Class: Aws::Bedrock::Client
- Inherits:
-
Seahorse::Client::Base
- Object
- Seahorse::Client::Base
- Aws::Bedrock::Client
- Includes:
- ClientStubs
- Defined in:
- 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](/sdk-for-ruby/v3/developer-guide/setup-config.html).
See #initialize for a full list of supported configuration options.
Class Attribute Summary collapse
- .identifier ⇒ Object readonly private
API Operations collapse
-
#batch_delete_advanced_prompt_optimization_job(params = {}) ⇒ Types::BatchDeleteAdvancedPromptOptimizationJobResponse
Deletes one or more advanced prompt optimization jobs.
-
#batch_delete_evaluation_job(params = {}) ⇒ Types::BatchDeleteEvaluationJobResponse
Deletes a batch of evaluation jobs.
-
#cancel_automated_reasoning_policy_build_workflow(params = {}) ⇒ Struct
Cancels a running Automated Reasoning policy build workflow.
-
#create_advanced_prompt_optimization_job(params = {}) ⇒ Types::CreateAdvancedPromptOptimizationJobResponse
Creates an advanced prompt optimization job.
-
#create_automated_reasoning_policy(params = {}) ⇒ Types::CreateAutomatedReasoningPolicyResponse
Creates an Automated Reasoning policy for Amazon Bedrock Guardrails.
-
#create_automated_reasoning_policy_test_case(params = {}) ⇒ Types::CreateAutomatedReasoningPolicyTestCaseResponse
Creates a test for an Automated Reasoning policy.
-
#create_automated_reasoning_policy_version(params = {}) ⇒ Types::CreateAutomatedReasoningPolicyVersionResponse
Creates a new version of an existing Automated Reasoning policy.
-
#create_custom_model(params = {}) ⇒ Types::CreateCustomModelResponse
Creates a new custom model in Amazon Bedrock.
-
#create_custom_model_deployment(params = {}) ⇒ Types::CreateCustomModelDeploymentResponse
Deploys a custom model for on-demand inference in Amazon Bedrock.
-
#create_evaluation_job(params = {}) ⇒ Types::CreateEvaluationJobResponse
Creates an evaluation job.
-
#create_foundation_model_agreement(params = {}) ⇒ Types::CreateFoundationModelAgreementResponse
Request a model access agreement for the specified model.
-
#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_marketplace_model_endpoint(params = {}) ⇒ Types::CreateMarketplaceModelEndpointResponse
Creates an endpoint for a model from Amazon Bedrock Marketplace.
-
#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_prompt_router(params = {}) ⇒ Types::CreatePromptRouterResponse
Creates a prompt router that manages the routing of requests between multiple foundation models based on the routing criteria.
-
#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_automated_reasoning_policy(params = {}) ⇒ Struct
Deletes an Automated Reasoning policy or policy version.
-
#delete_automated_reasoning_policy_build_workflow(params = {}) ⇒ Struct
Deletes an Automated Reasoning policy build workflow and its associated artifacts.
-
#delete_automated_reasoning_policy_test_case(params = {}) ⇒ Struct
Deletes an Automated Reasoning policy test.
-
#delete_custom_model(params = {}) ⇒ Struct
Deletes a custom model that you created earlier.
-
#delete_custom_model_deployment(params = {}) ⇒ Struct
Deletes a custom model deployment.
-
#delete_enforced_guardrail_configuration(params = {}) ⇒ Struct
Deletes the account-level enforced guardrail configuration.
-
#delete_foundation_model_agreement(params = {}) ⇒ Struct
Delete the model access agreement for the specified model.
-
#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_marketplace_model_endpoint(params = {}) ⇒ Struct
Deletes an endpoint for a model from Amazon Bedrock Marketplace.
-
#delete_model_invocation_logging_configuration(params = {}) ⇒ Struct
Delete the invocation logging.
-
#delete_prompt_router(params = {}) ⇒ Struct
Deletes a specified prompt router.
-
#delete_provisioned_model_throughput(params = {}) ⇒ Struct
Deletes a Provisioned Throughput.
-
#delete_resource_policy(params = {}) ⇒ Struct
Deletes a previously created Bedrock resource policy.
-
#deregister_marketplace_model_endpoint(params = {}) ⇒ Struct
Deregisters an endpoint for a model from Amazon Bedrock Marketplace.
-
#export_automated_reasoning_policy_version(params = {}) ⇒ Types::ExportAutomatedReasoningPolicyVersionResponse
Exports the policy definition for an Automated Reasoning policy version.
-
#get_advanced_prompt_optimization_job(params = {}) ⇒ Types::GetAdvancedPromptOptimizationJobResponse
Gets information about an advanced prompt optimization job.
-
#get_automated_reasoning_policy(params = {}) ⇒ Types::GetAutomatedReasoningPolicyResponse
Retrieves details about an Automated Reasoning policy or policy version.
-
#get_automated_reasoning_policy_annotations(params = {}) ⇒ Types::GetAutomatedReasoningPolicyAnnotationsResponse
Retrieves the current annotations for an Automated Reasoning policy build workflow.
-
#get_automated_reasoning_policy_build_workflow(params = {}) ⇒ Types::GetAutomatedReasoningPolicyBuildWorkflowResponse
Retrieves detailed information about an Automated Reasoning policy build workflow, including its status, configuration, and metadata.
-
#get_automated_reasoning_policy_build_workflow_result_assets(params = {}) ⇒ Types::GetAutomatedReasoningPolicyBuildWorkflowResultAssetsResponse
Retrieves 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_scenario(params = {}) ⇒ Types::GetAutomatedReasoningPolicyNextScenarioResponse
Retrieves the next test scenario for validating an Automated Reasoning policy.
-
#get_automated_reasoning_policy_test_case(params = {}) ⇒ Types::GetAutomatedReasoningPolicyTestCaseResponse
Retrieves details about a specific Automated Reasoning policy test.
-
#get_automated_reasoning_policy_test_result(params = {}) ⇒ Types::GetAutomatedReasoningPolicyTestResultResponse
Retrieves the test result for a specific Automated Reasoning policy test.
-
#get_custom_model(params = {}) ⇒ Types::GetCustomModelResponse
Get the properties associated with a Amazon Bedrock custom model that you have created.
-
#get_custom_model_deployment(params = {}) ⇒ Types::GetCustomModelDeploymentResponse
Retrieves information about a custom model deployment, including its status, configuration, and metadata.
-
#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_foundation_model_availability(params = {}) ⇒ Types::GetFoundationModelAvailabilityResponse
Get information about the Foundation model availability.
-
#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_marketplace_model_endpoint(params = {}) ⇒ Types::GetMarketplaceModelEndpointResponse
Retrieves details about a specific endpoint for a model from Amazon Bedrock Marketplace.
-
#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_prompt_router(params = {}) ⇒ Types::GetPromptRouterResponse
Retrieves details about a prompt router.
-
#get_provisioned_model_throughput(params = {}) ⇒ Types::GetProvisionedModelThroughputResponse
Returns details for a Provisioned Throughput.
-
#get_resource_policy(params = {}) ⇒ Types::GetResourcePolicyResponse
Gets the resource policy document for a Bedrock resource.
-
#get_use_case_for_model_access(params = {}) ⇒ Types::GetUseCaseForModelAccessResponse
Get usecase for model access.
-
#list_advanced_prompt_optimization_jobs(params = {}) ⇒ Types::ListAdvancedPromptOptimizationJobsResponse
Lists the advanced prompt optimization jobs in your account.
-
#list_automated_reasoning_policies(params = {}) ⇒ Types::ListAutomatedReasoningPoliciesResponse
Lists all Automated Reasoning policies in your account, with optional filtering by policy ARN.
-
#list_automated_reasoning_policy_build_workflows(params = {}) ⇒ Types::ListAutomatedReasoningPolicyBuildWorkflowsResponse
Lists all build workflows for an Automated Reasoning policy, showing the history of policy creation and modification attempts.
-
#list_automated_reasoning_policy_test_cases(params = {}) ⇒ Types::ListAutomatedReasoningPolicyTestCasesResponse
Lists tests for an Automated Reasoning policy.
-
#list_automated_reasoning_policy_test_results(params = {}) ⇒ Types::ListAutomatedReasoningPolicyTestResultsResponse
Lists test results for an Automated Reasoning policy, showing how the policy performed against various test scenarios and validation checks.
-
#list_custom_model_deployments(params = {}) ⇒ Types::ListCustomModelDeploymentsResponse
Lists custom model deployments in your account.
-
#list_custom_models(params = {}) ⇒ Types::ListCustomModelsResponse
Returns a list of the custom models that you have created with the ‘CreateModelCustomizationJob` operation.
-
#list_enforced_guardrails_configuration(params = {}) ⇒ Types::ListEnforcedGuardrailsConfigurationResponse
Lists the account-level enforced guardrail configurations.
-
#list_evaluation_jobs(params = {}) ⇒ Types::ListEvaluationJobsResponse
Lists all existing evaluation jobs.
-
#list_foundation_model_agreement_offers(params = {}) ⇒ Types::ListFoundationModelAgreementOffersResponse
Get the offers associated with the specified model.
-
#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_marketplace_model_endpoints(params = {}) ⇒ Types::ListMarketplaceModelEndpointsResponse
Lists the endpoints for models from Amazon Bedrock Marketplace in your Amazon Web Services account.
-
#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_prompt_routers(params = {}) ⇒ Types::ListPromptRoutersResponse
Retrieves a list of prompt routers.
-
#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_enforced_guardrail_configuration(params = {}) ⇒ Types::PutEnforcedGuardrailConfigurationResponse
Sets the account-level enforced guardrail configuration.
-
#put_model_invocation_logging_configuration(params = {}) ⇒ Struct
Set the configuration values for model invocation logging.
-
#put_resource_policy(params = {}) ⇒ Types::PutResourcePolicyResponse
Adds a resource policy for a Bedrock resource.
-
#put_use_case_for_model_access(params = {}) ⇒ Struct
Put usecase for model access.
-
#register_marketplace_model_endpoint(params = {}) ⇒ Types::RegisterMarketplaceModelEndpointResponse
Registers an existing Amazon SageMaker endpoint with Amazon Bedrock Marketplace, allowing it to be used with Amazon Bedrock APIs.
-
#start_automated_reasoning_policy_build_workflow(params = {}) ⇒ Types::StartAutomatedReasoningPolicyBuildWorkflowResponse
Starts a new build workflow for an Automated Reasoning policy.
-
#start_automated_reasoning_policy_test_workflow(params = {}) ⇒ Types::StartAutomatedReasoningPolicyTestWorkflowResponse
Initiates a test workflow to validate Automated Reasoning policy tests.
-
#stop_advanced_prompt_optimization_job(params = {}) ⇒ Struct
Stops an advanced prompt optimization job that is in progress.
-
#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_automated_reasoning_policy(params = {}) ⇒ Types::UpdateAutomatedReasoningPolicyResponse
Updates an existing Automated Reasoning policy with new rules, variables, or configuration.
-
#update_automated_reasoning_policy_annotations(params = {}) ⇒ Types::UpdateAutomatedReasoningPolicyAnnotationsResponse
Updates the annotations for an Automated Reasoning policy build workflow.
-
#update_automated_reasoning_policy_test_case(params = {}) ⇒ Types::UpdateAutomatedReasoningPolicyTestCaseResponse
Updates an existing Automated Reasoning policy test.
-
#update_custom_model_deployment(params = {}) ⇒ Types::UpdateCustomModelDeploymentResponse
Updates a custom model deployment with a new custom model.
-
#update_guardrail(params = {}) ⇒ Types::UpdateGuardrailResponse
Updates a guardrail with the values you specify.
-
#update_marketplace_model_endpoint(params = {}) ⇒ Types::UpdateMarketplaceModelEndpointResponse
Updates the configuration of an existing endpoint for a model from Amazon Bedrock Marketplace.
-
#update_provisioned_model_throughput(params = {}) ⇒ Struct
Updates the name or associated model for a Provisioned Throughput.
Class Method Summary collapse
- .errors_module ⇒ Object private
Instance Method Summary collapse
- #build_request(operation_name, params = {}) ⇒ Object private
-
#initialize(options) ⇒ Client
constructor
A new instance of Client.
- #waiter_names ⇒ Object deprecated private Deprecated.
Constructor Details
#initialize(options) ⇒ Client
Returns a new instance of Client.
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# File 'lib/aws-sdk-bedrock/client.rb', line 473 def initialize(*args) super end |
Class Attribute Details
.identifier ⇒ Object (readonly)
This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.
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# File 'lib/aws-sdk-bedrock/client.rb', line 8300 def identifier @identifier end |
Class Method Details
.errors_module ⇒ Object
This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.
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# File 'lib/aws-sdk-bedrock/client.rb', line 8303 def errors_module Errors end |
Instance Method Details
#batch_delete_advanced_prompt_optimization_job(params = {}) ⇒ Types::BatchDeleteAdvancedPromptOptimizationJobResponse
Deletes one or more advanced prompt optimization jobs.
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# File 'lib/aws-sdk-bedrock/client.rb', line 510 def batch_delete_advanced_prompt_optimization_job(params = {}, = {}) req = build_request(:batch_delete_advanced_prompt_optimization_job, params) req.send_request() end |
#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.
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# File 'lib/aws-sdk-bedrock/client.rb', line 578 def batch_delete_evaluation_job(params = {}, = {}) req = build_request(:batch_delete_evaluation_job, params) req.send_request() end |
#build_request(operation_name, params = {}) ⇒ Object
This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.
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# File 'lib/aws-sdk-bedrock/client.rb', line 8273 def build_request(operation_name, params = {}) handlers = @handlers.for(operation_name) tracer = config.telemetry_provider.tracer_provider.tracer( Aws::Telemetry.module_to_tracer_name('Aws::Bedrock') ) context = Seahorse::Client::RequestContext.new( operation_name: operation_name, operation: config.api.operation(operation_name), client: self, params: params, config: config, tracer: tracer ) context[:gem_name] = 'aws-sdk-bedrock' context[:gem_version] = '1.87.0' Seahorse::Client::Request.new(handlers, context) end |
#cancel_automated_reasoning_policy_build_workflow(params = {}) ⇒ Struct
Cancels a running Automated Reasoning policy build workflow. This stops the policy generation process and prevents further processing of the source documents.
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# File 'lib/aws-sdk-bedrock/client.rb', line 609 def cancel_automated_reasoning_policy_build_workflow(params = {}, = {}) req = build_request(:cancel_automated_reasoning_policy_build_workflow, params) req.send_request() end |
#create_advanced_prompt_optimization_job(params = {}) ⇒ Types::CreateAdvancedPromptOptimizationJobResponse
Creates an advanced prompt optimization job. The job optimizes your prompt templates for specific models using your evaluation dataset and criteria.
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# File 'lib/aws-sdk-bedrock/client.rb', line 700 def create_advanced_prompt_optimization_job(params = {}, = {}) req = build_request(:create_advanced_prompt_optimization_job, params) req.send_request() end |
#create_automated_reasoning_policy(params = {}) ⇒ Types::CreateAutomatedReasoningPolicyResponse
Creates an Automated Reasoning policy for Amazon Bedrock Guardrails. Automated Reasoning policies use mathematical techniques to detect hallucinations, suggest corrections, and highlight unstated assumptions in the responses of your GenAI application.
To create a policy, you upload a source document that describes the rules that you’re encoding. Automated Reasoning extracts important concepts from the source document that will become variables in the policy and infers policy rules.
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# File 'lib/aws-sdk-bedrock/client.rb', line 817 def create_automated_reasoning_policy(params = {}, = {}) req = build_request(:create_automated_reasoning_policy, params) req.send_request() end |
#create_automated_reasoning_policy_test_case(params = {}) ⇒ Types::CreateAutomatedReasoningPolicyTestCaseResponse
Creates a test for an Automated Reasoning policy. Tests validate that your policy works as expected by providing sample inputs and expected outcomes. Use tests to verify policy behavior before deploying to production.
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# File 'lib/aws-sdk-bedrock/client.rb', line 920 def create_automated_reasoning_policy_test_case(params = {}, = {}) req = build_request(:create_automated_reasoning_policy_test_case, params) req.send_request() end |
#create_automated_reasoning_policy_version(params = {}) ⇒ Types::CreateAutomatedReasoningPolicyVersionResponse
Creates a new version of an existing Automated Reasoning policy. This allows you to iterate on your policy rules while maintaining previous versions for rollback or comparison purposes.
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# File 'lib/aws-sdk-bedrock/client.rb', line 986 def create_automated_reasoning_policy_version(params = {}, = {}) req = build_request(:create_automated_reasoning_policy_version, params) req.send_request() end |
#create_custom_model(params = {}) ⇒ Types::CreateCustomModelResponse
Creates a new custom model in Amazon Bedrock. After the model is active, you can use it for inference.
You can provide the model data source in one of the following ways:
-
‘customModelDataSource` — Specify a SageMaker AI model package ARN. Amazon Bedrock resolves the model package to retrieve the model artifacts. This is the preferred method for new SageMaker AI training outputs.
-
‘modelSourceConfig` — Specify an Amazon S3 URI pointing to the Amazon-managed Amazon S3 bucket containing your model artifacts.
To use the model for inference, you must purchase Provisioned Throughput for it. You can’t use On-demand inference with these custom models. For more information about Provisioned Throughput, see [Provisioned Throughput].
The model appears in ‘ListCustomModels` with a `customizationType` of `imported`. To track the status of the new model, you use the `GetCustomModel` API operation. The model can be in the following states:
-
‘Creating` - Initial state during validation and registration
-
‘Active` - Model is ready for use in inference
-
‘Failed` - Creation process encountered an error
**Related APIs**
- GetCustomModel][2
- ListCustomModels][3
- DeleteCustomModel][4
[1]: docs.aws.amazon.com/bedrock/latest/userguide/prov-throughput.html [2]: docs.aws.amazon.com/bedrock/latest/APIReference/API_GetCustomModel.html [3]: docs.aws.amazon.com/bedrock/latest/APIReference/API_ListCustomModels.html [4]: docs.aws.amazon.com/bedrock/latest/APIReference/API_DeleteCustomModel.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 1175 def create_custom_model(params = {}, = {}) req = build_request(:create_custom_model, params) req.send_request() end |
#create_custom_model_deployment(params = {}) ⇒ Types::CreateCustomModelDeploymentResponse
Deploys a custom model for on-demand inference in Amazon Bedrock. After you deploy your custom model, you use the deployment’s Amazon Resource Name (ARN) as the ‘modelId` parameter when you submit prompts and generate responses with model inference.
For more information about setting up on-demand inference for custom models, see [Set up inference for a custom model].
The following actions are related to the ‘CreateCustomModelDeployment` operation:
- GetCustomModelDeployment][2
- ListCustomModelDeployments][3
- DeleteCustomModelDeployment][4
[1]: docs.aws.amazon.com/bedrock/latest/userguide/model-customization-use.html [2]: docs.aws.amazon.com/bedrock/latest/APIReference/API_GetCustomModelDeployment.html [3]: docs.aws.amazon.com/bedrock/latest/APIReference/API_ListCustomModelDeployments.html [4]: docs.aws.amazon.com/bedrock/latest/APIReference/API_DeleteCustomModelDeployment.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 1261 def create_custom_model_deployment(params = {}, = {}) req = build_request(:create_custom_model_deployment, params) req.send_request() end |
#create_evaluation_job(params = {}) ⇒ Types::CreateEvaluationJobResponse
Creates an evaluation job.
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# File 'lib/aws-sdk-bedrock/client.rb', line 1760 def create_evaluation_job(params = {}, = {}) req = build_request(:create_evaluation_job, params) req.send_request() end |
#create_foundation_model_agreement(params = {}) ⇒ Types::CreateFoundationModelAgreementResponse
Request a model access agreement for the specified model.
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# File 'lib/aws-sdk-bedrock/client.rb', line 1792 def create_foundation_model_agreement(params = {}, = {}) req = build_request(:create_foundation_model_agreement, params) req.send_request() 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*.
[1]: docs.aws.amazon.com/bedrock/latest/userguide/guardrails.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 2025 def create_guardrail(params = {}, = {}) req = build_request(:create_guardrail, params) req.send_request() 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.
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# File 'lib/aws-sdk-bedrock/client.rb', line 2076 def create_guardrail_version(params = {}, = {}) req = build_request(:create_guardrail_version, params) req.send_request() 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.
[1]: docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 2158 def create_inference_profile(params = {}, = {}) req = build_request(:create_inference_profile, params) req.send_request() end |
#create_marketplace_model_endpoint(params = {}) ⇒ Types::CreateMarketplaceModelEndpointResponse
Creates an endpoint for a model from Amazon Bedrock Marketplace. The endpoint is hosted by Amazon SageMaker.
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# File 'lib/aws-sdk-bedrock/client.rb', line 2251 def create_marketplace_model_endpoint(params = {}, = {}) req = build_request(:create_marketplace_model_endpoint, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/copy-model.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 2323 def create_model_copy_job(params = {}, = {}) req = build_request(:create_model_copy_job, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/model-customization-prepare.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/custom-models.html [3]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 2539 def create_model_customization_job(params = {}, = {}) req = build_request(:create_model_customization_job, params) req.send_request() 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]
[1]: docs.aws.amazon.com/bedrock/latest/userguide/model-customization-import-model.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 2630 def create_model_import_job(params = {}, = {}) req = build_request(:create_model_import_job, params) req.send_request() 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.
[1]: docs.aws.amazon.com/bedrock/latest/userguide/batch-inference-data [2]: docs.aws.amazon.com/bedrock/latest/userguide/batch-inference.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 2755 def create_model_invocation_job(params = {}, = {}) req = build_request(:create_model_invocation_job, params) req.send_request() end |
#create_prompt_router(params = {}) ⇒ Types::CreatePromptRouterResponse
Creates a prompt router that manages the routing of requests between multiple foundation models based on the routing criteria.
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# File 'lib/aws-sdk-bedrock/client.rb', line 2831 def create_prompt_router(params = {}, = {}) req = build_request(:create_prompt_router, params) req.send_request() 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].
[1]: aws.amazon.com/bedrock/pricing/ [2]: docs.aws.amazon.com/bedrock/latest/userguide/prov-throughput.html [3]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 2942 def create_provisioned_model_throughput(params = {}, = {}) req = build_request(:create_provisioned_model_throughput, params) req.send_request() end |
#delete_automated_reasoning_policy(params = {}) ⇒ Struct
Deletes an Automated Reasoning policy or policy version. This operation is idempotent. If you delete a policy more than once, each call succeeds. Deleting a policy removes it permanently and cannot be undone.
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# File 'lib/aws-sdk-bedrock/client.rb', line 2977 def delete_automated_reasoning_policy(params = {}, = {}) req = build_request(:delete_automated_reasoning_policy, params) req.send_request() end |
#delete_automated_reasoning_policy_build_workflow(params = {}) ⇒ Struct
Deletes an Automated Reasoning policy build workflow and its associated artifacts. This permanently removes the workflow history and any generated assets.
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# File 'lib/aws-sdk-bedrock/client.rb', line 3012 def delete_automated_reasoning_policy_build_workflow(params = {}, = {}) req = build_request(:delete_automated_reasoning_policy_build_workflow, params) req.send_request() end |
#delete_automated_reasoning_policy_test_case(params = {}) ⇒ Struct
Deletes an Automated Reasoning policy test. This operation is idempotent; if you delete a test more than once, each call succeeds.
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# File 'lib/aws-sdk-bedrock/client.rb', line 3045 def delete_automated_reasoning_policy_test_case(params = {}, = {}) req = build_request(:delete_automated_reasoning_policy_test_case, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/custom-models.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 3073 def delete_custom_model(params = {}, = {}) req = build_request(:delete_custom_model, params) req.send_request() end |
#delete_custom_model_deployment(params = {}) ⇒ Struct
Deletes a custom model deployment. This operation stops the deployment and removes it from your account. After deletion, the deployment ARN can no longer be used for inference requests.
The following actions are related to the ‘DeleteCustomModelDeployment` operation:
- CreateCustomModelDeployment][1
- GetCustomModelDeployment][2
- ListCustomModelDeployments][3
[1]: docs.aws.amazon.com/bedrock/latest/APIReference/API_CreateCustomModelDeployment.html [2]: docs.aws.amazon.com/bedrock/latest/APIReference/API_GetCustomModelDeployment.html [3]: docs.aws.amazon.com/bedrock/latest/APIReference/API_ListCustomModelDeployments.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 3113 def delete_custom_model_deployment(params = {}, = {}) req = build_request(:delete_custom_model_deployment, params) req.send_request() end |
#delete_enforced_guardrail_configuration(params = {}) ⇒ Struct
Deletes the account-level enforced guardrail configuration.
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# File 'lib/aws-sdk-bedrock/client.rb', line 3135 def delete_enforced_guardrail_configuration(params = {}, = {}) req = build_request(:delete_enforced_guardrail_configuration, params) req.send_request() end |
#delete_foundation_model_agreement(params = {}) ⇒ Struct
Delete the model access agreement for the specified model.
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# File 'lib/aws-sdk-bedrock/client.rb', line 3157 def delete_foundation_model_agreement(params = {}, = {}) req = build_request(:delete_foundation_model_agreement, params) req.send_request() 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.
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# File 'lib/aws-sdk-bedrock/client.rb', line 3191 def delete_guardrail(params = {}, = {}) req = build_request(:delete_guardrail, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/model-customization-import-model.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 3220 def delete_imported_model(params = {}, = {}) req = build_request(:delete_imported_model, params) req.send_request() 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.
[1]: docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 3249 def delete_inference_profile(params = {}, = {}) req = build_request(:delete_inference_profile, params) req.send_request() end |
#delete_marketplace_model_endpoint(params = {}) ⇒ Struct
Deletes an endpoint for a model from Amazon Bedrock Marketplace.
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# File 'lib/aws-sdk-bedrock/client.rb', line 3271 def delete_marketplace_model_endpoint(params = {}, = {}) req = build_request(:delete_marketplace_model_endpoint, params) req.send_request() end |
#delete_model_invocation_logging_configuration(params = {}) ⇒ Struct
Delete the invocation logging.
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# File 'lib/aws-sdk-bedrock/client.rb', line 3284 def delete_model_invocation_logging_configuration(params = {}, = {}) req = build_request(:delete_model_invocation_logging_configuration, params) req.send_request() end |
#delete_prompt_router(params = {}) ⇒ Struct
Deletes a specified prompt router. This action cannot be undone.
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# File 'lib/aws-sdk-bedrock/client.rb', line 3306 def delete_prompt_router(params = {}, = {}) req = build_request(:delete_prompt_router, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/prov-throughput.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 3335 def delete_provisioned_model_throughput(params = {}, = {}) req = build_request(:delete_provisioned_model_throughput, params) req.send_request() end |
#delete_resource_policy(params = {}) ⇒ Struct
Deletes a previously created Bedrock resource policy.
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# File 'lib/aws-sdk-bedrock/client.rb', line 3357 def delete_resource_policy(params = {}, = {}) req = build_request(:delete_resource_policy, params) req.send_request() end |
#deregister_marketplace_model_endpoint(params = {}) ⇒ Struct
Deregisters an endpoint for a model from Amazon Bedrock Marketplace. This operation removes the endpoint’s association with Amazon Bedrock but does not delete the underlying Amazon SageMaker endpoint.
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# File 'lib/aws-sdk-bedrock/client.rb', line 3381 def deregister_marketplace_model_endpoint(params = {}, = {}) req = build_request(:deregister_marketplace_model_endpoint, params) req.send_request() end |
#export_automated_reasoning_policy_version(params = {}) ⇒ Types::ExportAutomatedReasoningPolicyVersionResponse
Exports the policy definition for an Automated Reasoning policy version. Returns the complete policy definition including rules, variables, and custom variable types in a structured format.
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# File 'lib/aws-sdk-bedrock/client.rb', line 3427 def export_automated_reasoning_policy_version(params = {}, = {}) req = build_request(:export_automated_reasoning_policy_version, params) req.send_request() end |
#get_advanced_prompt_optimization_job(params = {}) ⇒ Types::GetAdvancedPromptOptimizationJobResponse
Gets information about an advanced prompt optimization job.
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# File 'lib/aws-sdk-bedrock/client.rb', line 3482 def get_advanced_prompt_optimization_job(params = {}, = {}) req = build_request(:get_advanced_prompt_optimization_job, params) req.send_request() end |
#get_automated_reasoning_policy(params = {}) ⇒ Types::GetAutomatedReasoningPolicyResponse
Retrieves details about an Automated Reasoning policy or policy version. Returns information including the policy definition, metadata, and timestamps.
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# File 'lib/aws-sdk-bedrock/client.rb', line 3530 def get_automated_reasoning_policy(params = {}, = {}) req = build_request(:get_automated_reasoning_policy, params) req.send_request() end |
#get_automated_reasoning_policy_annotations(params = {}) ⇒ Types::GetAutomatedReasoningPolicyAnnotationsResponse
Retrieves the current annotations for an Automated Reasoning policy build workflow. Annotations contain corrections to the rules, variables and types to be applied to the policy.
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# File 'lib/aws-sdk-bedrock/client.rb', line 3612 def get_automated_reasoning_policy_annotations(params = {}, = {}) req = build_request(:get_automated_reasoning_policy_annotations, params) req.send_request() end |
#get_automated_reasoning_policy_build_workflow(params = {}) ⇒ Types::GetAutomatedReasoningPolicyBuildWorkflowResponse
Retrieves detailed information about an Automated Reasoning policy build workflow, including its status, configuration, and metadata.
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# File 'lib/aws-sdk-bedrock/client.rb', line 3662 def get_automated_reasoning_policy_build_workflow(params = {}, = {}) req = build_request(:get_automated_reasoning_policy_build_workflow, params) req.send_request() end |
#get_automated_reasoning_policy_build_workflow_result_assets(params = {}) ⇒ Types::GetAutomatedReasoningPolicyBuildWorkflowResultAssetsResponse
Retrieves the resulting assets from a completed Automated Reasoning policy build workflow, including build logs, quality reports, and generated policy artifacts.
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# File 'lib/aws-sdk-bedrock/client.rb', line 3878 def get_automated_reasoning_policy_build_workflow_result_assets(params = {}, = {}) req = build_request(:get_automated_reasoning_policy_build_workflow_result_assets, params) req.send_request() end |
#get_automated_reasoning_policy_next_scenario(params = {}) ⇒ Types::GetAutomatedReasoningPolicyNextScenarioResponse
Retrieves the next test scenario for validating an Automated Reasoning policy. This is used during the interactive policy refinement process to test policy behavior.
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# File 'lib/aws-sdk-bedrock/client.rb', line 3920 def get_automated_reasoning_policy_next_scenario(params = {}, = {}) req = build_request(:get_automated_reasoning_policy_next_scenario, params) req.send_request() end |
#get_automated_reasoning_policy_test_case(params = {}) ⇒ Types::GetAutomatedReasoningPolicyTestCaseResponse
Retrieves details about a specific Automated Reasoning policy test.
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# File 'lib/aws-sdk-bedrock/client.rb', line 3961 def get_automated_reasoning_policy_test_case(params = {}, = {}) req = build_request(:get_automated_reasoning_policy_test_case, params) req.send_request() end |
#get_automated_reasoning_policy_test_result(params = {}) ⇒ Types::GetAutomatedReasoningPolicyTestResultResponse
Retrieves the test result for a specific Automated Reasoning policy test. Returns detailed validation findings and execution status.
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# File 'lib/aws-sdk-bedrock/client.rb', line 4118 def get_automated_reasoning_policy_test_result(params = {}, = {}) req = build_request(:get_automated_reasoning_policy_test_result, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/custom-models.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 4214 def get_custom_model(params = {}, = {}) req = build_request(:get_custom_model, params) req.send_request() end |
#get_custom_model_deployment(params = {}) ⇒ Types::GetCustomModelDeploymentResponse
Retrieves information about a custom model deployment, including its status, configuration, and metadata. Use this operation to monitor the deployment status and retrieve details needed for inference requests.
The following actions are related to the ‘GetCustomModelDeployment` operation:
- CreateCustomModelDeployment][1
- ListCustomModelDeployments][2
- DeleteCustomModelDeployment][3
[1]: docs.aws.amazon.com/bedrock/latest/APIReference/API_CreateCustomModelDeployment.html [2]: docs.aws.amazon.com/bedrock/latest/APIReference/API_ListCustomModelDeployments.html [3]: docs.aws.amazon.com/bedrock/latest/APIReference/API_DeleteCustomModelDeployment.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 4277 def get_custom_model_deployment(params = {}, = {}) req = build_request(:get_custom_model_deployment, params) req.send_request() end |
#get_evaluation_job(params = {}) ⇒ Types::GetEvaluationJobResponse
Gets information about an evaluation job, such as the status of the job.
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# File 'lib/aws-sdk-bedrock/client.rb', line 4461 def get_evaluation_job(params = {}, = {}) req = build_request(:get_evaluation_job, params) req.send_request() end |
#get_foundation_model(params = {}) ⇒ Types::GetFoundationModelResponse
Get details about a Amazon Bedrock foundation model.
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# File 'lib/aws-sdk-bedrock/client.rb', line 4506 def get_foundation_model(params = {}, = {}) req = build_request(:get_foundation_model, params) req.send_request() end |
#get_foundation_model_availability(params = {}) ⇒ Types::GetFoundationModelAvailabilityResponse
Get information about the Foundation model availability.
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# File 'lib/aws-sdk-bedrock/client.rb', line 4543 def get_foundation_model_availability(params = {}, = {}) req = build_request(:get_foundation_model_availability, params) req.send_request() 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.
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# File 'lib/aws-sdk-bedrock/client.rb', line 4674 def get_guardrail(params = {}, = {}) req = build_request(:get_guardrail, params) req.send_request() end |
#get_imported_model(params = {}) ⇒ Types::GetImportedModelResponse
Gets properties associated with a customized model you imported.
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# File 'lib/aws-sdk-bedrock/client.rb', line 4721 def get_imported_model(params = {}, = {}) req = build_request(:get_imported_model, params) req.send_request() 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.
[1]: docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 4772 def get_inference_profile(params = {}, = {}) req = build_request(:get_inference_profile, params) req.send_request() end |
#get_marketplace_model_endpoint(params = {}) ⇒ Types::GetMarketplaceModelEndpointResponse
Retrieves details about a specific endpoint for a model from Amazon Bedrock Marketplace.
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# File 'lib/aws-sdk-bedrock/client.rb', line 4817 def get_marketplace_model_endpoint(params = {}, = {}) req = build_request(:get_marketplace_model_endpoint, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/copy-model.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 4874 def get_model_copy_job(params = {}, = {}) req = build_request(:get_model_copy_job, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/custom-models.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 4993 def get_model_customization_job(params = {}, = {}) req = build_request(:get_model_customization_job, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/model-customization-import-model.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 5055 def get_model_import_job(params = {}, = {}) req = build_request(:get_model_import_job, params) req.send_request() end |
#get_model_invocation_job(params = {}) ⇒ Types::GetModelInvocationJobResponse
Gets details about a batch inference job. For more information, see
- Monitor batch inference jobs][1
-
[1]: docs.aws.amazon.com/bedrock/latest/userguide/batch-inference-monitor
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# File 'lib/aws-sdk-bedrock/client.rb', line 5133 def get_model_invocation_job(params = {}, = {}) req = build_request(:get_model_invocation_job, params) req.send_request() end |
#get_model_invocation_logging_configuration(params = {}) ⇒ Types::GetModelInvocationLoggingConfigurationResponse
Get the current configuration values for model invocation logging.
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# File 'lib/aws-sdk-bedrock/client.rb', line 5162 def get_model_invocation_logging_configuration(params = {}, = {}) req = build_request(:get_model_invocation_logging_configuration, params) req.send_request() end |
#get_prompt_router(params = {}) ⇒ Types::GetPromptRouterResponse
Retrieves details about a prompt router.
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# File 'lib/aws-sdk-bedrock/client.rb', line 5209 def get_prompt_router(params = {}, = {}) req = build_request(:get_prompt_router, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/prov-throughput.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 5267 def get_provisioned_model_throughput(params = {}, = {}) req = build_request(:get_provisioned_model_throughput, params) req.send_request() end |
#get_resource_policy(params = {}) ⇒ Types::GetResourcePolicyResponse
Gets the resource policy document for a Bedrock resource
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# File 'lib/aws-sdk-bedrock/client.rb', line 5295 def get_resource_policy(params = {}, = {}) req = build_request(:get_resource_policy, params) req.send_request() end |
#get_use_case_for_model_access(params = {}) ⇒ Types::GetUseCaseForModelAccessResponse
Get usecase for model access.
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# File 'lib/aws-sdk-bedrock/client.rb', line 5314 def get_use_case_for_model_access(params = {}, = {}) req = build_request(:get_use_case_for_model_access, params) req.send_request() end |
#list_advanced_prompt_optimization_jobs(params = {}) ⇒ Types::ListAdvancedPromptOptimizationJobsResponse
Lists the advanced prompt optimization jobs in your account.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-bedrock/client.rb', line 5365 def list_advanced_prompt_optimization_jobs(params = {}, = {}) req = build_request(:list_advanced_prompt_optimization_jobs, params) req.send_request() end |
#list_automated_reasoning_policies(params = {}) ⇒ Types::ListAutomatedReasoningPoliciesResponse
Lists all Automated Reasoning policies in your account, with optional filtering by policy ARN. This helps you manage and discover existing policies.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-bedrock/client.rb', line 5417 def list_automated_reasoning_policies(params = {}, = {}) req = build_request(:list_automated_reasoning_policies, params) req.send_request() end |
#list_automated_reasoning_policy_build_workflows(params = {}) ⇒ Types::ListAutomatedReasoningPolicyBuildWorkflowsResponse
Lists all build workflows for an Automated Reasoning policy, showing the history of policy creation and modification attempts.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-bedrock/client.rb', line 5467 def list_automated_reasoning_policy_build_workflows(params = {}, = {}) req = build_request(:list_automated_reasoning_policy_build_workflows, params) req.send_request() end |
#list_automated_reasoning_policy_test_cases(params = {}) ⇒ Types::ListAutomatedReasoningPolicyTestCasesResponse
Lists tests for an Automated Reasoning policy. We recommend using pagination to ensure that the operation returns quickly and successfully.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-bedrock/client.rb', line 5518 def list_automated_reasoning_policy_test_cases(params = {}, = {}) req = build_request(:list_automated_reasoning_policy_test_cases, params) req.send_request() end |
#list_automated_reasoning_policy_test_results(params = {}) ⇒ Types::ListAutomatedReasoningPolicyTestResultsResponse
Lists test results for an Automated Reasoning policy, showing how the policy performed against various test scenarios and validation checks.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-bedrock/client.rb', line 5687 def list_automated_reasoning_policy_test_results(params = {}, = {}) req = build_request(:list_automated_reasoning_policy_test_results, params) req.send_request() end |
#list_custom_model_deployments(params = {}) ⇒ Types::ListCustomModelDeploymentsResponse
Lists custom model deployments in your account. You can filter the results by creation time, name, status, and associated model. Use this operation to manage and monitor your custom model deployments.
We recommend using pagination to ensure that the operation returns quickly and successfully.
The following actions are related to the ‘ListCustomModelDeployments` operation:
- CreateCustomModelDeployment][1
- GetCustomModelDeployment][2
- DeleteCustomModelDeployment][3
[1]: docs.aws.amazon.com/bedrock/latest/APIReference/API_CreateCustomModelDeployment.html [2]: docs.aws.amazon.com/bedrock/latest/APIReference/API_GetCustomModelDeployment.html [3]: docs.aws.amazon.com/bedrock/latest/APIReference/API_DeleteCustomModelDeployment.html
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-bedrock/client.rb', line 5783 def list_custom_model_deployments(params = {}, = {}) req = build_request(:list_custom_model_deployments, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/custom-models.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-bedrock/client.rb', line 5892 def list_custom_models(params = {}, = {}) req = build_request(:list_custom_models, params) req.send_request() end |
#list_enforced_guardrails_configuration(params = {}) ⇒ Types::ListEnforcedGuardrailsConfigurationResponse
Lists the account-level enforced guardrail configurations.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-bedrock/client.rb', line 5940 def list_enforced_guardrails_configuration(params = {}, = {}) req = build_request(:list_enforced_guardrails_configuration, params) req.send_request() 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.
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# File 'lib/aws-sdk-bedrock/client.rb', line 6033 def list_evaluation_jobs(params = {}, = {}) req = build_request(:list_evaluation_jobs, params) req.send_request() end |
#list_foundation_model_agreement_offers(params = {}) ⇒ Types::ListFoundationModelAgreementOffersResponse
Get the offers associated with the specified model.
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# File 'lib/aws-sdk-bedrock/client.rb', line 6077 def list_foundation_model_agreement_offers(params = {}, = {}) req = build_request(:list_foundation_model_agreement_offers, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/foundation-models.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 6156 def list_foundation_models(params = {}, = {}) req = build_request(:list_foundation_models, params) req.send_request() 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.
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# File 'lib/aws-sdk-bedrock/client.rb', line 6216 def list_guardrails(params = {}, = {}) req = build_request(:list_guardrails, params) req.send_request() 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][1
-
in the [Amazon Bedrock User Guide].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/model-customization-import-model.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-bedrock/client.rb', line 6292 def list_imported_models(params = {}, = {}) req = build_request(:list_imported_models, params) req.send_request() 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.
[1]: docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference.html
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-bedrock/client.rb', line 6363 def list_inference_profiles(params = {}, = {}) req = build_request(:list_inference_profiles, params) req.send_request() end |
#list_marketplace_model_endpoints(params = {}) ⇒ Types::ListMarketplaceModelEndpointsResponse
Lists the endpoints for models from Amazon Bedrock Marketplace in your Amazon Web Services account.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-bedrock/client.rb', line 6413 def list_marketplace_model_endpoints(params = {}, = {}) req = build_request(:list_marketplace_model_endpoints, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/copy-model.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-bedrock/client.rb', line 6513 def list_model_copy_jobs(params = {}, = {}) req = build_request(:list_model_copy_jobs, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/custom-models.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-bedrock/client.rb', line 6608 def list_model_customization_jobs(params = {}, = {}) req = build_request(:list_model_customization_jobs, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/model-customization-import-model.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-bedrock/client.rb', line 6691 def list_model_import_jobs(params = {}, = {}) req = build_request(:list_model_import_jobs, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/batch-inference-view.html
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-bedrock/client.rb', line 6840 def list_model_invocation_jobs(params = {}, = {}) req = build_request(:list_model_invocation_jobs, params) req.send_request() end |
#list_prompt_routers(params = {}) ⇒ Types::ListPromptRoutersResponse
Retrieves a list of prompt routers.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-bedrock/client.rb', line 6893 def list_prompt_routers(params = {}, = {}) req = build_request(:list_prompt_routers, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/prov-throughput.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'lib/aws-sdk-bedrock/client.rb', line 6988 def list_provisioned_model_throughputs(params = {}, = {}) req = build_request(:list_provisioned_model_throughputs, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 7025 def (params = {}, = {}) req = build_request(:list_tags_for_resource, params) req.send_request() end |
#put_enforced_guardrail_configuration(params = {}) ⇒ Types::PutEnforcedGuardrailConfigurationResponse
Sets the account-level enforced guardrail configuration.
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# File 'lib/aws-sdk-bedrock/client.rb', line 7072 def put_enforced_guardrail_configuration(params = {}, = {}) req = build_request(:put_enforced_guardrail_configuration, params) req.send_request() end |
#put_model_invocation_logging_configuration(params = {}) ⇒ Struct
Set the configuration values for model invocation logging.
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# File 'lib/aws-sdk-bedrock/client.rb', line 7112 def put_model_invocation_logging_configuration(params = {}, = {}) req = build_request(:put_model_invocation_logging_configuration, params) req.send_request() end |
#put_resource_policy(params = {}) ⇒ Types::PutResourcePolicyResponse
Adds a resource policy for a Bedrock resource.
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# File 'lib/aws-sdk-bedrock/client.rb', line 7144 def put_resource_policy(params = {}, = {}) req = build_request(:put_resource_policy, params) req.send_request() end |
#put_use_case_for_model_access(params = {}) ⇒ Struct
Put usecase for model access.
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# File 'lib/aws-sdk-bedrock/client.rb', line 7166 def put_use_case_for_model_access(params = {}, = {}) req = build_request(:put_use_case_for_model_access, params) req.send_request() end |
#register_marketplace_model_endpoint(params = {}) ⇒ Types::RegisterMarketplaceModelEndpointResponse
Registers an existing Amazon SageMaker endpoint with Amazon Bedrock Marketplace, allowing it to be used with Amazon Bedrock APIs.
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# File 'lib/aws-sdk-bedrock/client.rb', line 7216 def register_marketplace_model_endpoint(params = {}, = {}) req = build_request(:register_marketplace_model_endpoint, params) req.send_request() end |
#start_automated_reasoning_policy_build_workflow(params = {}) ⇒ Types::StartAutomatedReasoningPolicyBuildWorkflowResponse
Starts a new build workflow for an Automated Reasoning policy. This initiates the process of analyzing source documents and generating policy rules, variables, and types.
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# File 'lib/aws-sdk-bedrock/client.rb', line 7397 def start_automated_reasoning_policy_build_workflow(params = {}, = {}) req = build_request(:start_automated_reasoning_policy_build_workflow, params) req.send_request() end |
#start_automated_reasoning_policy_test_workflow(params = {}) ⇒ Types::StartAutomatedReasoningPolicyTestWorkflowResponse
Initiates a test workflow to validate Automated Reasoning policy tests. The workflow executes the specified tests against the policy and generates validation results.
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# File 'lib/aws-sdk-bedrock/client.rb', line 7448 def start_automated_reasoning_policy_test_workflow(params = {}, = {}) req = build_request(:start_automated_reasoning_policy_test_workflow, params) req.send_request() end |
#stop_advanced_prompt_optimization_job(params = {}) ⇒ Struct
Stops an advanced prompt optimization job that is in progress.
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# File 'lib/aws-sdk-bedrock/client.rb', line 7470 def stop_advanced_prompt_optimization_job(params = {}, = {}) req = build_request(:stop_advanced_prompt_optimization_job, params) req.send_request() end |
#stop_evaluation_job(params = {}) ⇒ Struct
Stops an evaluation job that is current being created or running.
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# File 'lib/aws-sdk-bedrock/client.rb', line 7492 def stop_evaluation_job(params = {}, = {}) req = build_request(:stop_evaluation_job, params) req.send_request() end |
#stop_model_customization_job(params = {}) ⇒ Struct
Stops an active model customization job. For more information, see
- Custom models][1
-
in the [Amazon Bedrock User Guide].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/custom-models.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 7520 def stop_model_customization_job(params = {}, = {}) req = build_request(:stop_model_customization_job, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/batch-inference-stop.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 7548 def stop_model_invocation_job(params = {}, = {}) req = build_request(:stop_model_invocation_job, params) req.send_request() end |
#tag_resource(params = {}) ⇒ Struct
Associate tags with a resource. For more information, see [Tagging resources] in the [Amazon Bedrock User Guide].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 7584 def tag_resource(params = {}, = {}) req = build_request(:tag_resource, params) req.send_request() end |
#untag_resource(params = {}) ⇒ Struct
Remove one or more tags from a resource. For more information, see
- Tagging resources][1
-
in the [Amazon Bedrock User Guide].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 7615 def untag_resource(params = {}, = {}) req = build_request(:untag_resource, params) req.send_request() end |
#update_automated_reasoning_policy(params = {}) ⇒ Types::UpdateAutomatedReasoningPolicyResponse
Updates an existing Automated Reasoning policy with new rules, variables, or configuration. This creates a new version of the policy while preserving the previous version.
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# File 'lib/aws-sdk-bedrock/client.rb', line 7693 def update_automated_reasoning_policy(params = {}, = {}) req = build_request(:update_automated_reasoning_policy, params) req.send_request() end |
#update_automated_reasoning_policy_annotations(params = {}) ⇒ Types::UpdateAutomatedReasoningPolicyAnnotationsResponse
Updates the annotations for an Automated Reasoning policy build workflow. This allows you to modify extracted rules, variables, and types before finalizing the policy.
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# File 'lib/aws-sdk-bedrock/client.rb', line 7821 def update_automated_reasoning_policy_annotations(params = {}, = {}) req = build_request(:update_automated_reasoning_policy_annotations, params) req.send_request() end |
#update_automated_reasoning_policy_test_case(params = {}) ⇒ Types::UpdateAutomatedReasoningPolicyTestCaseResponse
Updates an existing Automated Reasoning policy test. You can modify the content, query, expected result, and confidence threshold.
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# File 'lib/aws-sdk-bedrock/client.rb', line 7889 def update_automated_reasoning_policy_test_case(params = {}, = {}) req = build_request(:update_automated_reasoning_policy_test_case, params) req.send_request() end |
#update_custom_model_deployment(params = {}) ⇒ Types::UpdateCustomModelDeploymentResponse
Updates a custom model deployment with a new custom model. This allows you to deploy updated models without creating new deployment endpoints.
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# File 'lib/aws-sdk-bedrock/client.rb', line 7925 def update_custom_model_deployment(params = {}, = {}) req = build_request(:update_custom_model_deployment, params) req.send_request() 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][2
-
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.
[1]: docs.aws.amazon.com/bedrock/latest/APIReference/API_GuardrailTopicConfig.html [2]: docs.aws.amazon.com/bedrock/latest/APIReference/API_GuardrailContentFilterConfig.html [3]: docs.aws.amazon.com/bedrock/latest/userguide/guardrails-content-filters
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# File 'lib/aws-sdk-bedrock/client.rb', line 8145 def update_guardrail(params = {}, = {}) req = build_request(:update_guardrail, params) req.send_request() end |
#update_marketplace_model_endpoint(params = {}) ⇒ Types::UpdateMarketplaceModelEndpointResponse
Updates the configuration of an existing endpoint for a model from Amazon Bedrock Marketplace.
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# File 'lib/aws-sdk-bedrock/client.rb', line 8216 def update_marketplace_model_endpoint(params = {}, = {}) req = build_request(:update_marketplace_model_endpoint, params) req.send_request() 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].
[1]: docs.aws.amazon.com/bedrock/latest/userguide/prov-throughput.html [2]: docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html
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# File 'lib/aws-sdk-bedrock/client.rb', line 8264 def update_provisioned_model_throughput(params = {}, = {}) req = build_request(:update_provisioned_model_throughput, params) req.send_request() end |
#waiter_names ⇒ Object
This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.
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# File 'lib/aws-sdk-bedrock/client.rb', line 8293 def waiter_names [] end |