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Get Evaluation Job

bedrock_get_evaluation_job R Documentation

Gets information about an evaluation job, such as the status of the job

Description

Gets information about an evaluation job, such as the status of the job.

Usage

bedrock_get_evaluation_job(jobIdentifier)

Arguments

jobIdentifier

[required] The Amazon Resource Name (ARN) of the evaluation job you want get information on.

Value

A list with the following syntax:

list(
  jobName = "string",
  status = "InProgress"|"Completed"|"Failed"|"Stopping"|"Stopped"|"Deleting",
  jobArn = "string",
  jobDescription = "string",
  roleArn = "string",
  customerEncryptionKeyId = "string",
  jobType = "Human"|"Automated",
  applicationType = "ModelEvaluation"|"RagEvaluation",
  evaluationConfig = list(
    automated = list(
      datasetMetricConfigs = list(
        list(
          taskType = "Summarization"|"Classification"|"QuestionAndAnswer"|"Generation"|"Custom",
          dataset = list(
            name = "string",
            datasetLocation = list(
              s3Uri = "string"
            )
          ),
          metricNames = list(
            "string"
          )
        )
      ),
      evaluatorModelConfig = list(
        bedrockEvaluatorModels = list(
          list(
            modelIdentifier = "string"
          )
        )
      )
    ),
    human = list(
      humanWorkflowConfig = list(
        flowDefinitionArn = "string",
        instructions = "string"
      ),
      customMetrics = list(
        list(
          name = "string",
          description = "string",
          ratingMethod = "string"
        )
      ),
      datasetMetricConfigs = list(
        list(
          taskType = "Summarization"|"Classification"|"QuestionAndAnswer"|"Generation"|"Custom",
          dataset = list(
            name = "string",
            datasetLocation = list(
              s3Uri = "string"
            )
          ),
          metricNames = list(
            "string"
          )
        )
      )
    )
  ),
  inferenceConfig = list(
    models = list(
      list(
        bedrockModel = list(
          modelIdentifier = "string",
          inferenceParams = "string",
          performanceConfig = list(
            latency = "standard"|"optimized"
          )
        )
      )
    ),
    ragConfigs = list(
      list(
        knowledgeBaseConfig = list(
          retrieveConfig = list(
            knowledgeBaseId = "string",
            knowledgeBaseRetrievalConfiguration = list(
              vectorSearchConfiguration = list(
                numberOfResults = 123,
                overrideSearchType = "HYBRID"|"SEMANTIC",
                filter = list(
                  equals = list(
                    key = "string",
                    value = list()
                  ),
                  notEquals = list(
                    key = "string",
                    value = list()
                  ),
                  greaterThan = list(
                    key = "string",
                    value = list()
                  ),
                  greaterThanOrEquals = list(
                    key = "string",
                    value = list()
                  ),
                  lessThan = list(
                    key = "string",
                    value = list()
                  ),
                  lessThanOrEquals = list(
                    key = "string",
                    value = list()
                  ),
                  in = list(
                    key = "string",
                    value = list()
                  ),
                  notIn = list(
                    key = "string",
                    value = list()
                  ),
                  startsWith = list(
                    key = "string",
                    value = list()
                  ),
                  listContains = list(
                    key = "string",
                    value = list()
                  ),
                  stringContains = list(
                    key = "string",
                    value = list()
                  ),
                  andAll = list(
                    list()
                  ),
                  orAll = list(
                    list()
                  )
                )
              )
            )
          ),
          retrieveAndGenerateConfig = list(
            type = "KNOWLEDGE_BASE"|"EXTERNAL_SOURCES",
            knowledgeBaseConfiguration = list(
              knowledgeBaseId = "string",
              modelArn = "string",
              retrievalConfiguration = list(
                vectorSearchConfiguration = list(
                  numberOfResults = 123,
                  overrideSearchType = "HYBRID"|"SEMANTIC",
                  filter = list(
                    equals = list(
                      key = "string",
                      value = list()
                    ),
                    notEquals = list(
                      key = "string",
                      value = list()
                    ),
                    greaterThan = list(
                      key = "string",
                      value = list()
                    ),
                    greaterThanOrEquals = list(
                      key = "string",
                      value = list()
                    ),
                    lessThan = list(
                      key = "string",
                      value = list()
                    ),
                    lessThanOrEquals = list(
                      key = "string",
                      value = list()
                    ),
                    in = list(
                      key = "string",
                      value = list()
                    ),
                    notIn = list(
                      key = "string",
                      value = list()
                    ),
                    startsWith = list(
                      key = "string",
                      value = list()
                    ),
                    listContains = list(
                      key = "string",
                      value = list()
                    ),
                    stringContains = list(
                      key = "string",
                      value = list()
                    ),
                    andAll = list(
                      list()
                    ),
                    orAll = list(
                      list()
                    )
                  )
                )
              ),
              generationConfiguration = list(
                promptTemplate = list(
                  textPromptTemplate = "string"
                ),
                guardrailConfiguration = list(
                  guardrailId = "string",
                  guardrailVersion = "string"
                ),
                kbInferenceConfig = list(
                  textInferenceConfig = list(
                    temperature = 123.0,
                    topP = 123.0,
                    maxTokens = 123,
                    stopSequences = list(
                      "string"
                    )
                  )
                ),
                additionalModelRequestFields = list(
                  list()
                )
              ),
              orchestrationConfiguration = list(
                queryTransformationConfiguration = list(
                  type = "QUERY_DECOMPOSITION"
                )
              )
            ),
            externalSourcesConfiguration = list(
              modelArn = "string",
              sources = list(
                list(
                  sourceType = "S3"|"BYTE_CONTENT",
                  s3Location = list(
                    uri = "string"
                  ),
                  byteContent = list(
                    identifier = "string",
                    contentType = "string",
                    data = raw
                  )
                )
              ),
              generationConfiguration = list(
                promptTemplate = list(
                  textPromptTemplate = "string"
                ),
                guardrailConfiguration = list(
                  guardrailId = "string",
                  guardrailVersion = "string"
                ),
                kbInferenceConfig = list(
                  textInferenceConfig = list(
                    temperature = 123.0,
                    topP = 123.0,
                    maxTokens = 123,
                    stopSequences = list(
                      "string"
                    )
                  )
                ),
                additionalModelRequestFields = list(
                  list()
                )
              )
            )
          )
        )
      )
    )
  ),
  outputDataConfig = list(
    s3Uri = "string"
  ),
  creationTime = as.POSIXct(
    "2015-01-01"
  ),
  lastModifiedTime = as.POSIXct(
    "2015-01-01"
  ),
  failureMessages = list(
    "string"
  )
)

Request syntax

svc$get_evaluation_job(
  jobIdentifier = "string"
)