Returns details of an AI recommendation job, including its status, model source, performance targets, optimization recommendations, and deployment configurations¶

Description¶

Returns details of an AI recommendation job, including its status, model source, performance targets, optimization recommendations, and deployment configurations.

Usage¶

sagemaker_describe_ai_recommendation_job(AIRecommendationJobName)

Arguments¶

AIRecommendationJobName

[required] The name of the AI recommendation job to describe.

Value¶

A list with the following syntax:

list(
  AIRecommendationJobName = "string",
  AIRecommendationJobArn = "string",
  AIRecommendationJobStatus = "InProgress"|"Completed"|"Failed"|"Stopping"|"Stopped",
  FailureReason = "string",
  ModelSource = list(
    S3 = list(
      S3Uri = "string"
    )
  ),
  OutputConfig = list(
    S3OutputLocation = "string",
    ModelPackageGroupIdentifier = "string",
    MlflowConfig = list(
      MlflowResourceArn = "string",
      MlflowExperimentName = "string",
      MlflowRunName = "string"
    )
  ),
  InferenceSpecification = list(
    Framework = "LMI"|"VLLM"
  ),
  AIWorkloadConfigIdentifier = "string",
  OptimizeModel = TRUE|FALSE,
  PerformanceTarget = list(
    Constraints = list(
      list(
        Metric = "ttft-ms"|"throughput"|"cost"
      )
    )
  ),
  Recommendations = list(
    list(
      RecommendationDescription = "string",
      OptimizationDetails = list(
        list(
          OptimizationType = "SpeculativeDecoding"|"KernelTuning",
          OptimizationConfig = list(
            "string"
          )
        )
      ),
      ModelDetails = list(
        ModelPackageArn = "string",
        InferenceSpecificationName = "string",
        InstanceDetails = list(
          list(
            InstanceType = "ml.g5.xlarge"|"ml.g5.2xlarge"|"ml.g5.4xlarge"|"ml.g5.8xlarge"|"ml.g5.12xlarge"|"ml.g5.16xlarge"|"ml.g5.24xlarge"|"ml.g5.48xlarge"|"ml.g6.xlarge"|"ml.g6.2xlarge"|"ml.g6.4xlarge"|"ml.g6.8xlarge"|"ml.g6.12xlarge"|"ml.g6.16xlarge"|"ml.g6.24xlarge"|"ml.g6.48xlarge"|"ml.g6e.xlarge"|"ml.g6e.2xlarge"|"ml.g6e.4xlarge"|"ml.g6e.8xlarge"|"ml.g6e.12xlarge"|"ml.g6e.16xlarge"|"ml.g6e.24xlarge"|"ml.g6e.48xlarge"|"ml.g7.2xlarge"|"ml.g7.4xlarge"|"ml.g7.8xlarge"|"ml.g7.12xlarge"|"ml.g7.24xlarge"|"ml.g7.48xlarge"|"ml.g7e.2xlarge"|"ml.g7e.4xlarge"|"ml.g7e.8xlarge"|"ml.g7e.12xlarge"|"ml.g7e.24xlarge"|"ml.g7e.48xlarge"|"ml.p3.2xlarge"|"ml.p3.8xlarge"|"ml.p3.16xlarge"|"ml.p4d.24xlarge"|"ml.p4de.24xlarge"|"ml.p5.4xlarge"|"ml.p5.48xlarge"|"ml.p5e.48xlarge"|"ml.p5en.48xlarge"|"ml.p6-b200.48xlarge",
            InstanceCount = 123,
            CopyCountPerInstance = 123
          )
        )
      ),
      DeploymentConfiguration = list(
        S3 = list(
          list(
            ChannelName = "string",
            Uri = "string"
          )
        ),
        ImageUri = "string",
        InstanceType = "ml.g5.xlarge"|"ml.g5.2xlarge"|"ml.g5.4xlarge"|"ml.g5.8xlarge"|"ml.g5.12xlarge"|"ml.g5.16xlarge"|"ml.g5.24xlarge"|"ml.g5.48xlarge"|"ml.g6.xlarge"|"ml.g6.2xlarge"|"ml.g6.4xlarge"|"ml.g6.8xlarge"|"ml.g6.12xlarge"|"ml.g6.16xlarge"|"ml.g6.24xlarge"|"ml.g6.48xlarge"|"ml.g6e.xlarge"|"ml.g6e.2xlarge"|"ml.g6e.4xlarge"|"ml.g6e.8xlarge"|"ml.g6e.12xlarge"|"ml.g6e.16xlarge"|"ml.g6e.24xlarge"|"ml.g6e.48xlarge"|"ml.g7.2xlarge"|"ml.g7.4xlarge"|"ml.g7.8xlarge"|"ml.g7.12xlarge"|"ml.g7.24xlarge"|"ml.g7.48xlarge"|"ml.g7e.2xlarge"|"ml.g7e.4xlarge"|"ml.g7e.8xlarge"|"ml.g7e.12xlarge"|"ml.g7e.24xlarge"|"ml.g7e.48xlarge"|"ml.p3.2xlarge"|"ml.p3.8xlarge"|"ml.p3.16xlarge"|"ml.p4d.24xlarge"|"ml.p4de.24xlarge"|"ml.p5.4xlarge"|"ml.p5.48xlarge"|"ml.p5e.48xlarge"|"ml.p5en.48xlarge"|"ml.p6-b200.48xlarge",
        InstanceCount = 123,
        CopyCountPerInstance = 123,
        EnvironmentVariables = list(
          "string"
        ),
        MinCpuMemoryRequiredInMb = 123
      ),
      AIBenchmarkJobArn = "string",
      ExpectedPerformance = list(
        list(
          Metric = "string",
          Stat = "string",
          Value = "string",
          Unit = "string"
        )
      ),
      AdapterDetails = list(
        ModelPackageArns = list(
          list(
            AdapterId = "string",
            ModelPackageArn = "string"
          )
        ),
        S3Uris = list(
          list(
            AdapterId = "string",
            S3Uri = "string"
          )
        )
      )
    )
  ),
  RoleArn = "string",
  ComputeSpec = list(
    InstanceTypes = list(
      "ml.g5.xlarge"|"ml.g5.2xlarge"|"ml.g5.4xlarge"|"ml.g5.8xlarge"|"ml.g5.12xlarge"|"ml.g5.16xlarge"|"ml.g5.24xlarge"|"ml.g5.48xlarge"|"ml.g6.xlarge"|"ml.g6.2xlarge"|"ml.g6.4xlarge"|"ml.g6.8xlarge"|"ml.g6.12xlarge"|"ml.g6.16xlarge"|"ml.g6.24xlarge"|"ml.g6.48xlarge"|"ml.g6e.xlarge"|"ml.g6e.2xlarge"|"ml.g6e.4xlarge"|"ml.g6e.8xlarge"|"ml.g6e.12xlarge"|"ml.g6e.16xlarge"|"ml.g6e.24xlarge"|"ml.g6e.48xlarge"|"ml.g7.2xlarge"|"ml.g7.4xlarge"|"ml.g7.8xlarge"|"ml.g7.12xlarge"|"ml.g7.24xlarge"|"ml.g7.48xlarge"|"ml.g7e.2xlarge"|"ml.g7e.4xlarge"|"ml.g7e.8xlarge"|"ml.g7e.12xlarge"|"ml.g7e.24xlarge"|"ml.g7e.48xlarge"|"ml.p3.2xlarge"|"ml.p3.8xlarge"|"ml.p3.16xlarge"|"ml.p4d.24xlarge"|"ml.p4de.24xlarge"|"ml.p5.4xlarge"|"ml.p5.48xlarge"|"ml.p5e.48xlarge"|"ml.p5en.48xlarge"|"ml.p6-b200.48xlarge"
    ),
    CapacityReservationConfig = list(
      CapacityReservationPreference = "capacity-reservations-only",
      MlReservationArns = list(
        "string"
      )
    )
  ),
  AdapterSource = list(
    ModelPackageArns = list(
      list(
        AdapterId = "string",
        ModelPackageArn = "string"
      )
    ),
    S3Uris = list(
      list(
        AdapterId = "string",
        S3Uri = "string"
      )
    )
  ),
  CreationTime = as.POSIXct(
    "2015-01-01"
  ),
  StartTime = as.POSIXct(
    "2015-01-01"
  ),
  EndTime = as.POSIXct(
    "2015-01-01"
  ),
  Tags = list(
    list(
      Key = "string",
      Value = "string"
    )
  )
)

Request syntax¶

svc$describe_ai_recommendation_job(
  AIRecommendationJobName = "string"
)