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Describes the API operations for creating, managing, fine-turning, and evaluating Amazon Bedrock models.

Usage

bedrock(config = list(), credentials = list(), endpoint = NULL, region = NULL)

Arguments

config

Optional configuration of credentials, endpoint, and/or region.

  • credentials:

    • creds:

      • access_key_id: AWS access key ID

      • secret_access_key: AWS secret access key

      • session_token: AWS temporary session token

    • profile: The name of a profile to use. If not given, then the default profile is used.

    • anonymous: Set anonymous credentials.

  • endpoint: The complete URL to use for the constructed client.

  • region: The AWS Region used in instantiating the client.

  • close_connection: Immediately close all HTTP connections.

  • timeout: The time in seconds till a timeout exception is thrown when attempting to make a connection. The default is 60 seconds.

  • s3_force_path_style: Set this to true to force the request to use path-style addressing, i.e. http://s3.amazonaws.com/BUCKET/KEY.

  • sts_regional_endpoint: Set sts regional endpoint resolver to regional or legacy https://docs.aws.amazon.com/sdkref/latest/guide/feature-sts-regionalized-endpoints.html

credentials

Optional credentials shorthand for the config parameter

  • creds:

    • access_key_id: AWS access key ID

    • secret_access_key: AWS secret access key

    • session_token: AWS temporary session token

  • profile: The name of a profile to use. If not given, then the default profile is used.

  • anonymous: Set anonymous credentials.

endpoint

Optional shorthand for complete URL to use for the constructed client.

region

Optional shorthand for AWS Region used in instantiating the client.

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- bedrock(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

batch_delete_advanced_prompt_optimization_jobBatch delete the specified advanced prompt optimization jobs
batch_delete_evaluation_jobDeletes a batch of evaluation jobs
cancel_automated_reasoning_policy_build_workflowCancels a running Automated Reasoning policy build workflow
create_advanced_prompt_optimization_jobCreates an asynchronous batch job for advanced prompt optimization
create_automated_reasoning_policyCreates an Automated Reasoning policy for Amazon Bedrock Guardrails
create_automated_reasoning_policy_test_caseCreates a test for an Automated Reasoning policy
create_automated_reasoning_policy_versionCreates a new version of an existing Automated Reasoning policy
create_custom_modelCreates a new custom model in Amazon Bedrock
create_custom_model_deploymentDeploys a custom model for on-demand inference in Amazon Bedrock
create_evaluation_jobCreates an evaluation job
create_foundation_model_agreementRequest a model access agreement for the specified model
create_guardrailCreates a guardrail to block topics and to implement safeguards for your generative AI applications
create_guardrail_versionCreates a version of the guardrail
create_inference_profileCreates an application inference profile to track metrics and costs when invoking a model
create_marketplace_model_endpointCreates an endpoint for a model from Amazon Bedrock Marketplace
create_model_copy_jobCopies a model to another region so that it can be used there
create_model_customization_jobCreates a fine-tuning job to customize a base model
create_model_import_jobCreates a model import job to import model that you have customized in other environments, such as Amazon SageMaker
create_model_invocation_jobCreates a batch inference job to invoke a model on multiple prompts
create_prompt_routerCreates a prompt router that manages the routing of requests between multiple foundation models based on the routing criteria
create_provisioned_model_throughputCreates dedicated throughput for a base or custom model with the model units and for the duration that you specify
delete_automated_reasoning_policyDeletes an Automated Reasoning policy or policy version
delete_automated_reasoning_policy_build_workflowDeletes an Automated Reasoning policy build workflow and its associated artifacts
delete_automated_reasoning_policy_test_caseDeletes an Automated Reasoning policy test
delete_custom_modelDeletes a custom model that you created earlier
delete_custom_model_deploymentDeletes a custom model deployment
delete_enforced_guardrail_configurationDeletes the account-level enforced guardrail configuration
delete_foundation_model_agreementDelete the model access agreement for the specified model
delete_guardrailDeletes a guardrail
delete_imported_modelDeletes a custom model that you imported earlier
delete_inference_profileDeletes an application inference profile
delete_marketplace_model_endpointDeletes an endpoint for a model from Amazon Bedrock Marketplace
delete_model_invocation_logging_configurationDelete the invocation logging
delete_prompt_routerDeletes a specified prompt router
delete_provisioned_model_throughputDeletes a Provisioned Throughput
delete_resource_policyDeletes a previously created Bedrock resource policy
deregister_marketplace_model_endpointDeregisters an endpoint for a model from Amazon Bedrock Marketplace
export_automated_reasoning_policy_versionExports the policy definition for an Automated Reasoning policy version
get_advanced_prompt_optimization_jobRetrieves the details and status of an advanced prompt optimization job
get_automated_reasoning_policyRetrieves details about an Automated Reasoning policy or policy version
get_automated_reasoning_policy_annotationsRetrieves the current annotations for an Automated Reasoning policy build workflow
get_automated_reasoning_policy_build_workflowRetrieves detailed information about an Automated Reasoning policy build workflow, including its status, configuration, and metadata
get_automated_reasoning_policy_build_workflow_result_assetsRetrieves the resulting assets from a completed Automated Reasoning policy build workflow, including build logs, quality reports, and generated policy artifacts
get_automated_reasoning_policy_next_scenarioRetrieves the next test scenario for validating an Automated Reasoning policy
get_automated_reasoning_policy_test_caseRetrieves details about a specific Automated Reasoning policy test
get_automated_reasoning_policy_test_resultRetrieves the test result for a specific Automated Reasoning policy test
get_custom_modelGet the properties associated with a Amazon Bedrock custom model that you have created
get_custom_model_deploymentRetrieves information about a custom model deployment, including its status, configuration, and metadata
get_evaluation_jobGets information about an evaluation job, such as the status of the job
get_foundation_modelGet details about a Amazon Bedrock foundation model
get_foundation_model_availabilityGet information about the Foundation model availability
get_guardrailGets details about a guardrail
get_imported_modelGets properties associated with a customized model you imported
get_inference_profileGets information about an inference profile
get_marketplace_model_endpointRetrieves details about a specific endpoint for a model from Amazon Bedrock Marketplace
get_model_copy_jobRetrieves information about a model copy job
get_model_customization_jobRetrieves the properties associated with a model-customization job, including the status of the job
get_model_import_jobRetrieves the properties associated with import model job, including the status of the job
get_model_invocation_jobGets details about a batch inference job
get_model_invocation_logging_configurationGet the current configuration values for model invocation logging
get_prompt_routerRetrieves details about a prompt router
get_provisioned_model_throughputReturns details for a Provisioned Throughput
get_resource_policyGets the resource policy document for a Bedrock resource
get_use_case_for_model_accessGet usecase for model access
list_advanced_prompt_optimization_jobsLists all advanced prompt optimization jobs for the account
list_automated_reasoning_policiesLists all Automated Reasoning policies in your account, with optional filtering by policy ARN
list_automated_reasoning_policy_build_workflowsLists all build workflows for an Automated Reasoning policy, showing the history of policy creation and modification attempts
list_automated_reasoning_policy_test_casesLists tests for an Automated Reasoning policy
list_automated_reasoning_policy_test_resultsLists test results for an Automated Reasoning policy, showing how the policy performed against various test scenarios and validation checks
list_custom_model_deploymentsLists custom model deployments in your account
list_custom_modelsReturns a list of the custom models that you have created with the CreateModelCustomizationJob operation
list_enforced_guardrails_configurationLists the account-level enforced guardrail configurations
list_evaluation_jobsLists all existing evaluation jobs
list_foundation_model_agreement_offersGet the offers associated with the specified model
list_foundation_modelsLists Amazon Bedrock foundation models that you can use
list_guardrailsLists details about all the guardrails in an account
list_imported_modelsReturns a list of models you've imported
list_inference_profilesReturns a list of inference profiles that you can use
list_marketplace_model_endpointsLists the endpoints for models from Amazon Bedrock Marketplace in your Amazon Web Services account
list_model_copy_jobsReturns a list of model copy jobs that you have submitted
list_model_customization_jobsReturns a list of model customization jobs that you have submitted
list_model_import_jobsReturns a list of import jobs you've submitted
list_model_invocation_jobsLists all batch inference jobs in the account
list_prompt_routersRetrieves a list of prompt routers
list_provisioned_model_throughputsLists the Provisioned Throughputs in the account
list_tags_for_resourceList the tags associated with the specified resource
put_enforced_guardrail_configurationSets the account-level enforced guardrail configuration
put_model_invocation_logging_configurationSet the configuration values for model invocation logging
put_resource_policyAdds a resource policy for a Bedrock resource
put_use_case_for_model_accessPut usecase for model access
register_marketplace_model_endpointRegisters an existing Amazon SageMaker endpoint with Amazon Bedrock Marketplace, allowing it to be used with Amazon Bedrock APIs
start_automated_reasoning_policy_build_workflowStarts a new build workflow for an Automated Reasoning policy
start_automated_reasoning_policy_test_workflowInitiates a test workflow to validate Automated Reasoning policy tests
stop_advanced_prompt_optimization_jobStops an in-progress advanced prompt optimization job
stop_evaluation_jobStops an evaluation job that is current being created or running
stop_model_customization_jobStops an active model customization job
stop_model_invocation_jobStops a batch inference job
tag_resourceAssociate tags with a resource
untag_resourceRemove one or more tags from a resource
update_automated_reasoning_policyUpdates an existing Automated Reasoning policy with new rules, variables, or configuration
update_automated_reasoning_policy_annotationsUpdates the annotations for an Automated Reasoning policy build workflow
update_automated_reasoning_policy_test_caseUpdates an existing Automated Reasoning policy test
update_custom_model_deploymentUpdates a custom model deployment with a new custom model
update_guardrailUpdates a guardrail with the values you specify
update_marketplace_model_endpointUpdates the configuration of an existing endpoint for a model from Amazon Bedrock Marketplace
update_provisioned_model_throughputUpdates the name or associated model for a Provisioned Throughput

Examples

if (FALSE) { # \dontrun{
svc <- bedrock()
svc$batch_delete_advanced_prompt_optimization_job(
  Foo = 123
)
} # }