Retrieves detailed information about an evaluator, including its configuration, status, and metadata¶

Description¶

Retrieves detailed information about an evaluator, including its configuration, status, and metadata. Works with both built-in and custom evaluators.

Usage¶

bedrockagentcorecontrol_get_evaluator(evaluatorId, includedData)

Arguments¶

evaluatorId

[required] The unique identifier of the evaluator to retrieve. Can be a built-in evaluator ID (e.g., Builtin.Helpfulness) or a custom evaluator ID.
includedData

Controls which data is returned in the response. ALL_DATA (default) returns the full evaluator including decrypted instructions and rating scale. For evaluators encrypted with a customer managed KMS key, this requires kms:Decrypt permission on the key. METADATA_ONLY returns evaluator metadata and model configuration without instructions or rating scale, and does not require any KMS permissions.

Value¶

A list with the following syntax:

list(
  evaluatorArn = "string",
  evaluatorId = "string",
  evaluatorName = "string",
  description = "string",
  evaluatorConfig = list(
    llmAsAJudge = list(
      instructions = "string",
      ratingScale = list(
        numerical = list(
          list(
            definition = "string",
            value = 123.0,
            label = "string"
          )
        ),
        categorical = list(
          list(
            definition = "string",
            label = "string"
          )
        )
      ),
      modelConfig = list(
        bedrockEvaluatorModelConfig = list(
          modelId = "string",
          inferenceConfig = list(
            maxTokens = 123,
            temperature = 123.0,
            topP = 123.0,
            stopSequences = list(
              "string"
            )
          ),
          additionalModelRequestFields = list()
        ),
        responsesEvaluatorModelConfig = list(
          modelId = "string",
          maxOutputTokens = 123,
          temperature = 123.0,
          topP = 123.0,
          reasoning = list(
            effort = "string"
          )
        )
      )
    ),
    codeBased = list(
      lambdaConfig = list(
        lambdaArn = "string",
        lambdaTimeoutInSeconds = 123
      )
    ),
    derived = list(
      baseEvaluatorId = "string",
      modelConfig = list(
        bedrockEvaluatorModelConfig = list(
          modelId = "string",
          inferenceConfig = list(
            maxTokens = 123,
            temperature = 123.0,
            topP = 123.0,
            stopSequences = list(
              "string"
            )
          ),
          additionalModelRequestFields = list()
        ),
        responsesEvaluatorModelConfig = list(
          modelId = "string",
          maxOutputTokens = 123,
          temperature = 123.0,
          topP = 123.0,
          reasoning = list(
            effort = "string"
          )
        )
      )
    )
  ),
  evaluatorType = "Builtin"|"ThirdParty"|"Custom"|"CustomCode"|"CustomDerived",
  provider = "AWS"|"DeepEval"|"AutoEval"|"Custom",
  level = "TOOL_CALL"|"TRACE"|"SESSION",
  status = "ACTIVE"|"CREATING"|"CREATE_FAILED"|"UPDATING"|"UPDATE_FAILED"|"DELETING",
  createdAt = as.POSIXct(
    "2015-01-01"
  ),
  updatedAt = as.POSIXct(
    "2015-01-01"
  ),
  lockedForModification = TRUE|FALSE,
  kmsKeyArn = "string"
)

Request syntax¶

svc$get_evaluator(
  evaluatorId = "string",
  includedData = "ALL_DATA"|"METADATA_ONLY"
)