Class: Aws::Bedrock::Client

Inherits:
Seahorse::Client::Base show all
Includes:
ClientStubs
Defined in:
gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb

Overview

An API client for Bedrock. To construct a client, you need to configure a :region and :credentials.

client = Aws::Bedrock::Client.new(
  region: region_name,
  credentials: credentials,
  # ...
)

For details on configuring region and credentials see the developer guide.

See #initialize for a full list of supported configuration options.

Instance Attribute Summary

Attributes inherited from Seahorse::Client::Base

#config, #handlers

API Operations collapse

Instance Method Summary collapse

Methods included from ClientStubs

#api_requests, #stub_data, #stub_responses

Methods inherited from Seahorse::Client::Base

add_plugin, api, clear_plugins, define, new, #operation_names, plugins, remove_plugin, set_api, set_plugins

Methods included from Seahorse::Client::HandlerBuilder

#handle, #handle_request, #handle_response

Constructor Details

#initialize(options) ⇒ Client

Returns a new instance of Client.

Parameters:

  • options (Hash)

Options Hash (options):

  • :plugins (Array<Seahorse::Client::Plugin>) — default: []] —

    A list of plugins to apply to the client. Each plugin is either a class name or an instance of a plugin class.

  • :credentials (required, Aws::CredentialProvider) —

    Your AWS credentials. This can be an instance of any one of the following classes:

    • Aws::Credentials - Used for configuring static, non-refreshing credentials.

    • Aws::SharedCredentials - Used for loading static credentials from a shared file, such as ~/.aws/config.

    • Aws::AssumeRoleCredentials - Used when you need to assume a role.

    • Aws::AssumeRoleWebIdentityCredentials - Used when you need to assume a role after providing credentials via the web.

    • Aws::SSOCredentials - Used for loading credentials from AWS SSO using an access token generated from aws login.

    • Aws::ProcessCredentials - Used for loading credentials from a process that outputs to stdout.

    • Aws::InstanceProfileCredentials - Used for loading credentials from an EC2 IMDS on an EC2 instance.

    • Aws::ECSCredentials - Used for loading credentials from instances running in ECS.

    • Aws::CognitoIdentityCredentials - Used for loading credentials from the Cognito Identity service.

    When :credentials are not configured directly, the following locations will be searched for credentials:

    • Aws.config[:credentials]
    • The :access_key_id, :secret_access_key, :session_token, and :account_id options.
    • ENV['AWS_ACCESS_KEY_ID'], ENV['AWS_SECRET_ACCESS_KEY'], ENV['AWS_SESSION_TOKEN'], and ENV['AWS_ACCOUNT_ID']
    • ~/.aws/credentials
    • ~/.aws/config
    • EC2/ECS IMDS instance profile - When used by default, the timeouts are very aggressive. Construct and pass an instance of Aws::InstanceProfileCredentials or Aws::ECSCredentials to enable retries and extended timeouts. Instance profile credential fetching can be disabled by setting ENV['AWS_EC2_METADATA_DISABLED'] to true.
  • :region (required, String) —

    The AWS region to connect to. The configured :region is used to determine the service :endpoint. When not passed, a default :region is searched for in the following locations:

    • Aws.config[:region]
    • ENV['AWS_REGION']
    • ENV['AMAZON_REGION']
    • ENV['AWS_DEFAULT_REGION']
    • ~/.aws/credentials
    • ~/.aws/config
  • :access_key_id (String)
  • :account_id (String)
  • :active_endpoint_cache (Boolean) — default: false —

    When set to true, a thread polling for endpoints will be running in the background every 60 secs (default). Defaults to false.

  • :adaptive_retry_wait_to_fill (Boolean) — default: true —

    Used only in adaptive retry mode. When true, the request will sleep until there is sufficent client side capacity to retry the request. When false, the request will raise a RetryCapacityNotAvailableError and will not retry instead of sleeping.

  • :client_side_monitoring (Boolean) — default: false —

    When true, client-side metrics will be collected for all API requests from this client.

  • :client_side_monitoring_client_id (String) — default: "" —

    Allows you to provide an identifier for this client which will be attached to all generated client side metrics. Defaults to an empty string.

  • :client_side_monitoring_host (String) — default: "127.0.0.1" —

    Allows you to specify the DNS hostname or IPv4 or IPv6 address that the client side monitoring agent is running on, where client metrics will be published via UDP.

  • :client_side_monitoring_port (Integer) — default: 31000 —

    Required for publishing client metrics. The port that the client side monitoring agent is running on, where client metrics will be published via UDP.

  • :client_side_monitoring_publisher (Aws::ClientSideMonitoring::Publisher) — default: Aws::ClientSideMonitoring::Publisher —

    Allows you to provide a custom client-side monitoring publisher class. By default, will use the Client Side Monitoring Agent Publisher.

  • :convert_params (Boolean) — default: true —

    When true, an attempt is made to coerce request parameters into the required types.

  • :correct_clock_skew (Boolean) — default: true —

    Used only in standard and adaptive retry modes. Specifies whether to apply a clock skew correction and retry requests with skewed client clocks.

  • :defaults_mode (String) — default: "legacy" —

    See DefaultsModeConfiguration for a list of the accepted modes and the configuration defaults that are included.

  • :disable_host_prefix_injection (Boolean) — default: false —

    When true, the SDK will not prepend the modeled host prefix to the endpoint.

  • :disable_request_compression (Boolean) — default: false —

    When set to 'true' the request body will not be compressed for supported operations.

  • :endpoint (String, URI::HTTPS, URI::HTTP) —

    Normally you should not configure the :endpoint option directly. This is normally constructed from the :region option. Configuring :endpoint is normally reserved for connecting to test or custom endpoints. The endpoint should be a URI formatted like:

    'http://example.com'
'https://example.com'
'http://example.com:123'
  • :endpoint_cache_max_entries (Integer) — default: 1000 —

    Used for the maximum size limit of the LRU cache storing endpoints data for endpoint discovery enabled operations. Defaults to 1000.

  • :endpoint_cache_max_threads (Integer) — default: 10 —

    Used for the maximum threads in use for polling endpoints to be cached, defaults to 10.

  • :endpoint_cache_poll_interval (Integer) — default: 60 —

    When :endpoint_discovery and :active_endpoint_cache is enabled, Use this option to config the time interval in seconds for making requests fetching endpoints information. Defaults to 60 sec.

  • :endpoint_discovery (Boolean) — default: false —

    When set to true, endpoint discovery will be enabled for operations when available.

  • :ignore_configured_endpoint_urls (Boolean) —

    Setting to true disables use of endpoint URLs provided via environment variables and the shared configuration file.

  • :log_formatter (Aws::Log::Formatter) — default: Aws::Log::Formatter.default —

    The log formatter.

  • :log_level (Symbol) — default: :info —

    The log level to send messages to the :logger at.

  • :logger (Logger) —

    The Logger instance to send log messages to. If this option is not set, logging will be disabled.

  • :max_attempts (Integer) — default: 3 —

    An integer representing the maximum number attempts that will be made for a single request, including the initial attempt. For example, setting this value to 5 will result in a request being retried up to 4 times. Used in standard and adaptive retry modes.

  • :profile (String) — default: "default" —

    Used when loading credentials from the shared credentials file at HOME/.aws/credentials. When not specified, 'default' is used.

  • :request_checksum_calculation (String) — default: "when_supported" —

    Determines when a checksum will be calculated for request payloads. Values are:

    • when_supported - (default) When set, a checksum will be calculated for all request payloads of operations modeled with the httpChecksum trait where requestChecksumRequired is true and/or a requestAlgorithmMember is modeled.
    • when_required - When set, a checksum will only be calculated for request payloads of operations modeled with the httpChecksum trait where requestChecksumRequired is true or where a requestAlgorithmMember is modeled and supplied.
  • :request_min_compression_size_bytes (Integer) — default: 10240 —

    The minimum size in bytes that triggers compression for request bodies. The value must be non-negative integer value between 0 and 10485780 bytes inclusive.

  • :response_checksum_validation (String) — default: "when_supported" —

    Determines when checksum validation will be performed on response payloads. Values are:

    • when_supported - (default) When set, checksum validation is performed on all response payloads of operations modeled with the httpChecksum trait where responseAlgorithms is modeled, except when no modeled checksum algorithms are supported.
    • when_required - When set, checksum validation is not performed on response payloads of operations unless the checksum algorithm is supported and the requestValidationModeMember member is set to ENABLED.
  • :retry_backoff (Proc) —

    A proc or lambda used for backoff. Defaults to 2**retries * retry_base_delay. This option is only used in the legacy retry mode.

  • :retry_base_delay (Float) — default: 0.3 —

    The base delay in seconds used by the default backoff function. This option is only used in the legacy retry mode.

  • :retry_jitter (Symbol) — default: :none —

    A delay randomiser function used by the default backoff function. Some predefined functions can be referenced by name - :none, :equal, :full, otherwise a Proc that takes and returns a number. This option is only used in the legacy retry mode.

    @see https://www.awsarchitectureblog.com/2015/03/backoff.html

  • :retry_limit (Integer) — default: 3 —

    The maximum number of times to retry failed requests. Only ~ 500 level server errors and certain ~ 400 level client errors are retried. Generally, these are throttling errors, data checksum errors, networking errors, timeout errors, auth errors, endpoint discovery, and errors from expired credentials. This option is only used in the legacy retry mode.

  • :retry_max_delay (Integer) — default: 0 —

    The maximum number of seconds to delay between retries (0 for no limit) used by the default backoff function. This option is only used in the legacy retry mode.

  • :retry_mode (String) — default: "legacy" —

    Specifies which retry algorithm to use. Values are:

    • legacy - The pre-existing retry behavior. This is default value if no retry mode is provided.

    • standard - A standardized set of retry rules across the AWS SDKs. This includes support for retry quotas, which limit the number of unsuccessful retries a client can make.

    • adaptive - An experimental retry mode that includes all the functionality of standard mode along with automatic client side throttling. This is a provisional mode that may change behavior in the future.

  • :sdk_ua_app_id (String) —

    A unique and opaque application ID that is appended to the User-Agent header as app/sdk_ua_app_id. It should have a maximum length of 50. This variable is sourced from environment variable AWS_SDK_UA_APP_ID or the shared config profile attribute sdk_ua_app_id.

  • :secret_access_key (String)
  • :session_token (String)
  • :sigv4a_signing_region_set (Array) —

    A list of regions that should be signed with SigV4a signing. When not passed, a default :sigv4a_signing_region_set is searched for in the following locations:

    • Aws.config[:sigv4a_signing_region_set]
    • ENV['AWS_SIGV4A_SIGNING_REGION_SET']
    • ~/.aws/config
  • :stub_responses (Boolean) — default: false —

    Causes the client to return stubbed responses. By default fake responses are generated and returned. You can specify the response data to return or errors to raise by calling ClientStubs#stub_responses. See ClientStubs for more information.

    Please note When response stubbing is enabled, no HTTP requests are made, and retries are disabled.

  • :telemetry_provider (Aws::Telemetry::TelemetryProviderBase) — default: Aws::Telemetry::NoOpTelemetryProvider —

    Allows you to provide a telemetry provider, which is used to emit telemetry data. By default, uses NoOpTelemetryProvider which will not record or emit any telemetry data. The SDK supports the following telemetry providers:

    • OpenTelemetry (OTel) - To use the OTel provider, install and require the opentelemetry-sdk gem and then, pass in an instance of a Aws::Telemetry::OTelProvider for telemetry provider.
  • :token_provider (Aws::TokenProvider) —

    A Bearer Token Provider. This can be an instance of any one of the following classes:

    • Aws::StaticTokenProvider - Used for configuring static, non-refreshing tokens.

    • Aws::SSOTokenProvider - Used for loading tokens from AWS SSO using an access token generated from aws login.

    When :token_provider is not configured directly, the Aws::TokenProviderChain will be used to search for tokens configured for your profile in shared configuration files.

  • :use_dualstack_endpoint (Boolean) —

    When set to true, dualstack enabled endpoints (with .aws TLD) will be used if available.

  • :use_fips_endpoint (Boolean) —

    When set to true, fips compatible endpoints will be used if available. When a fips region is used, the region is normalized and this config is set to true.

  • :validate_params (Boolean) — default: true —

    When true, request parameters are validated before sending the request.

  • :endpoint_provider (Aws::Bedrock::EndpointProvider) —

    The endpoint provider used to resolve endpoints. Any object that responds to #resolve_endpoint(parameters) where parameters is a Struct similar to Aws::Bedrock::EndpointParameters.

  • :http_continue_timeout (Float) — default: 1 —

    The number of seconds to wait for a 100-continue response before sending the request body. This option has no effect unless the request has "Expect" header set to "100-continue". Defaults to nil which disables this behaviour. This value can safely be set per request on the session.

  • :http_idle_timeout (Float) — default: 5 —

    The number of seconds a connection is allowed to sit idle before it is considered stale. Stale connections are closed and removed from the pool before making a request.

  • :http_open_timeout (Float) — default: 15 —

    The default number of seconds to wait for response data. This value can safely be set per-request on the session.

  • :http_proxy (URI::HTTP, String) —

    A proxy to send requests through. Formatted like 'http://proxy.com:123'.

  • :http_read_timeout (Float) — default: 60 —

    The default number of seconds to wait for response data. This value can safely be set per-request on the session.

  • :http_wire_trace (Boolean) — default: false —

    When true, HTTP debug output will be sent to the :logger.

  • :on_chunk_received (Proc) —

    When a Proc object is provided, it will be used as callback when each chunk of the response body is received. It provides three arguments: the chunk, the number of bytes received, and the total number of bytes in the response (or nil if the server did not send a content-length).

  • :on_chunk_sent (Proc) —

    When a Proc object is provided, it will be used as callback when each chunk of the request body is sent. It provides three arguments: the chunk, the number of bytes read from the body, and the total number of bytes in the body.

  • :raise_response_errors (Boolean) — default: true —

    When true, response errors are raised.

  • :ssl_ca_bundle (String) —

    Full path to the SSL certificate authority bundle file that should be used when verifying peer certificates. If you do not pass :ssl_ca_bundle or :ssl_ca_directory the the system default will be used if available.

  • :ssl_ca_directory (String) —

    Full path of the directory that contains the unbundled SSL certificate authority files for verifying peer certificates. If you do not pass :ssl_ca_bundle or :ssl_ca_directory the the system default will be used if available.

  • :ssl_ca_store (String) —

    Sets the X509::Store to verify peer certificate.

  • :ssl_cert (OpenSSL::X509::Certificate) —

    Sets a client certificate when creating http connections.

  • :ssl_key (OpenSSL::PKey) —

    Sets a client key when creating http connections.

  • :ssl_timeout (Float) —

    Sets the SSL timeout in seconds

  • :ssl_verify_peer (Boolean) — default: true —

    When true, SSL peer certificates are verified when establishing a connection.



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 466

def initialize(*args)
  super
end

Instance Method Details

#batch_delete_evaluation_job(params = {}) ⇒ Types::BatchDeleteEvaluationJobResponse

Deletes a batch of evaluation jobs. An evaluation job can only be deleted if it has following status FAILED, COMPLETED, and STOPPED. You can request up to 25 model evaluation jobs be deleted in a single request.

Examples:

Example: Delete evaluation jobs


# The following example shows a request to delete two model evaluation jobs, where one of the jobs is not found.

resp = client.batch_delete_evaluation_job({
  job_identifiers: [
    "arn:aws:bedrock:us-east-2:123456789012:evaluation-job/12rnxmplqv0v", 
    "arn:aws:bedrock:us-east-2:123456789012:evaluation-job/rispxmpl12rn", 
  ], 
})

resp.to_h outputs the following:
{
  errors: [
    {
      code: "404", 
      job_identifier: "arn:aws:bedrock:us-east-2:123456789012:evaluation-job/rispxmpl12rn", 
      message: "Unable to locate this job to delete.", 
    }, 
  ], 
  evaluation_jobs: [
    {
      job_identifier: "arn:aws:bedrock:us-east-2:123456789012:evaluation-job/12rnxmplqv0v", 
      job_status: "Deleting", 
    }, 
  ], 
}

Request syntax with placeholder values


resp = client.batch_delete_evaluation_job({
  job_identifiers: ["EvaluationJobIdentifier"], # required
})

Response structure


resp.errors #=> Array
resp.errors[0].job_identifier #=> String
resp.errors[0].code #=> String
resp.errors[0].message #=> String
resp.evaluation_jobs #=> Array
resp.evaluation_jobs[0].job_identifier #=> String
resp.evaluation_jobs[0].job_status #=> String, one of "InProgress", "Completed", "Failed", "Stopping", "Stopped", "Deleting"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :job_identifiers (required, Array<String>) —

    A list of one or more evaluation job Amazon Resource Names (ARNs) you want to delete.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 535

def batch_delete_evaluation_job(params = {}, options = {})
  req = build_request(:batch_delete_evaluation_job, params)
  req.send_request(options)
end

#create_custom_model(params = {}) ⇒ Types::CreateCustomModelResponse

Creates a new custom model in Amazon Bedrock. After the model is active, you can use it for inference.

To use the model for inference, you must purchase Provisioned Throughput for it. You can't use On-demand inference with these custom models. For more information about Provisioned Throughput, see Provisioned Throughput.

The model appears in ListCustomModels with a customizationType of imported. To track the status of the new model, you use the GetCustomModel API operation. The model can be in the following states:

  • Creating - Initial state during validation and registration

  • Active - Model is ready for use in inference

  • Failed - Creation process encountered an error

Related APIs

Examples:

Example: Successful CreateCustomModel API call


resp = client.create_custom_model({
  client_request_token: "foo", 
  model_kms_key_arn: "arn:aws:kms:us-east-1:123456789012:key/1234abcd-12ab-34cd-56ef-1234567890ab", 
  model_name: "SampleModel", 
  model_source_config: {
    s3_data_source: {
      s3_uri: "s3://my-bucket/folder", 
    }, 
  }, 
  model_tags: [
    {
      key: "foo", 
      value: "foo", 
    }, 
    {
      key: "foo", 
      value: "foo", 
    }, 
  ], 
  role_arn: "arn:aws:iam::123456789012:role/SampleRole", 
})

resp.to_h outputs the following:
{
  model_arn: "arn:aws:bedrock:us-east-1:123456789012:custom-model/imported/abcdef123456", 
}

Request syntax with placeholder values


resp = client.create_custom_model({
  model_name: "CustomModelName", # required
  model_source_config: { # required
    s3_data_source: {
      s3_uri: "S3Uri", # required
    },
  },
  model_kms_key_arn: "KmsKeyArn",
  role_arn: "RoleArn",
  model_tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
  client_request_token: "IdempotencyToken",
})

Response structure


resp.model_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_name (required, String) —

    A unique name for the custom model.

  • :model_source_config (required, Types::ModelDataSource) —

    The data source for the model. The Amazon S3 URI in the model source must be for the Amazon-managed Amazon S3 bucket containing your model artifacts.

  • :model_kms_key_arn (String) —

    The Amazon Resource Name (ARN) of the customer managed KMS key to encrypt the custom model. If you don't provide a KMS key, Amazon Bedrock uses an Amazon Web Services-managed KMS key to encrypt the model.

    If you provide a customer managed KMS key, your Amazon Bedrock service role must have permissions to use it. For more information see Encryption of imported models.

  • :role_arn (String) —

    The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock assumes to perform tasks on your behalf. This role must have permissions to access the Amazon S3 bucket containing your model artifacts and the KMS key (if specified). For more information, see Setting up an IAM service role for importing models in the Amazon Bedrock User Guide.

  • :model_tags (Array<Types::Tag>) —

    A list of key-value pairs to associate with the custom model resource. You can use these tags to organize and identify your resources.

    For more information, see Tagging resources in the Amazon Bedrock User Guide.

  • :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.

    A suitable default value is auto-generated. You should normally not need to pass this option.**

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 695

def create_custom_model(params = {}, options = {})
  req = build_request(:create_custom_model, params)
  req.send_request(options)
end

#create_evaluation_job(params = {}) ⇒ Types::CreateEvaluationJobResponse

Creates an evaluation job.

Examples:

Request syntax with placeholder values


resp = client.create_evaluation_job({
  job_name: "EvaluationJobName", # required
  job_description: "EvaluationJobDescription",
  client_request_token: "IdempotencyToken",
  role_arn: "RoleArn", # required
  customer_encryption_key_id: "KmsKeyId",
  job_tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
  application_type: "ModelEvaluation", # accepts ModelEvaluation, RagEvaluation
  evaluation_config: { # required
    automated: {
      dataset_metric_configs: [ # required
        {
          task_type: "Summarization", # required, accepts Summarization, Classification, QuestionAndAnswer, Generation, Custom
          dataset: { # required
            name: "EvaluationDatasetName", # required
            dataset_location: {
              s3_uri: "S3Uri",
            },
          },
          metric_names: ["EvaluationMetricName"], # required
        },
      ],
      evaluator_model_config: {
        bedrock_evaluator_models: [
          {
            model_identifier: "EvaluatorModelIdentifier", # required
          },
        ],
      },
      custom_metric_config: {
        custom_metrics: [ # required
          {
            custom_metric_definition: {
              name: "MetricName", # required
              instructions: "CustomMetricInstructions", # required
              rating_scale: [
                {
                  definition: "RatingScaleItemDefinition", # required
                  value: { # required
                    string_value: "RatingScaleItemValueStringValueString",
                    float_value: 1.0,
                  },
                },
              ],
            },
          },
        ],
        evaluator_model_config: { # required
          bedrock_evaluator_models: [ # required
            {
              model_identifier: "EvaluatorModelIdentifier", # required
            },
          ],
        },
      },
    },
    human: {
      human_workflow_config: {
        flow_definition_arn: "SageMakerFlowDefinitionArn", # required
        instructions: "HumanTaskInstructions",
      },
      custom_metrics: [
        {
          name: "EvaluationMetricName", # required
          description: "EvaluationMetricDescription",
          rating_method: "EvaluationRatingMethod", # required
        },
      ],
      dataset_metric_configs: [ # required
        {
          task_type: "Summarization", # required, accepts Summarization, Classification, QuestionAndAnswer, Generation, Custom
          dataset: { # required
            name: "EvaluationDatasetName", # required
            dataset_location: {
              s3_uri: "S3Uri",
            },
          },
          metric_names: ["EvaluationMetricName"], # required
        },
      ],
    },
  },
  inference_config: { # required
    models: [
      {
        bedrock_model: {
          model_identifier: "EvaluationBedrockModelIdentifier", # required
          inference_params: "EvaluationModelInferenceParams",
          performance_config: {
            latency: "standard", # accepts standard, optimized
          },
        },
        precomputed_inference_source: {
          inference_source_identifier: "EvaluationPrecomputedInferenceSourceIdentifier", # required
        },
      },
    ],
    rag_configs: [
      {
        knowledge_base_config: {
          retrieve_config: {
            knowledge_base_id: "KnowledgeBaseId", # required
            knowledge_base_retrieval_configuration: { # required
              vector_search_configuration: { # required
                number_of_results: 1,
                override_search_type: "HYBRID", # accepts HYBRID, SEMANTIC
                filter: {
                  equals: {
                    key: "FilterKey", # required
                    value: { # required
                    },
                  },
                  not_equals: {
                    key: "FilterKey", # required
                    value: { # required
                    },
                  },
                  greater_than: {
                    key: "FilterKey", # required
                    value: { # required
                    },
                  },
                  greater_than_or_equals: {
                    key: "FilterKey", # required
                    value: { # required
                    },
                  },
                  less_than: {
                    key: "FilterKey", # required
                    value: { # required
                    },
                  },
                  less_than_or_equals: {
                    key: "FilterKey", # required
                    value: { # required
                    },
                  },
                  in: {
                    key: "FilterKey", # required
                    value: { # required
                    },
                  },
                  not_in: {
                    key: "FilterKey", # required
                    value: { # required
                    },
                  },
                  starts_with: {
                    key: "FilterKey", # required
                    value: { # required
                    },
                  },
                  list_contains: {
                    key: "FilterKey", # required
                    value: { # required
                    },
                  },
                  string_contains: {
                    key: "FilterKey", # required
                    value: { # required
                    },
                  },
                  and_all: [
                    {
                      # recursive RetrievalFilter
                    },
                  ],
                  or_all: [
                    {
                      # recursive RetrievalFilter
                    },
                  ],
                },
              },
            },
          },
          retrieve_and_generate_config: {
            type: "KNOWLEDGE_BASE", # required, accepts KNOWLEDGE_BASE, EXTERNAL_SOURCES
            knowledge_base_configuration: {
              knowledge_base_id: "KnowledgeBaseId", # required
              model_arn: "BedrockModelArn", # required
              retrieval_configuration: {
                vector_search_configuration: { # required
                  number_of_results: 1,
                  override_search_type: "HYBRID", # accepts HYBRID, SEMANTIC
                  filter: {
                    equals: {
                      key: "FilterKey", # required
                      value: { # required
                      },
                    },
                    not_equals: {
                      key: "FilterKey", # required
                      value: { # required
                      },
                    },
                    greater_than: {
                      key: "FilterKey", # required
                      value: { # required
                      },
                    },
                    greater_than_or_equals: {
                      key: "FilterKey", # required
                      value: { # required
                      },
                    },
                    less_than: {
                      key: "FilterKey", # required
                      value: { # required
                      },
                    },
                    less_than_or_equals: {
                      key: "FilterKey", # required
                      value: { # required
                      },
                    },
                    in: {
                      key: "FilterKey", # required
                      value: { # required
                      },
                    },
                    not_in: {
                      key: "FilterKey", # required
                      value: { # required
                      },
                    },
                    starts_with: {
                      key: "FilterKey", # required
                      value: { # required
                      },
                    },
                    list_contains: {
                      key: "FilterKey", # required
                      value: { # required
                      },
                    },
                    string_contains: {
                      key: "FilterKey", # required
                      value: { # required
                      },
                    },
                    and_all: [
                      {
                        # recursive RetrievalFilter
                      },
                    ],
                    or_all: [
                      {
                        # recursive RetrievalFilter
                      },
                    ],
                  },
                },
              },
              generation_configuration: {
                prompt_template: {
                  text_prompt_template: "TextPromptTemplate",
                },
                guardrail_configuration: {
                  guardrail_id: "GuardrailConfigurationGuardrailIdString", # required
                  guardrail_version: "GuardrailConfigurationGuardrailVersionString", # required
                },
                kb_inference_config: {
                  text_inference_config: {
                    temperature: 1.0,
                    top_p: 1.0,
                    max_tokens: 1,
                    stop_sequences: ["RAGStopSequencesMemberString"],
                  },
                },
                additional_model_request_fields: {
                  "AdditionalModelRequestFieldsKey" => {
                  },
                },
              },
              orchestration_configuration: {
                query_transformation_configuration: { # required
                  type: "QUERY_DECOMPOSITION", # required, accepts QUERY_DECOMPOSITION
                },
              },
            },
            external_sources_configuration: {
              model_arn: "BedrockModelArn", # required
              sources: [ # required
                {
                  source_type: "S3", # required, accepts S3, BYTE_CONTENT
                  s3_location: {
                    uri: "kBS3Uri", # required
                  },
                  byte_content: {
                    identifier: "Identifier", # required
                    content_type: "ContentType", # required
                    data: "data", # required
                  },
                },
              ],
              generation_configuration: {
                prompt_template: {
                  text_prompt_template: "TextPromptTemplate",
                },
                guardrail_configuration: {
                  guardrail_id: "GuardrailConfigurationGuardrailIdString", # required
                  guardrail_version: "GuardrailConfigurationGuardrailVersionString", # required
                },
                kb_inference_config: {
                  text_inference_config: {
                    temperature: 1.0,
                    top_p: 1.0,
                    max_tokens: 1,
                    stop_sequences: ["RAGStopSequencesMemberString"],
                  },
                },
                additional_model_request_fields: {
                  "AdditionalModelRequestFieldsKey" => {
                  },
                },
              },
            },
          },
        },
        precomputed_rag_source_config: {
          retrieve_source_config: {
            rag_source_identifier: "EvaluationPrecomputedRagSourceIdentifier", # required
          },
          retrieve_and_generate_source_config: {
            rag_source_identifier: "EvaluationPrecomputedRagSourceIdentifier", # required
          },
        },
      },
    ],
  },
  output_data_config: { # required
    s3_uri: "S3Uri", # required
  },
})

Response structure


resp.job_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :job_name (required, String) —

    A name for the evaluation job. Names must unique with your Amazon Web Services account, and your account's Amazon Web Services region.

  • :job_description (String) —

    A description of the 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.

    A suitable default value is auto-generated. You should normally not need to pass this option.**

  • :role_arn (required, String) —

    The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. To learn more about the required permissions, see Required permissions for model evaluations.

  • :customer_encryption_key_id (String) —

    Specify your customer managed encryption key Amazon Resource Name (ARN) that will be used to encrypt your evaluation job.

  • :job_tags (Array<Types::Tag>) —

    Tags to attach to the model evaluation job.

  • :application_type (String) —

    Specifies whether the evaluation job is for evaluating a model or evaluating a knowledge base (retrieval and response generation).

  • :evaluation_config (required, Types::EvaluationConfig) —

    Contains the configuration details of either an automated or human-based evaluation job.

  • :inference_config (required, Types::EvaluationInferenceConfig) —

    Contains the configuration details of the inference model for the evaluation job.

    For model evaluation jobs, automated jobs support a single model or inference profile, and jobs that use human workers support two models or inference profiles.

  • :output_data_config (required, Types::EvaluationOutputDataConfig) —

    Contains the configuration details of the Amazon S3 bucket for storing the results of the evaluation job.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1118

def create_evaluation_job(params = {}, options = {})
  req = build_request(:create_evaluation_job, params)
  req.send_request(options)
end

#create_guardrail(params = {}) ⇒ Types::CreateGuardrailResponse

Creates a guardrail to block topics and to implement safeguards for your generative AI applications.

You can configure the following policies in a guardrail to avoid undesirable and harmful content, filter out denied topics and words, and remove sensitive information for privacy protection.

  • Content filters - Adjust filter strengths to block input prompts or model responses containing harmful content.

  • Denied topics - Define a set of topics that are undesirable in the context of your application. These topics will be blocked if detected in user queries or model responses.

  • Word filters - Configure filters to block undesirable words, phrases, and profanity. Such words can include offensive terms, competitor names etc.

  • Sensitive information filters - Block or mask sensitive information such as personally identifiable information (PII) or custom regex in user inputs and model responses.

In addition to the above policies, you can also configure the messages to be returned to the user if a user input or model response is in violation of the policies defined in the guardrail.

For more information, see Amazon Bedrock Guardrails in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.create_guardrail({
  name: "GuardrailName", # required
  description: "GuardrailDescription",
  topic_policy_config: {
    topics_config: [ # required
      {
        name: "GuardrailTopicName", # required
        definition: "GuardrailTopicDefinition", # required
        examples: ["GuardrailTopicExample"],
        type: "DENY", # required, accepts DENY
        input_action: "BLOCK", # accepts BLOCK, NONE
        output_action: "BLOCK", # accepts BLOCK, NONE
        input_enabled: false,
        output_enabled: false,
      },
    ],
  },
  content_policy_config: {
    filters_config: [ # required
      {
        type: "SEXUAL", # required, accepts SEXUAL, VIOLENCE, HATE, INSULTS, MISCONDUCT, PROMPT_ATTACK
        input_strength: "NONE", # required, accepts NONE, LOW, MEDIUM, HIGH
        output_strength: "NONE", # required, accepts NONE, LOW, MEDIUM, HIGH
        input_modalities: ["TEXT"], # accepts TEXT, IMAGE
        output_modalities: ["TEXT"], # accepts TEXT, IMAGE
        input_action: "BLOCK", # accepts BLOCK, NONE
        output_action: "BLOCK", # accepts BLOCK, NONE
        input_enabled: false,
        output_enabled: false,
      },
    ],
  },
  word_policy_config: {
    words_config: [
      {
        text: "GuardrailWordConfigTextString", # required
        input_action: "BLOCK", # accepts BLOCK, NONE
        output_action: "BLOCK", # accepts BLOCK, NONE
        input_enabled: false,
        output_enabled: false,
      },
    ],
    managed_word_lists_config: [
      {
        type: "PROFANITY", # required, accepts PROFANITY
        input_action: "BLOCK", # accepts BLOCK, NONE
        output_action: "BLOCK", # accepts BLOCK, NONE
        input_enabled: false,
        output_enabled: false,
      },
    ],
  },
  sensitive_information_policy_config: {
    pii_entities_config: [
      {
        type: "ADDRESS", # required, accepts ADDRESS, AGE, AWS_ACCESS_KEY, AWS_SECRET_KEY, CA_HEALTH_NUMBER, CA_SOCIAL_INSURANCE_NUMBER, CREDIT_DEBIT_CARD_CVV, CREDIT_DEBIT_CARD_EXPIRY, CREDIT_DEBIT_CARD_NUMBER, DRIVER_ID, EMAIL, INTERNATIONAL_BANK_ACCOUNT_NUMBER, IP_ADDRESS, LICENSE_PLATE, MAC_ADDRESS, NAME, PASSWORD, PHONE, PIN, SWIFT_CODE, UK_NATIONAL_HEALTH_SERVICE_NUMBER, UK_NATIONAL_INSURANCE_NUMBER, UK_UNIQUE_TAXPAYER_REFERENCE_NUMBER, URL, USERNAME, US_BANK_ACCOUNT_NUMBER, US_BANK_ROUTING_NUMBER, US_INDIVIDUAL_TAX_IDENTIFICATION_NUMBER, US_PASSPORT_NUMBER, US_SOCIAL_SECURITY_NUMBER, VEHICLE_IDENTIFICATION_NUMBER
        action: "BLOCK", # required, accepts BLOCK, ANONYMIZE, NONE
        input_action: "BLOCK", # accepts BLOCK, ANONYMIZE, NONE
        output_action: "BLOCK", # accepts BLOCK, ANONYMIZE, NONE
        input_enabled: false,
        output_enabled: false,
      },
    ],
    regexes_config: [
      {
        name: "GuardrailRegexConfigNameString", # required
        description: "GuardrailRegexConfigDescriptionString",
        pattern: "GuardrailRegexConfigPatternString", # required
        action: "BLOCK", # required, accepts BLOCK, ANONYMIZE, NONE
        input_action: "BLOCK", # accepts BLOCK, ANONYMIZE, NONE
        output_action: "BLOCK", # accepts BLOCK, ANONYMIZE, NONE
        input_enabled: false,
        output_enabled: false,
      },
    ],
  },
  contextual_grounding_policy_config: {
    filters_config: [ # required
      {
        type: "GROUNDING", # required, accepts GROUNDING, RELEVANCE
        threshold: 1.0, # required
        action: "BLOCK", # accepts BLOCK, NONE
        enabled: false,
      },
    ],
  },
  cross_region_config: {
    guardrail_profile_identifier: "GuardrailCrossRegionGuardrailProfileIdentifier", # required
  },
  blocked_input_messaging: "GuardrailBlockedMessaging", # required
  blocked_outputs_messaging: "GuardrailBlockedMessaging", # required
  kms_key_id: "KmsKeyId",
  tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
  client_request_token: "IdempotencyToken",
})

Response structure


resp.guardrail_id #=> String
resp.guardrail_arn #=> String
resp.version #=> String
resp.created_at #=> Time

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :name (required, String) —

    The name to give the guardrail.

  • :description (String) —

    A description of the guardrail.

  • :topic_policy_config (Types::GuardrailTopicPolicyConfig) —

    The topic policies to configure for the guardrail.

  • :content_policy_config (Types::GuardrailContentPolicyConfig) —

    The content filter policies to configure for the guardrail.

  • :word_policy_config (Types::GuardrailWordPolicyConfig) —

    The word policy you configure for the guardrail.

  • :sensitive_information_policy_config (Types::GuardrailSensitiveInformationPolicyConfig) —

    The sensitive information policy to configure for the guardrail.

  • :contextual_grounding_policy_config (Types::GuardrailContextualGroundingPolicyConfig) —

    The contextual grounding policy configuration used to create a guardrail.

  • :cross_region_config (Types::GuardrailCrossRegionConfig) —

    The system-defined guardrail profile that you're using with your guardrail. Guardrail profiles define the destination Amazon Web Services Regions where guardrail inference requests can be automatically routed.

    For more information, see the Amazon Bedrock User Guide.

  • :blocked_input_messaging (required, String) —

    The message to return when the guardrail blocks a prompt.

  • :blocked_outputs_messaging (required, String) —

    The message to return when the guardrail blocks a model response.

  • :kms_key_id (String) —

    The ARN of the KMS key that you use to encrypt the guardrail.

  • :tags (Array<Types::Tag>) —

    The tags that you want to attach to the guardrail.

  • :client_request_token (String) —

    A unique, case-sensitive identifier to ensure that the API request completes no more than once. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see Ensuring idempotency in the Amazon S3 User Guide.

    A suitable default value is auto-generated. You should normally not need to pass this option.**

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1337

def create_guardrail(params = {}, options = {})
  req = build_request(:create_guardrail, params)
  req.send_request(options)
end

#create_guardrail_version(params = {}) ⇒ Types::CreateGuardrailVersionResponse

Creates a version of the guardrail. Use this API to create a snapshot of the guardrail when you are satisfied with a configuration, or to compare the configuration with another version.

Examples:

Request syntax with placeholder values


resp = client.create_guardrail_version({
  guardrail_identifier: "GuardrailIdentifier", # required
  description: "GuardrailDescription",
  client_request_token: "IdempotencyToken",
})

Response structure


resp.guardrail_id #=> String
resp.version #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :guardrail_identifier (required, String) —

    The unique identifier of the guardrail. This can be an ID or the ARN.

  • :description (String) —

    A description of the guardrail version.

  • :client_request_token (String) —

    A unique, case-sensitive identifier to ensure that the API request completes no more than once. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see Ensuring idempotency in the Amazon S3 User Guide.

    A suitable default value is auto-generated. You should normally not need to pass this option.**

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1388

def create_guardrail_version(params = {}, options = {})
  req = build_request(:create_guardrail_version, params)
  req.send_request(options)
end

#create_inference_profile(params = {}) ⇒ Types::CreateInferenceProfileResponse

Creates an application inference profile to track metrics and costs when invoking a model. To create an application inference profile for a foundation model in one region, specify the ARN of the model in that region. To create an application inference profile for a foundation model across multiple regions, specify the ARN of the system-defined inference profile that contains the regions that you want to route requests to. For more information, see Increase throughput and resilience with cross-region inference in Amazon Bedrock. in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.create_inference_profile({
  inference_profile_name: "InferenceProfileName", # required
  description: "InferenceProfileDescription",
  client_request_token: "IdempotencyToken",
  model_source: { # required
    copy_from: "InferenceProfileModelSourceArn",
  },
  tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
})

Response structure


resp.inference_profile_arn #=> String
resp.status #=> String, one of "ACTIVE"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :inference_profile_name (required, String) —

    A name for the inference profile.

  • :description (String) —

    A description for the inference profile.

  • :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.

    A suitable default value is auto-generated. You should normally not need to pass this option.**

  • :model_source (required, Types::InferenceProfileModelSource) —

    The foundation model or system-defined inference profile that the inference profile will track metrics and costs for.

  • :tags (Array<Types::Tag>) —

    An array of objects, each of which contains a tag and its value. For more information, see Tagging resources in the Amazon Bedrock User Guide.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1470

def create_inference_profile(params = {}, options = {})
  req = build_request(:create_inference_profile, params)
  req.send_request(options)
end

#create_marketplace_model_endpoint(params = {}) ⇒ Types::CreateMarketplaceModelEndpointResponse

Creates an endpoint for a model from Amazon Bedrock Marketplace. The endpoint is hosted by Amazon SageMaker.

Examples:

Request syntax with placeholder values


resp = client.create_marketplace_model_endpoint({
  model_source_identifier: "ModelSourceIdentifier", # required
  endpoint_config: { # required
    sage_maker: {
      initial_instance_count: 1, # required
      instance_type: "InstanceType", # required
      execution_role: "RoleArn", # required
      kms_encryption_key: "KmsKeyId",
      vpc: {
        subnet_ids: ["SubnetId"], # required
        security_group_ids: ["SecurityGroupId"], # required
      },
    },
  },
  accept_eula: false,
  endpoint_name: "EndpointName", # required
  client_request_token: "IdempotencyToken",
  tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
})

Response structure


resp.marketplace_model_endpoint.endpoint_arn #=> String
resp.marketplace_model_endpoint.model_source_identifier #=> String
resp.marketplace_model_endpoint.status #=> String, one of "REGISTERED", "INCOMPATIBLE_ENDPOINT"
resp.marketplace_model_endpoint.status_message #=> String
resp.marketplace_model_endpoint.created_at #=> Time
resp.marketplace_model_endpoint.updated_at #=> Time
resp.marketplace_model_endpoint.endpoint_config.sage_maker.initial_instance_count #=> Integer
resp.marketplace_model_endpoint.endpoint_config.sage_maker.instance_type #=> String
resp.marketplace_model_endpoint.endpoint_config.sage_maker.execution_role #=> String
resp.marketplace_model_endpoint.endpoint_config.sage_maker.kms_encryption_key #=> String
resp.marketplace_model_endpoint.endpoint_config.sage_maker.vpc.subnet_ids #=> Array
resp.marketplace_model_endpoint.endpoint_config.sage_maker.vpc.subnet_ids[0] #=> String
resp.marketplace_model_endpoint.endpoint_config.sage_maker.vpc.security_group_ids #=> Array
resp.marketplace_model_endpoint.endpoint_config.sage_maker.vpc.security_group_ids[0] #=> String
resp.marketplace_model_endpoint.endpoint_status #=> String
resp.marketplace_model_endpoint.endpoint_status_message #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_source_identifier (required, String) —

    The ARN of the model from Amazon Bedrock Marketplace that you want to deploy to the endpoint.

  • :endpoint_config (required, Types::EndpointConfig) —

    The configuration for the endpoint, including the number and type of instances to use.

  • :accept_eula (Boolean) —

    Indicates whether you accept the end-user license agreement (EULA) for the model. Set to true to accept the EULA.

  • :endpoint_name (required, String) —

    The name of the endpoint. This name must be unique within your Amazon Web Services account and region.

  • :client_request_token (String) —

    A unique, case-sensitive identifier that you provide to ensure the idempotency of the request. This token is listed as not required because Amazon Web Services SDKs automatically generate it for you and set this parameter. If you're not using the Amazon Web Services SDK or the CLI, you must provide this token or the action will fail.

    A suitable default value is auto-generated. You should normally not need to pass this option.**

  • :tags (Array<Types::Tag>) —

    An array of key-value pairs to apply to the underlying Amazon SageMaker endpoint. You can use these tags to organize and identify your Amazon Web Services resources.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1563

def create_marketplace_model_endpoint(params = {}, options = {})
  req = build_request(:create_marketplace_model_endpoint, params)
  req.send_request(options)
end

#create_model_copy_job(params = {}) ⇒ Types::CreateModelCopyJobResponse

Copies a model to another region so that it can be used there. For more information, see Copy models to be used in other regions in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.create_model_copy_job({
  source_model_arn: "ModelArn", # required
  target_model_name: "CustomModelName", # required
  model_kms_key_id: "KmsKeyId",
  target_model_tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
  client_request_token: "IdempotencyToken",
})

Response structure


resp.job_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :source_model_arn (required, String) —

    The Amazon Resource Name (ARN) of the model to be copied.

  • :target_model_name (required, String) —

    A name for the copied model.

  • :model_kms_key_id (String) —

    The ARN of the KMS key that you use to encrypt the model copy.

  • :target_model_tags (Array<Types::Tag>) —

    Tags to associate with the target model. For more information, see Tag resources in the Amazon Bedrock User Guide.

  • :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.

    A suitable default value is auto-generated. You should normally not need to pass this option.**

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1635

def create_model_copy_job(params = {}, options = {})
  req = build_request(:create_model_copy_job, params)
  req.send_request(options)
end

#create_model_customization_job(params = {}) ⇒ Types::CreateModelCustomizationJobResponse

Creates a fine-tuning job to customize a base model.

You specify the base foundation model and the location of the training data. After the model-customization job completes successfully, your custom model resource will be ready to use. Amazon Bedrock returns validation loss metrics and output generations after the job completes.

For information on the format of training and validation data, see Prepare the datasets.

Model-customization jobs are asynchronous and the completion time depends on the base model and the training/validation data size. To monitor a job, use the GetModelCustomizationJob operation to retrieve the job status.

For more information, see Custom models in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.create_model_customization_job({
  job_name: "JobName", # required
  custom_model_name: "CustomModelName", # required
  role_arn: "RoleArn", # required
  client_request_token: "IdempotencyToken",
  base_model_identifier: "BaseModelIdentifier", # required
  customization_type: "FINE_TUNING", # accepts FINE_TUNING, CONTINUED_PRE_TRAINING, DISTILLATION, IMPORTED
  custom_model_kms_key_id: "KmsKeyId",
  job_tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
  custom_model_tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
  training_data_config: { # required
    s3_uri: "S3Uri",
    invocation_logs_config: {
      use_prompt_response: false,
      invocation_log_source: { # required
        s3_uri: "S3Uri",
      },
      request_metadata_filters: {
        equals: {
          "RequestMetadataMapKeyString" => "RequestMetadataMapValueString",
        },
        not_equals: {
          "RequestMetadataMapKeyString" => "RequestMetadataMapValueString",
        },
        and_all: [
          {
            equals: {
              "RequestMetadataMapKeyString" => "RequestMetadataMapValueString",
            },
            not_equals: {
              "RequestMetadataMapKeyString" => "RequestMetadataMapValueString",
            },
          },
        ],
        or_all: [
          {
            equals: {
              "RequestMetadataMapKeyString" => "RequestMetadataMapValueString",
            },
            not_equals: {
              "RequestMetadataMapKeyString" => "RequestMetadataMapValueString",
            },
          },
        ],
      },
    },
  },
  validation_data_config: {
    validators: [ # required
      {
        s3_uri: "S3Uri", # required
      },
    ],
  },
  output_data_config: { # required
    s3_uri: "S3Uri", # required
  },
  hyper_parameters: {
    "String" => "String",
  },
  vpc_config: {
    subnet_ids: ["SubnetId"], # required
    security_group_ids: ["SecurityGroupId"], # required
  },
  customization_config: {
    distillation_config: {
      teacher_model_config: { # required
        teacher_model_identifier: "TeacherModelIdentifier", # required
        max_response_length_for_inference: 1,
      },
    },
  },
})

Response structure


resp.job_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :job_name (required, String) —

    A name for the fine-tuning job.

  • :custom_model_name (required, String) —

    A name for the resulting custom model.

  • :role_arn (required, String) —

    The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. For example, during model training, Amazon Bedrock needs your permission to read input data from an S3 bucket, write model artifacts to an S3 bucket. To pass this role to Amazon Bedrock, the caller of this API must have the iam:PassRole permission.

  • :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.

    A suitable default value is auto-generated. You should normally not need to pass this option.**

  • :base_model_identifier (required, String) —

    Name of the base model.

  • :customization_type (String) —

    The customization type.

  • :custom_model_kms_key_id (String) —

    The custom model is encrypted at rest using this key.

  • :job_tags (Array<Types::Tag>) —

    Tags to attach to the job.

  • :custom_model_tags (Array<Types::Tag>) —

    Tags to attach to the resulting custom model.

  • :training_data_config (required, Types::TrainingDataConfig) —

    Information about the training dataset.

  • :validation_data_config (Types::ValidationDataConfig) —

    Information about the validation dataset.

  • :output_data_config (required, Types::OutputDataConfig) —

    S3 location for the output data.

  • :hyper_parameters (Hash<String,String>) —

    Parameters related to tuning the model. For details on the format for different models, see Custom model hyperparameters.

  • :vpc_config (Types::VpcConfig) —

    The configuration of the Virtual Private Cloud (VPC) that contains the resources that you're using for this job. For more information, see Protect your model customization jobs using a VPC.

  • :customization_config (Types::CustomizationConfig) —

    The customization configuration for the model customization job.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1834

def create_model_customization_job(params = {}, options = {})
  req = build_request(:create_model_customization_job, params)
  req.send_request(options)
end

#create_model_import_job(params = {}) ⇒ Types::CreateModelImportJobResponse

Creates a model import job to import model that you have customized in other environments, such as Amazon SageMaker. For more information, see Import a customized model

Examples:

Request syntax with placeholder values


resp = client.create_model_import_job({
  job_name: "JobName", # required
  imported_model_name: "ImportedModelName", # required
  role_arn: "RoleArn", # required
  model_data_source: { # required
    s3_data_source: {
      s3_uri: "S3Uri", # required
    },
  },
  job_tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
  imported_model_tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
  client_request_token: "IdempotencyToken",
  vpc_config: {
    subnet_ids: ["SubnetId"], # required
    security_group_ids: ["SecurityGroupId"], # required
  },
  imported_model_kms_key_id: "KmsKeyId",
})

Response structure


resp.job_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :job_name (required, String) —

    The name of the import job.

  • :imported_model_name (required, String) —

    The name of the imported model.

  • :role_arn (required, String) —

    The Amazon Resource Name (ARN) of the model import job.

  • :model_data_source (required, Types::ModelDataSource) —

    The data source for the imported model.

  • :job_tags (Array<Types::Tag>) —

    Tags to attach to this import job.

  • :imported_model_tags (Array<Types::Tag>) —

    Tags to attach to the imported model.

  • :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.

  • :vpc_config (Types::VpcConfig) —

    VPC configuration parameters for the private Virtual Private Cloud (VPC) that contains the resources you are using for the import job.

  • :imported_model_kms_key_id (String) —

    The imported model is encrypted at rest using this key.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1925

def create_model_import_job(params = {}, options = {})
  req = build_request(:create_model_import_job, params)
  req.send_request(options)
end

#create_model_invocation_job(params = {}) ⇒ Types::CreateModelInvocationJobResponse

Creates a batch inference job to invoke a model on multiple prompts. Format your data according to Format your inference data and upload it to an Amazon S3 bucket. For more information, see Process multiple prompts with batch inference.

The response returns a jobArn that you can use to stop or get details about the job.

Examples:

Request syntax with placeholder values


resp = client.create_model_invocation_job({
  job_name: "ModelInvocationJobName", # required
  role_arn: "RoleArn", # required
  client_request_token: "ModelInvocationIdempotencyToken",
  model_id: "ModelId", # required
  input_data_config: { # required
    s3_input_data_config: {
      s3_input_format: "JSONL", # accepts JSONL
      s3_uri: "S3Uri", # required
      s3_bucket_owner: "AccountId",
    },
  },
  output_data_config: { # required
    s3_output_data_config: {
      s3_uri: "S3Uri", # required
      s3_encryption_key_id: "KmsKeyId",
      s3_bucket_owner: "AccountId",
    },
  },
  vpc_config: {
    subnet_ids: ["SubnetId"], # required
    security_group_ids: ["SecurityGroupId"], # required
  },
  timeout_duration_in_hours: 1,
  tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
})

Response structure


resp.job_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :job_name (required, String) —

    A name to give the batch inference job.

  • :role_arn (required, String) —

    The Amazon Resource Name (ARN) of the service role with permissions to carry out and manage batch inference. You can use the console to create a default service role or follow the steps at Create a service role for batch inference.

  • :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.

    A suitable default value is auto-generated. You should normally not need to pass this option.**

  • :model_id (required, String) —

    The unique identifier of the foundation model to use for the batch inference job.

  • :input_data_config (required, Types::ModelInvocationJobInputDataConfig) —

    Details about the location of the input to the batch inference job.

  • :output_data_config (required, Types::ModelInvocationJobOutputDataConfig) —

    Details about the location of the output of the batch inference job.

  • :vpc_config (Types::VpcConfig) —

    The configuration of the Virtual Private Cloud (VPC) for the data in the batch inference job. For more information, see Protect batch inference jobs using a VPC.

  • :timeout_duration_in_hours (Integer) —

    The number of hours after which to force the batch inference job to time out.

  • :tags (Array<Types::Tag>) —

    Any tags to associate with the batch inference job. For more information, see Tagging Amazon Bedrock resources.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2046

def create_model_invocation_job(params = {}, options = {})
  req = build_request(:create_model_invocation_job, params)
  req.send_request(options)
end

#create_prompt_router(params = {}) ⇒ Types::CreatePromptRouterResponse

Creates a prompt router that manages the routing of requests between multiple foundation models based on the routing criteria.

Examples:

Request syntax with placeholder values


resp = client.create_prompt_router({
  client_request_token: "IdempotencyToken",
  prompt_router_name: "PromptRouterName", # required
  models: [ # required
    {
      model_arn: "PromptRouterTargetModelArn", # required
    },
  ],
  description: "PromptRouterDescription",
  routing_criteria: { # required
    response_quality_difference: 1.0, # required
  },
  fallback_model: { # required
    model_arn: "PromptRouterTargetModelArn", # required
  },
  tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
})

Response structure


resp.prompt_router_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :client_request_token (String) —

    A unique, case-sensitive identifier that you provide to ensure idempotency of your requests. If not specified, the Amazon Web Services SDK automatically generates one for you.

    A suitable default value is auto-generated. You should normally not need to pass this option.**

  • :prompt_router_name (required, String) —

    The name of the prompt router. The name must be unique within your Amazon Web Services account in the current region.

  • :models (required, Array<Types::PromptRouterTargetModel>) —

    A list of foundation models that the prompt router can route requests to. At least one model must be specified.

  • :description (String) —

    An optional description of the prompt router to help identify its purpose.

  • :routing_criteria (required, Types::RoutingCriteria) —

    The criteria, which is the response quality difference, used to determine how incoming requests are routed to different models.

  • :fallback_model (required, Types::PromptRouterTargetModel) —

    The default model to use when the routing criteria is not met.

  • :tags (Array<Types::Tag>) —

    An array of key-value pairs to apply to this resource as tags. You can use tags to categorize and manage your Amazon Web Services resources.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2122

def create_prompt_router(params = {}, options = {})
  req = build_request(:create_prompt_router, params)
  req.send_request(options)
end

#create_provisioned_model_throughput(params = {}) ⇒ Types::CreateProvisionedModelThroughputResponse

Creates dedicated throughput for a base or custom model with the model units and for the duration that you specify. For pricing details, see Amazon Bedrock Pricing. For more information, see Provisioned Throughput in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.create_provisioned_model_throughput({
  client_request_token: "IdempotencyToken",
  model_units: 1, # required
  provisioned_model_name: "ProvisionedModelName", # required
  model_id: "ModelIdentifier", # required
  commitment_duration: "OneMonth", # accepts OneMonth, SixMonths
  tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
})

Response structure


resp.provisioned_model_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :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 in the Amazon S3 User Guide.

    A suitable default value is auto-generated. You should normally not need to pass this option.**

  • :model_units (required, Integer) —

    Number of model units to allocate. A model unit delivers a specific throughput level for the specified model. The throughput level of a model unit specifies the total number of input and output tokens that it can process and generate within a span of one minute. By default, your account has no model units for purchasing Provisioned Throughputs with commitment. You must first visit the Amazon Web Services support center to request MUs.

    For model unit quotas, see Provisioned Throughput quotas in the Amazon Bedrock User Guide.

    For more information about what an MU specifies, contact your Amazon Web Services account manager.

  • :provisioned_model_name (required, String) —

    The name for this Provisioned Throughput.

  • :model_id (required, String) —

    The Amazon Resource Name (ARN) or name of the model to associate with this Provisioned Throughput. For a list of models for which you can purchase Provisioned Throughput, see Amazon Bedrock model IDs for purchasing Provisioned Throughput in the Amazon Bedrock User Guide.

  • :commitment_duration (String) —

    The commitment duration requested for the Provisioned Throughput. Billing occurs hourly and is discounted for longer commitment terms. To request a no-commit Provisioned Throughput, omit this field.

    Custom models support all levels of commitment. To see which base models support no commitment, see Supported regions and models for Provisioned Throughput in the Amazon Bedrock User Guide

  • :tags (Array<Types::Tag>) —

    Tags to associate with this Provisioned Throughput.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2233

def create_provisioned_model_throughput(params = {}, options = {})
  req = build_request(:create_provisioned_model_throughput, params)
  req.send_request(options)
end

#delete_custom_model(params = {}) ⇒ Struct

Deletes a custom model that you created earlier. For more information, see Custom models in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.delete_custom_model({
  model_identifier: "ModelIdentifier", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_identifier (required, String) —

    Name of the model to delete.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2261

def delete_custom_model(params = {}, options = {})
  req = build_request(:delete_custom_model, params)
  req.send_request(options)
end

#delete_guardrail(params = {}) ⇒ Struct

Deletes a guardrail.

  • To delete a guardrail, only specify the ARN of the guardrail in the guardrailIdentifier field. If you delete a guardrail, all of its versions will be deleted.

  • To delete a version of a guardrail, specify the ARN of the guardrail in the guardrailIdentifier field and the version in the guardrailVersion field.

Examples:

Request syntax with placeholder values


resp = client.delete_guardrail({
  guardrail_identifier: "GuardrailIdentifier", # required
  guardrail_version: "GuardrailNumericalVersion",
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :guardrail_identifier (required, String) —

    The unique identifier of the guardrail. This can be an ID or the ARN.

  • :guardrail_version (String) —

    The version of the guardrail.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2295

def delete_guardrail(params = {}, options = {})
  req = build_request(:delete_guardrail, params)
  req.send_request(options)
end

#delete_imported_model(params = {}) ⇒ Struct

Deletes a custom model that you imported earlier. For more information, see Import a customized model in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.delete_imported_model({
  model_identifier: "ImportedModelIdentifier", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_identifier (required, String) —

    Name of the imported model to delete.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2324

def delete_imported_model(params = {}, options = {})
  req = build_request(:delete_imported_model, params)
  req.send_request(options)
end

#delete_inference_profile(params = {}) ⇒ Struct

Deletes an application inference profile. For more information, see Increase throughput and resilience with cross-region inference in Amazon Bedrock. in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.delete_inference_profile({
  inference_profile_identifier: "InferenceProfileIdentifier", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :inference_profile_identifier (required, String) —

    The Amazon Resource Name (ARN) or ID of the application inference profile to delete.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2353

def delete_inference_profile(params = {}, options = {})
  req = build_request(:delete_inference_profile, params)
  req.send_request(options)
end

#delete_marketplace_model_endpoint(params = {}) ⇒ Struct

Deletes an endpoint for a model from Amazon Bedrock Marketplace.

Examples:

Request syntax with placeholder values


resp = client.delete_marketplace_model_endpoint({
  endpoint_arn: "Arn", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :endpoint_arn (required, String) —

    The Amazon Resource Name (ARN) of the endpoint you want to delete.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2375

def delete_marketplace_model_endpoint(params = {}, options = {})
  req = build_request(:delete_marketplace_model_endpoint, params)
  req.send_request(options)
end

#delete_model_invocation_logging_configuration(params = {}) ⇒ Struct

Delete the invocation logging.

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2388

def delete_model_invocation_logging_configuration(params = {}, options = {})
  req = build_request(:delete_model_invocation_logging_configuration, params)
  req.send_request(options)
end

#delete_prompt_router(params = {}) ⇒ Struct

Deletes a specified prompt router. This action cannot be undone.

Examples:

Request syntax with placeholder values


resp = client.delete_prompt_router({
  prompt_router_arn: "PromptRouterArn", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :prompt_router_arn (required, String) —

    The Amazon Resource Name (ARN) of the prompt router to delete.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2410

def delete_prompt_router(params = {}, options = {})
  req = build_request(:delete_prompt_router, params)
  req.send_request(options)
end

#delete_provisioned_model_throughput(params = {}) ⇒ Struct

Deletes a Provisioned Throughput. You can't delete a Provisioned Throughput before the commitment term is over. For more information, see Provisioned Throughput in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.delete_provisioned_model_throughput({
  provisioned_model_id: "ProvisionedModelId", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :provisioned_model_id (required, String) —

    The Amazon Resource Name (ARN) or name of the Provisioned Throughput.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2439

def delete_provisioned_model_throughput(params = {}, options = {})
  req = build_request(:delete_provisioned_model_throughput, params)
  req.send_request(options)
end

#deregister_marketplace_model_endpoint(params = {}) ⇒ Struct

Deregisters an endpoint for a model from Amazon Bedrock Marketplace. This operation removes the endpoint's association with Amazon Bedrock but does not delete the underlying Amazon SageMaker endpoint.

Examples:

Request syntax with placeholder values


resp = client.deregister_marketplace_model_endpoint({
  endpoint_arn: "Arn", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :endpoint_arn (required, String) —

    The Amazon Resource Name (ARN) of the endpoint you want to deregister.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2463

def deregister_marketplace_model_endpoint(params = {}, options = {})
  req = build_request(:deregister_marketplace_model_endpoint, params)
  req.send_request(options)
end

#get_custom_model(params = {}) ⇒ Types::GetCustomModelResponse

Get the properties associated with a Amazon Bedrock custom model that you have created. For more information, see Custom models in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.get_custom_model({
  model_identifier: "ModelIdentifier", # required
})

Response structure


resp.model_arn #=> String
resp.model_name #=> String
resp.job_name #=> String
resp.job_arn #=> String
resp.base_model_arn #=> String
resp.customization_type #=> String, one of "FINE_TUNING", "CONTINUED_PRE_TRAINING", "DISTILLATION", "IMPORTED"
resp.model_kms_key_arn #=> String
resp.hyper_parameters #=> Hash
resp.hyper_parameters["String"] #=> String
resp.training_data_config.s3_uri #=> String
resp.training_data_config.invocation_logs_config.use_prompt_response #=> Boolean
resp.training_data_config.invocation_logs_config.invocation_log_source.s3_uri #=> String
resp.training_data_config.invocation_logs_config.request_metadata_filters.equals #=> Hash
resp.training_data_config.invocation_logs_config.request_metadata_filters.equals["RequestMetadataMapKeyString"] #=> String
resp.training_data_config.invocation_logs_config.request_metadata_filters.not_equals #=> Hash
resp.training_data_config.invocation_logs_config.request_metadata_filters.not_equals["RequestMetadataMapKeyString"] #=> String
resp.training_data_config.invocation_logs_config.request_metadata_filters.and_all #=> Array
resp.training_data_config.invocation_logs_config.request_metadata_filters.and_all[0].equals #=> Hash
resp.training_data_config.invocation_logs_config.request_metadata_filters.and_all[0].equals["RequestMetadataMapKeyString"] #=> String
resp.training_data_config.invocation_logs_config.request_metadata_filters.and_all[0].not_equals #=> Hash
resp.training_data_config.invocation_logs_config.request_metadata_filters.and_all[0].not_equals["RequestMetadataMapKeyString"] #=> String
resp.training_data_config.invocation_logs_config.request_metadata_filters.or_all #=> Array
resp.training_data_config.invocation_logs_config.request_metadata_filters.or_all[0].equals #=> Hash
resp.training_data_config.invocation_logs_config.request_metadata_filters.or_all[0].equals["RequestMetadataMapKeyString"] #=> String
resp.training_data_config.invocation_logs_config.request_metadata_filters.or_all[0].not_equals #=> Hash
resp.training_data_config.invocation_logs_config.request_metadata_filters.or_all[0].not_equals["RequestMetadataMapKeyString"] #=> String
resp.validation_data_config.validators #=> Array
resp.validation_data_config.validators[0].s3_uri #=> String
resp.output_data_config.s3_uri #=> String
resp.training_metrics.training_loss #=> Float
resp.validation_metrics #=> Array
resp.validation_metrics[0].validation_loss #=> Float
resp.creation_time #=> Time
resp.customization_config.distillation_config.teacher_model_config.teacher_model_identifier #=> String
resp.customization_config.distillation_config.teacher_model_config.max_response_length_for_inference #=> Integer
resp.model_status #=> String, one of "Active", "Creating", "Failed"
resp.failure_message #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_identifier (required, String) —

    Name or Amazon Resource Name (ARN) of the custom model.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2550

def get_custom_model(params = {}, options = {})
  req = build_request(:get_custom_model, params)
  req.send_request(options)
end

#get_evaluation_job(params = {}) ⇒ Types::GetEvaluationJobResponse

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

Examples:

Request syntax with placeholder values


resp = client.get_evaluation_job({
  job_identifier: "EvaluationJobIdentifier", # required
})

Response structure


resp.job_name #=> String
resp.status #=> String, one of "InProgress", "Completed", "Failed", "Stopping", "Stopped", "Deleting"
resp.job_arn #=> String
resp.job_description #=> String
resp.role_arn #=> String
resp.customer_encryption_key_id #=> String
resp.job_type #=> String, one of "Human", "Automated"
resp.application_type #=> String, one of "ModelEvaluation", "RagEvaluation"
resp.evaluation_config.automated.dataset_metric_configs #=> Array
resp.evaluation_config.automated.dataset_metric_configs[0].task_type #=> String, one of "Summarization", "Classification", "QuestionAndAnswer", "Generation", "Custom"
resp.evaluation_config.automated.dataset_metric_configs[0].dataset.name #=> String
resp.evaluation_config.automated.dataset_metric_configs[0].dataset.dataset_location.s3_uri #=> String
resp.evaluation_config.automated.dataset_metric_configs[0].metric_names #=> Array
resp.evaluation_config.automated.dataset_metric_configs[0].metric_names[0] #=> String
resp.evaluation_config.automated.evaluator_model_config.bedrock_evaluator_models #=> Array
resp.evaluation_config.automated.evaluator_model_config.bedrock_evaluator_models[0].model_identifier #=> String
resp.evaluation_config.automated.custom_metric_config.custom_metrics #=> Array
resp.evaluation_config.automated.custom_metric_config.custom_metrics[0].custom_metric_definition.name #=> String
resp.evaluation_config.automated.custom_metric_config.custom_metrics[0].custom_metric_definition.instructions #=> String
resp.evaluation_config.automated.custom_metric_config.custom_metrics[0].custom_metric_definition.rating_scale #=> Array
resp.evaluation_config.automated.custom_metric_config.custom_metrics[0].custom_metric_definition.rating_scale[0].definition #=> String
resp.evaluation_config.automated.custom_metric_config.custom_metrics[0].custom_metric_definition.rating_scale[0].value.string_value #=> String
resp.evaluation_config.automated.custom_metric_config.custom_metrics[0].custom_metric_definition.rating_scale[0].value.float_value #=> Float
resp.evaluation_config.automated.custom_metric_config.evaluator_model_config.bedrock_evaluator_models #=> Array
resp.evaluation_config.automated.custom_metric_config.evaluator_model_config.bedrock_evaluator_models[0].model_identifier #=> String
resp.evaluation_config.human.human_workflow_config.flow_definition_arn #=> String
resp.evaluation_config.human.human_workflow_config.instructions #=> String
resp.evaluation_config.human.custom_metrics #=> Array
resp.evaluation_config.human.custom_metrics[0].name #=> String
resp.evaluation_config.human.custom_metrics[0].description #=> String
resp.evaluation_config.human.custom_metrics[0].rating_method #=> String
resp.evaluation_config.human.dataset_metric_configs #=> Array
resp.evaluation_config.human.dataset_metric_configs[0].task_type #=> String, one of "Summarization", "Classification", "QuestionAndAnswer", "Generation", "Custom"
resp.evaluation_config.human.dataset_metric_configs[0].dataset.name #=> String
resp.evaluation_config.human.dataset_metric_configs[0].dataset.dataset_location.s3_uri #=> String
resp.evaluation_config.human.dataset_metric_configs[0].metric_names #=> Array
resp.evaluation_config.human.dataset_metric_configs[0].metric_names[0] #=> String
resp.inference_config.models #=> Array
resp.inference_config.models[0].bedrock_model.model_identifier #=> String
resp.inference_config.models[0].bedrock_model.inference_params #=> String
resp.inference_config.models[0].bedrock_model.performance_config.latency #=> String, one of "standard", "optimized"
resp.inference_config.models[0].precomputed_inference_source.inference_source_identifier #=> String
resp.inference_config.rag_configs #=> Array
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_config.knowledge_base_id #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_config.knowledge_base_retrieval_configuration.vector_search_configuration.number_of_results #=> Integer
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_config.knowledge_base_retrieval_configuration.vector_search_configuration.override_search_type #=> String, one of "HYBRID", "SEMANTIC"
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_config.knowledge_base_retrieval_configuration.vector_search_configuration.filter.equals.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_config.knowledge_base_retrieval_configuration.vector_search_configuration.filter.not_equals.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_config.knowledge_base_retrieval_configuration.vector_search_configuration.filter.greater_than.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_config.knowledge_base_retrieval_configuration.vector_search_configuration.filter.greater_than_or_equals.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_config.knowledge_base_retrieval_configuration.vector_search_configuration.filter.less_than.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_config.knowledge_base_retrieval_configuration.vector_search_configuration.filter.less_than_or_equals.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_config.knowledge_base_retrieval_configuration.vector_search_configuration.filter.in.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_config.knowledge_base_retrieval_configuration.vector_search_configuration.filter.not_in.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_config.knowledge_base_retrieval_configuration.vector_search_configuration.filter.starts_with.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_config.knowledge_base_retrieval_configuration.vector_search_configuration.filter.list_contains.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_config.knowledge_base_retrieval_configuration.vector_search_configuration.filter.string_contains.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_config.knowledge_base_retrieval_configuration.vector_search_configuration.filter.and_all #=> Array
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_config.knowledge_base_retrieval_configuration.vector_search_configuration.filter.and_all[0] #=> Types::RetrievalFilter
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_config.knowledge_base_retrieval_configuration.vector_search_configuration.filter.or_all #=> Array
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_config.knowledge_base_retrieval_configuration.vector_search_configuration.filter.or_all[0] #=> Types::RetrievalFilter
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.type #=> String, one of "KNOWLEDGE_BASE", "EXTERNAL_SOURCES"
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.knowledge_base_id #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.model_arn #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.retrieval_configuration.vector_search_configuration.number_of_results #=> Integer
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.retrieval_configuration.vector_search_configuration.override_search_type #=> String, one of "HYBRID", "SEMANTIC"
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.retrieval_configuration.vector_search_configuration.filter.equals.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.retrieval_configuration.vector_search_configuration.filter.not_equals.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.retrieval_configuration.vector_search_configuration.filter.greater_than.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.retrieval_configuration.vector_search_configuration.filter.greater_than_or_equals.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.retrieval_configuration.vector_search_configuration.filter.less_than.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.retrieval_configuration.vector_search_configuration.filter.less_than_or_equals.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.retrieval_configuration.vector_search_configuration.filter.in.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.retrieval_configuration.vector_search_configuration.filter.not_in.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.retrieval_configuration.vector_search_configuration.filter.starts_with.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.retrieval_configuration.vector_search_configuration.filter.list_contains.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.retrieval_configuration.vector_search_configuration.filter.string_contains.key #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.retrieval_configuration.vector_search_configuration.filter.and_all #=> Array
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.retrieval_configuration.vector_search_configuration.filter.and_all[0] #=> Types::RetrievalFilter
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.retrieval_configuration.vector_search_configuration.filter.or_all #=> Array
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.retrieval_configuration.vector_search_configuration.filter.or_all[0] #=> Types::RetrievalFilter
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.generation_configuration.prompt_template.text_prompt_template #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.generation_configuration.guardrail_configuration.guardrail_id #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.generation_configuration.guardrail_configuration.guardrail_version #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.generation_configuration.kb_inference_config.text_inference_config.temperature #=> Float
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.generation_configuration.kb_inference_config.text_inference_config.top_p #=> Float
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.generation_configuration.kb_inference_config.text_inference_config.max_tokens #=> Integer
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.generation_configuration.kb_inference_config.text_inference_config.stop_sequences #=> Array
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.generation_configuration.kb_inference_config.text_inference_config.stop_sequences[0] #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.generation_configuration.additional_model_request_fields #=> Hash
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.knowledge_base_configuration.orchestration_configuration.query_transformation_configuration.type #=> String, one of "QUERY_DECOMPOSITION"
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.external_sources_configuration.model_arn #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.external_sources_configuration.sources #=> Array
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.external_sources_configuration.sources[0].source_type #=> String, one of "S3", "BYTE_CONTENT"
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.external_sources_configuration.sources[0].s3_location.uri #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.external_sources_configuration.sources[0].byte_content.identifier #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.external_sources_configuration.sources[0].byte_content.content_type #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.external_sources_configuration.sources[0].byte_content.data #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.external_sources_configuration.generation_configuration.prompt_template.text_prompt_template #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.external_sources_configuration.generation_configuration.guardrail_configuration.guardrail_id #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.external_sources_configuration.generation_configuration.guardrail_configuration.guardrail_version #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.external_sources_configuration.generation_configuration.kb_inference_config.text_inference_config.temperature #=> Float
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.external_sources_configuration.generation_configuration.kb_inference_config.text_inference_config.top_p #=> Float
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.external_sources_configuration.generation_configuration.kb_inference_config.text_inference_config.max_tokens #=> Integer
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.external_sources_configuration.generation_configuration.kb_inference_config.text_inference_config.stop_sequences #=> Array
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.external_sources_configuration.generation_configuration.kb_inference_config.text_inference_config.stop_sequences[0] #=> String
resp.inference_config.rag_configs[0].knowledge_base_config.retrieve_and_generate_config.external_sources_configuration.generation_configuration.additional_model_request_fields #=> Hash
resp.inference_config.rag_configs[0].precomputed_rag_source_config.retrieve_source_config.rag_source_identifier #=> String
resp.inference_config.rag_configs[0].precomputed_rag_source_config.retrieve_and_generate_source_config.rag_source_identifier #=> String
resp.output_data_config.s3_uri #=> String
resp.creation_time #=> Time
resp.last_modified_time #=> Time
resp.failure_messages #=> Array
resp.failure_messages[0] #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :job_identifier (required, String) —

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

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2706

def get_evaluation_job(params = {}, options = {})
  req = build_request(:get_evaluation_job, params)
  req.send_request(options)
end

#get_foundation_model(params = {}) ⇒ Types::GetFoundationModelResponse

Get details about a Amazon Bedrock foundation model.

Examples:

Request syntax with placeholder values


resp = client.get_foundation_model({
  model_identifier: "ModelIdentifier", # required
})

Response structure


resp.model_details.model_arn #=> String
resp.model_details.model_id #=> String
resp.model_details.model_name #=> String
resp.model_details.provider_name #=> String
resp.model_details.input_modalities #=> Array
resp.model_details.input_modalities[0] #=> String, one of "TEXT", "IMAGE", "EMBEDDING"
resp.model_details.output_modalities #=> Array
resp.model_details.output_modalities[0] #=> String, one of "TEXT", "IMAGE", "EMBEDDING"
resp.model_details.response_streaming_supported #=> Boolean
resp.model_details.customizations_supported #=> Array
resp.model_details.customizations_supported[0] #=> String, one of "FINE_TUNING", "CONTINUED_PRE_TRAINING", "DISTILLATION"
resp.model_details.inference_types_supported #=> Array
resp.model_details.inference_types_supported[0] #=> String, one of "ON_DEMAND", "PROVISIONED"
resp.model_details.model_lifecycle.status #=> String, one of "ACTIVE", "LEGACY"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_identifier (required, String) —

    The model identifier.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2747

def get_foundation_model(params = {}, options = {})
  req = build_request(:get_foundation_model, params)
  req.send_request(options)
end

#get_guardrail(params = {}) ⇒ Types::GetGuardrailResponse

Gets details about a guardrail. If you don't specify a version, the response returns details for the DRAFT version.

Examples:

Request syntax with placeholder values


resp = client.get_guardrail({
  guardrail_identifier: "GuardrailIdentifier", # required
  guardrail_version: "GuardrailVersion",
})

Response structure


resp.name #=> String
resp.description #=> String
resp.guardrail_id #=> String
resp.guardrail_arn #=> String
resp.version #=> String
resp.status #=> String, one of "CREATING", "UPDATING", "VERSIONING", "READY", "FAILED", "DELETING"
resp.topic_policy.topics #=> Array
resp.topic_policy.topics[0].name #=> String
resp.topic_policy.topics[0].definition #=> String
resp.topic_policy.topics[0].examples #=> Array
resp.topic_policy.topics[0].examples[0] #=> String
resp.topic_policy.topics[0].type #=> String, one of "DENY"
resp.topic_policy.topics[0].input_action #=> String, one of "BLOCK", "NONE"
resp.topic_policy.topics[0].output_action #=> String, one of "BLOCK", "NONE"
resp.topic_policy.topics[0].input_enabled #=> Boolean
resp.topic_policy.topics[0].output_enabled #=> Boolean
resp.content_policy.filters #=> Array
resp.content_policy.filters[0].type #=> String, one of "SEXUAL", "VIOLENCE", "HATE", "INSULTS", "MISCONDUCT", "PROMPT_ATTACK"
resp.content_policy.filters[0].input_strength #=> String, one of "NONE", "LOW", "MEDIUM", "HIGH"
resp.content_policy.filters[0].output_strength #=> String, one of "NONE", "LOW", "MEDIUM", "HIGH"
resp.content_policy.filters[0].input_modalities #=> Array
resp.content_policy.filters[0].input_modalities[0] #=> String, one of "TEXT", "IMAGE"
resp.content_policy.filters[0].output_modalities #=> Array
resp.content_policy.filters[0].output_modalities[0] #=> String, one of "TEXT", "IMAGE"
resp.content_policy.filters[0].input_action #=> String, one of "BLOCK", "NONE"
resp.content_policy.filters[0].output_action #=> String, one of "BLOCK", "NONE"
resp.content_policy.filters[0].input_enabled #=> Boolean
resp.content_policy.filters[0].output_enabled #=> Boolean
resp.word_policy.words #=> Array
resp.word_policy.words[0].text #=> String
resp.word_policy.words[0].input_action #=> String, one of "BLOCK", "NONE"
resp.word_policy.words[0].output_action #=> String, one of "BLOCK", "NONE"
resp.word_policy.words[0].input_enabled #=> Boolean
resp.word_policy.words[0].output_enabled #=> Boolean
resp.word_policy.managed_word_lists #=> Array
resp.word_policy.managed_word_lists[0].type #=> String, one of "PROFANITY"
resp.word_policy.managed_word_lists[0].input_action #=> String, one of "BLOCK", "NONE"
resp.word_policy.managed_word_lists[0].output_action #=> String, one of "BLOCK", "NONE"
resp.word_policy.managed_word_lists[0].input_enabled #=> Boolean
resp.word_policy.managed_word_lists[0].output_enabled #=> Boolean
resp.sensitive_information_policy.pii_entities #=> Array
resp.sensitive_information_policy.pii_entities[0].type #=> String, one of "ADDRESS", "AGE", "AWS_ACCESS_KEY", "AWS_SECRET_KEY", "CA_HEALTH_NUMBER", "CA_SOCIAL_INSURANCE_NUMBER", "CREDIT_DEBIT_CARD_CVV", "CREDIT_DEBIT_CARD_EXPIRY", "CREDIT_DEBIT_CARD_NUMBER", "DRIVER_ID", "EMAIL", "INTERNATIONAL_BANK_ACCOUNT_NUMBER", "IP_ADDRESS", "LICENSE_PLATE", "MAC_ADDRESS", "NAME", "PASSWORD", "PHONE", "PIN", "SWIFT_CODE", "UK_NATIONAL_HEALTH_SERVICE_NUMBER", "UK_NATIONAL_INSURANCE_NUMBER", "UK_UNIQUE_TAXPAYER_REFERENCE_NUMBER", "URL", "USERNAME", "US_BANK_ACCOUNT_NUMBER", "US_BANK_ROUTING_NUMBER", "US_INDIVIDUAL_TAX_IDENTIFICATION_NUMBER", "US_PASSPORT_NUMBER", "US_SOCIAL_SECURITY_NUMBER", "VEHICLE_IDENTIFICATION_NUMBER"
resp.sensitive_information_policy.pii_entities[0].action #=> String, one of "BLOCK", "ANONYMIZE", "NONE"
resp.sensitive_information_policy.pii_entities[0].input_action #=> String, one of "BLOCK", "ANONYMIZE", "NONE"
resp.sensitive_information_policy.pii_entities[0].output_action #=> String, one of "BLOCK", "ANONYMIZE", "NONE"
resp.sensitive_information_policy.pii_entities[0].input_enabled #=> Boolean
resp.sensitive_information_policy.pii_entities[0].output_enabled #=> Boolean
resp.sensitive_information_policy.regexes #=> Array
resp.sensitive_information_policy.regexes[0].name #=> String
resp.sensitive_information_policy.regexes[0].description #=> String
resp.sensitive_information_policy.regexes[0].pattern #=> String
resp.sensitive_information_policy.regexes[0].action #=> String, one of "BLOCK", "ANONYMIZE", "NONE"
resp.sensitive_information_policy.regexes[0].input_action #=> String, one of "BLOCK", "ANONYMIZE", "NONE"
resp.sensitive_information_policy.regexes[0].output_action #=> String, one of "BLOCK", "ANONYMIZE", "NONE"
resp.sensitive_information_policy.regexes[0].input_enabled #=> Boolean
resp.sensitive_information_policy.regexes[0].output_enabled #=> Boolean
resp.contextual_grounding_policy.filters #=> Array
resp.contextual_grounding_policy.filters[0].type #=> String, one of "GROUNDING", "RELEVANCE"
resp.contextual_grounding_policy.filters[0].threshold #=> Float
resp.contextual_grounding_policy.filters[0].action #=> String, one of "BLOCK", "NONE"
resp.contextual_grounding_policy.filters[0].enabled #=> Boolean
resp.cross_region_details.guardrail_profile_id #=> String
resp.cross_region_details.guardrail_profile_arn #=> String
resp.created_at #=> Time
resp.updated_at #=> Time
resp.status_reasons #=> Array
resp.status_reasons[0] #=> String
resp.failure_recommendations #=> Array
resp.failure_recommendations[0] #=> String
resp.blocked_input_messaging #=> String
resp.blocked_outputs_messaging #=> String
resp.kms_key_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :guardrail_identifier (required, String) —

    The unique identifier of the guardrail for which to get details. This can be an ID or the ARN.

  • :guardrail_version (String) —

    The version of the guardrail for which to get details. If you don't specify a version, the response returns details for the DRAFT version.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2872

def get_guardrail(params = {}, options = {})
  req = build_request(:get_guardrail, params)
  req.send_request(options)
end

#get_imported_model(params = {}) ⇒ Types::GetImportedModelResponse

Gets properties associated with a customized model you imported.

Examples:

Request syntax with placeholder values


resp = client.get_imported_model({
  model_identifier: "ImportedModelIdentifier", # required
})

Response structure


resp.model_arn #=> String
resp.model_name #=> String
resp.job_name #=> String
resp.job_arn #=> String
resp.model_data_source.s3_data_source.s3_uri #=> String
resp.creation_time #=> Time
resp.model_architecture #=> String
resp.model_kms_key_arn #=> String
resp.instruct_supported #=> Boolean
resp.custom_model_units.custom_model_units_per_model_copy #=> Integer
resp.custom_model_units.custom_model_units_version #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :model_identifier (required, String) —

    Name or Amazon Resource Name (ARN) of the imported model.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2919

def get_imported_model(params = {}, options = {})
  req = build_request(:get_imported_model, params)
  req.send_request(options)
end

#get_inference_profile(params = {}) ⇒ Types::GetInferenceProfileResponse

Gets information about an inference profile. For more information, see Increase throughput and resilience with cross-region inference in Amazon Bedrock. in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.get_inference_profile({
  inference_profile_identifier: "InferenceProfileIdentifier", # required
})

Response structure


resp.inference_profile_name #=> String
resp.description #=> String
resp.created_at #=> Time
resp.updated_at #=> Time
resp.inference_profile_arn #=> String
resp.models #=> Array
resp.models[0].model_arn #=> String
resp.inference_profile_id #=> String
resp.status #=> String, one of "ACTIVE"
resp.type #=> String, one of "SYSTEM_DEFINED", "APPLICATION"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :inference_profile_identifier (required, String) —

    The ID or Amazon Resource Name (ARN) of the inference profile.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2970

def get_inference_profile(params = {}, options = {})
  req = build_request(:get_inference_profile, params)
  req.send_request(options)
end

#get_marketplace_model_endpoint(params = {}) ⇒ Types::GetMarketplaceModelEndpointResponse

Retrieves details about a specific endpoint for a model from Amazon Bedrock Marketplace.

Examples:

Request syntax with placeholder values


resp = client.get_marketplace_model_endpoint({
  endpoint_arn: "Arn", # required
})

Response structure


resp.marketplace_model_endpoint.endpoint_arn #=> String
resp.marketplace_model_endpoint.model_source_identifier #=> String
resp.marketplace_model_endpoint.status #=> String, one of "REGISTERED", "INCOMPATIBLE_ENDPOINT"
resp.marketplace_model_endpoint.status_message #=> String
resp.marketplace_model_endpoint.created_at #=> Time
resp.marketplace_model_endpoint.updated_at #=> Time
resp.marketplace_model_endpoint.endpoint_config.sage_maker.initial_instance_count #=> Integer
resp.marketplace_model_endpoint.endpoint_config.sage_maker.instance_type #=> String
resp.marketplace_model_endpoint.endpoint_config.sage_maker.execution_role #=> String
resp.marketplace_model_endpoint.endpoint_config.sage_maker.kms_encryption_key #=> String
resp.marketplace_model_endpoint.endpoint_config.sage_maker.vpc.subnet_ids #=> Array
resp.marketplace_model_endpoint.endpoint_config.sage_maker.vpc.subnet_ids[0] #=> String
resp.marketplace_model_endpoint.endpoint_config.sage_maker.vpc.security_group_ids #=> Array
resp.marketplace_model_endpoint.endpoint_config.sage_maker.vpc.security_group_ids[0] #=> String
resp.marketplace_model_endpoint.endpoint_status #=> String
resp.marketplace_model_endpoint.endpoint_status_message #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :endpoint_arn (required, String) —

    The Amazon Resource Name (ARN) of the endpoint you want to get information about.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3015

def get_marketplace_model_endpoint(params = {}, options = {})
  req = build_request(:get_marketplace_model_endpoint, params)
  req.send_request(options)
end

#get_model_copy_job(params = {}) ⇒ Types::GetModelCopyJobResponse

Retrieves information about a model copy job. For more information, see Copy models to be used in other regions in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.get_model_copy_job({
  job_arn: "ModelCopyJobArn", # required
})

Response structure


resp.job_arn #=> String
resp.status #=> String, one of "InProgress", "Completed", "Failed"
resp.creation_time #=> Time
resp.target_model_arn #=> String
resp.target_model_name #=> String
resp. #=> String
resp.source_model_arn #=> String
resp.target_model_kms_key_arn #=> String
resp.target_model_tags #=> Array
resp.target_model_tags[0].key #=> String
resp.target_model_tags[0].value #=> String
resp.failure_message #=> String
resp.source_model_name #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :job_arn (required, String) —

    The Amazon Resource Name (ARN) of the model copy job.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3072

def get_model_copy_job(params = {}, options = {})
  req = build_request(:get_model_copy_job, params)
  req.send_request(options)
end

#get_model_customization_job(params = {}) ⇒ Types::GetModelCustomizationJobResponse

Retrieves the properties associated with a model-customization job, including the status of the job. For more information, see Custom models in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.get_model_customization_job({
  job_identifier: "ModelCustomizationJobIdentifier", # required
})

Response structure


resp.job_arn #=> String
resp.job_name #=> String
resp.output_model_name #=> String
resp.output_model_arn #=> String
resp.client_request_token #=> String
resp.role_arn #=> String
resp.status #=> String, one of "InProgress", "Completed", "Failed", "Stopping", "Stopped"
resp.status_details.validation_details.status #=> String, one of "InProgress", "Completed", "Stopping", "Stopped", "Failed", "NotStarted"
resp.status_details.validation_details.creation_time #=> Time
resp.status_details.validation_details.last_modified_time #=> Time
resp.status_details.data_processing_details.status #=> String, one of "InProgress", "Completed", "Stopping", "Stopped", "Failed", "NotStarted"
resp.status_details.data_processing_details.creation_time #=> Time
resp.status_details.data_processing_details.last_modified_time #=> Time
resp.status_details.training_details.status #=> String, one of "InProgress", "Completed", "Stopping", "Stopped", "Failed", "NotStarted"
resp.status_details.training_details.creation_time #=> Time
resp.status_details.training_details.last_modified_time #=> Time
resp.failure_message #=> String
resp.creation_time #=> Time
resp.last_modified_time #=> Time
resp.end_time #=> Time
resp.base_model_arn #=> String
resp.hyper_parameters #=> Hash
resp.hyper_parameters["String"] #=> String
resp.training_data_config.s3_uri #=> String
resp.training_data_config.invocation_logs_config.use_prompt_response #=> Boolean
resp.training_data_config.invocation_logs_config.invocation_log_source.s3_uri #=> String
resp.training_data_config.invocation_logs_config.request_metadata_filters.equals #=> Hash
resp.training_data_config.invocation_logs_config.request_metadata_filters.equals["RequestMetadataMapKeyString"] #=> String
resp.training_data_config.invocation_logs_config.request_metadata_filters.not_equals #=> Hash
resp.training_data_config.invocation_logs_config.request_metadata_filters.not_equals["RequestMetadataMapKeyString"] #=> String
resp.training_data_config.invocation_logs_config.request_metadata_filters.and_all #=> Array
resp.training_data_config.invocation_logs_config.request_metadata_filters.and_all[0].equals #=> Hash
resp.training_data_config.invocation_logs_config.request_metadata_filters.and_all[0].equals["RequestMetadataMapKeyString"] #=> String
resp.training_data_config.invocation_logs_config.request_metadata_filters.and_all[0].not_equals #=> Hash
resp.training_data_config.invocation_logs_config.request_metadata_filters.and_all[0].not_equals["RequestMetadataMapKeyString"] #=> String
resp.training_data_config.invocation_logs_config.request_metadata_filters.or_all #=> Array
resp.training_data_config.invocation_logs_config.request_metadata_filters.or_all[0].equals #=> Hash
resp.training_data_config.invocation_logs_config.request_metadata_filters.or_all[0].equals["RequestMetadataMapKeyString"] #=> String
resp.training_data_config.invocation_logs_config.request_metadata_filters.or_all[0].not_equals #=> Hash
resp.training_data_config.invocation_logs_config.request_metadata_filters.or_all[0].not_equals["RequestMetadataMapKeyString"] #=> String
resp.validation_data_config.validators #=> Array
resp.validation_data_config.validators[0].s3_uri #=> String
resp.output_data_config.s3_uri #=> String
resp.customization_type #=> String, one of "FINE_TUNING", "CONTINUED_PRE_TRAINING", "DISTILLATION", "IMPORTED"
resp.output_model_kms_key_arn #=> String
resp.training_metrics.training_loss #=> Float
resp.validation_metrics #=> Array
resp.validation_metrics[0].validation_loss #=> Float
resp.vpc_config.subnet_ids #=> Array
resp.vpc_config.subnet_ids[0] #=> String
resp.vpc_config.security_group_ids #=> Array
resp.vpc_config.security_group_ids[0] #=> String
resp.customization_config.distillation_config.teacher_model_config.teacher_model_identifier #=> String
resp.customization_config.distillation_config.teacher_model_config.max_response_length_for_inference #=> Integer

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :job_identifier (required, String) —

    Identifier for the customization job.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3182

def get_model_customization_job(params = {}, options = {})
  req = build_request(:get_model_customization_job, params)
  req.send_request(options)
end

#get_model_import_job(params = {}) ⇒ Types::GetModelImportJobResponse

Retrieves the properties associated with import model job, including the status of the job. For more information, see Import a customized model in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.get_model_import_job({
  job_identifier: "ModelImportJobIdentifier", # required
})

Response structure


resp.job_arn #=> String
resp.job_name #=> String
resp.imported_model_name #=> String
resp.imported_model_arn #=> String
resp.role_arn #=> String
resp.model_data_source.s3_data_source.s3_uri #=> String
resp.status #=> String, one of "InProgress", "Completed", "Failed"
resp.failure_message #=> String
resp.creation_time #=> Time
resp.last_modified_time #=> Time
resp.end_time #=> Time
resp.vpc_config.subnet_ids #=> Array
resp.vpc_config.subnet_ids[0] #=> String
resp.vpc_config.security_group_ids #=> Array
resp.vpc_config.security_group_ids[0] #=> String
resp.imported_model_kms_key_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :job_identifier (required, String) —

    The identifier of the import job.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3244

def get_model_import_job(params = {}, options = {})
  req = build_request(:get_model_import_job, params)
  req.send_request(options)
end

#get_model_invocation_job(params = {}) ⇒ Types::GetModelInvocationJobResponse

Gets details about a batch inference job. For more information, see Monitor batch inference jobs

Examples:

Request syntax with placeholder values


resp = client.get_model_invocation_job({
  job_identifier: "ModelInvocationJobIdentifier", # required
})

Response structure


resp.job_arn #=> String
resp.job_name #=> String
resp.model_id #=> String
resp.client_request_token #=> String
resp.role_arn #=> String
resp.status #=> String, one of "Submitted", "InProgress", "Completed", "Failed", "Stopping", "Stopped", "PartiallyCompleted", "Expired", "Validating", "Scheduled"
resp.message #=> String
resp.submit_time #=> Time
resp.last_modified_time #=> Time
resp.end_time #=> Time
resp.input_data_config.s3_input_data_config.s3_input_format #=> String, one of "JSONL"
resp.input_data_config.s3_input_data_config.s3_uri #=> String
resp.input_data_config.s3_input_data_config.s3_bucket_owner #=> String
resp.output_data_config.s3_output_data_config.s3_uri #=> String
resp.output_data_config.s3_output_data_config.s3_encryption_key_id #=> String
resp.output_data_config.s3_output_data_config.s3_bucket_owner #=> String
resp.vpc_config.subnet_ids #=> Array
resp.vpc_config.subnet_ids[0] #=> String
resp.vpc_config.security_group_ids #=> Array
resp.vpc_config.security_group_ids[0] #=> String
resp.timeout_duration_in_hours #=> Integer
resp.job_expiration_time #=> Time

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :job_identifier (required, String) —

    The Amazon Resource Name (ARN) of the batch inference job.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3312

def get_model_invocation_job(params = {}, options = {})
  req = build_request(:get_model_invocation_job, params)
  req.send_request(options)
end

#get_model_invocation_logging_configuration(params = {}) ⇒ Types::GetModelInvocationLoggingConfigurationResponse

Get the current configuration values for model invocation logging.

Examples:

Response structure


resp.logging_config.cloud_watch_config.log_group_name #=> String
resp.logging_config.cloud_watch_config.role_arn #=> String
resp.logging_config.cloud_watch_config.large_data_delivery_s3_config.bucket_name #=> String
resp.logging_config.cloud_watch_config.large_data_delivery_s3_config.key_prefix #=> String
resp.logging_config.s3_config.bucket_name #=> String
resp.logging_config.s3_config.key_prefix #=> String
resp.logging_config.text_data_delivery_enabled #=> Boolean
resp.logging_config.image_data_delivery_enabled #=> Boolean
resp.logging_config.embedding_data_delivery_enabled #=> Boolean
resp.logging_config.video_data_delivery_enabled #=> Boolean

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3340

def get_model_invocation_logging_configuration(params = {}, options = {})
  req = build_request(:get_model_invocation_logging_configuration, params)
  req.send_request(options)
end

#get_prompt_router(params = {}) ⇒ Types::GetPromptRouterResponse

Retrieves details about a prompt router.

Examples:

Request syntax with placeholder values


resp = client.get_prompt_router({
  prompt_router_arn: "PromptRouterArn", # required
})

Response structure


resp.prompt_router_name #=> String
resp.routing_criteria.response_quality_difference #=> Float
resp.description #=> String
resp.created_at #=> Time
resp.updated_at #=> Time
resp.prompt_router_arn #=> String
resp.models #=> Array
resp.models[0].model_arn #=> String
resp.fallback_model.model_arn #=> String
resp.status #=> String, one of "AVAILABLE"
resp.type #=> String, one of "custom", "default"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :prompt_router_arn (required, String) —

    The prompt router's ARN

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3387

def get_prompt_router(params = {}, options = {})
  req = build_request(:get_prompt_router, params)
  req.send_request(options)
end

#get_provisioned_model_throughput(params = {}) ⇒ Types::GetProvisionedModelThroughputResponse

Returns details for a Provisioned Throughput. For more information, see Provisioned Throughput in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.get_provisioned_model_throughput({
  provisioned_model_id: "ProvisionedModelId", # required
})

Response structure


resp.model_units #=> Integer
resp.desired_model_units #=> Integer
resp.provisioned_model_name #=> String
resp.provisioned_model_arn #=> String
resp.model_arn #=> String
resp.desired_model_arn #=> String
resp.foundation_model_arn #=> String
resp.status #=> String, one of "Creating", "InService", "Updating", "Failed"
resp.creation_time #=> Time
resp.last_modified_time #=> Time
resp.failure_message #=> String
resp.commitment_duration #=> String, one of "OneMonth", "SixMonths"
resp.commitment_expiration_time #=> Time

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :provisioned_model_id (required, String) —

    The Amazon Resource Name (ARN) or name of the Provisioned Throughput.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3445

def get_provisioned_model_throughput(params = {}, options = {})
  req = build_request(:get_provisioned_model_throughput, params)
  req.send_request(options)
end

#list_custom_models(params = {}) ⇒ Types::ListCustomModelsResponse

Returns a list of the custom models that you have created with the CreateModelCustomizationJob operation.

For more information, see Custom models in the Amazon Bedrock User Guide.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_custom_models({
  creation_time_before: Time.now,
  creation_time_after: Time.now,
  name_contains: "CustomModelName",
  base_model_arn_equals: "ModelArn",
  foundation_model_arn_equals: "FoundationModelArn",
  max_results: 1,
  next_token: "PaginationToken",
  sort_by: "CreationTime", # accepts CreationTime
  sort_order: "Ascending", # accepts Ascending, Descending
  is_owned: false,
  model_status: "Active", # accepts Active, Creating, Failed
})

Response structure


resp.next_token #=> String
resp.model_summaries #=> Array
resp.model_summaries[0].model_arn #=> String
resp.model_summaries[0].model_name #=> String
resp.model_summaries[0].creation_time #=> Time
resp.model_summaries[0].base_model_arn #=> String
resp.model_summaries[0].base_model_name #=> String
resp.model_summaries[0].customization_type #=> String, one of "FINE_TUNING", "CONTINUED_PRE_TRAINING", "DISTILLATION", "IMPORTED"
resp.model_summaries[0]. #=> String
resp.model_summaries[0].model_status #=> String, one of "Active", "Creating", "Failed"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :creation_time_before (Time, DateTime, Date, Integer, String) —

    Return custom models created before the specified time.

  • :creation_time_after (Time, DateTime, Date, Integer, String) —

    Return custom models created after the specified time.

  • :name_contains (String) —

    Return custom models only if the job name contains these characters.

  • :base_model_arn_equals (String) —

    Return custom models only if the base model Amazon Resource Name (ARN) matches this parameter.

  • :foundation_model_arn_equals (String) —

    Return custom models only if the foundation model Amazon Resource Name (ARN) matches this parameter.

  • :max_results (Integer) —

    The maximum number of results to return in the response. If the total number of results is greater than this value, use the token returned in the response in the nextToken field when making another request to return the next batch of results.

  • :next_token (String) —

    If the total number of results is greater than the maxResults value provided in the request, enter the token returned in the nextToken field in the response in this field to return the next batch of results.

  • :sort_by (String) —

    The field to sort by in the returned list of models.

  • :sort_order (String) —

    The sort order of the results.

  • :is_owned (Boolean) —

    Return custom models depending on if the current account owns them (true) or if they were shared with the current account (false).

  • :model_status (String) —

    The status of them model to filter results by. Possible values include:

    • Creating - Include only models that are currently being created and validated.

    • Active - Include only models that have been successfully created and are ready for use.

    • Failed - Include only models where the creation process failed.

    If you don't specify a status, the API returns models in all states.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3554

def list_custom_models(params = {}, options = {})
  req = build_request(:list_custom_models, params)
  req.send_request(options)
end

#list_evaluation_jobs(params = {}) ⇒ Types::ListEvaluationJobsResponse

Lists all existing evaluation jobs.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_evaluation_jobs({
  creation_time_after: Time.now,
  creation_time_before: Time.now,
  status_equals: "InProgress", # accepts InProgress, Completed, Failed, Stopping, Stopped, Deleting
  application_type_equals: "ModelEvaluation", # accepts ModelEvaluation, RagEvaluation
  name_contains: "EvaluationJobName",
  max_results: 1,
  next_token: "PaginationToken",
  sort_by: "CreationTime", # accepts CreationTime
  sort_order: "Ascending", # accepts Ascending, Descending
})

Response structure


resp.next_token #=> String
resp.job_summaries #=> Array
resp.job_summaries[0].job_arn #=> String
resp.job_summaries[0].job_name #=> String
resp.job_summaries[0].status #=> String, one of "InProgress", "Completed", "Failed", "Stopping", "Stopped", "Deleting"
resp.job_summaries[0].creation_time #=> Time
resp.job_summaries[0].job_type #=> String, one of "Human", "Automated"
resp.job_summaries[0].evaluation_task_types #=> Array
resp.job_summaries[0].evaluation_task_types[0] #=> String, one of "Summarization", "Classification", "QuestionAndAnswer", "Generation", "Custom"
resp.job_summaries[0].model_identifiers #=> Array
resp.job_summaries[0].model_identifiers[0] #=> String
resp.job_summaries[0].rag_identifiers #=> Array
resp.job_summaries[0].rag_identifiers[0] #=> String
resp.job_summaries[0].evaluator_model_identifiers #=> Array
resp.job_summaries[0].evaluator_model_identifiers[0] #=> String
resp.job_summaries[0].custom_metrics_evaluator_model_identifiers #=> Array
resp.job_summaries[0].custom_metrics_evaluator_model_identifiers[0] #=> String
resp.job_summaries[0].inference_config_summary.model_config_summary.bedrock_model_identifiers #=> Array
resp.job_summaries[0].inference_config_summary.model_config_summary.bedrock_model_identifiers[0] #=> String
resp.job_summaries[0].inference_config_summary.model_config_summary.precomputed_inference_source_identifiers #=> Array
resp.job_summaries[0].inference_config_summary.model_config_summary.precomputed_inference_source_identifiers[0] #=> String
resp.job_summaries[0].inference_config_summary.rag_config_summary.bedrock_knowledge_base_identifiers #=> Array
resp.job_summaries[0].inference_config_summary.rag_config_summary.bedrock_knowledge_base_identifiers[0] #=> String
resp.job_summaries[0].inference_config_summary.rag_config_summary.precomputed_rag_source_identifiers #=> Array
resp.job_summaries[0].inference_config_summary.rag_config_summary.precomputed_rag_source_identifiers[0] #=> String
resp.job_summaries[0].application_type #=> String, one of "ModelEvaluation", "RagEvaluation"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :creation_time_after (Time, DateTime, Date, Integer, String) —

    A filter to only list evaluation jobs created after a specified time.

  • :creation_time_before (Time, DateTime, Date, Integer, String) —

    A filter to only list evaluation jobs created before a specified time.

  • :status_equals (String) —

    A filter to only list evaluation jobs that are of a certain status.

  • :application_type_equals (String) —

    A filter to only list evaluation jobs that are either model evaluations or knowledge base evaluations.

  • :name_contains (String) —

    A filter to only list evaluation jobs that contain a specified string in the job name.

  • :max_results (Integer) —

    The maximum number of results to return.

  • :next_token (String) —

    Continuation token from the previous response, for Amazon Bedrock to list the next set of results.

  • :sort_by (String) —

    Specifies a creation time to sort the list of evaluation jobs by when they were created.

  • :sort_order (String) —

    Specifies whether to sort the list of evaluation jobs by either ascending or descending order.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3647

def list_evaluation_jobs(params = {}, options = {})
  req = build_request(:list_evaluation_jobs, params)
  req.send_request(options)
end

#list_foundation_models(params = {}) ⇒ Types::ListFoundationModelsResponse

Lists Amazon Bedrock foundation models that you can use. You can filter the results with the request parameters. For more information, see Foundation models in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.list_foundation_models({
  by_provider: "Provider",
  by_customization_type: "FINE_TUNING", # accepts FINE_TUNING, CONTINUED_PRE_TRAINING, DISTILLATION
  by_output_modality: "TEXT", # accepts TEXT, IMAGE, EMBEDDING
  by_inference_type: "ON_DEMAND", # accepts ON_DEMAND, PROVISIONED
})

Response structure


resp.model_summaries #=> Array
resp.model_summaries[0].model_arn #=> String
resp.model_summaries[0].model_id #=> String
resp.model_summaries[0].model_name #=> String
resp.model_summaries[0].provider_name #=> String
resp.model_summaries[0].input_modalities #=> Array
resp.model_summaries[0].input_modalities[0] #=> String, one of "TEXT", "IMAGE", "EMBEDDING"
resp.model_summaries[0].output_modalities #=> Array
resp.model_summaries[0].output_modalities[0] #=> String, one of "TEXT", "IMAGE", "EMBEDDING"
resp.model_summaries[0].response_streaming_supported #=> Boolean
resp.model_summaries[0].customizations_supported #=> Array
resp.model_summaries[0].customizations_supported[0] #=> String, one of "FINE_TUNING", "CONTINUED_PRE_TRAINING", "DISTILLATION"
resp.model_summaries[0].inference_types_supported #=> Array
resp.model_summaries[0].inference_types_supported[0] #=> String, one of "ON_DEMAND", "PROVISIONED"
resp.model_summaries[0].model_lifecycle.status #=> String, one of "ACTIVE", "LEGACY"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :by_provider (String) —

    Return models belonging to the model provider that you specify.

  • :by_customization_type (String) —

    Return models that support the customization type that you specify. For more information, see Custom models in the Amazon Bedrock User Guide.

  • :by_output_modality (String) —

    Return models that support the output modality that you specify.

  • :by_inference_type (String) —

    Return models that support the inference type that you specify. For more information, see Provisioned Throughput in the Amazon Bedrock User Guide.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3722

def list_foundation_models(params = {}, options = {})
  req = build_request(:list_foundation_models, params)
  req.send_request(options)
end

#list_guardrails(params = {}) ⇒ Types::ListGuardrailsResponse

Lists details about all the guardrails in an account. To list the DRAFT version of all your guardrails, don't specify the guardrailIdentifier field. To list all versions of a guardrail, specify the ARN of the guardrail in the guardrailIdentifier field.

You can set the maximum number of results to return in a response in the maxResults field. If there are more results than the number you set, the response returns a nextToken that you can send in another ListGuardrails request to see the next batch of results.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_guardrails({
  guardrail_identifier: "GuardrailIdentifier",
  max_results: 1,
  next_token: "PaginationToken",
})

Response structure


resp.guardrails #=> Array
resp.guardrails[0].id #=> String
resp.guardrails[0].arn #=> String
resp.guardrails[0].status #=> String, one of "CREATING", "UPDATING", "VERSIONING", "READY", "FAILED", "DELETING"
resp.guardrails[0].name #=> String
resp.guardrails[0].description #=> String
resp.guardrails[0].version #=> String
resp.guardrails[0].created_at #=> Time
resp.guardrails[0].updated_at #=> Time
resp.guardrails[0].cross_region_details.guardrail_profile_id #=> String
resp.guardrails[0].cross_region_details.guardrail_profile_arn #=> String
resp.next_token #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :guardrail_identifier (String) —

    The unique identifier of the guardrail. This can be an ID or the ARN.

  • :max_results (Integer) —

    The maximum number of results to return in the response.

  • :next_token (String) —

    If there are more results than were returned in the response, the response returns a nextToken that you can send in another ListGuardrails request to see the next batch of results.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3782

def list_guardrails(params = {}, options = {})
  req = build_request(:list_guardrails, params)
  req.send_request(options)
end

#list_imported_models(params = {}) ⇒ Types::ListImportedModelsResponse

Returns a list of models you've imported. You can filter the results to return based on one or more criteria. For more information, see Import a customized model in the Amazon Bedrock User Guide.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_imported_models({
  creation_time_before: Time.now,
  creation_time_after: Time.now,
  name_contains: "ImportedModelName",
  max_results: 1,
  next_token: "PaginationToken",
  sort_by: "CreationTime", # accepts CreationTime
  sort_order: "Ascending", # accepts Ascending, Descending
})

Response structure


resp.next_token #=> String
resp.model_summaries #=> Array
resp.model_summaries[0].model_arn #=> String
resp.model_summaries[0].model_name #=> String
resp.model_summaries[0].creation_time #=> Time
resp.model_summaries[0].instruct_supported #=> Boolean
resp.model_summaries[0].model_architecture #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :creation_time_before (Time, DateTime, Date, Integer, String) —

    Return imported models that created before the specified time.

  • :creation_time_after (Time, DateTime, Date, Integer, String) —

    Return imported models that were created after the specified time.

  • :name_contains (String) —

    Return imported models only if the model name contains these characters.

  • :max_results (Integer) —

    The maximum number of results to return in the response. If the total number of results is greater than this value, use the token returned in the response in the nextToken field when making another request to return the next batch of results.

  • :next_token (String) —

    If the total number of results is greater than the maxResults value provided in the request, enter the token returned in the nextToken field in the response in this field to return the next batch of results.

  • :sort_by (String) —

    The field to sort by in the returned list of imported models.

  • :sort_order (String) —

    Specifies whetehr to sort the results in ascending or descending order.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3858

def list_imported_models(params = {}, options = {})
  req = build_request(:list_imported_models, params)
  req.send_request(options)
end

#list_inference_profiles(params = {}) ⇒ Types::ListInferenceProfilesResponse

Returns a list of inference profiles that you can use. For more information, see Increase throughput and resilience with cross-region inference in Amazon Bedrock. in the Amazon Bedrock User Guide.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_inference_profiles({
  max_results: 1,
  next_token: "PaginationToken",
  type_equals: "SYSTEM_DEFINED", # accepts SYSTEM_DEFINED, APPLICATION
})

Response structure


resp.inference_profile_summaries #=> Array
resp.inference_profile_summaries[0].inference_profile_name #=> String
resp.inference_profile_summaries[0].description #=> String
resp.inference_profile_summaries[0].created_at #=> Time
resp.inference_profile_summaries[0].updated_at #=> Time
resp.inference_profile_summaries[0].inference_profile_arn #=> String
resp.inference_profile_summaries[0].models #=> Array
resp.inference_profile_summaries[0].models[0].model_arn #=> String
resp.inference_profile_summaries[0].inference_profile_id #=> String
resp.inference_profile_summaries[0].status #=> String, one of "ACTIVE"
resp.inference_profile_summaries[0].type #=> String, one of "SYSTEM_DEFINED", "APPLICATION"
resp.next_token #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :max_results (Integer) —

    The maximum number of results to return in the response. If the total number of results is greater than this value, use the token returned in the response in the nextToken field when making another request to return the next batch of results.

  • :next_token (String) —

    If the total number of results is greater than the maxResults value provided in the request, enter the token returned in the nextToken field in the response in this field to return the next batch of results.

  • :type_equals (String) —

    Filters for inference profiles that match the type you specify.

    • SYSTEM_DEFINED – The inference profile is defined by Amazon Bedrock. You can route inference requests across regions with these inference profiles.

    • APPLICATION – The inference profile was created by a user. This type of inference profile can track metrics and costs when invoking the model in it. The inference profile may route requests to one or multiple regions.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3929

def list_inference_profiles(params = {}, options = {})
  req = build_request(:list_inference_profiles, params)
  req.send_request(options)
end

#list_marketplace_model_endpoints(params = {}) ⇒ Types::ListMarketplaceModelEndpointsResponse

Lists the endpoints for models from Amazon Bedrock Marketplace in your Amazon Web Services account.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_marketplace_model_endpoints({
  max_results: 1,
  next_token: "PaginationToken",
  model_source_equals: "ModelSourceIdentifier",
})

Response structure


resp.marketplace_model_endpoints #=> Array
resp.marketplace_model_endpoints[0].endpoint_arn #=> String
resp.marketplace_model_endpoints[0].model_source_identifier #=> String
resp.marketplace_model_endpoints[0].status #=> String, one of "REGISTERED", "INCOMPATIBLE_ENDPOINT"
resp.marketplace_model_endpoints[0].status_message #=> String
resp.marketplace_model_endpoints[0].created_at #=> Time
resp.marketplace_model_endpoints[0].updated_at #=> Time
resp.next_token #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :max_results (Integer) —

    The maximum number of results to return in a single call. If more results are available, the operation returns a NextToken value.

  • :next_token (String) —

    The token for the next set of results. You receive this token from a previous ListMarketplaceModelEndpoints call.

  • :model_source_equals (String) —

    If specified, only endpoints for the given model source identifier are returned.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3979

def list_marketplace_model_endpoints(params = {}, options = {})
  req = build_request(:list_marketplace_model_endpoints, params)
  req.send_request(options)
end

#list_model_copy_jobs(params = {}) ⇒ Types::ListModelCopyJobsResponse

Returns a list of model copy jobs that you have submitted. You can filter the jobs to return based on one or more criteria. For more information, see Copy models to be used in other regions in the Amazon Bedrock User Guide.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_model_copy_jobs({
  creation_time_after: Time.now,
  creation_time_before: Time.now,
  status_equals: "InProgress", # accepts InProgress, Completed, Failed
  source_account_equals: "AccountId",
  source_model_arn_equals: "ModelArn",
  target_model_name_contains: "CustomModelName",
  max_results: 1,
  next_token: "PaginationToken",
  sort_by: "CreationTime", # accepts CreationTime
  sort_order: "Ascending", # accepts Ascending, Descending
})

Response structure


resp.next_token #=> String
resp.model_copy_job_summaries #=> Array
resp.model_copy_job_summaries[0].job_arn #=> String
resp.model_copy_job_summaries[0].status #=> String, one of "InProgress", "Completed", "Failed"
resp.model_copy_job_summaries[0].creation_time #=> Time
resp.model_copy_job_summaries[0].target_model_arn #=> String
resp.model_copy_job_summaries[0].target_model_name #=> String
resp.model_copy_job_summaries[0]. #=> String
resp.model_copy_job_summaries[0].source_model_arn #=> String
resp.model_copy_job_summaries[0].target_model_kms_key_arn #=> String
resp.model_copy_job_summaries[0].target_model_tags #=> Array
resp.model_copy_job_summaries[0].target_model_tags[0].key #=> String
resp.model_copy_job_summaries[0].target_model_tags[0].value #=> String
resp.model_copy_job_summaries[0].failure_message #=> String
resp.model_copy_job_summaries[0].source_model_name #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :creation_time_after (Time, DateTime, Date, Integer, String) —

    Filters for model copy jobs created after the specified time.

  • :creation_time_before (Time, DateTime, Date, Integer, String) —

    Filters for model copy jobs created before the specified time.

  • :status_equals (String) —

    Filters for model copy jobs whose status matches the value that you specify.

  • :source_account_equals (String) —

    Filters for model copy jobs in which the account that the source model belongs to is equal to the value that you specify.

  • :source_model_arn_equals (String) —

    Filters for model copy jobs in which the Amazon Resource Name (ARN) of the source model to is equal to the value that you specify.

  • :target_model_name_contains (String) —

    Filters for model copy jobs in which the name of the copied model contains the string that you specify.

  • :max_results (Integer) —

    The maximum number of results to return in the response. If the total number of results is greater than this value, use the token returned in the response in the nextToken field when making another request to return the next batch of results.

  • :next_token (String) —

    If the total number of results is greater than the maxResults value provided in the request, enter the token returned in the nextToken field in the response in this field to return the next batch of results.

  • :sort_by (String) —

    The field to sort by in the returned list of model copy jobs.

  • :sort_order (String) —

    Specifies whether to sort the results in ascending or descending order.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 4079

def list_model_copy_jobs(params = {}, options = {})
  req = build_request(:list_model_copy_jobs, params)
  req.send_request(options)
end

#list_model_customization_jobs(params = {}) ⇒ Types::ListModelCustomizationJobsResponse

Returns a list of model customization jobs that you have submitted. You can filter the jobs to return based on one or more criteria.

For more information, see Custom models in the Amazon Bedrock User Guide.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_model_customization_jobs({
  creation_time_after: Time.now,
  creation_time_before: Time.now,
  status_equals: "InProgress", # accepts InProgress, Completed, Failed, Stopping, Stopped
  name_contains: "JobName",
  max_results: 1,
  next_token: "PaginationToken",
  sort_by: "CreationTime", # accepts CreationTime
  sort_order: "Ascending", # accepts Ascending, Descending
})

Response structure


resp.next_token #=> String
resp.model_customization_job_summaries #=> Array
resp.model_customization_job_summaries[0].job_arn #=> String
resp.model_customization_job_summaries[0].base_model_arn #=> String
resp.model_customization_job_summaries[0].job_name #=> String
resp.model_customization_job_summaries[0].status #=> String, one of "InProgress", "Completed", "Failed", "Stopping", "Stopped"
resp.model_customization_job_summaries[0].status_details.validation_details.status #=> String, one of "InProgress", "Completed", "Stopping", "Stopped", "Failed", "NotStarted"
resp.model_customization_job_summaries[0].status_details.validation_details.creation_time #=> Time
resp.model_customization_job_summaries[0].status_details.validation_details.last_modified_time #=> Time
resp.model_customization_job_summaries[0].status_details.data_processing_details.status #=> String, one of "InProgress", "Completed", "Stopping", "Stopped", "Failed", "NotStarted"
resp.model_customization_job_summaries[0].status_details.data_processing_details.creation_time #=> Time
resp.model_customization_job_summaries[0].status_details.data_processing_details.last_modified_time #=> Time
resp.model_customization_job_summaries[0].status_details.training_details.status #=> String, one of "InProgress", "Completed", "Stopping", "Stopped", "Failed", "NotStarted"
resp.model_customization_job_summaries[0].status_details.training_details.creation_time #=> Time
resp.model_customization_job_summaries[0].status_details.training_details.last_modified_time #=> Time
resp.model_customization_job_summaries[0].last_modified_time #=> Time
resp.model_customization_job_summaries[0].creation_time #=> Time
resp.model_customization_job_summaries[0].end_time #=> Time
resp.model_customization_job_summaries[0].custom_model_arn #=> String
resp.model_customization_job_summaries[0].custom_model_name #=> String
resp.model_customization_job_summaries[0].customization_type #=> String, one of "FINE_TUNING", "CONTINUED_PRE_TRAINING", "DISTILLATION", "IMPORTED"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :creation_time_after (Time, DateTime, Date, Integer, String) —

    Return customization jobs created after the specified time.

  • :creation_time_before (Time, DateTime, Date, Integer, String) —

    Return customization jobs created before the specified time.

  • :status_equals (String) —

    Return customization jobs with the specified status.

  • :name_contains (String) —

    Return customization jobs only if the job name contains these characters.

  • :max_results (Integer) —

    The maximum number of results to return in the response. If the total number of results is greater than this value, use the token returned in the response in the nextToken field when making another request to return the next batch of results.

  • :next_token (String) —

    If the total number of results is greater than the maxResults value provided in the request, enter the token returned in the nextToken field in the response in this field to return the next batch of results.

  • :sort_by (String) —

    The field to sort by in the returned list of jobs.

  • :sort_order (String) —

    The sort order of the results.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 4174

def list_model_customization_jobs(params = {}, options = {})
  req = build_request(:list_model_customization_jobs, params)
  req.send_request(options)
end

#list_model_import_jobs(params = {}) ⇒ Types::ListModelImportJobsResponse

Returns a list of import jobs you've submitted. You can filter the results to return based on one or more criteria. For more information, see Import a customized model in the Amazon Bedrock User Guide.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_model_import_jobs({
  creation_time_after: Time.now,
  creation_time_before: Time.now,
  status_equals: "InProgress", # accepts InProgress, Completed, Failed
  name_contains: "JobName",
  max_results: 1,
  next_token: "PaginationToken",
  sort_by: "CreationTime", # accepts CreationTime
  sort_order: "Ascending", # accepts Ascending, Descending
})

Response structure


resp.next_token #=> String
resp.model_import_job_summaries #=> Array
resp.model_import_job_summaries[0].job_arn #=> String
resp.model_import_job_summaries[0].job_name #=> String
resp.model_import_job_summaries[0].status #=> String, one of "InProgress", "Completed", "Failed"
resp.model_import_job_summaries[0].last_modified_time #=> Time
resp.model_import_job_summaries[0].creation_time #=> Time
resp.model_import_job_summaries[0].end_time #=> Time
resp.model_import_job_summaries[0].imported_model_arn #=> String
resp.model_import_job_summaries[0].imported_model_name #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :creation_time_after (Time, DateTime, Date, Integer, String) —

    Return import jobs that were created after the specified time.

  • :creation_time_before (Time, DateTime, Date, Integer, String) —

    Return import jobs that were created before the specified time.

  • :status_equals (String) —

    Return imported jobs with the specified status.

  • :name_contains (String) —

    Return imported jobs only if the job name contains these characters.

  • :max_results (Integer) —

    The maximum number of results to return in the response. If the total number of results is greater than this value, use the token returned in the response in the nextToken field when making another request to return the next batch of results.

  • :next_token (String) —

    If the total number of results is greater than the maxResults value provided in the request, enter the token returned in the nextToken field in the response in this field to return the next batch of results.

  • :sort_by (String) —

    The field to sort by in the returned list of imported jobs.

  • :sort_order (String) —

    Specifies whether to sort the results in ascending or descending order.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 4257

def list_model_import_jobs(params = {}, options = {})
  req = build_request(:list_model_import_jobs, params)
  req.send_request(options)
end

#list_model_invocation_jobs(params = {}) ⇒ Types::ListModelInvocationJobsResponse

Lists all batch inference jobs in the account. For more information, see View details about a batch inference job.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_model_invocation_jobs({
  submit_time_after: Time.now,
  submit_time_before: Time.now,
  status_equals: "Submitted", # accepts Submitted, InProgress, Completed, Failed, Stopping, Stopped, PartiallyCompleted, Expired, Validating, Scheduled
  name_contains: "ModelInvocationJobName",
  max_results: 1,
  next_token: "PaginationToken",
  sort_by: "CreationTime", # accepts CreationTime
  sort_order: "Ascending", # accepts Ascending, Descending
})

Response structure


resp.next_token #=> String
resp.invocation_job_summaries #=> Array
resp.invocation_job_summaries[0].job_arn #=> String
resp.invocation_job_summaries[0].job_name #=> String
resp.invocation_job_summaries[0].model_id #=> String
resp.invocation_job_summaries[0].client_request_token #=> String
resp.invocation_job_summaries[0].role_arn #=> String
resp.invocation_job_summaries[0].status #=> String, one of "Submitted", "InProgress", "Completed", "Failed", "Stopping", "Stopped", "PartiallyCompleted", "Expired", "Validating", "Scheduled"
resp.invocation_job_summaries[0].message #=> String
resp.invocation_job_summaries[0].submit_time #=> Time
resp.invocation_job_summaries[0].last_modified_time #=> Time
resp.invocation_job_summaries[0].end_time #=> Time
resp.invocation_job_summaries[0].input_data_config.s3_input_data_config.s3_input_format #=> String, one of "JSONL"
resp.invocation_job_summaries[0].input_data_config.s3_input_data_config.s3_uri #=> String
resp.invocation_job_summaries[0].input_data_config.s3_input_data_config.s3_bucket_owner #=> String
resp.invocation_job_summaries[0].output_data_config.s3_output_data_config.s3_uri #=> String
resp.invocation_job_summaries[0].output_data_config.s3_output_data_config.s3_encryption_key_id #=> String
resp.invocation_job_summaries[0].output_data_config.s3_output_data_config.s3_bucket_owner #=> String
resp.invocation_job_summaries[0].vpc_config.subnet_ids #=> Array
resp.invocation_job_summaries[0].vpc_config.subnet_ids[0] #=> String
resp.invocation_job_summaries[0].vpc_config.security_group_ids #=> Array
resp.invocation_job_summaries[0].vpc_config.security_group_ids[0] #=> String
resp.invocation_job_summaries[0].timeout_duration_in_hours #=> Integer
resp.invocation_job_summaries[0].job_expiration_time #=> Time

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :submit_time_after (Time, DateTime, Date, Integer, String) —

    Specify a time to filter for batch inference jobs that were submitted after the time you specify.

  • :submit_time_before (Time, DateTime, Date, Integer, String) —

    Specify a time to filter for batch inference jobs that were submitted before the time you specify.

  • :status_equals (String) —

    Specify a status to filter for batch inference jobs whose statuses match the string you specify.

    The following statuses are possible:

    • Submitted – This job has been submitted to a queue for validation.

    • Validating – This job is being validated for the requirements described in Format and upload your batch inference data. The criteria include the following:

      • Your IAM service role has access to the Amazon S3 buckets containing your files.

      • Your files are .jsonl files and each individual record is a JSON object in the correct format. Note that validation doesn't check if the modelInput value matches the request body for the model.

      • Your files fulfill the requirements for file size and number of records. For more information, see Quotas for Amazon Bedrock.

    • Scheduled – This job has been validated and is now in a queue. The job will automatically start when it reaches its turn.

    • Expired – This job timed out because it was scheduled but didn't begin before the set timeout duration. Submit a new job request.

    • InProgress – This job has begun. You can start viewing the results in the output S3 location.

    • Completed – This job has successfully completed. View the output files in the output S3 location.

    • PartiallyCompleted – This job has partially completed. Not all of your records could be processed in time. View the output files in the output S3 location.

    • Failed – This job has failed. Check the failure message for any further details. For further assistance, reach out to the Amazon Web ServicesSupport Center.

    • Stopped – This job was stopped by a user.

    • Stopping – This job is being stopped by a user.

  • :name_contains (String) —

    Specify a string to filter for batch inference jobs whose names contain the string.

  • :max_results (Integer) —

    The maximum number of results to return. If there are more results than the number that you specify, a nextToken value is returned. Use the nextToken in a request to return the next batch of results.

  • :next_token (String) —

    If there were more results than the value you specified in the maxResults field in a previous ListModelInvocationJobs request, the response would have returned a nextToken value. To see the next batch of results, send the nextToken value in another request.

  • :sort_by (String) —

    An attribute by which to sort the results.

  • :sort_order (String) —

    Specifies whether to sort the results by ascending or descending order.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 4401

def list_model_invocation_jobs(params = {}, options = {})
  req = build_request(:list_model_invocation_jobs, params)
  req.send_request(options)
end

#list_prompt_routers(params = {}) ⇒ Types::ListPromptRoutersResponse

Retrieves a list of prompt routers.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_prompt_routers({
  max_results: 1,
  next_token: "PaginationToken",
  type: "custom", # accepts custom, default
})

Response structure


resp.prompt_router_summaries #=> Array
resp.prompt_router_summaries[0].prompt_router_name #=> String
resp.prompt_router_summaries[0].routing_criteria.response_quality_difference #=> Float
resp.prompt_router_summaries[0].description #=> String
resp.prompt_router_summaries[0].created_at #=> Time
resp.prompt_router_summaries[0].updated_at #=> Time
resp.prompt_router_summaries[0].prompt_router_arn #=> String
resp.prompt_router_summaries[0].models #=> Array
resp.prompt_router_summaries[0].models[0].model_arn #=> String
resp.prompt_router_summaries[0].fallback_model.model_arn #=> String
resp.prompt_router_summaries[0].status #=> String, one of "AVAILABLE"
resp.prompt_router_summaries[0].type #=> String, one of "custom", "default"
resp.next_token #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :max_results (Integer) —

    The maximum number of prompt routers to return in one page of results.

  • :next_token (String) —

    Specify the pagination token from a previous request to retrieve the next page of results.

  • :type (String) —

    The type of the prompt routers, such as whether it's default or custom.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 4454

def list_prompt_routers(params = {}, options = {})
  req = build_request(:list_prompt_routers, params)
  req.send_request(options)
end

#list_provisioned_model_throughputs(params = {}) ⇒ Types::ListProvisionedModelThroughputsResponse

Lists the Provisioned Throughputs in the account. For more information, see Provisioned Throughput in the Amazon Bedrock User Guide.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_provisioned_model_throughputs({
  creation_time_after: Time.now,
  creation_time_before: Time.now,
  status_equals: "Creating", # accepts Creating, InService, Updating, Failed
  model_arn_equals: "ModelArn",
  name_contains: "ProvisionedModelName",
  max_results: 1,
  next_token: "PaginationToken",
  sort_by: "CreationTime", # accepts CreationTime
  sort_order: "Ascending", # accepts Ascending, Descending
})

Response structure


resp.next_token #=> String
resp.provisioned_model_summaries #=> Array
resp.provisioned_model_summaries[0].provisioned_model_name #=> String
resp.provisioned_model_summaries[0].provisioned_model_arn #=> String
resp.provisioned_model_summaries[0].model_arn #=> String
resp.provisioned_model_summaries[0].desired_model_arn #=> String
resp.provisioned_model_summaries[0].foundation_model_arn #=> String
resp.provisioned_model_summaries[0].model_units #=> Integer
resp.provisioned_model_summaries[0].desired_model_units #=> Integer
resp.provisioned_model_summaries[0].status #=> String, one of "Creating", "InService", "Updating", "Failed"
resp.provisioned_model_summaries[0].commitment_duration #=> String, one of "OneMonth", "SixMonths"
resp.provisioned_model_summaries[0].commitment_expiration_time #=> Time
resp.provisioned_model_summaries[0].creation_time #=> Time
resp.provisioned_model_summaries[0].last_modified_time #=> Time

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :creation_time_after (Time, DateTime, Date, Integer, String) —

    A filter that returns Provisioned Throughputs created after the specified time.

  • :creation_time_before (Time, DateTime, Date, Integer, String) —

    A filter that returns Provisioned Throughputs created before the specified time.

  • :status_equals (String) —

    A filter that returns Provisioned Throughputs if their statuses matches the value that you specify.

  • :model_arn_equals (String) —

    A filter that returns Provisioned Throughputs whose model Amazon Resource Name (ARN) is equal to the value that you specify.

  • :name_contains (String) —

    A filter that returns Provisioned Throughputs if their name contains the expression that you specify.

  • :max_results (Integer) —

    THe maximum number of results to return in the response. If there are more results than the number you specified, the response returns a nextToken value. To see the next batch of results, send the nextToken value in another list request.

  • :next_token (String) —

    If there are more results than the number you specified in the maxResults field, the response returns a nextToken value. To see the next batch of results, specify the nextToken value in this field.

  • :sort_by (String) —

    The field by which to sort the returned list of Provisioned Throughputs.

  • :sort_order (String) —

    The sort order of the results.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 4549

def list_provisioned_model_throughputs(params = {}, options = {})
  req = build_request(:list_provisioned_model_throughputs, params)
  req.send_request(options)
end

#list_tags_for_resource(params = {}) ⇒ Types::ListTagsForResourceResponse

List the tags associated with the specified resource.

For more information, see Tagging resources in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.list_tags_for_resource({
  resource_arn: "TaggableResourcesArn", # required
})

Response structure


resp.tags #=> Array
resp.tags[0].key #=> String
resp.tags[0].value #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :resource_arn (required, String) —

    The Amazon Resource Name (ARN) of the resource.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 4586

def list_tags_for_resource(params = {}, options = {})
  req = build_request(:list_tags_for_resource, params)
  req.send_request(options)
end

#put_model_invocation_logging_configuration(params = {}) ⇒ Struct

Set the configuration values for model invocation logging.

Examples:

Request syntax with placeholder values


resp = client.put_model_invocation_logging_configuration({
  logging_config: { # required
    cloud_watch_config: {
      log_group_name: "LogGroupName", # required
      role_arn: "RoleArn", # required
      large_data_delivery_s3_config: {
        bucket_name: "BucketName", # required
        key_prefix: "KeyPrefix",
      },
    },
    s3_config: {
      bucket_name: "BucketName", # required
      key_prefix: "KeyPrefix",
    },
    text_data_delivery_enabled: false,
    image_data_delivery_enabled: false,
    embedding_data_delivery_enabled: false,
    video_data_delivery_enabled: false,
  },
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 4625

def put_model_invocation_logging_configuration(params = {}, options = {})
  req = build_request(:put_model_invocation_logging_configuration, params)
  req.send_request(options)
end

#register_marketplace_model_endpoint(params = {}) ⇒ Types::RegisterMarketplaceModelEndpointResponse

Registers an existing Amazon SageMaker endpoint with Amazon Bedrock Marketplace, allowing it to be used with Amazon Bedrock APIs.

Examples:

Request syntax with placeholder values


resp = client.register_marketplace_model_endpoint({
  endpoint_identifier: "Arn", # required
  model_source_identifier: "ModelSourceIdentifier", # required
})

Response structure


resp.marketplace_model_endpoint.endpoint_arn #=> String
resp.marketplace_model_endpoint.model_source_identifier #=> String
resp.marketplace_model_endpoint.status #=> String, one of "REGISTERED", "INCOMPATIBLE_ENDPOINT"
resp.marketplace_model_endpoint.status_message #=> String
resp.marketplace_model_endpoint.created_at #=> Time
resp.marketplace_model_endpoint.updated_at #=> Time
resp.marketplace_model_endpoint.endpoint_config.sage_maker.initial_instance_count #=> Integer
resp.marketplace_model_endpoint.endpoint_config.sage_maker.instance_type #=> String
resp.marketplace_model_endpoint.endpoint_config.sage_maker.execution_role #=> String
resp.marketplace_model_endpoint.endpoint_config.sage_maker.kms_encryption_key #=> String
resp.marketplace_model_endpoint.endpoint_config.sage_maker.vpc.subnet_ids #=> Array
resp.marketplace_model_endpoint.endpoint_config.sage_maker.vpc.subnet_ids[0] #=> String
resp.marketplace_model_endpoint.endpoint_config.sage_maker.vpc.security_group_ids #=> Array
resp.marketplace_model_endpoint.endpoint_config.sage_maker.vpc.security_group_ids[0] #=> String
resp.marketplace_model_endpoint.endpoint_status #=> String
resp.marketplace_model_endpoint.endpoint_status_message #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :endpoint_identifier (required, String) —

    The ARN of the Amazon SageMaker endpoint you want to register with Amazon Bedrock Marketplace.

  • :model_source_identifier (required, String) —

    The ARN of the model from Amazon Bedrock Marketplace that is deployed on the endpoint.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 4675

def register_marketplace_model_endpoint(params = {}, options = {})
  req = build_request(:register_marketplace_model_endpoint, params)
  req.send_request(options)
end

#stop_evaluation_job(params = {}) ⇒ Struct

Stops an evaluation job that is current being created or running.

Examples:

Request syntax with placeholder values


resp = client.stop_evaluation_job({
  job_identifier: "EvaluationJobIdentifier", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :job_identifier (required, String) —

    The Amazon Resource Name (ARN) of the evaluation job you want to stop.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 4697

def stop_evaluation_job(params = {}, options = {})
  req = build_request(:stop_evaluation_job, params)
  req.send_request(options)
end

#stop_model_customization_job(params = {}) ⇒ Struct

Stops an active model customization job. For more information, see Custom models in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.stop_model_customization_job({
  job_identifier: "ModelCustomizationJobIdentifier", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :job_identifier (required, String) —

    Job identifier of the job to stop.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 4725

def stop_model_customization_job(params = {}, options = {})
  req = build_request(:stop_model_customization_job, params)
  req.send_request(options)
end

#stop_model_invocation_job(params = {}) ⇒ Struct

Stops a batch inference job. You're only charged for tokens that were already processed. For more information, see Stop a batch inference job.

Examples:

Request syntax with placeholder values


resp = client.stop_model_invocation_job({
  job_identifier: "ModelInvocationJobIdentifier", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :job_identifier (required, String) —

    The Amazon Resource Name (ARN) of the batch inference job to stop.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 4753

def stop_model_invocation_job(params = {}, options = {})
  req = build_request(:stop_model_invocation_job, params)
  req.send_request(options)
end

#tag_resource(params = {}) ⇒ Struct

Associate tags with a resource. For more information, see Tagging resources in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.tag_resource({
  resource_arn: "TaggableResourcesArn", # required
  tags: [ # required
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :resource_arn (required, String) —

    The Amazon Resource Name (ARN) of the resource to tag.

  • :tags (required, Array<Types::Tag>) —

    Tags to associate with the resource.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 4789

def tag_resource(params = {}, options = {})
  req = build_request(:tag_resource, params)
  req.send_request(options)
end

#untag_resource(params = {}) ⇒ Struct

Remove one or more tags from a resource. For more information, see Tagging resources in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.untag_resource({
  resource_arn: "TaggableResourcesArn", # required
  tag_keys: ["TagKey"], # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :resource_arn (required, String) —

    The Amazon Resource Name (ARN) of the resource to untag.

  • :tag_keys (required, Array<String>) —

    Tag keys of the tags to remove from the resource.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 4820

def untag_resource(params = {}, options = {})
  req = build_request(:untag_resource, params)
  req.send_request(options)
end

#update_guardrail(params = {}) ⇒ Types::UpdateGuardrailResponse

Updates a guardrail with the values you specify.

  • Specify a name and optional description.

  • Specify messages for when the guardrail successfully blocks a prompt or a model response in the blockedInputMessaging and blockedOutputsMessaging fields.

  • Specify topics for the guardrail to deny in the topicPolicyConfig object. Each GuardrailTopicConfig object in the topicsConfig list pertains to one topic.

    • Give a name and description so that the guardrail can properly identify the topic.

    • Specify DENY in the type field.

    • (Optional) Provide up to five prompts that you would categorize as belonging to the topic in the examples list.

  • Specify filter strengths for the harmful categories defined in Amazon Bedrock in the contentPolicyConfig object. Each GuardrailContentFilterConfig object in the filtersConfig list pertains to a harmful category. For more information, see Content filters. For more information about the fields in a content filter, see GuardrailContentFilterConfig.

    • Specify the category in the type field.

    • Specify the strength of the filter for prompts in the inputStrength field and for model responses in the strength field of the GuardrailContentFilterConfig.

  • (Optional) For security, include the ARN of a KMS key in the kmsKeyId field.

Examples:

Request syntax with placeholder values


resp = client.update_guardrail({
  guardrail_identifier: "GuardrailIdentifier", # required
  name: "GuardrailName", # required
  description: "GuardrailDescription",
  topic_policy_config: {
    topics_config: [ # required
      {
        name: "GuardrailTopicName", # required
        definition: "GuardrailTopicDefinition", # required
        examples: ["GuardrailTopicExample"],
        type: "DENY", # required, accepts DENY
        input_action: "BLOCK", # accepts BLOCK, NONE
        output_action: "BLOCK", # accepts BLOCK, NONE
        input_enabled: false,
        output_enabled: false,
      },
    ],
  },
  content_policy_config: {
    filters_config: [ # required
      {
        type: "SEXUAL", # required, accepts SEXUAL, VIOLENCE, HATE, INSULTS, MISCONDUCT, PROMPT_ATTACK
        input_strength: "NONE", # required, accepts NONE, LOW, MEDIUM, HIGH
        output_strength: "NONE", # required, accepts NONE, LOW, MEDIUM, HIGH
        input_modalities: ["TEXT"], # accepts TEXT, IMAGE
        output_modalities: ["TEXT"], # accepts TEXT, IMAGE
        input_action: "BLOCK", # accepts BLOCK, NONE
        output_action: "BLOCK", # accepts BLOCK, NONE
        input_enabled: false,
        output_enabled: false,
      },
    ],
  },
  word_policy_config: {
    words_config: [
      {
        text: "GuardrailWordConfigTextString", # required
        input_action: "BLOCK", # accepts BLOCK, NONE
        output_action: "BLOCK", # accepts BLOCK, NONE
        input_enabled: false,
        output_enabled: false,
      },
    ],
    managed_word_lists_config: [
      {
        type: "PROFANITY", # required, accepts PROFANITY
        input_action: "BLOCK", # accepts BLOCK, NONE
        output_action: "BLOCK", # accepts BLOCK, NONE
        input_enabled: false,
        output_enabled: false,
      },
    ],
  },
  sensitive_information_policy_config: {
    pii_entities_config: [
      {
        type: "ADDRESS", # required, accepts ADDRESS, AGE, AWS_ACCESS_KEY, AWS_SECRET_KEY, CA_HEALTH_NUMBER, CA_SOCIAL_INSURANCE_NUMBER, CREDIT_DEBIT_CARD_CVV, CREDIT_DEBIT_CARD_EXPIRY, CREDIT_DEBIT_CARD_NUMBER, DRIVER_ID, EMAIL, INTERNATIONAL_BANK_ACCOUNT_NUMBER, IP_ADDRESS, LICENSE_PLATE, MAC_ADDRESS, NAME, PASSWORD, PHONE, PIN, SWIFT_CODE, UK_NATIONAL_HEALTH_SERVICE_NUMBER, UK_NATIONAL_INSURANCE_NUMBER, UK_UNIQUE_TAXPAYER_REFERENCE_NUMBER, URL, USERNAME, US_BANK_ACCOUNT_NUMBER, US_BANK_ROUTING_NUMBER, US_INDIVIDUAL_TAX_IDENTIFICATION_NUMBER, US_PASSPORT_NUMBER, US_SOCIAL_SECURITY_NUMBER, VEHICLE_IDENTIFICATION_NUMBER
        action: "BLOCK", # required, accepts BLOCK, ANONYMIZE, NONE
        input_action: "BLOCK", # accepts BLOCK, ANONYMIZE, NONE
        output_action: "BLOCK", # accepts BLOCK, ANONYMIZE, NONE
        input_enabled: false,
        output_enabled: false,
      },
    ],
    regexes_config: [
      {
        name: "GuardrailRegexConfigNameString", # required
        description: "GuardrailRegexConfigDescriptionString",
        pattern: "GuardrailRegexConfigPatternString", # required
        action: "BLOCK", # required, accepts BLOCK, ANONYMIZE, NONE
        input_action: "BLOCK", # accepts BLOCK, ANONYMIZE, NONE
        output_action: "BLOCK", # accepts BLOCK, ANONYMIZE, NONE
        input_enabled: false,
        output_enabled: false,
      },
    ],
  },
  contextual_grounding_policy_config: {
    filters_config: [ # required
      {
        type: "GROUNDING", # required, accepts GROUNDING, RELEVANCE
        threshold: 1.0, # required
        action: "BLOCK", # accepts BLOCK, NONE
        enabled: false,
      },
    ],
  },
  cross_region_config: {
    guardrail_profile_identifier: "GuardrailCrossRegionGuardrailProfileIdentifier", # required
  },
  blocked_input_messaging: "GuardrailBlockedMessaging", # required
  blocked_outputs_messaging: "GuardrailBlockedMessaging", # required
  kms_key_id: "KmsKeyId",
})

Response structure


resp.guardrail_id #=> String
resp.guardrail_arn #=> String
resp.version #=> String
resp.updated_at #=> Time

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :guardrail_identifier (required, String) —

    The unique identifier of the guardrail. This can be an ID or the ARN.

  • :name (required, String) —

    A name for the guardrail.

  • :description (String) —

    A description of the guardrail.

  • :topic_policy_config (Types::GuardrailTopicPolicyConfig) —

    The topic policy to configure for the guardrail.

  • :content_policy_config (Types::GuardrailContentPolicyConfig) —

    The content policy to configure for the guardrail.

  • :word_policy_config (Types::GuardrailWordPolicyConfig) —

    The word policy to configure for the guardrail.

  • :sensitive_information_policy_config (Types::GuardrailSensitiveInformationPolicyConfig) —

    The sensitive information policy to configure for the guardrail.

  • :contextual_grounding_policy_config (Types::GuardrailContextualGroundingPolicyConfig) —

    The contextual grounding policy configuration used to update a guardrail.

  • :cross_region_config (Types::GuardrailCrossRegionConfig) —

    The system-defined guardrail profile that you're using with your guardrail. Guardrail profiles define the destination Amazon Web Services Regions where guardrail inference requests can be automatically routed.

    For more information, see the Amazon Bedrock User Guide.

  • :blocked_input_messaging (required, String) —

    The message to return when the guardrail blocks a prompt.

  • :blocked_outputs_messaging (required, String) —

    The message to return when the guardrail blocks a model response.

  • :kms_key_id (String) —

    The ARN of the KMS key with which to encrypt the guardrail.

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 5026

def update_guardrail(params = {}, options = {})
  req = build_request(:update_guardrail, params)
  req.send_request(options)
end

#update_marketplace_model_endpoint(params = {}) ⇒ Types::UpdateMarketplaceModelEndpointResponse

Updates the configuration of an existing endpoint for a model from Amazon Bedrock Marketplace.

Examples:

Request syntax with placeholder values


resp = client.update_marketplace_model_endpoint({
  endpoint_arn: "Arn", # required
  endpoint_config: { # required
    sage_maker: {
      initial_instance_count: 1, # required
      instance_type: "InstanceType", # required
      execution_role: "RoleArn", # required
      kms_encryption_key: "KmsKeyId",
      vpc: {
        subnet_ids: ["SubnetId"], # required
        security_group_ids: ["SecurityGroupId"], # required
      },
    },
  },
  client_request_token: "IdempotencyToken",
})

Response structure


resp.marketplace_model_endpoint.endpoint_arn #=> String
resp.marketplace_model_endpoint.model_source_identifier #=> String
resp.marketplace_model_endpoint.status #=> String, one of "REGISTERED", "INCOMPATIBLE_ENDPOINT"
resp.marketplace_model_endpoint.status_message #=> String
resp.marketplace_model_endpoint.created_at #=> Time
resp.marketplace_model_endpoint.updated_at #=> Time
resp.marketplace_model_endpoint.endpoint_config.sage_maker.initial_instance_count #=> Integer
resp.marketplace_model_endpoint.endpoint_config.sage_maker.instance_type #=> String
resp.marketplace_model_endpoint.endpoint_config.sage_maker.execution_role #=> String
resp.marketplace_model_endpoint.endpoint_config.sage_maker.kms_encryption_key #=> String
resp.marketplace_model_endpoint.endpoint_config.sage_maker.vpc.subnet_ids #=> Array
resp.marketplace_model_endpoint.endpoint_config.sage_maker.vpc.subnet_ids[0] #=> String
resp.marketplace_model_endpoint.endpoint_config.sage_maker.vpc.security_group_ids #=> Array
resp.marketplace_model_endpoint.endpoint_config.sage_maker.vpc.security_group_ids[0] #=> String
resp.marketplace_model_endpoint.endpoint_status #=> String
resp.marketplace_model_endpoint.endpoint_status_message #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :endpoint_arn (required, String) —

    The Amazon Resource Name (ARN) of the endpoint you want to update.

  • :endpoint_config (required, Types::EndpointConfig) —

    The new configuration for the endpoint, including the number and type of instances to use.

  • :client_request_token (String) —

    A unique, case-sensitive identifier that you provide to ensure the idempotency of the request. This token is listed as not required because Amazon Web Services SDKs automatically generate it for you and set this parameter. If you're not using the Amazon Web Services SDK or the CLI, you must provide this token or the action will fail.

    A suitable default value is auto-generated. You should normally not need to pass this option.**

Returns:

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 5097

def update_marketplace_model_endpoint(params = {}, options = {})
  req = build_request(:update_marketplace_model_endpoint, params)
  req.send_request(options)
end

#update_provisioned_model_throughput(params = {}) ⇒ Struct

Updates the name or associated model for a Provisioned Throughput. For more information, see Provisioned Throughput in the Amazon Bedrock User Guide.

Examples:

Request syntax with placeholder values


resp = client.update_provisioned_model_throughput({
  provisioned_model_id: "ProvisionedModelId", # required
  desired_provisioned_model_name: "ProvisionedModelName",
  desired_model_id: "ModelIdentifier",
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :provisioned_model_id (required, String) —

    The Amazon Resource Name (ARN) or name of the Provisioned Throughput to update.

  • :desired_provisioned_model_name (String) —

    The new name for this Provisioned Throughput.

  • :desired_model_id (String) —

    The Amazon Resource Name (ARN) of the new model to associate with this Provisioned Throughput. You can't specify this field if this Provisioned Throughput is associated with a base model.

    If this Provisioned Throughput is associated with a custom model, you can specify one of the following options:

    • The base model from which the custom model was customized.

    • Another custom model that was customized from the same base model as the custom model.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 5145

def update_provisioned_model_throughput(params = {}, options = {})
  req = build_request(:update_provisioned_model_throughput, params)
  req.send_request(options)
end