of the Amazon Bedrock model, or inference profile, used to compute the metrics.
    modelIdentifier String
    Identifier of the Amazon Bedrock model, or inference profile, used to compute the metrics.

    EvaluationJobEvaluationConfigAutomatedDatasetMetricConfig, EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigArgs

    Dataset EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDataset
    Prompt dataset to use. See dataset Block below.
    MetricNames List<string>
    Names of the metrics to use for the evaluation job.
    TaskType string
    Type of task to evaluate. Common values are Summarization, Classification, QuestionAndAnswer, Generation, and Custom.
    Dataset EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDataset
    Prompt dataset to use. See dataset Block below.
    MetricNames []string
    Names of the metrics to use for the evaluation job.
    TaskType string
    Type of task to evaluate. Common values are Summarization, Classification, QuestionAndAnswer, Generation, and Custom.
    dataset object
    Prompt dataset to use. See dataset Block below.
    metric_names list(string)
    Names of the metrics to use for the evaluation job.
    task_type string
    Type of task to evaluate. Common values are Summarization, Classification, QuestionAndAnswer, Generation, and Custom.
    dataset EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDataset
    Prompt dataset to use. See dataset Block below.
    metricNames List<String>
    Names of the metrics to use for the evaluation job.
    taskType String
    Type of task to evaluate. Common values are Summarization, Classification, QuestionAndAnswer, Generation, and Custom.
    dataset EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDataset
    Prompt dataset to use. See dataset Block below.
    metricNames string[]
    Names of the metrics to use for the evaluation job.
    taskType string
    Type of task to evaluate. Common values are Summarization, Classification, QuestionAndAnswer, Generation, and Custom.
    dataset EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDataset
    Prompt dataset to use. See dataset Block below.
    metric_names Sequence[str]
    Names of the metrics to use for the evaluation job.
    task_type str
    Type of task to evaluate. Common values are Summarization, Classification, QuestionAndAnswer, Generation, and Custom.
    dataset Property Map
    Prompt dataset to use. See dataset Block below.
    metricNames List<String>
    Names of the metrics to use for the evaluation job.
    taskType String
    Type of task to evaluate. Common values are Summarization, Classification, QuestionAndAnswer, Generation, and Custom.

    EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDataset, EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDatasetArgs

    Name string
    Name of a built-in prompt dataset, for example Builtin.Bold, or a label for a custom prompt dataset.
    DatasetLocation EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDatasetDatasetLocation
    Location of a custom prompt dataset. See datasetLocation Block below.
    Name string
    Name of a built-in prompt dataset, for example Builtin.Bold, or a label for a custom prompt dataset.
    DatasetLocation EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDatasetDatasetLocation
    Location of a custom prompt dataset. See datasetLocation Block below.
    name string
    Name of a built-in prompt dataset, for example Builtin.Bold, or a label for a custom prompt dataset.
    dataset_location object
    Location of a custom prompt dataset. See datasetLocation Block below.
    name String
    Name of a built-in prompt dataset, for example Builtin.Bold, or a label for a custom prompt dataset.
    datasetLocation EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDatasetDatasetLocation
    Location of a custom prompt dataset. See datasetLocation Block below.
    name string
    Name of a built-in prompt dataset, for example Builtin.Bold, or a label for a custom prompt dataset.
    datasetLocation EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDatasetDatasetLocation
    Location of a custom prompt dataset. See datasetLocation Block below.
    name str
    Name of a built-in prompt dataset, for example Builtin.Bold, or a label for a custom prompt dataset.
    dataset_location EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDatasetDatasetLocation
    Location of a custom prompt dataset. See datasetLocation Block below.
    name String
    Name of a built-in prompt dataset, for example Builtin.Bold, or a label for a custom prompt dataset.
    datasetLocation Property Map
    Location of a custom prompt dataset. See datasetLocation Block below.

    EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDatasetDatasetLocation, EvaluationJobEvaluationConfigAutomatedDatasetMetricConfigDatasetDatasetLocationArgs

    S3Uri string
    S3 URI of the custom prompt dataset.
    S3Uri string
    S3 URI of the custom prompt dataset.
    s3_uri string
    S3 URI of the custom prompt dataset.
    s3Uri String
    S3 URI of the custom prompt dataset.
    s3Uri string
    S3 URI of the custom prompt dataset.
    s3_uri str
    S3 URI of the custom prompt dataset.
    s3Uri String
    S3 URI of the custom prompt dataset.

    EvaluationJobEvaluationConfigAutomatedEvaluatorModelConfig, EvaluationJobEvaluationConfigAutomatedEvaluatorModelConfigArgs

    bedrock_evaluator_model object
    Evaluator model. See bedrockEvaluatorModel Block below.
    bedrockEvaluatorModel Property Map
    Evaluator model. See bedrockEvaluatorModel Block below.

    EvaluationJobEvaluationConfigAutomatedEvaluatorModelConfigBedrockEvaluatorModel, EvaluationJobEvaluationConfigAutomatedEvaluatorModelConfigBedrockEvaluatorModelArgs

    ModelIdentifier string
    Identifier of the Amazon Bedrock model, or inference profile, used to compute the metrics.
    ModelIdentifier string
    Identifier of the Amazon Bedrock model, or inference profile, used to compute the metrics.
    model_identifier string
    Identifier of the Amazon Bedrock model, or inference profile, used to compute the metrics.
    modelIdentifier String
    Identifier of the Amazon Bedrock model, or inference profile, used to compute the metrics.
    modelIdentifier string
    Identifier of the Amazon Bedrock model, or inference profile, used to compute the metrics.
    model_identifier str
    Identifier of the Amazon Bedrock model, or inference profile, used to compute the metrics.
    modelIdentifier String
    Identifier of the Amazon Bedrock model, or inference profile, used to compute the metrics.

    EvaluationJobEvaluationConfigHuman, EvaluationJobEvaluationConfigHumanArgs

    DatasetMetricConfigs List<EvaluationJobEvaluationConfigHumanDatasetMetricConfig>
    One or more configurations for the prompt datasets and metrics to use. See evaluation_config.human.dataset_metric_config Block below.
    CustomMetrics List<EvaluationJobEvaluationConfigHumanCustomMetric>
    One or more custom metrics for your human workers to use. See evaluation_config.human.custom_metric Block below.
    HumanWorkflowConfig EvaluationJobEvaluationConfigHumanHumanWorkflowConfig
    Configuration for the human workflow. See humanWorkflowConfig Block below.
    DatasetMetricConfigs []EvaluationJobEvaluationConfigHumanDatasetMetricConfig
    One or more configurations for the prompt datasets and metrics to use. See evaluation_config.human.dataset_metric_config Block below.
    CustomMetrics []EvaluationJobEvaluationConfigHumanCustomMetric
    One or more custom metrics for your human workers to use. See evaluation_config.human.custom_metric Block below.
    HumanWorkflowConfig EvaluationJobEvaluationConfigHumanHumanWorkflowConfig
    Configuration for the human workflow. See humanWorkflowConfig Block below.
    dataset_metric_configs list(object)
    One or more configurations for the prompt datasets and metrics to use. See evaluation_config.human.dataset_metric_config Block below.
    custom_metrics list(object)
    One or more custom metrics for your human workers to use. See evaluation_config.human.custom_metric Block below.
    human_workflow_config object
    Configuration for the human workflow. See humanWorkflowConfig Block below.
    datasetMetricConfigs List<EvaluationJobEvaluationConfigHumanDatasetMetricConfig>
    One or more configurations for the prompt datasets and metrics to use. See evaluation_config.human.dataset_metric_config Block below.
    customMetrics List<EvaluationJobEvaluationConfigHumanCustomMetric>
    One or more custom metrics for your human workers to use. See evaluation_config.human.custom_metric Block below.
    humanWorkflowConfig EvaluationJobEvaluationConfigHumanHumanWorkflowConfig
    Configuration for the human workflow. See humanWorkflowConfig Block below.
    datasetMetricConfigs EvaluationJobEvaluationConfigHumanDatasetMetricConfig[]
    One or more configurations for the prompt datasets and metrics to use. See evaluation_config.human.dataset_metric_config Block below.
    customMetrics EvaluationJobEvaluationConfigHumanCustomMetric[]
    One or more custom metrics for your human workers to use. See evaluation_config.human.custom_metric Block below.
    humanWorkflowConfig EvaluationJobEvaluationConfigHumanHumanWorkflowConfig
    Configuration for the human workflow. See humanWorkflowConfig Block below.
    dataset_metric_configs Sequence[EvaluationJobEvaluationConfigHumanDatasetMetricConfig]
    One or more configurations for the prompt datasets and metrics to use. See evaluation_config.human.dataset_metric_config Block below.
    custom_metrics Sequence[EvaluationJobEvaluationConfigHumanCustomMetric]
    One or more custom metrics for your human workers to use. See evaluation_config.human.custom_metric Block below.
    human_workflow_config EvaluationJobEvaluationConfigHumanHumanWorkflowConfig
    Configuration for the human workflow. See humanWorkflowConfig Block below.
    datasetMetricConfigs List<Property Map>
    One or more configurations for the prompt datasets and metrics to use. See evaluation_config.human.dataset_metric_config Block below.
    customMetrics List<Property Map>
    One or more custom metrics for your human workers to use. See evaluation_config.human.custom_metric Block below.
    humanWorkflowConfig Property Map
    Configuration for the human workflow. See humanWorkflowConfig Block below.

    EvaluationJobEvaluationConfigHumanCustomMetric, EvaluationJobEvaluationConfigHumanCustomMetricArgs

    Name string
    Name of the metric.
    RatingMethod string
    How the metric is rated. Valid values: ThumbsUpDown, IndividualLikertScale, ComparisonLikertScale, ComparisonChoice, ComparisonRank.
    Description string
    Description of the metric.
    Name string
    Name of the metric.
    RatingMethod string
    How the metric is rated. Valid values: ThumbsUpDown, IndividualLikertScale, ComparisonLikertScale, ComparisonChoice, ComparisonRank.
    Description string
    Description of the metric.
    name string
    Name of the metric.
    rating_method string
    How the metric is rated. Valid values: ThumbsUpDown, IndividualLikertScale, ComparisonLikertScale, ComparisonChoice, ComparisonRank.
    description string
    Description of the metric.
    name String
    Name of the metric.
    ratingMethod String
    How the metric is rated. Valid values: ThumbsUpDown, IndividualLikertScale, ComparisonLikertScale, ComparisonChoice, ComparisonRank.
    description String
    Description of the metric.
    name string
    Name of the metric.
    ratingMethod string
    How the metric is rated. Valid values: ThumbsUpDown, IndividualLikertScale, ComparisonLikertScale, ComparisonChoice, ComparisonRank.
    description string
    Description of the metric.
    name str
    Name of the metric.
    rating_method str
    How the metric is rated. Valid values: ThumbsUpDown, IndividualLikertScale, ComparisonLikertScale, ComparisonChoice, ComparisonRank.
    description str
    Description of the metric.
    name String
    Name of the metric.
    ratingMethod String
    How the metric is rated. Valid values: ThumbsUpDown, IndividualLikertScale, ComparisonLikertScale, ComparisonChoice, ComparisonRank.
    description String
    Description of the metric.

    EvaluationJobEvaluationConfigHumanDatasetMetricConfig, EvaluationJobEvaluationConfigHumanDatasetMetricConfigArgs

    Dataset EvaluationJobEvaluationConfigHumanDatasetMetricConfigDataset
    Prompt dataset to use. See dataset Block below.
    MetricNames List<string>
    Names of the metrics to use for the evaluation job.
    TaskType string
    Type of task to evaluate. Common values are Summarization, Classification, QuestionAndAnswer, Generation, and Custom.
    Dataset EvaluationJobEvaluationConfigHumanDatasetMetricConfigDataset
    Prompt dataset to use. See dataset Block below.
    MetricNames []string
    Names of the metrics to use for the evaluation job.
    TaskType string
    Type of task to evaluate. Common values are Summarization, Classification, QuestionAndAnswer, Generation, and Custom.
    dataset object
    Prompt dataset to use. See dataset Block below.
    metric_names list(string)
    Names of the metrics to use for the evaluation job.
    task_type string
    Type of task to evaluate. Common values are Summarization, Classification, QuestionAndAnswer, Generation, and Custom.
    dataset EvaluationJobEvaluationConfigHumanDatasetMetricConfigDataset
    Prompt dataset to use. See dataset Block below.
    metricNames List<String>
    Names of the metrics to use for the evaluation job.
    taskType String
    Type of task to evaluate. Common values are Summarization, Classification, QuestionAndAnswer, Generation, and Custom.
    dataset EvaluationJobEvaluationConfigHumanDatasetMetricConfigDataset
    Prompt dataset to use. See dataset Block below.
    metricNames string[]
    Names of the metrics to use for the evaluation job.
    taskType string
    Type of task to evaluate. Common values are Summarization, Classification, QuestionAndAnswer, Generation, and Custom.
    dataset EvaluationJobEvaluationConfigHumanDatasetMetricConfigDataset
    Prompt dataset to use. See dataset Block below.
    metric_names Sequence[str]
    Names of the metrics to use for the evaluation job.
    task_type str
    Type of task to evaluate. Common values are Summarization, Classification, QuestionAndAnswer, Generation, and Custom.
    dataset Property Map
    Prompt dataset to use. See dataset Block below.
    metricNames List<String>
    Names of the metrics to use for the evaluation job.
    taskType String
    Type of task to evaluate. Common values are Summarization, Classification, QuestionAndAnswer, Generation, and Custom.

    EvaluationJobEvaluationConfigHumanDatasetMetricConfigDataset, EvaluationJobEvaluationConfigHumanDatasetMetricConfigDatasetArgs

    Name string
    Name of a built-in prompt dataset, for example Builtin.Bold, or a label for a custom prompt dataset.
    DatasetLocation EvaluationJobEvaluationConfigHumanDatasetMetricConfigDatasetDatasetLocation
    Location of a custom prompt dataset. See datasetLocation Block below.
    Name string
    Name of a built-in prompt dataset, for example Builtin.Bold, or a label for a custom prompt dataset.
    DatasetLocation EvaluationJobEvaluationConfigHumanDatasetMetricConfigDatasetDatasetLocation
    Location of a custom prompt dataset. See datasetLocation Block below.
    name string
    Name of a built-in prompt dataset, for example Builtin.Bold, or a label for a custom prompt dataset.
    dataset_location object
    Location of a custom prompt dataset. See datasetLocation Block below.
    name String
    Name of a built-in prompt dataset, for example Builtin.Bold, or a label for a custom prompt dataset.
    datasetLocation EvaluationJobEvaluationConfigHumanDatasetMetricConfigDatasetDatasetLocation
    Location of a custom prompt dataset. See datasetLocation Block below.
    name string
    Name of a built-in prompt dataset, for example Builtin.Bold, or a label for a custom prompt dataset.
    datasetLocation EvaluationJobEvaluationConfigHumanDatasetMetricConfigDatasetDatasetLocation
    Location of a custom prompt dataset. See datasetLocation Block below.
    name str
    Name of a built-in prompt dataset, for example Builtin.Bold, or a label for a custom prompt dataset.
    dataset_location EvaluationJobEvaluationConfigHumanDatasetMetricConfigDatasetDatasetLocation
    Location of a custom prompt dataset. See datasetLocation Block below.
    name String
    Name of a built-in prompt dataset, for example Builtin.Bold, or a label for a custom prompt dataset.
    datasetLocation Property Map
    Location of a custom prompt dataset. See datasetLocation Block below.

    EvaluationJobEvaluationConfigHumanDatasetMetricConfigDatasetDatasetLocation, EvaluationJobEvaluationConfigHumanDatasetMetricConfigDatasetDatasetLocationArgs

    S3Uri string
    S3 URI of the custom prompt dataset.
    S3Uri string
    S3 URI of the custom prompt dataset.
    s3_uri string
    S3 URI of the custom prompt dataset.
    s3Uri String
    S3 URI of the custom prompt dataset.
    s3Uri string
    S3 URI of the custom prompt dataset.
    s3_uri str
    S3 URI of the custom prompt dataset.
    s3Uri String
    S3 URI of the custom prompt dataset.

    EvaluationJobEvaluationConfigHumanHumanWorkflowConfig, EvaluationJobEvaluationConfigHumanHumanWorkflowConfigArgs

    FlowDefinitionArn string
    ARN of the Amazon SageMaker AI flow definition.
    Instructions string
    Instructions for the flow definition.
    FlowDefinitionArn string
    ARN of the Amazon SageMaker AI flow definition.
    Instructions string
    Instructions for the flow definition.
    flow_definition_arn string
    ARN of the Amazon SageMaker AI flow definition.
    instructions string
    Instructions for the flow definition.
    flowDefinitionArn String
    ARN of the Amazon SageMaker AI flow definition.
    instructions String
    Instructions for the flow definition.
    flowDefinitionArn string
    ARN of the Amazon SageMaker AI flow definition.
    instructions string
    Instructions for the flow definition.
    flow_definition_arn str
    ARN of the Amazon SageMaker AI flow definition.
    instructions str
    Instructions for the flow definition.
    flowDefinitionArn String
    ARN of the Amazon SageMaker AI flow definition.
    instructions String
    Instructions for the flow definition.

    EvaluationJobInferenceConfig, EvaluationJobInferenceConfigArgs

    Models List<EvaluationJobInferenceConfigModel>
    One or more inference models. Automated jobs support a single model; jobs that use human workers support up to two models. See model Block below.
    RagConfig EvaluationJobInferenceConfigRagConfig
    Inference configuration for a knowledge base evaluation job. See ragConfig Block below.
    Models []EvaluationJobInferenceConfigModel
    One or more inference models. Automated jobs support a single model; jobs that use human workers support up to two models. See model Block below.
    RagConfig EvaluationJobInferenceConfigRagConfig
    Inference configuration for a knowledge base evaluation job. See ragConfig Block below.
    models list(object)
    One or more inference models. Automated jobs support a single model; jobs that use human workers support up to two models. See model Block below.
    rag_config object
    Inference configuration for a knowledge base evaluation job. See ragConfig Block below.
    models List<EvaluationJobInferenceConfigModel>
    One or more inference models. Automated jobs support a single model; jobs that use human workers support up to two models. See model Block below.
    ragConfig EvaluationJobInferenceConfigRagConfig
    Inference configuration for a knowledge base evaluation job. See ragConfig Block below.
    models EvaluationJobInferenceConfigModel[]
    One or more inference models. Automated jobs support a single model; jobs that use human workers support up to two models. See model Block below.
    ragConfig EvaluationJobInferenceConfigRagConfig
    Inference configuration for a knowledge base evaluation job. See ragConfig Block below.
    models Sequence[EvaluationJobInferenceConfigModel]
    One or more inference models. Automated jobs support a single model; jobs that use human workers support up to two models. See model Block below.
    rag_config EvaluationJobInferenceConfigRagConfig
    Inference configuration for a knowledge base evaluation job. See ragConfig Block below.
    models List<Property Map>
    One or more inference models. Automated jobs support a single model; jobs that use human workers support up to two models. See model Block below.
    ragConfig Property Map
    Inference configuration for a knowledge base evaluation job. See ragConfig Block below.

    EvaluationJobInferenceConfigModel, EvaluationJobInferenceConfigModelArgs

    BedrockModel EvaluationJobInferenceConfigModelBedrockModel
    Amazon Bedrock model. See bedrockModel Block below.
    PrecomputedInferenceSource EvaluationJobInferenceConfigModelPrecomputedInferenceSource
    Model where you provide your own precomputed inference response data. See precomputedInferenceSource Block below.
    BedrockModel EvaluationJobInferenceConfigModelBedrockModel
    Amazon Bedrock model. See bedrockModel Block below.
    PrecomputedInferenceSource EvaluationJobInferenceConfigModelPrecomputedInferenceSource
    Model where you provide your own precomputed inference response data. See precomputedInferenceSource Block below.
    bedrock_model object
    Amazon Bedrock model. See bedrockModel Block below.
    precomputed_inference_source object
    Model where you provide your own precomputed inference response data. See precomputedInferenceSource Block below.
    bedrockModel EvaluationJobInferenceConfigModelBedrockModel
    Amazon Bedrock model. See bedrockModel Block below.
    precomputedInferenceSource EvaluationJobInferenceConfigModelPrecomputedInferenceSource
    Model where you provide your own precomputed inference response data. See precomputedInferenceSource Block below.
    bedrockModel EvaluationJobInferenceConfigModelBedrockModel
    Amazon Bedrock model. See bedrockModel Block below.
    precomputedInferenceSource EvaluationJobInferenceConfigModelPrecomputedInferenceSource
    Model where you provide your own precomputed inference response data. See precomputedInferenceSource Block below.
    bedrock_model EvaluationJobInferenceConfigModelBedrockModel
    Amazon Bedrock model. See bedrockModel Block below.
    precomputed_inference_source EvaluationJobInferenceConfigModelPrecomputedInferenceSource
    Model where you provide your own precomputed inference response data. See precomputedInferenceSource Block below.
    bedrockModel Property Map
    Amazon Bedrock model. See bedrockModel Block below.
    precomputedInferenceSource Property Map
    Model where you provide your own precomputed inference response data. See precomputedInferenceSource Block below.

    EvaluationJobInferenceConfigModelBedrockModel, EvaluationJobInferenceConfigModelBedrockModelArgs

    ModelIdentifier string
    Identifier of the Amazon Bedrock model, or inference profile, used for inference.
    InferenceParams string
    JSON-formatted string of inference parameters for the model.
    PerformanceConfig EvaluationJobInferenceConfigModelBedrockModelPerformanceConfig
    Model's performance settings. See performanceConfig Block below.
    ModelIdentifier string
    Identifier of the Amazon Bedrock model, or inference profile, used for inference.
    InferenceParams string
    JSON-formatted string of inference parameters for the model.
    PerformanceConfig EvaluationJobInferenceConfigModelBedrockModelPerformanceConfig
    Model's performance settings. See performanceConfig Block below.
    model_identifier string
    Identifier of the Amazon Bedrock model, or inference profile, used for inference.
    inference_params string
    JSON-formatted string of inference parameters for the model.
    performance_config object
    Model's performance settings. See performanceConfig Block below.
    modelIdentifier String
    Identifier of the Amazon Bedrock model, or inference profile, used for inference.
    inferenceParams String
    JSON-formatted string of inference parameters for the model.
    performanceConfig EvaluationJobInferenceConfigModelBedrockModelPerformanceConfig
    Model's performance settings. See performanceConfig Block below.
    modelIdentifier string
    Identifier of the Amazon Bedrock model, or inference profile, used for inference.
    inferenceParams string
    JSON-formatted string of inference parameters for the model.
    performanceConfig EvaluationJobInferenceConfigModelBedrockModelPerformanceConfig
    Model's performance settings. See performanceConfig Block below.
    model_identifier str
    Identifier of the Amazon Bedrock model, or inference profile, used for inference.
    inference_params str
    JSON-formatted string of inference parameters for the model.
    performance_config EvaluationJobInferenceConfigModelBedrockModelPerformanceConfig
    Model's performance settings. See performanceConfig Block below.
    modelIdentifier String
    Identifier of the Amazon Bedrock model, or inference profile, used for inference.
    inferenceParams String
    JSON-formatted string of inference parameters for the model.
    performanceConfig Property Map
    Model's performance settings. See performanceConfig Block below.

    EvaluationJobInferenceConfigModelBedrockModelPerformanceConfig, EvaluationJobInferenceConfigModelBedrockModelPerformanceConfigArgs

    Latency string
    Whether to use the latency-optimized or standard version of the model. Valid values: standard, optimized.
    Latency string
    Whether to use the latency-optimized or standard version of the model. Valid values: standard, optimized.
    latency string
    Whether to use the latency-optimized or standard version of the model. Valid values: standard, optimized.
    latency String
    Whether to use the latency-optimized or standard version of the model. Valid values: standard, optimized.
    latency string
    Whether to use the latency-optimized or standard version of the model. Valid values: standard, optimized.
    latency str
    Whether to use the latency-optimized or standard version of the model. Valid values: standard, optimized.
    latency String
    Whether to use the latency-optimized or standard version of the model. Valid values: standard, optimized.

    EvaluationJobInferenceConfigModelPrecomputedInferenceSource, EvaluationJobInferenceConfigModelPrecomputedInferenceSourceArgs

    InferenceSourceIdentifier string
    Label that identifies the precomputed inference source.
    InferenceSourceIdentifier string
    Label that identifies the precomputed inference source.
    inference_source_identifier string
    Label that identifies the precomputed inference source.
    inferenceSourceIdentifier String
    Label that identifies the precomputed inference source.
    inferenceSourceIdentifier string
    Label that identifies the precomputed inference source.
    inference_source_identifier str
    Label that identifies the precomputed inference source.
    inferenceSourceIdentifier String
    Label that identifies the precomputed inference source.

    EvaluationJobInferenceConfigRagConfig, EvaluationJobInferenceConfigRagConfigArgs

    KnowledgeBaseConfig EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfig
    Amazon Bedrock knowledge base. See knowledgeBaseConfig Block below.
    PrecomputedRagSourceConfig EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfig
    RAG source where you provide your own precomputed inference response data. See precomputedRagSourceConfig Block below.
    KnowledgeBaseConfig EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfig
    Amazon Bedrock knowledge base. See knowledgeBaseConfig Block below.
    PrecomputedRagSourceConfig EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfig
    RAG source where you provide your own precomputed inference response data. See precomputedRagSourceConfig Block below.
    knowledge_base_config object
    Amazon Bedrock knowledge base. See knowledgeBaseConfig Block below.
    precomputed_rag_source_config object
    RAG source where you provide your own precomputed inference response data. See precomputedRagSourceConfig Block below.
    knowledgeBaseConfig EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfig
    Amazon Bedrock knowledge base. See knowledgeBaseConfig Block below.
    precomputedRagSourceConfig EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfig
    RAG source where you provide your own precomputed inference response data. See precomputedRagSourceConfig Block below.
    knowledgeBaseConfig EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfig
    Amazon Bedrock knowledge base. See knowledgeBaseConfig Block below.
    precomputedRagSourceConfig EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfig
    RAG source where you provide your own precomputed inference response data. See precomputedRagSourceConfig Block below.
    knowledge_base_config EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfig
    Amazon Bedrock knowledge base. See knowledgeBaseConfig Block below.
    precomputed_rag_source_config EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfig
    RAG source where you provide your own precomputed inference response data. See precomputedRagSourceConfig Block below.
    knowledgeBaseConfig Property Map
    Amazon Bedrock knowledge base. See knowledgeBaseConfig Block below.
    precomputedRagSourceConfig Property Map
    RAG source where you provide your own precomputed inference response data. See precomputedRagSourceConfig Block below.

    EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfig, EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigArgs

    RetrieveAndGenerateConfig EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfig
    Configuration for retrieval with response generation. See retrieveAndGenerateConfig Block below.
    RetrieveConfig EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfig
    Configuration for retrieval only. See retrieveConfig Block below.
    RetrieveAndGenerateConfig EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfig
    Configuration for retrieval with response generation. See retrieveAndGenerateConfig Block below.
    RetrieveConfig EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfig
    Configuration for retrieval only. See retrieveConfig Block below.
    retrieve_and_generate_config object
    Configuration for retrieval with response generation. See retrieveAndGenerateConfig Block below.
    retrieve_config object
    Configuration for retrieval only. See retrieveConfig Block below.
    retrieveAndGenerateConfig EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfig
    Configuration for retrieval with response generation. See retrieveAndGenerateConfig Block below.
    retrieveConfig EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfig
    Configuration for retrieval only. See retrieveConfig Block below.
    retrieveAndGenerateConfig EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfig
    Configuration for retrieval with response generation. See retrieveAndGenerateConfig Block below.
    retrieveConfig EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfig
    Configuration for retrieval only. See retrieveConfig Block below.
    retrieve_and_generate_config EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfig
    Configuration for retrieval with response generation. See retrieveAndGenerateConfig Block below.
    retrieve_config EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfig
    Configuration for retrieval only. See retrieveConfig Block below.
    retrieveAndGenerateConfig Property Map
    Configuration for retrieval with response generation. See retrieveAndGenerateConfig Block below.
    retrieveConfig Property Map
    Configuration for retrieval only. See retrieveConfig Block below.

    EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfig, EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigArgs

    KnowledgeBaseId string
    Identifier of the knowledge base.
    ModelArn string
    ARN of the foundation model, or inference profile, used to generate responses.
    RetrievalConfiguration EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigRetrievalConfiguration
    Knowledge base retrieval configuration. See retrievalConfiguration Block below.
    KnowledgeBaseId string
    Identifier of the knowledge base.
    ModelArn string
    ARN of the foundation model, or inference profile, used to generate responses.
    RetrievalConfiguration EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigRetrievalConfiguration
    Knowledge base retrieval configuration. See retrievalConfiguration Block below.
    knowledge_base_id string
    Identifier of the knowledge base.
    model_arn string
    ARN of the foundation model, or inference profile, used to generate responses.
    retrieval_configuration object
    Knowledge base retrieval configuration. See retrievalConfiguration Block below.
    knowledgeBaseId String
    Identifier of the knowledge base.
    modelArn String
    ARN of the foundation model, or inference profile, used to generate responses.
    retrievalConfiguration EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigRetrievalConfiguration
    Knowledge base retrieval configuration. See retrievalConfiguration Block below.
    knowledgeBaseId string
    Identifier of the knowledge base.
    modelArn string
    ARN of the foundation model, or inference profile, used to generate responses.
    retrievalConfiguration EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigRetrievalConfiguration
    Knowledge base retrieval configuration. See retrievalConfiguration Block below.
    knowledge_base_id str
    Identifier of the knowledge base.
    model_arn str
    ARN of the foundation model, or inference profile, used to generate responses.
    retrieval_configuration EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigRetrievalConfiguration
    Knowledge base retrieval configuration. See retrievalConfiguration Block below.
    knowledgeBaseId String
    Identifier of the knowledge base.
    modelArn String
    ARN of the foundation model, or inference profile, used to generate responses.
    retrievalConfiguration Property Map
    Knowledge base retrieval configuration. See retrievalConfiguration Block below.

    EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigRetrievalConfiguration, EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigRetrievalConfigurationArgs

    vector_search_configuration object
    Vector search configuration. See vectorSearchConfiguration Block below.
    vectorSearchConfiguration Property Map
    Vector search configuration. See vectorSearchConfiguration Block below.

    EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigRetrievalConfigurationVectorSearchConfiguration, EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveAndGenerateConfigRetrievalConfigurationVectorSearchConfigurationArgs

    NumberOfResults int
    Number of text chunks to retrieve.
    NumberOfResults int
    Number of text chunks to retrieve.
    number_of_results number
    Number of text chunks to retrieve.
    numberOfResults Integer
    Number of text chunks to retrieve.
    numberOfResults number
    Number of text chunks to retrieve.
    number_of_results int
    Number of text chunks to retrieve.
    numberOfResults Number
    Number of text chunks to retrieve.

    EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfig, EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigArgs

    KnowledgeBaseId string
    Identifier of the knowledge base.
    KnowledgeBaseRetrievalConfiguration EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigKnowledgeBaseRetrievalConfiguration
    Knowledge base retrieval configuration. See knowledgeBaseRetrievalConfiguration Block below.
    KnowledgeBaseId string
    Identifier of the knowledge base.
    KnowledgeBaseRetrievalConfiguration EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigKnowledgeBaseRetrievalConfiguration
    Knowledge base retrieval configuration. See knowledgeBaseRetrievalConfiguration Block below.
    knowledge_base_id string
    Identifier of the knowledge base.
    knowledge_base_retrieval_configuration object
    Knowledge base retrieval configuration. See knowledgeBaseRetrievalConfiguration Block below.
    knowledgeBaseId String
    Identifier of the knowledge base.
    knowledgeBaseRetrievalConfiguration EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigKnowledgeBaseRetrievalConfiguration
    Knowledge base retrieval configuration. See knowledgeBaseRetrievalConfiguration Block below.
    knowledgeBaseId string
    Identifier of the knowledge base.
    knowledgeBaseRetrievalConfiguration EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigKnowledgeBaseRetrievalConfiguration
    Knowledge base retrieval configuration. See knowledgeBaseRetrievalConfiguration Block below.
    knowledge_base_id str
    Identifier of the knowledge base.
    knowledge_base_retrieval_configuration EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigKnowledgeBaseRetrievalConfiguration
    Knowledge base retrieval configuration. See knowledgeBaseRetrievalConfiguration Block below.
    knowledgeBaseId String
    Identifier of the knowledge base.
    knowledgeBaseRetrievalConfiguration Property Map
    Knowledge base retrieval configuration. See knowledgeBaseRetrievalConfiguration Block below.

    EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigKnowledgeBaseRetrievalConfiguration, EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigKnowledgeBaseRetrievalConfigurationArgs

    vector_search_configuration object
    Vector search configuration. See vectorSearchConfiguration Block above.
    vectorSearchConfiguration Property Map
    Vector search configuration. See vectorSearchConfiguration Block above.

    EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigKnowledgeBaseRetrievalConfigurationVectorSearchConfiguration, EvaluationJobInferenceConfigRagConfigKnowledgeBaseConfigRetrieveConfigKnowledgeBaseRetrievalConfigurationVectorSearchConfigurationArgs

    NumberOfResults int
    Number of text chunks to retrieve.
    NumberOfResults int
    Number of text chunks to retrieve.
    number_of_results number
    Number of text chunks to retrieve.
    numberOfResults Integer
    Number of text chunks to retrieve.
    numberOfResults number
    Number of text chunks to retrieve.
    number_of_results int
    Number of text chunks to retrieve.
    numberOfResults Number
    Number of text chunks to retrieve.

    EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfig, EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigArgs

    RetrieveAndGenerateSourceConfig EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveAndGenerateSourceConfig
    Configuration for retrieval with response generation. See retrieveAndGenerateSourceConfig Block below.
    RetrieveSourceConfig EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveSourceConfig
    Configuration for retrieval only. See retrieveSourceConfig Block below.
    RetrieveAndGenerateSourceConfig EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveAndGenerateSourceConfig
    Configuration for retrieval with response generation. See retrieveAndGenerateSourceConfig Block below.
    RetrieveSourceConfig EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveSourceConfig
    Configuration for retrieval only. See retrieveSourceConfig Block below.
    retrieve_and_generate_source_config object
    Configuration for retrieval with response generation. See retrieveAndGenerateSourceConfig Block below.
    retrieve_source_config object
    Configuration for retrieval only. See retrieveSourceConfig Block below.
    retrieveAndGenerateSourceConfig EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveAndGenerateSourceConfig
    Configuration for retrieval with response generation. See retrieveAndGenerateSourceConfig Block below.
    retrieveSourceConfig EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveSourceConfig
    Configuration for retrieval only. See retrieveSourceConfig Block below.
    retrieveAndGenerateSourceConfig EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveAndGenerateSourceConfig
    Configuration for retrieval with response generation. See retrieveAndGenerateSourceConfig Block below.
    retrieveSourceConfig EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveSourceConfig
    Configuration for retrieval only. See retrieveSourceConfig Block below.
    retrieve_and_generate_source_config EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveAndGenerateSourceConfig
    Configuration for retrieval with response generation. See retrieveAndGenerateSourceConfig Block below.
    retrieve_source_config EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveSourceConfig
    Configuration for retrieval only. See retrieveSourceConfig Block below.
    retrieveAndGenerateSourceConfig Property Map
    Configuration for retrieval with response generation. See retrieveAndGenerateSourceConfig Block below.
    retrieveSourceConfig Property Map
    Configuration for retrieval only. See retrieveSourceConfig Block below.

    EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveAndGenerateSourceConfig, EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveAndGenerateSourceConfigArgs

    RagSourceIdentifier string
    Label that identifies the precomputed RAG source.
    RagSourceIdentifier string
    Label that identifies the precomputed RAG source.
    rag_source_identifier string
    Label that identifies the precomputed RAG source.
    ragSourceIdentifier String
    Label that identifies the precomputed RAG source.
    ragSourceIdentifier string
    Label that identifies the precomputed RAG source.
    rag_source_identifier str
    Label that identifies the precomputed RAG source.
    ragSourceIdentifier String
    Label that identifies the precomputed RAG source.

    EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveSourceConfig, EvaluationJobInferenceConfigRagConfigPrecomputedRagSourceConfigRetrieveSourceConfigArgs

    RagSourceIdentifier string
    Label that identifies the precomputed RAG source.
    RagSourceIdentifier string
    Label that identifies the precomputed RAG source.
    rag_source_identifier string
    Label that identifies the precomputed RAG source.
    ragSourceIdentifier String
    Label that identifies the precomputed RAG source.
    ragSourceIdentifier string
    Label that identifies the precomputed RAG source.
    rag_source_identifier str
    Label that identifies the precomputed RAG source.
    ragSourceIdentifier String
    Label that identifies the precomputed RAG source.

    EvaluationJobOutputDataConfig, EvaluationJobOutputDataConfigArgs

    S3Uri string
    S3 URI where the results of the evaluation job are stored.
    S3Uri string
    S3 URI where the results of the evaluation job are stored.
    s3_uri string
    S3 URI where the results of the evaluation job are stored.
    s3Uri String
    S3 URI where the results of the evaluation job are stored.
    s3Uri string
    S3 URI where the results of the evaluation job are stored.
    s3_uri str
    S3 URI where the results of the evaluation job are stored.
    s3Uri String
    S3 URI where the results of the evaluation job are stored.

    EvaluationJobTimeouts, EvaluationJobTimeoutsArgs

    Create string
    A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).
    Delete string
    A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours). Setting a timeout for a Delete operation is only applicable if changes are saved into state before the destroy operation occurs.
    Create string
    A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).
    Delete string
    A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours). Setting a timeout for a Delete operation is only applicable if changes are saved into state before the destroy operation occurs.
    create string
    A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).
    delete string
    A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours). Setting a timeout for a Delete operation is only applicable if changes are saved into state before the destroy operation occurs.
    create String
    A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).
    delete String
    A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours). Setting a timeout for a Delete operation is only applicable if changes are saved into state before the destroy operation occurs.
    create string
    A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).
    delete string
    A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours). Setting a timeout for a Delete operation is only applicable if changes are saved into state before the destroy operation occurs.
    create str
    A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).
    delete str
    A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours). Setting a timeout for a Delete operation is only applicable if changes are saved into state before the destroy operation occurs.
    create String
    A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).
    delete String
    A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours). Setting a timeout for a Delete operation is only applicable if changes are saved into state before the destroy operation occurs.

    Import

    Identity Schema

    Required

    • jobArn (String) ARN of the evaluation job.

    Using pulumi import, import Bedrock Evaluation Job using the jobArn. For example:

    $ pulumi import aws:bedrock/evaluationJob:EvaluationJob example arn:aws:bedrock:us-west-2:123456789012:evaluation-job/abcdefgh1234

    To learn more about importing existing cloud resources, see Importing resources.

    Package Details

    Repository
    AWS Classic pulumi/pulumi-aws
    License
    Apache-2.0
    Notes
    This Pulumi package is based on the aws Terraform Provider.
    aws logo aws logo
    Viewing docs for AWS v7.41.0
    published on Friday, Aug 7, 2026 by Pulumi
    Schema (JSON)
    pulumi/pulumi-aws

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