Class: Aws::Bedrock::Client

Inherits:

Seahorse::Client::Base

Object
Seahorse::Client::Base
Aws::Bedrock::Client

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

#batch_delete_evaluation_job(params = {}) ⇒ Types::BatchDeleteEvaluationJobResponse
Deletes a batch of evaluation jobs.
#create_evaluation_job(params = {}) ⇒ Types::CreateEvaluationJobResponse
Creates an evaluation job.
#create_guardrail(params = {}) ⇒ Types::CreateGuardrailResponse
Creates a guardrail to block topics and to implement safeguards for your generative AI applications.
#create_guardrail_version(params = {}) ⇒ Types::CreateGuardrailVersionResponse
Creates a version of the guardrail.
#create_inference_profile(params = {}) ⇒ Types::CreateInferenceProfileResponse
Creates an application inference profile to track metrics and costs when invoking a model.
#create_model_copy_job(params = {}) ⇒ Types::CreateModelCopyJobResponse
Copies a model to another region so that it can be used there.
#create_model_customization_job(params = {}) ⇒ Types::CreateModelCustomizationJobResponse
Creates a fine-tuning job to customize a base model.
#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.
#create_model_invocation_job(params = {}) ⇒ Types::CreateModelInvocationJobResponse
Creates a batch inference job to invoke a model on multiple prompts.
#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.
#delete_custom_model(params = {}) ⇒ Struct
Deletes a custom model that you created earlier.
#delete_guardrail(params = {}) ⇒ Struct
Deletes a guardrail.
#delete_imported_model(params = {}) ⇒ Struct
Deletes a custom model that you imported earlier.
#delete_inference_profile(params = {}) ⇒ Struct
Deletes an application inference profile.
#delete_model_invocation_logging_configuration(params = {}) ⇒ Struct
Delete the invocation logging.
#delete_provisioned_model_throughput(params = {}) ⇒ Struct
Deletes a Provisioned Throughput.
#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][1] in the [Amazon Bedrock User Guide][2].
#get_evaluation_job(params = {}) ⇒ Types::GetEvaluationJobResponse
Gets information about an evaluation job, such as the status of the job.
#get_foundation_model(params = {}) ⇒ Types::GetFoundationModelResponse
Get details about a Amazon Bedrock foundation model.
#get_guardrail(params = {}) ⇒ Types::GetGuardrailResponse
Gets details about a guardrail.
#get_imported_model(params = {}) ⇒ Types::GetImportedModelResponse
Gets properties associated with a customized model you imported.
#get_inference_profile(params = {}) ⇒ Types::GetInferenceProfileResponse
Gets information about an inference profile.
#get_model_copy_job(params = {}) ⇒ Types::GetModelCopyJobResponse
Retrieves information about a model copy job.
#get_model_customization_job(params = {}) ⇒ Types::GetModelCustomizationJobResponse
Retrieves the properties associated with a model-customization job, including the status of the job.
#get_model_import_job(params = {}) ⇒ Types::GetModelImportJobResponse
Retrieves the properties associated with import model job, including the status of the job.
#get_model_invocation_job(params = {}) ⇒ Types::GetModelInvocationJobResponse
Gets details about a batch inference job.
#get_model_invocation_logging_configuration(params = {}) ⇒ Types::GetModelInvocationLoggingConfigurationResponse
Get the current configuration values for model invocation logging.
#get_provisioned_model_throughput(params = {}) ⇒ Types::GetProvisionedModelThroughputResponse
Returns details for a Provisioned Throughput.
#list_custom_models(params = {}) ⇒ Types::ListCustomModelsResponse
Returns a list of the custom models that you have created with the CreateModelCustomizationJob operation.
#list_evaluation_jobs(params = {}) ⇒ Types::ListEvaluationJobsResponse
Lists all existing evaluation jobs.
#list_foundation_models(params = {}) ⇒ Types::ListFoundationModelsResponse
Lists Amazon Bedrock foundation models that you can use.
#list_guardrails(params = {}) ⇒ Types::ListGuardrailsResponse
Lists details about all the guardrails in an account.
#list_imported_models(params = {}) ⇒ Types::ListImportedModelsResponse
Returns a list of models you've imported.
#list_inference_profiles(params = {}) ⇒ Types::ListInferenceProfilesResponse
Returns a list of inference profiles that you can use.
#list_model_copy_jobs(params = {}) ⇒ Types::ListModelCopyJobsResponse
Returns a list of model copy jobs that you have submitted.
#list_model_customization_jobs(params = {}) ⇒ Types::ListModelCustomizationJobsResponse
Returns a list of model customization jobs that you have submitted.
#list_model_import_jobs(params = {}) ⇒ Types::ListModelImportJobsResponse
Returns a list of import jobs you've submitted.
#list_model_invocation_jobs(params = {}) ⇒ Types::ListModelInvocationJobsResponse
Lists all batch inference jobs in the account.
#list_provisioned_model_throughputs(params = {}) ⇒ Types::ListProvisionedModelThroughputsResponse
Lists the Provisioned Throughputs in the account.
#list_tags_for_resource(params = {}) ⇒ Types::ListTagsForResourceResponse
List the tags associated with the specified resource.
#put_model_invocation_logging_configuration(params = {}) ⇒ Struct
Set the configuration values for model invocation logging.
#stop_evaluation_job(params = {}) ⇒ Struct
Stops an evaluation job that is current being created or running.
#stop_model_customization_job(params = {}) ⇒ Struct
Stops an active model customization job.
#stop_model_invocation_job(params = {}) ⇒ Struct
Stops a batch inference job.
#tag_resource(params = {}) ⇒ Struct
Associate tags with a resource.
#untag_resource(params = {}) ⇒ Struct
Remove one or more tags from a resource.
#update_guardrail(params = {}) ⇒ Types::UpdateGuardrailResponse
Updates a guardrail with the values you specify.
#update_provisioned_model_throughput(params = {}) ⇒ Struct
Updates the name or associated model for a Provisioned Throughput.

Instance Method Summary collapse

#initialize(options) ⇒ Client constructor
A new instance of Client.

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 —
Set to true to disable SDK automatically adding host prefix to default service endpoint when available.
: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_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.
: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 444

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:

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:

(Types::BatchDeleteEvaluationJobResponse) —
Returns a response object which responds to the following methods:
- #errors => Array<Types::BatchDeleteEvaluationJobError>
- #evaluation_jobs => Array<Types::BatchDeleteEvaluationJobItem>

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 484

def batch_delete_evaluation_job(params = {}, options = {})
  req = build_request(:batch_delete_evaluation_job, 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
          },
        ],
      },
    },
    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: "EvaluationModelIdentifier", # required
          inference_params: "EvaluationModelInferenceParams",
        },
      },
    ],
    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" => {
                  },
                },
              },
            },
          },
        },
      },
    ],
  },
  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:

(Types::CreateEvaluationJobResponse) —
Returns a response object which responds to the following methods:
- #job_arn => String

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 867

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
      },
    ],
  },
  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
      },
    ],
  },
  word_policy_config: {
    words_config: [
      {
        text: "GuardrailWordConfigTextString", # required
      },
    ],
    managed_word_lists_config: [
      {
        type: "PROFANITY", # required, accepts PROFANITY
      },
    ],
  },
  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
      },
    ],
    regexes_config: [
      {
        name: "GuardrailRegexConfigNameString", # required
        description: "GuardrailRegexConfigDescriptionString",
        pattern: "GuardrailRegexConfigPatternString", # required
        action: "BLOCK", # required, accepts BLOCK, ANONYMIZE
      },
    ],
  },
  contextual_grounding_policy_config: {
    filters_config: [ # required
      {
        type: "GROUNDING", # required, accepts GROUNDING, RELEVANCE
        threshold: 1.0, # 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.
: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:

(Types::CreateGuardrailResponse) —
Returns a response object which responds to the following methods:
- #guardrail_id => String
- #guardrail_arn => String
- #version => String
- #created_at => Time

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1043

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:

(Types::CreateGuardrailVersionResponse) —
Returns a response object which responds to the following methods:
- #guardrail_id => String
- #version => String

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1094

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:

(Types::CreateInferenceProfileResponse) —
Returns a response object which responds to the following methods:
- #inference_profile_arn => String
- #status => String

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1176

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

(Types::CreateModelCopyJobResponse) —
Returns a response object which responds to the following methods:
- #job_arn => String

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1248

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
  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:

(Types::CreateModelCustomizationJobResponse) —
Returns a response object which responds to the following methods:
- #job_arn => String

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1447

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:

(Types::CreateModelImportJobResponse) —
Returns a response object which responds to the following methods:
- #job_arn => String

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1538

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:

(Types::CreateModelInvocationJobResponse) —
Returns a response object which responds to the following methods:
- #job_arn => String

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1659

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

(Types::CreateProvisionedModelThroughputResponse) —
Returns a response object which responds to the following methods:
- #provisioned_model_arn => String

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1770

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:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1798

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:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1832

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:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1861

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:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1890

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

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1903

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

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 1932

def delete_provisioned_model_throughput(params = {}, options = {})
  req = build_request(:delete_provisioned_model_throughput, 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"
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

Parameters:

params (Hash) (defaults to: {}) —
({})

Options Hash (params):

:model_identifier (required, String) —
Name or Amazon Resource Name (ARN) of the custom model.

Returns:

(Types::GetCustomModelResponse) —
Returns a response object which responds to the following methods:
- #model_arn => String
- #model_name => String
- #job_name => String
- #job_arn => String
- #base_model_arn => String
- #customization_type => String
- #model_kms_key_arn => String
- #hyper_parameters => Hash<String,String>
- #training_data_config => Types::TrainingDataConfig
- #validation_data_config => Types::ValidationDataConfig
- #output_data_config => Types::OutputDataConfig
- #training_metrics => Types::TrainingMetrics
- #validation_metrics => Array<Types::ValidatorMetric>
- #creation_time => Time
- #customization_config => Types::CustomizationConfig

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2015

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.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.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.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:

(Types::GetEvaluationJobResponse) —
Returns a response object which responds to the following methods:
- #job_name => String
- #status => String
- #job_arn => String
- #job_description => String
- #role_arn => String
- #customer_encryption_key_id => String
- #job_type => String
- #application_type => String
- #evaluation_config => Types::EvaluationConfig
- #inference_config => Types::EvaluationInferenceConfig
- #output_data_config => Types::EvaluationOutputDataConfig
- #creation_time => Time
- #last_modified_time => Time
- #failure_messages => Array<String>

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2158

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:

(Types::GetFoundationModelResponse) —
Returns a response object which responds to the following methods:
- #model_details => Types::FoundationModelDetails

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2199

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.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.word_policy.words #=> Array
resp.word_policy.words[0].text #=> String
resp.word_policy.managed_word_lists #=> Array
resp.word_policy.managed_word_lists[0].type #=> String, one of "PROFANITY"
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"
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"
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.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:

(Types::GetGuardrailResponse) —
Returns a response object which responds to the following methods:
- #name => String
- #description => String
- #guardrail_id => String
- #guardrail_arn => String
- #version => String
- #status => String
- #topic_policy => Types::GuardrailTopicPolicy
- #content_policy => Types::GuardrailContentPolicy
- #word_policy => Types::GuardrailWordPolicy
- #sensitive_information_policy => Types::GuardrailSensitiveInformationPolicy
- #contextual_grounding_policy => Types::GuardrailContextualGroundingPolicy
- #created_at => Time
- #updated_at => Time
- #status_reasons => Array<String>
- #failure_recommendations => Array<String>
- #blocked_input_messaging => String
- #blocked_outputs_messaging => String
- #kms_key_arn => String

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2291

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

Parameters:

params (Hash) (defaults to: {}) —
({})

Options Hash (params):

:model_identifier (required, String) —
Name or Amazon Resource Name (ARN) of the imported model.

Returns:

(Types::GetImportedModelResponse) —
Returns a response object which responds to the following methods:
- #model_arn => String
- #model_name => String
- #job_name => String
- #job_arn => String
- #model_data_source => Types::ModelDataSource
- #creation_time => Time
- #model_architecture => String
- #model_kms_key_arn => String
- #instruct_supported => Boolean

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2335

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:

(Types::GetInferenceProfileResponse) —
Returns a response object which responds to the following methods:
- #inference_profile_name => String
- #description => String
- #created_at => Time
- #updated_at => Time
- #inference_profile_arn => String
- #models => Array<Types::InferenceProfileModel>
- #inference_profile_id => String
- #status => String
- #type => String

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2386

def get_inference_profile(params = {}, options = {})
  req = build_request(:get_inference_profile, 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.source_account_id #=> 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:

(Types::GetModelCopyJobResponse) —
Returns a response object which responds to the following methods:
- #job_arn => String
- #status => String
- #creation_time => Time
- #target_model_arn => String
- #target_model_name => String
- #source_account_id => String
- #source_model_arn => String
- #target_model_kms_key_arn => String
- #target_model_tags => Array<Types::Tag>
- #failure_message => String
- #source_model_name => String

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2443

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.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"
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:

(Types::GetModelCustomizationJobResponse) —
Returns a response object which responds to the following methods:
- #job_arn => String
- #job_name => String
- #output_model_name => String
- #output_model_arn => String
- #client_request_token => String
- #role_arn => String
- #status => String
- #failure_message => String
- #creation_time => Time
- #last_modified_time => Time
- #end_time => Time
- #base_model_arn => String
- #hyper_parameters => Hash<String,String>
- #training_data_config => Types::TrainingDataConfig
- #validation_data_config => Types::ValidationDataConfig
- #output_data_config => Types::OutputDataConfig
- #customization_type => String
- #output_model_kms_key_arn => String
- #training_metrics => Types::TrainingMetrics
- #validation_metrics => Array<Types::ValidatorMetric>
- #vpc_config => Types::VpcConfig
- #customization_config => Types::CustomizationConfig

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2543

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:

(Types::GetModelImportJobResponse) —
Returns a response object which responds to the following methods:
- #job_arn => String
- #job_name => String
- #imported_model_name => String
- #imported_model_arn => String
- #role_arn => String
- #model_data_source => Types::ModelDataSource
- #status => String
- #failure_message => String
- #creation_time => Time
- #last_modified_time => Time
- #end_time => Time
- #vpc_config => Types::VpcConfig
- #imported_model_kms_key_arn => String

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2605

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:

(Types::GetModelInvocationJobResponse) —
Returns a response object which responds to the following methods:
- #job_arn => String
- #job_name => String
- #model_id => String
- #client_request_token => String
- #role_arn => String
- #status => String
- #message => String
- #submit_time => Time
- #last_modified_time => Time
- #end_time => Time
- #input_data_config => Types::ModelInvocationJobInputDataConfig
- #output_data_config => Types::ModelInvocationJobOutputDataConfig
- #vpc_config => Types::VpcConfig
- #timeout_duration_in_hours => Integer
- #job_expiration_time => Time

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2673

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:

(Types::GetModelInvocationLoggingConfigurationResponse) —
Returns a response object which responds to the following methods:
- #logging_config => Types::LoggingConfig

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2701

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

(Types::GetProvisionedModelThroughputResponse) —
Returns a response object which responds to the following methods:
- #model_units => Integer
- #desired_model_units => Integer
- #provisioned_model_name => String
- #provisioned_model_arn => String
- #model_arn => String
- #desired_model_arn => String
- #foundation_model_arn => String
- #status => String
- #creation_time => Time
- #last_modified_time => Time
- #failure_message => String
- #commitment_duration => String
- #commitment_expiration_time => Time

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2759

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,
})

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"
resp.model_summaries[0].owner_account_id #=> String

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).

Returns:

(Types::ListCustomModelsResponse) —
Returns a response object which responds to the following methods:
- #next_token => String
- #model_summaries => Array<Types::CustomModelSummary>

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2852

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].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:

(Types::ListEvaluationJobsResponse) —
Returns a response object which responds to the following methods:
- #next_token => String
- #job_summaries => Array<Types::EvaluationSummary>

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 2935

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:

(Types::ListFoundationModelsResponse) —
Returns a response object which responds to the following methods:
- #model_summaries => Array<Types::FoundationModelSummary>

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3010

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.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:

(Types::ListGuardrailsResponse) —
Returns a response object which responds to the following methods:
- #guardrails => Array<Types::GuardrailSummary>
- #next_token => String

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3068

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:

(Types::ListImportedModelsResponse) —
Returns a response object which responds to the following methods:
- #next_token => String
- #model_summaries => Array<Types::ImportedModelSummary>

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3144

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:

(Types::ListInferenceProfilesResponse) —
Returns a response object which responds to the following methods:
- #inference_profile_summaries => Array<Types::InferenceProfileSummary>
- #next_token => String

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3215

def list_inference_profiles(params = {}, options = {})
  req = build_request(:list_inference_profiles, 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].source_account_id #=> 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:

(Types::ListModelCopyJobsResponse) —
Returns a response object which responds to the following methods:
- #next_token => String
- #model_copy_job_summaries => Array<Types::ModelCopyJobSummary>

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3315

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].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"

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:

(Types::ListModelCustomizationJobsResponse) —
Returns a response object which responds to the following methods:
- #next_token => String
- #model_customization_job_summaries => Array<Types::ModelCustomizationJobSummary>

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3401

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:

(Types::ListModelImportJobsResponse) —
Returns a response object which responds to the following methods:
- #next_token => String
- #model_import_job_summaries => Array<Types::ModelImportJobSummary>

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3484

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 Services Support 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:

(Types::ListModelInvocationJobsResponse) —
Returns a response object which responds to the following methods:
- #next_token => String
- #invocation_job_summaries => Array<Types::ModelInvocationJobSummary>

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3628

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

(Types::ListProvisionedModelThroughputsResponse) —
Returns a response object which responds to the following methods:
- #next_token => String
- #provisioned_model_summaries => Array<Types::ProvisionedModelSummary>

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3723

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:

(Types::ListTagsForResourceResponse) —
Returns a response object which responds to the following methods:
- #tags => Array<Types::Tag>

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3760

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):

:logging_config (required, Types::LoggingConfig) —
The logging configuration values to set.

Returns:

(Struct) —
Returns an empty response.

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3799

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

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3821

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:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3849

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:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3877

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:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3913

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:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 3944

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
      },
    ],
  },
  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
      },
    ],
  },
  word_policy_config: {
    words_config: [
      {
        text: "GuardrailWordConfigTextString", # required
      },
    ],
    managed_word_lists_config: [
      {
        type: "PROFANITY", # required, accepts PROFANITY
      },
    ],
  },
  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
      },
    ],
    regexes_config: [
      {
        name: "GuardrailRegexConfigNameString", # required
        description: "GuardrailRegexConfigDescriptionString",
        pattern: "GuardrailRegexConfigPatternString", # required
        action: "BLOCK", # required, accepts BLOCK, ANONYMIZE
      },
    ],
  },
  contextual_grounding_policy_config: {
    filters_config: [ # required
      {
        type: "GROUNDING", # required, accepts GROUNDING, RELEVANCE
        threshold: 1.0, # 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.
: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:

(Types::UpdateGuardrailResponse) —
Returns a response object which responds to the following methods:
- #guardrail_id => String
- #guardrail_arn => String
- #version => String
- #updated_at => Time

See Also:

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 4107

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

AWS API Documentation

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/client.rb', line 4155

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

Class: Aws::Bedrock::Client

Overview

Instance Attribute Summary

Attributes inherited from Seahorse::Client::Base

API Operations collapse

Instance Method Summary collapse

Methods included from ClientStubs

Methods inherited from Seahorse::Client::Base

Methods included from Seahorse::Client::HandlerBuilder

Constructor Details

#initialize(options) ⇒ Client

Instance Method Details

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

Examples:

Request syntax with placeholder values

Response structure

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

Examples:

Request syntax with placeholder values

Response structure

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

Examples:

Request syntax with placeholder values

Response structure

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

Examples:

Request syntax with placeholder values

Response structure

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

Examples:

Request syntax with placeholder values

Response structure

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

Examples:

Request syntax with placeholder values

Response structure

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

Examples:

Request syntax with placeholder values

Response structure

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

Examples:

Request syntax with placeholder values

Response structure

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

Examples:

Request syntax with placeholder values

Response structure

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

Examples:

Request syntax with placeholder values

Response structure

#delete_custom_model(params = {}) ⇒ Struct

Examples:

Request syntax with placeholder values

#delete_guardrail(params = {}) ⇒ Struct

Examples:

Request syntax with placeholder values

#delete_imported_model(params = {}) ⇒ Struct

Examples:

Request syntax with placeholder values

#delete_inference_profile(params = {}) ⇒ Struct

Examples:

Request syntax with placeholder values

#delete_model_invocation_logging_configuration(params = {}) ⇒ Struct

#delete_provisioned_model_throughput(params = {}) ⇒ Struct

Examples:

Request syntax with placeholder values

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

Examples:

Request syntax with placeholder values

Response structure

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

Examples:

Request syntax with placeholder values

Response structure

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

Examples:

Request syntax with placeholder values

Response structure

#initialize(options) ⇒ `Client`

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

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

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

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

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

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

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

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

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

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

#delete_custom_model(params = {}) ⇒ `Struct`

#delete_guardrail(params = {}) ⇒ `Struct`

#delete_imported_model(params = {}) ⇒ `Struct`

#delete_inference_profile(params = {}) ⇒ `Struct`

#delete_model_invocation_logging_configuration(params = {}) ⇒ `Struct`

#delete_provisioned_model_throughput(params = {}) ⇒ `Struct`

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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