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[ aws . bedrock ]

create-evaluation-job

Description

API operation for creating and managing Amazon Bedrock automatic model evaluation jobs and model evaluation jobs that use human workers. To learn more about the requirements for creating a model evaluation job see, Model evaluation .

See also: AWS API Documentation

Synopsis

  create-evaluation-job
--job-name <value>
[--job-description <value>]
[--client-request-token <value>]
--role-arn <value>
[--customer-encryption-key-id <value>]
[--job-tags <value>]
--evaluation-config <value>
--inference-config <value>
--output-data-config <value>
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]
[--debug]
[--endpoint-url <value>]
[--no-verify-ssl]
[--no-paginate]
[--output <value>]
[--query <value>]
[--profile <value>]
[--region <value>]
[--version <value>]
[--color <value>]
[--no-sign-request]
[--ca-bundle <value>]
[--cli-read-timeout <value>]
[--cli-connect-timeout <value>]

Options

--job-name (string)

The name of the model evaluation job. Model evaluation job names must unique with your AWS account, and your account's AWS region.

--job-description (string)

A description of the model evaluation job.

--client-request-token (string)

A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see Ensuring idempotency .

--role-arn (string)

The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. The service role must have Amazon Bedrock as the service principal, and provide access to any Amazon S3 buckets specified in the EvaluationConfig object. To pass this role to Amazon Bedrock, the caller of this API must have the iam:PassRole permission. To learn more about the required permissions, see Required permissions .

--customer-encryption-key-id (string)

Specify your customer managed key ARN that will be used to encrypt your model evaluation job.

--job-tags (list)

Tags to attach to the model evaluation job.

(structure)

Definition of the key/value pair for a tag.

key -> (string)

Key for the tag.

value -> (string)

Value for the tag.

Shorthand Syntax:

key=string,value=string ...

JSON Syntax:

[
  {
    "key": "string",
    "value": "string"
  }
  ...
]

--evaluation-config (tagged union structure)

Specifies whether the model evaluation job is automatic or uses human worker.

Note

This is a Tagged Union structure. Only one of the following top level keys can be set: automated, human.

automated -> (structure)

Used to specify an automated model evaluation job. See AutomatedEvaluationConfig to view the required parameters.

datasetMetricConfigs -> (list)

Specifies the required elements for an automatic model evaluation job.

(structure)

Defines the built-in prompt datasets, built-in metric names and custom metric names, and the task type.

taskType -> (string)

The task type you want the model to carry out.

dataset -> (structure)

Specifies the prompt dataset.

name -> (string)

Used to specify supported built-in prompt datasets. Valid values are Builtin.Bold , Builtin.BoolQ , Builtin.NaturalQuestions , Builtin.Gigaword , Builtin.RealToxicityPrompts , Builtin.TriviaQA , Builtin.T-Rex , Builtin.WomensEcommerceClothingReviews and Builtin.Wikitext2 .

datasetLocation -> (tagged union structure)

For custom prompt datasets, you must specify the location in Amazon S3 where the prompt dataset is saved.

Note

This is a Tagged Union structure. Only one of the following top level keys can be set: s3Uri.

s3Uri -> (string)

The S3 URI of the S3 bucket specified in the job.

metricNames -> (list)

The names of the metrics used. For automated model evaluation jobs valid values are "Builtin.Accuracy" , "Builtin.Robustness" , and "Builtin.Toxicity" . In human-based model evaluation jobs the array of strings must match the name parameter specified in HumanEvaluationCustomMetric .

(string)

human -> (structure)

Used to specify a model evaluation job that uses human workers.See HumanEvaluationConfig to view the required parameters.

humanWorkflowConfig -> (structure)

The parameters of the human workflow.

flowDefinitionArn -> (string)

The Amazon Resource Number (ARN) for the flow definition

instructions -> (string)

Instructions for the flow definition

customMetrics -> (list)

A HumanEvaluationCustomMetric object. It contains the names the metrics, how the metrics are to be evaluated, an optional description.

(structure)

In a model evaluation job that uses human workers you must define the name of the metric, and how you want that metric rated ratingMethod , and an optional description of the metric.

name -> (string)

The name of the metric. Your human evaluators will see this name in the evaluation UI.

description -> (string)

An optional description of the metric. Use this parameter to provide more details about the metric.

ratingMethod -> (string)

Choose how you want your human workers to evaluation your model. Valid values for rating methods are ThumbsUpDown , IndividualLikertScale ,``ComparisonLikertScale`` , ComparisonChoice , and ComparisonRank

datasetMetricConfigs -> (list)

Use to specify the metrics, task, and prompt dataset to be used in your model evaluation job.

(structure)

Defines the built-in prompt datasets, built-in metric names and custom metric names, and the task type.

taskType -> (string)

The task type you want the model to carry out.

dataset -> (structure)

Specifies the prompt dataset.

name -> (string)

Used to specify supported built-in prompt datasets. Valid values are Builtin.Bold , Builtin.BoolQ , Builtin.NaturalQuestions , Builtin.Gigaword , Builtin.RealToxicityPrompts , Builtin.TriviaQA , Builtin.T-Rex , Builtin.WomensEcommerceClothingReviews and Builtin.Wikitext2 .

datasetLocation -> (tagged union structure)

For custom prompt datasets, you must specify the location in Amazon S3 where the prompt dataset is saved.

Note

This is a Tagged Union structure. Only one of the following top level keys can be set: s3Uri.

s3Uri -> (string)

The S3 URI of the S3 bucket specified in the job.

metricNames -> (list)

The names of the metrics used. For automated model evaluation jobs valid values are "Builtin.Accuracy" , "Builtin.Robustness" , and "Builtin.Toxicity" . In human-based model evaluation jobs the array of strings must match the name parameter specified in HumanEvaluationCustomMetric .

(string)

JSON Syntax:

{
  "automated": {
    "datasetMetricConfigs": [
      {
        "taskType": "Summarization"|"Classification"|"QuestionAndAnswer"|"Generation"|"Custom",
        "dataset": {
          "name": "string",
          "datasetLocation": {
            "s3Uri": "string"
          }
        },
        "metricNames": ["string", ...]
      }
      ...
    ]
  },
  "human": {
    "humanWorkflowConfig": {
      "flowDefinitionArn": "string",
      "instructions": "string"
    },
    "customMetrics": [
      {
        "name": "string",
        "description": "string",
        "ratingMethod": "string"
      }
      ...
    ],
    "datasetMetricConfigs": [
      {
        "taskType": "Summarization"|"Classification"|"QuestionAndAnswer"|"Generation"|"Custom",
        "dataset": {
          "name": "string",
          "datasetLocation": {
            "s3Uri": "string"
          }
        },
        "metricNames": ["string", ...]
      }
      ...
    ]
  }
}

--inference-config (tagged union structure)

Specify the models you want to use in your model evaluation job. Automatic model evaluation jobs support a single model or inference profile , and model evaluation job that use human workers support two models or inference profiles.

Note

This is a Tagged Union structure. Only one of the following top level keys can be set: models.

models -> (list)

Used to specify the models.

(tagged union structure)

Defines the models used in the model evaluation job.

Note

This is a Tagged Union structure. Only one of the following top level keys can be set: bedrockModel.

bedrockModel -> (structure)

Defines the Amazon Bedrock model or inference profile and inference parameters you want used.

modelIdentifier -> (string)

The ARN of the Amazon Bedrock model or inference profile specified.

inferenceParams -> (string)

Each Amazon Bedrock support different inference parameters that change how the model behaves during inference.

JSON Syntax:

{
  "models": [
    {
      "bedrockModel": {
        "modelIdentifier": "string",
        "inferenceParams": "string"
      }
    }
    ...
  ]
}

--output-data-config (structure)

An object that defines where the results of model evaluation job will be saved in Amazon S3.

s3Uri -> (string)

The Amazon S3 URI where the results of model evaluation job are saved.

Shorthand Syntax:

s3Uri=string

JSON Syntax:

{
  "s3Uri": "string"
}

--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

Global Options

--debug (boolean)

Turn on debug logging.

--endpoint-url (string)

Override command's default URL with the given URL.

--no-verify-ssl (boolean)

By default, the AWS CLI uses SSL when communicating with AWS services. For each SSL connection, the AWS CLI will verify SSL certificates. This option overrides the default behavior of verifying SSL certificates.

--no-paginate (boolean)

Disable automatic pagination. If automatic pagination is disabled, the AWS CLI will only make one call, for the first page of results.

--output (string)

The formatting style for command output.

• json
• text
• table

--query (string)

A JMESPath query to use in filtering the response data.

--profile (string)

Use a specific profile from your credential file.

--region (string)

The region to use. Overrides config/env settings.

--version (string)

Display the version of this tool.

--color (string)

Turn on/off color output.

• on
• off
• auto

--no-sign-request (boolean)

Do not sign requests. Credentials will not be loaded if this argument is provided.

--ca-bundle (string)

The CA certificate bundle to use when verifying SSL certificates. Overrides config/env settings.

--cli-read-timeout (int)

The maximum socket read time in seconds. If the value is set to 0, the socket read will be blocking and not timeout. The default value is 60 seconds.

--cli-connect-timeout (int)

The maximum socket connect time in seconds. If the value is set to 0, the socket connect will be blocking and not timeout. The default value is 60 seconds.

Output

jobArn -> (string)

The ARN of the model evaluation job.