R/bedrock_operations.R

In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

# This file is generated by make.paws. Please do not edit here.
#' @importFrom paws.common get_config new_operation new_request send_request
#' @include bedrock_service.R
NULL

#' Batch delete the specified advanced prompt optimization jobs
#'
#' @description
#' Batch delete the specified advanced prompt optimization jobs.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_batch_delete_advanced_prompt_optimization_job/](https://www.paws-r-sdk.com/docs/bedrock_batch_delete_advanced_prompt_optimization_job/) for full documentation.
#'
#' @param jobIdentifiers [required] List of advanced prompt optimization job identifiers to delete.
#'
#' @keywords internal
#'
#' @rdname bedrock_batch_delete_advanced_prompt_optimization_job
bedrock_batch_delete_advanced_prompt_optimization_job <- function(jobIdentifiers) {
  op <- new_operation(
    name = "BatchDeleteAdvancedPromptOptimizationJob",
    http_method = "POST",
    http_path = "/advanced-prompt-optimization-job/batch-delete",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$batch_delete_advanced_prompt_optimization_job_input(jobIdentifiers = jobIdentifiers)
  output <- .bedrock$batch_delete_advanced_prompt_optimization_job_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$batch_delete_advanced_prompt_optimization_job <- bedrock_batch_delete_advanced_prompt_optimization_job

#' Deletes a batch of evaluation jobs
#'
#' @description
#' 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.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_batch_delete_evaluation_job/](https://www.paws-r-sdk.com/docs/bedrock_batch_delete_evaluation_job/) for full documentation.
#'
#' @param jobIdentifiers &#91;required&#93; A list of one or more evaluation job Amazon Resource Names (ARNs) you want to delete.
#'
#' @keywords internal
#'
#' @rdname bedrock_batch_delete_evaluation_job
bedrock_batch_delete_evaluation_job <- function(jobIdentifiers) {
  op <- new_operation(
    name = "BatchDeleteEvaluationJob",
    http_method = "POST",
    http_path = "/evaluation-jobs/batch-delete",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$batch_delete_evaluation_job_input(jobIdentifiers = jobIdentifiers)
  output <- .bedrock$batch_delete_evaluation_job_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$batch_delete_evaluation_job <- bedrock_batch_delete_evaluation_job

#' Cancels a running Automated Reasoning policy build workflow
#'
#' @description
#' Cancels a running Automated Reasoning policy build workflow. This stops the policy generation process and prevents further processing of the source documents.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_cancel_automated_reasoning_policy_build_workflow/](https://www.paws-r-sdk.com/docs/bedrock_cancel_automated_reasoning_policy_build_workflow/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy whose build workflow you want to cancel.
#' @param buildWorkflowId &#91;required&#93; The unique identifier of the build workflow to cancel. You can get this ID from the StartAutomatedReasoningPolicyBuildWorkflow response or by listing build workflows.
#'
#' @keywords internal
#'
#' @rdname bedrock_cancel_automated_reasoning_policy_build_workflow
bedrock_cancel_automated_reasoning_policy_build_workflow <- function(policyArn, buildWorkflowId) {
  op <- new_operation(
    name = "CancelAutomatedReasoningPolicyBuildWorkflow",
    http_method = "POST",
    http_path = "/automated-reasoning-policies/{policyArn}/build-workflows/{buildWorkflowId}/cancel",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$cancel_automated_reasoning_policy_build_workflow_input(policyArn = policyArn, buildWorkflowId = buildWorkflowId)
  output <- .bedrock$cancel_automated_reasoning_policy_build_workflow_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$cancel_automated_reasoning_policy_build_workflow <- bedrock_cancel_automated_reasoning_policy_build_workflow

#' Creates an asynchronous batch job for advanced prompt optimization
#'
#' @description
#' Creates an asynchronous batch job for advanced prompt optimization.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_create_advanced_prompt_optimization_job/](https://www.paws-r-sdk.com/docs/bedrock_create_advanced_prompt_optimization_job/) for full documentation.
#'
#' @param jobName &#91;required&#93; Name of the advanced prompt optimization job.
#' @param jobDescription Description of the advanced prompt optimization job.
#' @param clientToken Idempotency token for the request.
#' @param inputConfig &#91;required&#93; Input data configuration for the advanced prompt optimization job.
#' @param outputConfig &#91;required&#93; Output data configuration for the advanced prompt optimization job.
#' @param encryptionKeyArn KMS key ARN for encrypting output data.
#' @param tags Tags to associate with the job.
#' @param modelConfigurations &#91;required&#93; Model configurations for advanced prompt optimization.
#'
#' @keywords internal
#'
#' @rdname bedrock_create_advanced_prompt_optimization_job
bedrock_create_advanced_prompt_optimization_job <- function(jobName, jobDescription = NULL, clientToken = NULL, inputConfig, outputConfig, encryptionKeyArn = NULL, tags = NULL, modelConfigurations) {
  op <- new_operation(
    name = "CreateAdvancedPromptOptimizationJob",
    http_method = "POST",
    http_path = "/advanced-prompt-optimization-jobs",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$create_advanced_prompt_optimization_job_input(jobName = jobName, jobDescription = jobDescription, clientToken = clientToken, inputConfig = inputConfig, outputConfig = outputConfig, encryptionKeyArn = encryptionKeyArn, tags = tags, modelConfigurations = modelConfigurations)
  output <- .bedrock$create_advanced_prompt_optimization_job_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$create_advanced_prompt_optimization_job <- bedrock_create_advanced_prompt_optimization_job

#' Creates an Automated Reasoning policy for Amazon Bedrock Guardrails
#'
#' @description
#' 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.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_create_automated_reasoning_policy/](https://www.paws-r-sdk.com/docs/bedrock_create_automated_reasoning_policy/) for full documentation.
#'
#' @param name &#91;required&#93; A unique name for the Automated Reasoning policy. The name must be between 1 and 63 characters and can contain letters, numbers, hyphens, and underscores.
#' @param description A description of the Automated Reasoning policy. Use this to provide context about the policy's purpose and the types of validations it performs.
#' @param clientRequestToken A unique, case-sensitive identifier to ensure that the operation completes no more than once. If this token matches a previous request, Amazon Bedrock ignores the request but doesn't return an error.
#' @param policyDefinition The policy definition that contains the formal logic rules, variables, and custom variable types used to validate foundation model responses in your application.
#' @param kmsKeyId The identifier of the KMS key to use for encrypting the automated reasoning policy and its associated artifacts. If you don't specify a KMS key, Amazon Bedrock uses an KMS managed key for encryption. For enhanced security and control, you can specify a customer managed KMS key.
#' @param tags A list of tags to associate with the Automated Reasoning policy. Tags help you organize and manage your policies.
#'
#' @keywords internal
#'
#' @rdname bedrock_create_automated_reasoning_policy
bedrock_create_automated_reasoning_policy <- function(name, description = NULL, clientRequestToken = NULL, policyDefinition = NULL, kmsKeyId = NULL, tags = NULL) {
  op <- new_operation(
    name = "CreateAutomatedReasoningPolicy",
    http_method = "POST",
    http_path = "/automated-reasoning-policies",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$create_automated_reasoning_policy_input(name = name, description = description, clientRequestToken = clientRequestToken, policyDefinition = policyDefinition, kmsKeyId = kmsKeyId, tags = tags)
  output <- .bedrock$create_automated_reasoning_policy_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$create_automated_reasoning_policy <- bedrock_create_automated_reasoning_policy

#' Creates a test for an Automated Reasoning policy
#'
#' @description
#' 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.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_create_automated_reasoning_policy_test_case/](https://www.paws-r-sdk.com/docs/bedrock_create_automated_reasoning_policy_test_case/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy for which to create the test.
#' @param guardContent &#91;required&#93; The output content that's validated by the Automated Reasoning policy. This represents the foundation model response that will be checked for accuracy.
#' @param queryContent The input query or prompt that generated the content. This provides context for the validation.
#' @param expectedAggregatedFindingsResult &#91;required&#93; The expected result of the Automated Reasoning check. Valid values include: , TOO_COMPLEX, and NO_TRANSLATIONS.
#' 
#' -   `VALID` - The claims are true. The claims are implied by the premises and the Automated Reasoning policy. Given the Automated Reasoning policy and premises, it is not possible for these claims to be false. In other words, there are no alternative answers that are true that contradict the claims.
#' 
#' -   `INVALID` - The claims are false. The claims are not implied by the premises and Automated Reasoning policy. Furthermore, there exists different claims that are consistent with the premises and Automated Reasoning policy.
#' 
#' -   `SATISFIABLE` - The claims can be true or false. It depends on what assumptions are made for the claim to be implied from the premises and Automated Reasoning policy rules. In this situation, different assumptions can make input claims false and alternative claims true.
#' 
#' -   `IMPOSSIBLE` - Automated Reasoning can’t make a statement about the claims. This can happen if the premises are logically incorrect, or if there is a conflict within the Automated Reasoning policy itself.
#' 
#' -   `TRANSLATION_AMBIGUOUS` - Detected an ambiguity in the translation meant it would be unsound to continue with validity checking. Additional context or follow-up questions might be needed to get translation to succeed.
#' 
#' -   `TOO_COMPLEX` - The input contains too much information for Automated Reasoning to process within its latency limits.
#' 
#' -   `NO_TRANSLATIONS` - Identifies that some or all of the input prompt wasn't translated into logic. This can happen if the input isn't relevant to the Automated Reasoning policy, or if the policy doesn't have variables to model relevant input. If Automated Reasoning can't translate anything, you get a single `NO_TRANSLATIONS` finding. You might also see a `NO_TRANSLATIONS` (along with other findings) if some part of the validation isn't translated.
#' @param clientRequestToken A unique, case-sensitive identifier to ensure that the operation completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error.
#' @param confidenceThreshold The minimum confidence level for logic validation. Content that meets the threshold is considered a high-confidence finding that can be validated.
#'
#' @keywords internal
#'
#' @rdname bedrock_create_automated_reasoning_policy_test_case
bedrock_create_automated_reasoning_policy_test_case <- function(policyArn, guardContent, queryContent = NULL, expectedAggregatedFindingsResult, clientRequestToken = NULL, confidenceThreshold = NULL) {
  op <- new_operation(
    name = "CreateAutomatedReasoningPolicyTestCase",
    http_method = "POST",
    http_path = "/automated-reasoning-policies/{policyArn}/test-cases",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$create_automated_reasoning_policy_test_case_input(policyArn = policyArn, guardContent = guardContent, queryContent = queryContent, expectedAggregatedFindingsResult = expectedAggregatedFindingsResult, clientRequestToken = clientRequestToken, confidenceThreshold = confidenceThreshold)
  output <- .bedrock$create_automated_reasoning_policy_test_case_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$create_automated_reasoning_policy_test_case <- bedrock_create_automated_reasoning_policy_test_case

#' Creates a new version of an existing Automated Reasoning policy
#'
#' @description
#' 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.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_create_automated_reasoning_policy_version/](https://www.paws-r-sdk.com/docs/bedrock_create_automated_reasoning_policy_version/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy for which to create a version.
#' @param clientRequestToken A unique, case-sensitive identifier to ensure that the operation completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error.
#' @param lastUpdatedDefinitionHash &#91;required&#93; The hash of the current policy definition used as a concurrency token to ensure the policy hasn't been modified since you last retrieved it.
#' @param tags A list of tags to associate with the policy version.
#'
#' @keywords internal
#'
#' @rdname bedrock_create_automated_reasoning_policy_version
bedrock_create_automated_reasoning_policy_version <- function(policyArn, clientRequestToken = NULL, lastUpdatedDefinitionHash, tags = NULL) {
  op <- new_operation(
    name = "CreateAutomatedReasoningPolicyVersion",
    http_method = "POST",
    http_path = "/automated-reasoning-policies/{policyArn}/versions",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$create_automated_reasoning_policy_version_input(policyArn = policyArn, clientRequestToken = clientRequestToken, lastUpdatedDefinitionHash = lastUpdatedDefinitionHash, tags = tags)
  output <- .bedrock$create_automated_reasoning_policy_version_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$create_automated_reasoning_policy_version <- bedrock_create_automated_reasoning_policy_version

#' Creates a new custom model in Amazon Bedrock
#'
#' @description
#' Creates a new custom model in Amazon Bedrock. After the model is active, you can use it for inference.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_create_custom_model/](https://www.paws-r-sdk.com/docs/bedrock_create_custom_model/) for full documentation.
#'
#' @param modelName &#91;required&#93; A unique name for the custom model.
#' @param modelSourceConfig &#91;required&#93; The data source for the model. The Amazon S3 URI in the model source must be for the Amazon-managed Amazon S3 bucket containing your model artifacts.
#' @param modelKmsKeyArn The Amazon Resource Name (ARN) of the customer managed KMS key to encrypt the custom model. If you don't provide a KMS key, Amazon Bedrock uses an Amazon Web Services-managed KMS key to encrypt the model.
#' 
#' If you provide a customer managed KMS key, your Amazon Bedrock service role must have permissions to use it. For more information see [Encryption of imported models](https://docs.aws.amazon.com/bedrock/latest/userguide/encryption-import-model.html).
#' @param roleArn The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock assumes to perform tasks on your behalf. This role must have permissions to access the Amazon S3 bucket containing your model artifacts and the KMS key (if specified). For more information, see [Setting up an IAM service role for importing models](https://docs.aws.amazon.com/bedrock/latest/userguide/model-import-iam-role.html) in the Amazon Bedrock User Guide.
#' @param modelTags A list of key-value pairs to associate with the custom model resource. You can use these tags to organize and identify your resources.
#' 
#' For more information, see [Tagging resources](https://docs.aws.amazon.com/bedrock/latest/userguide/tagging.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#' @param clientRequestToken A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see [Ensuring idempotency](https://docs.aws.amazon.com/ec2/latest/devguide/ec2-api-idempotency.html).
#'
#' @keywords internal
#'
#' @rdname bedrock_create_custom_model
bedrock_create_custom_model <- function(modelName, modelSourceConfig, modelKmsKeyArn = NULL, roleArn = NULL, modelTags = NULL, clientRequestToken = NULL) {
  op <- new_operation(
    name = "CreateCustomModel",
    http_method = "POST",
    http_path = "/custom-models/create-custom-model",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$create_custom_model_input(modelName = modelName, modelSourceConfig = modelSourceConfig, modelKmsKeyArn = modelKmsKeyArn, roleArn = roleArn, modelTags = modelTags, clientRequestToken = clientRequestToken)
  output <- .bedrock$create_custom_model_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$create_custom_model <- bedrock_create_custom_model

#' Deploys a custom model for on-demand inference in Amazon Bedrock
#'
#' @description
#' 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.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_create_custom_model_deployment/](https://www.paws-r-sdk.com/docs/bedrock_create_custom_model_deployment/) for full documentation.
#'
#' @param modelDeploymentName &#91;required&#93; The name for the custom model deployment. The name must be unique within your Amazon Web Services account and Region.
#' @param modelArn &#91;required&#93; The Amazon Resource Name (ARN) of the custom model to deploy for on-demand inference. The custom model must be in the `Active` state.
#' @param description A description for the custom model deployment to help you identify its purpose.
#' @param tags Tags to assign to the custom model deployment. You can use tags to organize and track your Amazon Web Services resources for cost allocation and management purposes.
#' @param clientRequestToken A unique, case-sensitive identifier to ensure that the operation completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see [Ensuring idempotency](https://docs.aws.amazon.com/bedrock/latest/userguide/).
#'
#' @keywords internal
#'
#' @rdname bedrock_create_custom_model_deployment
bedrock_create_custom_model_deployment <- function(modelDeploymentName, modelArn, description = NULL, tags = NULL, clientRequestToken = NULL) {
  op <- new_operation(
    name = "CreateCustomModelDeployment",
    http_method = "POST",
    http_path = "/model-customization/custom-model-deployments",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$create_custom_model_deployment_input(modelDeploymentName = modelDeploymentName, modelArn = modelArn, description = description, tags = tags, clientRequestToken = clientRequestToken)
  output <- .bedrock$create_custom_model_deployment_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$create_custom_model_deployment <- bedrock_create_custom_model_deployment

#' Creates an evaluation job
#'
#' @description
#' Creates an evaluation job.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_create_evaluation_job/](https://www.paws-r-sdk.com/docs/bedrock_create_evaluation_job/) for full documentation.
#'
#' @param jobName &#91;required&#93; A name for the evaluation job. Names must unique with your Amazon Web Services account, and your account's Amazon Web Services region.
#' @param jobDescription A description of the evaluation job.
#' @param clientRequestToken A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see [Ensuring idempotency](https://docs.aws.amazon.com/ec2/latest/devguide/ec2-api-idempotency.html).
#' @param roleArn &#91;required&#93; The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. To learn more about the required permissions, see [Required permissions for model evaluations](https://docs.aws.amazon.com/bedrock/latest/userguide/model-evaluation-security-service-roles.html).
#' @param customerEncryptionKeyId Specify your customer managed encryption key Amazon Resource Name (ARN) that will be used to encrypt your evaluation job.
#' @param jobTags Tags to attach to the model evaluation job.
#' @param applicationType Specifies whether the evaluation job is for evaluating a model or evaluating a knowledge base (retrieval and response generation).
#' @param evaluationConfig &#91;required&#93; Contains the configuration details of either an automated or human-based evaluation job.
#' @param inferenceConfig &#91;required&#93; Contains the configuration details of the inference model for the evaluation job.
#' 
#' For model evaluation jobs, automated jobs support a single model or [inference profile](https://docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference.html), and jobs that use human workers support two models or inference profiles.
#' @param outputDataConfig &#91;required&#93; Contains the configuration details of the Amazon S3 bucket for storing the results of the evaluation job.
#'
#' @keywords internal
#'
#' @rdname bedrock_create_evaluation_job
bedrock_create_evaluation_job <- function(jobName, jobDescription = NULL, clientRequestToken = NULL, roleArn, customerEncryptionKeyId = NULL, jobTags = NULL, applicationType = NULL, evaluationConfig, inferenceConfig, outputDataConfig) {
  op <- new_operation(
    name = "CreateEvaluationJob",
    http_method = "POST",
    http_path = "/evaluation-jobs",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$create_evaluation_job_input(jobName = jobName, jobDescription = jobDescription, clientRequestToken = clientRequestToken, roleArn = roleArn, customerEncryptionKeyId = customerEncryptionKeyId, jobTags = jobTags, applicationType = applicationType, evaluationConfig = evaluationConfig, inferenceConfig = inferenceConfig, outputDataConfig = outputDataConfig)
  output <- .bedrock$create_evaluation_job_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$create_evaluation_job <- bedrock_create_evaluation_job

#' Request a model access agreement for the specified model
#'
#' @description
#' Request a model access agreement for the specified model.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_create_foundation_model_agreement/](https://www.paws-r-sdk.com/docs/bedrock_create_foundation_model_agreement/) for full documentation.
#'
#' @param offerToken &#91;required&#93; An offer token encapsulates the information for an offer.
#' @param modelId &#91;required&#93; Model Id of the model for the access request.
#'
#' @keywords internal
#'
#' @rdname bedrock_create_foundation_model_agreement
bedrock_create_foundation_model_agreement <- function(offerToken, modelId) {
  op <- new_operation(
    name = "CreateFoundationModelAgreement",
    http_method = "POST",
    http_path = "/create-foundation-model-agreement",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$create_foundation_model_agreement_input(offerToken = offerToken, modelId = modelId)
  output <- .bedrock$create_foundation_model_agreement_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$create_foundation_model_agreement <- bedrock_create_foundation_model_agreement

#' Creates a guardrail to block topics and to implement safeguards for your
#' generative AI applications
#'
#' @description
#' Creates a guardrail to block topics and to implement safeguards for your generative AI applications.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_create_guardrail/](https://www.paws-r-sdk.com/docs/bedrock_create_guardrail/) for full documentation.
#'
#' @param name &#91;required&#93; The name to give the guardrail.
#' @param description A description of the guardrail.
#' @param topicPolicyConfig The topic policies to configure for the guardrail.
#' @param contentPolicyConfig The content filter policies to configure for the guardrail.
#' @param wordPolicyConfig The word policy you configure for the guardrail.
#' @param sensitiveInformationPolicyConfig The sensitive information policy to configure for the guardrail.
#' @param contextualGroundingPolicyConfig The contextual grounding policy configuration used to create a guardrail.
#' @param automatedReasoningPolicyConfig Optional configuration for integrating Automated Reasoning policies with the new guardrail.
#' @param crossRegionConfig The system-defined guardrail profile that you're using with your guardrail. Guardrail profiles define the destination Amazon Web Services Regions where guardrail inference requests can be automatically routed.
#' 
#' For more information, see the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/guardrails-cross-region.html).
#' @param blockedInputMessaging &#91;required&#93; The message to return when the guardrail blocks a prompt.
#' @param blockedOutputsMessaging &#91;required&#93; The message to return when the guardrail blocks a model response.
#' @param kmsKeyId The ARN of the KMS key that you use to encrypt the guardrail.
#' @param tags The tags that you want to attach to the guardrail.
#' @param clientRequestToken A unique, case-sensitive identifier to ensure that the API request completes no more than once. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see [Ensuring idempotency](https://docs.aws.amazon.com/ec2/latest/devguide/ec2-api-idempotency.html) in the *Amazon S3 User Guide*.
#'
#' @keywords internal
#'
#' @rdname bedrock_create_guardrail
bedrock_create_guardrail <- function(name, description = NULL, topicPolicyConfig = NULL, contentPolicyConfig = NULL, wordPolicyConfig = NULL, sensitiveInformationPolicyConfig = NULL, contextualGroundingPolicyConfig = NULL, automatedReasoningPolicyConfig = NULL, crossRegionConfig = NULL, blockedInputMessaging, blockedOutputsMessaging, kmsKeyId = NULL, tags = NULL, clientRequestToken = NULL) {
  op <- new_operation(
    name = "CreateGuardrail",
    http_method = "POST",
    http_path = "/guardrails",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$create_guardrail_input(name = name, description = description, topicPolicyConfig = topicPolicyConfig, contentPolicyConfig = contentPolicyConfig, wordPolicyConfig = wordPolicyConfig, sensitiveInformationPolicyConfig = sensitiveInformationPolicyConfig, contextualGroundingPolicyConfig = contextualGroundingPolicyConfig, automatedReasoningPolicyConfig = automatedReasoningPolicyConfig, crossRegionConfig = crossRegionConfig, blockedInputMessaging = blockedInputMessaging, blockedOutputsMessaging = blockedOutputsMessaging, kmsKeyId = kmsKeyId, tags = tags, clientRequestToken = clientRequestToken)
  output <- .bedrock$create_guardrail_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$create_guardrail <- bedrock_create_guardrail

#' Creates a version of the guardrail
#'
#' @description
#' 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.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_create_guardrail_version/](https://www.paws-r-sdk.com/docs/bedrock_create_guardrail_version/) for full documentation.
#'
#' @param guardrailIdentifier &#91;required&#93; The unique identifier of the guardrail. This can be an ID or the ARN.
#' @param description A description of the guardrail version.
#' @param clientRequestToken A unique, case-sensitive identifier to ensure that the API request completes no more than once. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see [Ensuring idempotency](https://docs.aws.amazon.com/ec2/latest/devguide/ec2-api-idempotency.html) in the *Amazon S3 User Guide*.
#'
#' @keywords internal
#'
#' @rdname bedrock_create_guardrail_version
bedrock_create_guardrail_version <- function(guardrailIdentifier, description = NULL, clientRequestToken = NULL) {
  op <- new_operation(
    name = "CreateGuardrailVersion",
    http_method = "POST",
    http_path = "/guardrails/{guardrailIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$create_guardrail_version_input(guardrailIdentifier = guardrailIdentifier, description = description, clientRequestToken = clientRequestToken)
  output <- .bedrock$create_guardrail_version_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$create_guardrail_version <- bedrock_create_guardrail_version

#' Creates an application inference profile to track metrics and costs when
#' invoking a model
#'
#' @description
#' 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](https://docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference.html). in the Amazon Bedrock User Guide.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_create_inference_profile/](https://www.paws-r-sdk.com/docs/bedrock_create_inference_profile/) for full documentation.
#'
#' @param inferenceProfileName &#91;required&#93; A name for the inference profile.
#' @param description A description for the inference profile.
#' @param clientRequestToken A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see [Ensuring idempotency](https://docs.aws.amazon.com/ec2/latest/devguide/ec2-api-idempotency.html).
#' @param modelSource &#91;required&#93; The foundation model or system-defined inference profile that the inference profile will track metrics and costs for.
#' @param tags An array of objects, each of which contains a tag and its value. For more information, see [Tagging resources](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' @keywords internal
#'
#' @rdname bedrock_create_inference_profile
bedrock_create_inference_profile <- function(inferenceProfileName, description = NULL, clientRequestToken = NULL, modelSource, tags = NULL) {
  op <- new_operation(
    name = "CreateInferenceProfile",
    http_method = "POST",
    http_path = "/inference-profiles",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$create_inference_profile_input(inferenceProfileName = inferenceProfileName, description = description, clientRequestToken = clientRequestToken, modelSource = modelSource, tags = tags)
  output <- .bedrock$create_inference_profile_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$create_inference_profile <- bedrock_create_inference_profile

#' Creates an endpoint for a model from Amazon Bedrock Marketplace
#'
#' @description
#' Creates an endpoint for a model from Amazon Bedrock Marketplace. The endpoint is hosted by Amazon SageMaker.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_create_marketplace_model_endpoint/](https://www.paws-r-sdk.com/docs/bedrock_create_marketplace_model_endpoint/) for full documentation.
#'
#' @param modelSourceIdentifier &#91;required&#93; The ARN of the model from Amazon Bedrock Marketplace that you want to deploy to the endpoint.
#' @param endpointConfig &#91;required&#93; The configuration for the endpoint, including the number and type of instances to use.
#' @param acceptEula Indicates whether you accept the end-user license agreement (EULA) for the model. Set to `true` to accept the EULA.
#' @param endpointName &#91;required&#93; The name of the endpoint. This name must be unique within your Amazon Web Services account and region.
#' @param clientRequestToken A unique, case-sensitive identifier that you provide to ensure the idempotency of the request. This token is listed as not required because Amazon Web Services SDKs automatically generate it for you and set this parameter. If you're not using the Amazon Web Services SDK or the CLI, you must provide this token or the action will fail.
#' @param tags An array of key-value pairs to apply to the underlying Amazon SageMaker endpoint. You can use these tags to organize and identify your Amazon Web Services resources.
#'
#' @keywords internal
#'
#' @rdname bedrock_create_marketplace_model_endpoint
bedrock_create_marketplace_model_endpoint <- function(modelSourceIdentifier, endpointConfig, acceptEula = NULL, endpointName, clientRequestToken = NULL, tags = NULL) {
  op <- new_operation(
    name = "CreateMarketplaceModelEndpoint",
    http_method = "POST",
    http_path = "/marketplace-model/endpoints",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$create_marketplace_model_endpoint_input(modelSourceIdentifier = modelSourceIdentifier, endpointConfig = endpointConfig, acceptEula = acceptEula, endpointName = endpointName, clientRequestToken = clientRequestToken, tags = tags)
  output <- .bedrock$create_marketplace_model_endpoint_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$create_marketplace_model_endpoint <- bedrock_create_marketplace_model_endpoint

#' Copies a model to another region so that it can be used there
#'
#' @description
#' 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](https://docs.aws.amazon.com/bedrock/latest/userguide/copy-model.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_create_model_copy_job/](https://www.paws-r-sdk.com/docs/bedrock_create_model_copy_job/) for full documentation.
#'
#' @param sourceModelArn &#91;required&#93; The Amazon Resource Name (ARN) of the model to be copied.
#' @param targetModelName &#91;required&#93; A name for the copied model.
#' @param modelKmsKeyId The ARN of the KMS key that you use to encrypt the model copy.
#' @param targetModelTags Tags to associate with the target model. For more information, see [Tag resources](https://docs.aws.amazon.com/bedrock/latest/userguide/tagging.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#' @param clientRequestToken A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see [Ensuring idempotency](https://docs.aws.amazon.com/ec2/latest/devguide/ec2-api-idempotency.html).
#'
#' @keywords internal
#'
#' @rdname bedrock_create_model_copy_job
bedrock_create_model_copy_job <- function(sourceModelArn, targetModelName, modelKmsKeyId = NULL, targetModelTags = NULL, clientRequestToken = NULL) {
  op <- new_operation(
    name = "CreateModelCopyJob",
    http_method = "POST",
    http_path = "/model-copy-jobs",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$create_model_copy_job_input(sourceModelArn = sourceModelArn, targetModelName = targetModelName, modelKmsKeyId = modelKmsKeyId, targetModelTags = targetModelTags, clientRequestToken = clientRequestToken)
  output <- .bedrock$create_model_copy_job_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$create_model_copy_job <- bedrock_create_model_copy_job

#' Creates a fine-tuning job to customize a base model
#'
#' @description
#' Creates a fine-tuning job to customize a base model.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_create_model_customization_job/](https://www.paws-r-sdk.com/docs/bedrock_create_model_customization_job/) for full documentation.
#'
#' @param jobName &#91;required&#93; A name for the fine-tuning job.
#' @param customModelName &#91;required&#93; A name for the resulting custom model.
#' @param roleArn &#91;required&#93; The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. For example, during model training, Amazon Bedrock needs your permission to read input data from an S3 bucket, write model artifacts to an S3 bucket. To pass this role to Amazon Bedrock, the caller of this API must have the `iam:PassRole` permission.
#' @param clientRequestToken A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see [Ensuring idempotency](https://docs.aws.amazon.com/ec2/latest/devguide/ec2-api-idempotency.html).
#' @param baseModelIdentifier &#91;required&#93; Name of the base model.
#' @param customizationType The customization type.
#' @param customModelKmsKeyId The custom model is encrypted at rest using this key.
#' @param jobTags Tags to attach to the job.
#' @param customModelTags Tags to attach to the resulting custom model.
#' @param trainingDataConfig &#91;required&#93; Information about the training dataset.
#' @param validationDataConfig Information about the validation dataset.
#' @param outputDataConfig &#91;required&#93; S3 location for the output data.
#' @param hyperParameters Parameters related to tuning the model. For details on the format for different models, see [Custom model hyperparameters](https://docs.aws.amazon.com/bedrock/latest/userguide/custom-models-hp.html).
#' @param vpcConfig The configuration of the Virtual Private Cloud (VPC) that contains the resources that you're using for this job. For more information, see [Protect your model customization jobs using a VPC](https://docs.aws.amazon.com/bedrock/latest/userguide/).
#' @param customizationConfig The customization configuration for the model customization job.
#'
#' @keywords internal
#'
#' @rdname bedrock_create_model_customization_job
bedrock_create_model_customization_job <- function(jobName, customModelName, roleArn, clientRequestToken = NULL, baseModelIdentifier, customizationType = NULL, customModelKmsKeyId = NULL, jobTags = NULL, customModelTags = NULL, trainingDataConfig, validationDataConfig = NULL, outputDataConfig, hyperParameters = NULL, vpcConfig = NULL, customizationConfig = NULL) {
  op <- new_operation(
    name = "CreateModelCustomizationJob",
    http_method = "POST",
    http_path = "/model-customization-jobs",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$create_model_customization_job_input(jobName = jobName, customModelName = customModelName, roleArn = roleArn, clientRequestToken = clientRequestToken, baseModelIdentifier = baseModelIdentifier, customizationType = customizationType, customModelKmsKeyId = customModelKmsKeyId, jobTags = jobTags, customModelTags = customModelTags, trainingDataConfig = trainingDataConfig, validationDataConfig = validationDataConfig, outputDataConfig = outputDataConfig, hyperParameters = hyperParameters, vpcConfig = vpcConfig, customizationConfig = customizationConfig)
  output <- .bedrock$create_model_customization_job_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$create_model_customization_job <- bedrock_create_model_customization_job

#' Creates a model import job to import model that you have customized in
#' other environments, such as Amazon SageMaker
#'
#' @description
#' 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](https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-import-model.html)
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_create_model_import_job/](https://www.paws-r-sdk.com/docs/bedrock_create_model_import_job/) for full documentation.
#'
#' @param jobName &#91;required&#93; The name of the import job.
#' @param importedModelName &#91;required&#93; The name of the imported model.
#' @param roleArn &#91;required&#93; The Amazon Resource Name (ARN) of the model import job.
#' @param modelDataSource &#91;required&#93; The data source for the imported model.
#' @param jobTags Tags to attach to this import job.
#' @param importedModelTags Tags to attach to the imported model.
#' @param clientRequestToken A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see [Ensuring idempotency](https://docs.aws.amazon.com/ec2/latest/devguide/ec2-api-idempotency.html).
#' @param vpcConfig VPC configuration parameters for the private Virtual Private Cloud (VPC) that contains the resources you are using for the import job.
#' @param importedModelKmsKeyId The imported model is encrypted at rest using this key.
#'
#' @keywords internal
#'
#' @rdname bedrock_create_model_import_job
bedrock_create_model_import_job <- function(jobName, importedModelName, roleArn, modelDataSource, jobTags = NULL, importedModelTags = NULL, clientRequestToken = NULL, vpcConfig = NULL, importedModelKmsKeyId = NULL) {
  op <- new_operation(
    name = "CreateModelImportJob",
    http_method = "POST",
    http_path = "/model-import-jobs",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$create_model_import_job_input(jobName = jobName, importedModelName = importedModelName, roleArn = roleArn, modelDataSource = modelDataSource, jobTags = jobTags, importedModelTags = importedModelTags, clientRequestToken = clientRequestToken, vpcConfig = vpcConfig, importedModelKmsKeyId = importedModelKmsKeyId)
  output <- .bedrock$create_model_import_job_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$create_model_import_job <- bedrock_create_model_import_job

#' Creates a batch inference job to invoke a model on multiple prompts
#'
#' @description
#' Creates a batch inference job to invoke a model on multiple prompts. Format your data according to [Format your inference data](https://docs.aws.amazon.com/bedrock/latest/userguide/batch-inference-data.html) and upload it to an Amazon S3 bucket. For more information, see [Process multiple prompts with batch inference](https://docs.aws.amazon.com/bedrock/latest/userguide/batch-inference.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_create_model_invocation_job/](https://www.paws-r-sdk.com/docs/bedrock_create_model_invocation_job/) for full documentation.
#'
#' @param jobName &#91;required&#93; A name to give the batch inference job.
#' @param roleArn &#91;required&#93; The Amazon Resource Name (ARN) of the service role with permissions to carry out and manage batch inference. You can use the console to create a default service role or follow the steps at [Create a service role for batch inference](https://docs.aws.amazon.com/bedrock/latest/userguide/batch-iam-sr.html).
#' @param clientRequestToken A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see [Ensuring idempotency](https://docs.aws.amazon.com/ec2/latest/devguide/ec2-api-idempotency.html).
#' @param modelId &#91;required&#93; The unique identifier of the foundation model to use for the batch inference job.
#' @param inputDataConfig &#91;required&#93; Details about the location of the input to the batch inference job.
#' @param outputDataConfig &#91;required&#93; Details about the location of the output of the batch inference job.
#' @param vpcConfig The configuration of the Virtual Private Cloud (VPC) for the data in the batch inference job. For more information, see [Protect batch inference jobs using a VPC](https://docs.aws.amazon.com/bedrock/latest/userguide/batch-vpc.html).
#' @param timeoutDurationInHours The number of hours after which to force the batch inference job to time out.
#' @param tags Any tags to associate with the batch inference job. For more information, see [Tagging Amazon Bedrock resources](https://docs.aws.amazon.com/bedrock/latest/userguide/tagging.html).
#' @param modelInvocationType The invocation endpoint for ModelInvocationJob
#'
#' @keywords internal
#'
#' @rdname bedrock_create_model_invocation_job
bedrock_create_model_invocation_job <- function(jobName, roleArn, clientRequestToken = NULL, modelId, inputDataConfig, outputDataConfig, vpcConfig = NULL, timeoutDurationInHours = NULL, tags = NULL, modelInvocationType = NULL) {
  op <- new_operation(
    name = "CreateModelInvocationJob",
    http_method = "POST",
    http_path = "/model-invocation-job",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$create_model_invocation_job_input(jobName = jobName, roleArn = roleArn, clientRequestToken = clientRequestToken, modelId = modelId, inputDataConfig = inputDataConfig, outputDataConfig = outputDataConfig, vpcConfig = vpcConfig, timeoutDurationInHours = timeoutDurationInHours, tags = tags, modelInvocationType = modelInvocationType)
  output <- .bedrock$create_model_invocation_job_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$create_model_invocation_job <- bedrock_create_model_invocation_job

#' Creates a prompt router that manages the routing of requests between
#' multiple foundation models based on the routing criteria
#'
#' @description
#' Creates a prompt router that manages the routing of requests between multiple foundation models based on the routing criteria.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_create_prompt_router/](https://www.paws-r-sdk.com/docs/bedrock_create_prompt_router/) for full documentation.
#'
#' @param clientRequestToken A unique, case-sensitive identifier that you provide to ensure idempotency of your requests. If not specified, the Amazon Web Services SDK automatically generates one for you.
#' @param promptRouterName &#91;required&#93; The name of the prompt router. The name must be unique within your Amazon Web Services account in the current region.
#' @param models &#91;required&#93; A list of foundation models that the prompt router can route requests to. At least one model must be specified.
#' @param description An optional description of the prompt router to help identify its purpose.
#' @param routingCriteria &#91;required&#93; The criteria, which is the response quality difference, used to determine how incoming requests are routed to different models.
#' @param fallbackModel &#91;required&#93; The default model to use when the routing criteria is not met.
#' @param tags An array of key-value pairs to apply to this resource as tags. You can use tags to categorize and manage your Amazon Web Services resources.
#'
#' @keywords internal
#'
#' @rdname bedrock_create_prompt_router
bedrock_create_prompt_router <- function(clientRequestToken = NULL, promptRouterName, models, description = NULL, routingCriteria, fallbackModel, tags = NULL) {
  op <- new_operation(
    name = "CreatePromptRouter",
    http_method = "POST",
    http_path = "/prompt-routers",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$create_prompt_router_input(clientRequestToken = clientRequestToken, promptRouterName = promptRouterName, models = models, description = description, routingCriteria = routingCriteria, fallbackModel = fallbackModel, tags = tags)
  output <- .bedrock$create_prompt_router_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$create_prompt_router <- bedrock_create_prompt_router

#' Creates dedicated throughput for a base or custom model with the model
#' units and for the duration that you specify
#'
#' @description
#' 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](https://aws.amazon.com/bedrock/pricing/). For more information, see [Provisioned Throughput](https://docs.aws.amazon.com/bedrock/latest/userguide/prov-throughput.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_create_provisioned_model_throughput/](https://www.paws-r-sdk.com/docs/bedrock_create_provisioned_model_throughput/) for full documentation.
#'
#' @param clientRequestToken A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see [Ensuring idempotency](https://docs.aws.amazon.com/ec2/latest/devguide/ec2-api-idempotency.html) in the Amazon S3 User Guide.
#' @param modelUnits &#91;required&#93; Number of model units to allocate. A model unit delivers a specific throughput level for the specified model. The throughput level of a model unit specifies the total number of input and output tokens that it can process and generate within a span of one minute. By default, your account has no model units for purchasing Provisioned Throughputs with commitment. You must first visit the Amazon Web Services support center to request MUs.
#' 
#' For model unit quotas, see [Provisioned Throughput quotas](https://docs.aws.amazon.com/bedrock/latest/userguide/quotas.html#prov-thru-quotas) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#' 
#' For more information about what an MU specifies, contact your Amazon Web Services account manager.
#' @param provisionedModelName &#91;required&#93; The name for this Provisioned Throughput.
#' @param modelId &#91;required&#93; The Amazon Resource Name (ARN) or name of the model to associate with this Provisioned Throughput. For a list of models for which you can purchase Provisioned Throughput, see [Amazon Bedrock model IDs for purchasing Provisioned Throughput](https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html#prov-throughput-models) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#' @param commitmentDuration The commitment duration requested for the Provisioned Throughput. Billing occurs hourly and is discounted for longer commitment terms. To request a no-commit Provisioned Throughput, omit this field.
#' 
#' Custom models support all levels of commitment. To see which base models support no commitment, see [Supported regions and models for Provisioned Throughput](https://docs.aws.amazon.com/bedrock/latest/userguide/) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html)
#' @param tags Tags to associate with this Provisioned Throughput.
#'
#' @keywords internal
#'
#' @rdname bedrock_create_provisioned_model_throughput
bedrock_create_provisioned_model_throughput <- function(clientRequestToken = NULL, modelUnits, provisionedModelName, modelId, commitmentDuration = NULL, tags = NULL) {
  op <- new_operation(
    name = "CreateProvisionedModelThroughput",
    http_method = "POST",
    http_path = "/provisioned-model-throughput",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$create_provisioned_model_throughput_input(clientRequestToken = clientRequestToken, modelUnits = modelUnits, provisionedModelName = provisionedModelName, modelId = modelId, commitmentDuration = commitmentDuration, tags = tags)
  output <- .bedrock$create_provisioned_model_throughput_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$create_provisioned_model_throughput <- bedrock_create_provisioned_model_throughput

#' Deletes an Automated Reasoning policy or policy version
#'
#' @description
#' 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.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_delete_automated_reasoning_policy/](https://www.paws-r-sdk.com/docs/bedrock_delete_automated_reasoning_policy/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy to delete.
#' @param force Specifies whether to force delete the automated reasoning policy even if it has active resources. When `false`, Amazon Bedrock validates if all artifacts have been deleted (e.g. policy version, test case, test result) for a policy before deletion. When `true`, Amazon Bedrock will delete the policy and all its artifacts without validation. Default is `false`.
#'
#' @keywords internal
#'
#' @rdname bedrock_delete_automated_reasoning_policy
bedrock_delete_automated_reasoning_policy <- function(policyArn, force = NULL) {
  op <- new_operation(
    name = "DeleteAutomatedReasoningPolicy",
    http_method = "DELETE",
    http_path = "/automated-reasoning-policies/{policyArn}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$delete_automated_reasoning_policy_input(policyArn = policyArn, force = force)
  output <- .bedrock$delete_automated_reasoning_policy_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$delete_automated_reasoning_policy <- bedrock_delete_automated_reasoning_policy

#' Deletes an Automated Reasoning policy build workflow and its associated
#' artifacts
#'
#' @description
#' Deletes an Automated Reasoning policy build workflow and its associated artifacts. This permanently removes the workflow history and any generated assets.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_delete_automated_reasoning_policy_build_workflow/](https://www.paws-r-sdk.com/docs/bedrock_delete_automated_reasoning_policy_build_workflow/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy whose build workflow you want to delete.
#' @param buildWorkflowId &#91;required&#93; The unique identifier of the build workflow to delete.
#' @param lastUpdatedAt &#91;required&#93; The timestamp when the build workflow was last updated. This is used for optimistic concurrency control to prevent accidental deletion of workflows that have been modified.
#'
#' @keywords internal
#'
#' @rdname bedrock_delete_automated_reasoning_policy_build_workflow
bedrock_delete_automated_reasoning_policy_build_workflow <- function(policyArn, buildWorkflowId, lastUpdatedAt) {
  op <- new_operation(
    name = "DeleteAutomatedReasoningPolicyBuildWorkflow",
    http_method = "DELETE",
    http_path = "/automated-reasoning-policies/{policyArn}/build-workflows/{buildWorkflowId}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$delete_automated_reasoning_policy_build_workflow_input(policyArn = policyArn, buildWorkflowId = buildWorkflowId, lastUpdatedAt = lastUpdatedAt)
  output <- .bedrock$delete_automated_reasoning_policy_build_workflow_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$delete_automated_reasoning_policy_build_workflow <- bedrock_delete_automated_reasoning_policy_build_workflow

#' Deletes an Automated Reasoning policy test
#'
#' @description
#' Deletes an Automated Reasoning policy test. This operation is idempotent; if you delete a test more than once, each call succeeds.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_delete_automated_reasoning_policy_test_case/](https://www.paws-r-sdk.com/docs/bedrock_delete_automated_reasoning_policy_test_case/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy that contains the test.
#' @param testCaseId &#91;required&#93; The unique identifier of the test to delete.
#' @param lastUpdatedAt &#91;required&#93; The timestamp when the test was last updated. This is used as a concurrency token to prevent conflicting modifications.
#'
#' @keywords internal
#'
#' @rdname bedrock_delete_automated_reasoning_policy_test_case
bedrock_delete_automated_reasoning_policy_test_case <- function(policyArn, testCaseId, lastUpdatedAt) {
  op <- new_operation(
    name = "DeleteAutomatedReasoningPolicyTestCase",
    http_method = "DELETE",
    http_path = "/automated-reasoning-policies/{policyArn}/test-cases/{testCaseId}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$delete_automated_reasoning_policy_test_case_input(policyArn = policyArn, testCaseId = testCaseId, lastUpdatedAt = lastUpdatedAt)
  output <- .bedrock$delete_automated_reasoning_policy_test_case_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$delete_automated_reasoning_policy_test_case <- bedrock_delete_automated_reasoning_policy_test_case

#' Deletes a custom model that you created earlier
#'
#' @description
#' Deletes a custom model that you created earlier. For more information, see [Custom models](https://docs.aws.amazon.com/bedrock/latest/userguide/custom-models.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_delete_custom_model/](https://www.paws-r-sdk.com/docs/bedrock_delete_custom_model/) for full documentation.
#'
#' @param modelIdentifier &#91;required&#93; Name of the model to delete.
#'
#' @keywords internal
#'
#' @rdname bedrock_delete_custom_model
bedrock_delete_custom_model <- function(modelIdentifier) {
  op <- new_operation(
    name = "DeleteCustomModel",
    http_method = "DELETE",
    http_path = "/custom-models/{modelIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$delete_custom_model_input(modelIdentifier = modelIdentifier)
  output <- .bedrock$delete_custom_model_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$delete_custom_model <- bedrock_delete_custom_model

#' Deletes a custom model deployment
#'
#' @description
#' 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.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_delete_custom_model_deployment/](https://www.paws-r-sdk.com/docs/bedrock_delete_custom_model_deployment/) for full documentation.
#'
#' @param customModelDeploymentIdentifier &#91;required&#93; The Amazon Resource Name (ARN) or name of the custom model deployment to delete.
#'
#' @keywords internal
#'
#' @rdname bedrock_delete_custom_model_deployment
bedrock_delete_custom_model_deployment <- function(customModelDeploymentIdentifier) {
  op <- new_operation(
    name = "DeleteCustomModelDeployment",
    http_method = "DELETE",
    http_path = "/model-customization/custom-model-deployments/{customModelDeploymentIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$delete_custom_model_deployment_input(customModelDeploymentIdentifier = customModelDeploymentIdentifier)
  output <- .bedrock$delete_custom_model_deployment_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$delete_custom_model_deployment <- bedrock_delete_custom_model_deployment

#' Deletes the account-level enforced guardrail configuration
#'
#' @description
#' Deletes the account-level enforced guardrail configuration.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_delete_enforced_guardrail_configuration/](https://www.paws-r-sdk.com/docs/bedrock_delete_enforced_guardrail_configuration/) for full documentation.
#'
#' @param configId &#91;required&#93; Unique ID for the account enforced configuration.
#'
#' @keywords internal
#'
#' @rdname bedrock_delete_enforced_guardrail_configuration
bedrock_delete_enforced_guardrail_configuration <- function(configId) {
  op <- new_operation(
    name = "DeleteEnforcedGuardrailConfiguration",
    http_method = "DELETE",
    http_path = "/enforcedGuardrailsConfiguration/{configId}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$delete_enforced_guardrail_configuration_input(configId = configId)
  output <- .bedrock$delete_enforced_guardrail_configuration_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$delete_enforced_guardrail_configuration <- bedrock_delete_enforced_guardrail_configuration

#' Delete the model access agreement for the specified model
#'
#' @description
#' Delete the model access agreement for the specified model.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_delete_foundation_model_agreement/](https://www.paws-r-sdk.com/docs/bedrock_delete_foundation_model_agreement/) for full documentation.
#'
#' @param modelId &#91;required&#93; Model Id of the model access to delete.
#'
#' @keywords internal
#'
#' @rdname bedrock_delete_foundation_model_agreement
bedrock_delete_foundation_model_agreement <- function(modelId) {
  op <- new_operation(
    name = "DeleteFoundationModelAgreement",
    http_method = "POST",
    http_path = "/delete-foundation-model-agreement",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$delete_foundation_model_agreement_input(modelId = modelId)
  output <- .bedrock$delete_foundation_model_agreement_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$delete_foundation_model_agreement <- bedrock_delete_foundation_model_agreement

#' Deletes a guardrail
#'
#' @description
#' Deletes a guardrail.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_delete_guardrail/](https://www.paws-r-sdk.com/docs/bedrock_delete_guardrail/) for full documentation.
#'
#' @param guardrailIdentifier &#91;required&#93; The unique identifier of the guardrail. This can be an ID or the ARN.
#' @param guardrailVersion The version of the guardrail.
#'
#' @keywords internal
#'
#' @rdname bedrock_delete_guardrail
bedrock_delete_guardrail <- function(guardrailIdentifier, guardrailVersion = NULL) {
  op <- new_operation(
    name = "DeleteGuardrail",
    http_method = "DELETE",
    http_path = "/guardrails/{guardrailIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$delete_guardrail_input(guardrailIdentifier = guardrailIdentifier, guardrailVersion = guardrailVersion)
  output <- .bedrock$delete_guardrail_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$delete_guardrail <- bedrock_delete_guardrail

#' Deletes a custom model that you imported earlier
#'
#' @description
#' Deletes a custom model that you imported earlier. For more information, see [Import a customized model](https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-import-model.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_delete_imported_model/](https://www.paws-r-sdk.com/docs/bedrock_delete_imported_model/) for full documentation.
#'
#' @param modelIdentifier &#91;required&#93; Name of the imported model to delete.
#'
#' @keywords internal
#'
#' @rdname bedrock_delete_imported_model
bedrock_delete_imported_model <- function(modelIdentifier) {
  op <- new_operation(
    name = "DeleteImportedModel",
    http_method = "DELETE",
    http_path = "/imported-models/{modelIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$delete_imported_model_input(modelIdentifier = modelIdentifier)
  output <- .bedrock$delete_imported_model_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$delete_imported_model <- bedrock_delete_imported_model

#' Deletes an application inference profile
#'
#' @description
#' Deletes an application inference profile. For more information, see [Increase throughput and resilience with cross-region inference in Amazon Bedrock](https://docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference.html). in the Amazon Bedrock User Guide.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_delete_inference_profile/](https://www.paws-r-sdk.com/docs/bedrock_delete_inference_profile/) for full documentation.
#'
#' @param inferenceProfileIdentifier &#91;required&#93; The Amazon Resource Name (ARN) or ID of the application inference profile to delete.
#'
#' @keywords internal
#'
#' @rdname bedrock_delete_inference_profile
bedrock_delete_inference_profile <- function(inferenceProfileIdentifier) {
  op <- new_operation(
    name = "DeleteInferenceProfile",
    http_method = "DELETE",
    http_path = "/inference-profiles/{inferenceProfileIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$delete_inference_profile_input(inferenceProfileIdentifier = inferenceProfileIdentifier)
  output <- .bedrock$delete_inference_profile_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$delete_inference_profile <- bedrock_delete_inference_profile

#' Deletes an endpoint for a model from Amazon Bedrock Marketplace
#'
#' @description
#' Deletes an endpoint for a model from Amazon Bedrock Marketplace.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_delete_marketplace_model_endpoint/](https://www.paws-r-sdk.com/docs/bedrock_delete_marketplace_model_endpoint/) for full documentation.
#'
#' @param endpointArn &#91;required&#93; The Amazon Resource Name (ARN) of the endpoint you want to delete.
#'
#' @keywords internal
#'
#' @rdname bedrock_delete_marketplace_model_endpoint
bedrock_delete_marketplace_model_endpoint <- function(endpointArn) {
  op <- new_operation(
    name = "DeleteMarketplaceModelEndpoint",
    http_method = "DELETE",
    http_path = "/marketplace-model/endpoints/{endpointArn}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$delete_marketplace_model_endpoint_input(endpointArn = endpointArn)
  output <- .bedrock$delete_marketplace_model_endpoint_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$delete_marketplace_model_endpoint <- bedrock_delete_marketplace_model_endpoint

#' Delete the invocation logging
#'
#' @description
#' Delete the invocation logging.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_delete_model_invocation_logging_configuration/](https://www.paws-r-sdk.com/docs/bedrock_delete_model_invocation_logging_configuration/) for full documentation.
#'

#'
#' @keywords internal
#'
#' @rdname bedrock_delete_model_invocation_logging_configuration
bedrock_delete_model_invocation_logging_configuration <- function() {
  op <- new_operation(
    name = "DeleteModelInvocationLoggingConfiguration",
    http_method = "DELETE",
    http_path = "/logging/modelinvocations",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$delete_model_invocation_logging_configuration_input()
  output <- .bedrock$delete_model_invocation_logging_configuration_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$delete_model_invocation_logging_configuration <- bedrock_delete_model_invocation_logging_configuration

#' Deletes a specified prompt router
#'
#' @description
#' Deletes a specified prompt router. This action cannot be undone.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_delete_prompt_router/](https://www.paws-r-sdk.com/docs/bedrock_delete_prompt_router/) for full documentation.
#'
#' @param promptRouterArn &#91;required&#93; The Amazon Resource Name (ARN) of the prompt router to delete.
#'
#' @keywords internal
#'
#' @rdname bedrock_delete_prompt_router
bedrock_delete_prompt_router <- function(promptRouterArn) {
  op <- new_operation(
    name = "DeletePromptRouter",
    http_method = "DELETE",
    http_path = "/prompt-routers/{promptRouterArn}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$delete_prompt_router_input(promptRouterArn = promptRouterArn)
  output <- .bedrock$delete_prompt_router_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$delete_prompt_router <- bedrock_delete_prompt_router

#' Deletes a Provisioned Throughput
#'
#' @description
#' Deletes a Provisioned Throughput. You can't delete a Provisioned Throughput before the commitment term is over. For more information, see [Provisioned Throughput](https://docs.aws.amazon.com/bedrock/latest/userguide/prov-throughput.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_delete_provisioned_model_throughput/](https://www.paws-r-sdk.com/docs/bedrock_delete_provisioned_model_throughput/) for full documentation.
#'
#' @param provisionedModelId &#91;required&#93; The Amazon Resource Name (ARN) or name of the Provisioned Throughput.
#'
#' @keywords internal
#'
#' @rdname bedrock_delete_provisioned_model_throughput
bedrock_delete_provisioned_model_throughput <- function(provisionedModelId) {
  op <- new_operation(
    name = "DeleteProvisionedModelThroughput",
    http_method = "DELETE",
    http_path = "/provisioned-model-throughput/{provisionedModelId}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$delete_provisioned_model_throughput_input(provisionedModelId = provisionedModelId)
  output <- .bedrock$delete_provisioned_model_throughput_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$delete_provisioned_model_throughput <- bedrock_delete_provisioned_model_throughput

#' Deletes a previously created Bedrock resource policy
#'
#' @description
#' Deletes a previously created Bedrock resource policy.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_delete_resource_policy/](https://www.paws-r-sdk.com/docs/bedrock_delete_resource_policy/) for full documentation.
#'
#' @param resourceArn &#91;required&#93; The ARN of the Bedrock resource to which this resource policy applies.
#'
#' @keywords internal
#'
#' @rdname bedrock_delete_resource_policy
bedrock_delete_resource_policy <- function(resourceArn) {
  op <- new_operation(
    name = "DeleteResourcePolicy",
    http_method = "DELETE",
    http_path = "/resource-policy/{resourceArn}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$delete_resource_policy_input(resourceArn = resourceArn)
  output <- .bedrock$delete_resource_policy_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$delete_resource_policy <- bedrock_delete_resource_policy

#' Deregisters an endpoint for a model from Amazon Bedrock Marketplace
#'
#' @description
#' 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.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_deregister_marketplace_model_endpoint/](https://www.paws-r-sdk.com/docs/bedrock_deregister_marketplace_model_endpoint/) for full documentation.
#'
#' @param endpointArn &#91;required&#93; The Amazon Resource Name (ARN) of the endpoint you want to deregister.
#'
#' @keywords internal
#'
#' @rdname bedrock_deregister_marketplace_model_endpoint
bedrock_deregister_marketplace_model_endpoint <- function(endpointArn) {
  op <- new_operation(
    name = "DeregisterMarketplaceModelEndpoint",
    http_method = "DELETE",
    http_path = "/marketplace-model/endpoints/{endpointArn}/registration",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$deregister_marketplace_model_endpoint_input(endpointArn = endpointArn)
  output <- .bedrock$deregister_marketplace_model_endpoint_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$deregister_marketplace_model_endpoint <- bedrock_deregister_marketplace_model_endpoint

#' Exports the policy definition for an Automated Reasoning policy version
#'
#' @description
#' 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.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_export_automated_reasoning_policy_version/](https://www.paws-r-sdk.com/docs/bedrock_export_automated_reasoning_policy_version/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy to export. Can be either the unversioned ARN for the draft policy or a versioned ARN for a specific policy version.
#'
#' @keywords internal
#'
#' @rdname bedrock_export_automated_reasoning_policy_version
bedrock_export_automated_reasoning_policy_version <- function(policyArn) {
  op <- new_operation(
    name = "ExportAutomatedReasoningPolicyVersion",
    http_method = "GET",
    http_path = "/automated-reasoning-policies/{policyArn}/export",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$export_automated_reasoning_policy_version_input(policyArn = policyArn)
  output <- .bedrock$export_automated_reasoning_policy_version_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$export_automated_reasoning_policy_version <- bedrock_export_automated_reasoning_policy_version

#' Retrieves the details and status of an advanced prompt optimization job
#'
#' @description
#' Retrieves the details and status of an advanced prompt optimization job.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_advanced_prompt_optimization_job/](https://www.paws-r-sdk.com/docs/bedrock_get_advanced_prompt_optimization_job/) for full documentation.
#'
#' @param jobIdentifier &#91;required&#93; ARN or ID of the advanced prompt optimization job.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_advanced_prompt_optimization_job
bedrock_get_advanced_prompt_optimization_job <- function(jobIdentifier) {
  op <- new_operation(
    name = "GetAdvancedPromptOptimizationJob",
    http_method = "GET",
    http_path = "/advanced-prompt-optimization-jobs/{jobIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_advanced_prompt_optimization_job_input(jobIdentifier = jobIdentifier)
  output <- .bedrock$get_advanced_prompt_optimization_job_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_advanced_prompt_optimization_job <- bedrock_get_advanced_prompt_optimization_job

#' Retrieves details about an Automated Reasoning policy or policy version
#'
#' @description
#' Retrieves details about an Automated Reasoning policy or policy version. Returns information including the policy definition, metadata, and timestamps.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_automated_reasoning_policy/](https://www.paws-r-sdk.com/docs/bedrock_get_automated_reasoning_policy/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy to retrieve. Can be either the unversioned ARN for the draft policy or an ARN for a specific policy version.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_automated_reasoning_policy
bedrock_get_automated_reasoning_policy <- function(policyArn) {
  op <- new_operation(
    name = "GetAutomatedReasoningPolicy",
    http_method = "GET",
    http_path = "/automated-reasoning-policies/{policyArn}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_automated_reasoning_policy_input(policyArn = policyArn)
  output <- .bedrock$get_automated_reasoning_policy_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_automated_reasoning_policy <- bedrock_get_automated_reasoning_policy

#' Retrieves the current annotations for an Automated Reasoning policy
#' build workflow
#'
#' @description
#' 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.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_automated_reasoning_policy_annotations/](https://www.paws-r-sdk.com/docs/bedrock_get_automated_reasoning_policy_annotations/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy whose annotations you want to retrieve.
#' @param buildWorkflowId &#91;required&#93; The unique identifier of the build workflow whose annotations you want to retrieve.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_automated_reasoning_policy_annotations
bedrock_get_automated_reasoning_policy_annotations <- function(policyArn, buildWorkflowId) {
  op <- new_operation(
    name = "GetAutomatedReasoningPolicyAnnotations",
    http_method = "GET",
    http_path = "/automated-reasoning-policies/{policyArn}/build-workflows/{buildWorkflowId}/annotations",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_automated_reasoning_policy_annotations_input(policyArn = policyArn, buildWorkflowId = buildWorkflowId)
  output <- .bedrock$get_automated_reasoning_policy_annotations_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_automated_reasoning_policy_annotations <- bedrock_get_automated_reasoning_policy_annotations

#' Retrieves detailed information about an Automated Reasoning policy build
#' workflow, including its status, configuration, and metadata
#'
#' @description
#' Retrieves detailed information about an Automated Reasoning policy build workflow, including its status, configuration, and metadata.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_automated_reasoning_policy_build_workflow/](https://www.paws-r-sdk.com/docs/bedrock_get_automated_reasoning_policy_build_workflow/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy whose build workflow you want to retrieve.
#' @param buildWorkflowId &#91;required&#93; The unique identifier of the build workflow to retrieve.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_automated_reasoning_policy_build_workflow
bedrock_get_automated_reasoning_policy_build_workflow <- function(policyArn, buildWorkflowId) {
  op <- new_operation(
    name = "GetAutomatedReasoningPolicyBuildWorkflow",
    http_method = "GET",
    http_path = "/automated-reasoning-policies/{policyArn}/build-workflows/{buildWorkflowId}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_automated_reasoning_policy_build_workflow_input(policyArn = policyArn, buildWorkflowId = buildWorkflowId)
  output <- .bedrock$get_automated_reasoning_policy_build_workflow_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_automated_reasoning_policy_build_workflow <- bedrock_get_automated_reasoning_policy_build_workflow

#' Retrieves the resulting assets from a completed Automated Reasoning
#' policy build workflow, including build logs, quality reports, and
#' generated policy artifacts
#'
#' @description
#' Retrieves the resulting assets from a completed Automated Reasoning policy build workflow, including build logs, quality reports, and generated policy artifacts.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_automated_reasoning_policy_build_workflow_result_assets/](https://www.paws-r-sdk.com/docs/bedrock_get_automated_reasoning_policy_build_workflow_result_assets/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy whose build workflow assets you want to retrieve.
#' @param buildWorkflowId &#91;required&#93; The unique identifier of the build workflow whose result assets you want to retrieve.
#' @param assetType &#91;required&#93; The type of asset to retrieve (e.g., BUILD_LOG, QUALITY_REPORT, POLICY_DEFINITION, GENERATED_TEST_CASES, POLICY_SCENARIOS, FIDELITY_REPORT, ASSET_MANIFEST, SOURCE_DOCUMENT).
#' @param assetId The unique identifier of the specific asset to retrieve when multiple assets of the same type exist. This is required when retrieving SOURCE_DOCUMENT assets, as multiple source documents may have been used in the workflow. The asset ID can be obtained from the asset manifest.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_autom_reaso_polic_build_workf_resul_asset
bedrock_get_automated_reasoning_policy_build_workflow_result_assets <- function(policyArn, buildWorkflowId, assetType, assetId = NULL) {
  op <- new_operation(
    name = "GetAutomatedReasoningPolicyBuildWorkflowResultAssets",
    http_method = "GET",
    http_path = "/automated-reasoning-policies/{policyArn}/build-workflows/{buildWorkflowId}/result-assets",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_automated_reasoning_policy_build_workflow_result_assets_input(policyArn = policyArn, buildWorkflowId = buildWorkflowId, assetType = assetType, assetId = assetId)
  output <- .bedrock$get_automated_reasoning_policy_build_workflow_result_assets_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_automated_reasoning_policy_build_workflow_result_assets <- bedrock_get_automated_reasoning_policy_build_workflow_result_assets

#' Retrieves the next test scenario for validating an Automated Reasoning
#' policy
#'
#' @description
#' Retrieves the next test scenario for validating an Automated Reasoning policy. This is used during the interactive policy refinement process to test policy behavior.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_automated_reasoning_policy_next_scenario/](https://www.paws-r-sdk.com/docs/bedrock_get_automated_reasoning_policy_next_scenario/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy for which you want to get the next test scenario.
#' @param buildWorkflowId &#91;required&#93; The unique identifier of the build workflow associated with the test scenarios.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_automated_reasoning_policy_next_scenario
bedrock_get_automated_reasoning_policy_next_scenario <- function(policyArn, buildWorkflowId) {
  op <- new_operation(
    name = "GetAutomatedReasoningPolicyNextScenario",
    http_method = "GET",
    http_path = "/automated-reasoning-policies/{policyArn}/build-workflows/{buildWorkflowId}/scenarios",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_automated_reasoning_policy_next_scenario_input(policyArn = policyArn, buildWorkflowId = buildWorkflowId)
  output <- .bedrock$get_automated_reasoning_policy_next_scenario_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_automated_reasoning_policy_next_scenario <- bedrock_get_automated_reasoning_policy_next_scenario

#' Retrieves details about a specific Automated Reasoning policy test
#'
#' @description
#' Retrieves details about a specific Automated Reasoning policy test.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_automated_reasoning_policy_test_case/](https://www.paws-r-sdk.com/docs/bedrock_get_automated_reasoning_policy_test_case/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy that contains the test.
#' @param testCaseId &#91;required&#93; The unique identifier of the test to retrieve.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_automated_reasoning_policy_test_case
bedrock_get_automated_reasoning_policy_test_case <- function(policyArn, testCaseId) {
  op <- new_operation(
    name = "GetAutomatedReasoningPolicyTestCase",
    http_method = "GET",
    http_path = "/automated-reasoning-policies/{policyArn}/test-cases/{testCaseId}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_automated_reasoning_policy_test_case_input(policyArn = policyArn, testCaseId = testCaseId)
  output <- .bedrock$get_automated_reasoning_policy_test_case_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_automated_reasoning_policy_test_case <- bedrock_get_automated_reasoning_policy_test_case

#' Retrieves the test result for a specific Automated Reasoning policy test
#'
#' @description
#' Retrieves the test result for a specific Automated Reasoning policy test. Returns detailed validation findings and execution status.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_automated_reasoning_policy_test_result/](https://www.paws-r-sdk.com/docs/bedrock_get_automated_reasoning_policy_test_result/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy.
#' @param buildWorkflowId &#91;required&#93; The build workflow identifier. The build workflow must display a `COMPLETED` status to get results.
#' @param testCaseId &#91;required&#93; The unique identifier of the test for which to retrieve results.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_automated_reasoning_policy_test_result
bedrock_get_automated_reasoning_policy_test_result <- function(policyArn, buildWorkflowId, testCaseId) {
  op <- new_operation(
    name = "GetAutomatedReasoningPolicyTestResult",
    http_method = "GET",
    http_path = "/automated-reasoning-policies/{policyArn}/build-workflows/{buildWorkflowId}/test-cases/{testCaseId}/test-results",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_automated_reasoning_policy_test_result_input(policyArn = policyArn, buildWorkflowId = buildWorkflowId, testCaseId = testCaseId)
  output <- .bedrock$get_automated_reasoning_policy_test_result_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_automated_reasoning_policy_test_result <- bedrock_get_automated_reasoning_policy_test_result

#' Get the properties associated with a Amazon Bedrock custom model that
#' you have created
#'
#' @description
#' Get the properties associated with a Amazon Bedrock custom model that you have created. For more information, see [Custom models](https://docs.aws.amazon.com/bedrock/latest/userguide/custom-models.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_custom_model/](https://www.paws-r-sdk.com/docs/bedrock_get_custom_model/) for full documentation.
#'
#' @param modelIdentifier &#91;required&#93; Name or Amazon Resource Name (ARN) of the custom model.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_custom_model
bedrock_get_custom_model <- function(modelIdentifier) {
  op <- new_operation(
    name = "GetCustomModel",
    http_method = "GET",
    http_path = "/custom-models/{modelIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_custom_model_input(modelIdentifier = modelIdentifier)
  output <- .bedrock$get_custom_model_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_custom_model <- bedrock_get_custom_model

#' Retrieves information about a custom model deployment, including its
#' status, configuration, and metadata
#'
#' @description
#' 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.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_custom_model_deployment/](https://www.paws-r-sdk.com/docs/bedrock_get_custom_model_deployment/) for full documentation.
#'
#' @param customModelDeploymentIdentifier &#91;required&#93; The Amazon Resource Name (ARN) or name of the custom model deployment to retrieve information about.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_custom_model_deployment
bedrock_get_custom_model_deployment <- function(customModelDeploymentIdentifier) {
  op <- new_operation(
    name = "GetCustomModelDeployment",
    http_method = "GET",
    http_path = "/model-customization/custom-model-deployments/{customModelDeploymentIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_custom_model_deployment_input(customModelDeploymentIdentifier = customModelDeploymentIdentifier)
  output <- .bedrock$get_custom_model_deployment_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_custom_model_deployment <- bedrock_get_custom_model_deployment

#' Gets information about an evaluation job, such as the status of the job
#'
#' @description
#' Gets information about an evaluation job, such as the status of the job.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_evaluation_job/](https://www.paws-r-sdk.com/docs/bedrock_get_evaluation_job/) for full documentation.
#'
#' @param jobIdentifier &#91;required&#93; The Amazon Resource Name (ARN) of the evaluation job you want get information on.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_evaluation_job
bedrock_get_evaluation_job <- function(jobIdentifier) {
  op <- new_operation(
    name = "GetEvaluationJob",
    http_method = "GET",
    http_path = "/evaluation-jobs/{jobIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_evaluation_job_input(jobIdentifier = jobIdentifier)
  output <- .bedrock$get_evaluation_job_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_evaluation_job <- bedrock_get_evaluation_job

#' Get details about a Amazon Bedrock foundation model
#'
#' @description
#' Get details about a Amazon Bedrock foundation model.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_foundation_model/](https://www.paws-r-sdk.com/docs/bedrock_get_foundation_model/) for full documentation.
#'
#' @param modelIdentifier &#91;required&#93; The model identifier.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_foundation_model
bedrock_get_foundation_model <- function(modelIdentifier) {
  op <- new_operation(
    name = "GetFoundationModel",
    http_method = "GET",
    http_path = "/foundation-models/{modelIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_foundation_model_input(modelIdentifier = modelIdentifier)
  output <- .bedrock$get_foundation_model_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_foundation_model <- bedrock_get_foundation_model

#' Get information about the Foundation model availability
#'
#' @description
#' Get information about the Foundation model availability.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_foundation_model_availability/](https://www.paws-r-sdk.com/docs/bedrock_get_foundation_model_availability/) for full documentation.
#'
#' @param modelId &#91;required&#93; The model Id of the foundation model.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_foundation_model_availability
bedrock_get_foundation_model_availability <- function(modelId) {
  op <- new_operation(
    name = "GetFoundationModelAvailability",
    http_method = "GET",
    http_path = "/foundation-model-availability/{modelId}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_foundation_model_availability_input(modelId = modelId)
  output <- .bedrock$get_foundation_model_availability_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_foundation_model_availability <- bedrock_get_foundation_model_availability

#' Gets details about a guardrail
#'
#' @description
#' Gets details about a guardrail. If you don't specify a version, the response returns details for the `DRAFT` version.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_guardrail/](https://www.paws-r-sdk.com/docs/bedrock_get_guardrail/) for full documentation.
#'
#' @param guardrailIdentifier &#91;required&#93; The unique identifier of the guardrail for which to get details. This can be an ID or the ARN.
#' @param guardrailVersion The version of the guardrail for which to get details. If you don't specify a version, the response returns details for the `DRAFT` version.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_guardrail
bedrock_get_guardrail <- function(guardrailIdentifier, guardrailVersion = NULL) {
  op <- new_operation(
    name = "GetGuardrail",
    http_method = "GET",
    http_path = "/guardrails/{guardrailIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_guardrail_input(guardrailIdentifier = guardrailIdentifier, guardrailVersion = guardrailVersion)
  output <- .bedrock$get_guardrail_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_guardrail <- bedrock_get_guardrail

#' Gets properties associated with a customized model you imported
#'
#' @description
#' Gets properties associated with a customized model you imported.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_imported_model/](https://www.paws-r-sdk.com/docs/bedrock_get_imported_model/) for full documentation.
#'
#' @param modelIdentifier &#91;required&#93; Name or Amazon Resource Name (ARN) of the imported model.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_imported_model
bedrock_get_imported_model <- function(modelIdentifier) {
  op <- new_operation(
    name = "GetImportedModel",
    http_method = "GET",
    http_path = "/imported-models/{modelIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_imported_model_input(modelIdentifier = modelIdentifier)
  output <- .bedrock$get_imported_model_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_imported_model <- bedrock_get_imported_model

#' Gets information about an inference profile
#'
#' @description
#' Gets information about an inference profile. For more information, see [Increase throughput and resilience with cross-region inference in Amazon Bedrock](https://docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference.html). in the Amazon Bedrock User Guide.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_inference_profile/](https://www.paws-r-sdk.com/docs/bedrock_get_inference_profile/) for full documentation.
#'
#' @param inferenceProfileIdentifier &#91;required&#93; The ID or Amazon Resource Name (ARN) of the inference profile.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_inference_profile
bedrock_get_inference_profile <- function(inferenceProfileIdentifier) {
  op <- new_operation(
    name = "GetInferenceProfile",
    http_method = "GET",
    http_path = "/inference-profiles/{inferenceProfileIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_inference_profile_input(inferenceProfileIdentifier = inferenceProfileIdentifier)
  output <- .bedrock$get_inference_profile_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_inference_profile <- bedrock_get_inference_profile

#' Retrieves details about a specific endpoint for a model from Amazon
#' Bedrock Marketplace
#'
#' @description
#' Retrieves details about a specific endpoint for a model from Amazon Bedrock Marketplace.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_marketplace_model_endpoint/](https://www.paws-r-sdk.com/docs/bedrock_get_marketplace_model_endpoint/) for full documentation.
#'
#' @param endpointArn &#91;required&#93; The Amazon Resource Name (ARN) of the endpoint you want to get information about.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_marketplace_model_endpoint
bedrock_get_marketplace_model_endpoint <- function(endpointArn) {
  op <- new_operation(
    name = "GetMarketplaceModelEndpoint",
    http_method = "GET",
    http_path = "/marketplace-model/endpoints/{endpointArn}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_marketplace_model_endpoint_input(endpointArn = endpointArn)
  output <- .bedrock$get_marketplace_model_endpoint_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_marketplace_model_endpoint <- bedrock_get_marketplace_model_endpoint

#' Retrieves information about a model copy job
#'
#' @description
#' Retrieves information about a model copy job. For more information, see [Copy models to be used in other regions](https://docs.aws.amazon.com/bedrock/latest/userguide/copy-model.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_model_copy_job/](https://www.paws-r-sdk.com/docs/bedrock_get_model_copy_job/) for full documentation.
#'
#' @param jobArn &#91;required&#93; The Amazon Resource Name (ARN) of the model copy job.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_model_copy_job
bedrock_get_model_copy_job <- function(jobArn) {
  op <- new_operation(
    name = "GetModelCopyJob",
    http_method = "GET",
    http_path = "/model-copy-jobs/{jobArn}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_model_copy_job_input(jobArn = jobArn)
  output <- .bedrock$get_model_copy_job_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_model_copy_job <- bedrock_get_model_copy_job

#' Retrieves the properties associated with a model-customization job,
#' including the status of the job
#'
#' @description
#' Retrieves the properties associated with a model-customization job, including the status of the job. For more information, see [Custom models](https://docs.aws.amazon.com/bedrock/latest/userguide/custom-models.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_model_customization_job/](https://www.paws-r-sdk.com/docs/bedrock_get_model_customization_job/) for full documentation.
#'
#' @param jobIdentifier &#91;required&#93; Identifier for the customization job.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_model_customization_job
bedrock_get_model_customization_job <- function(jobIdentifier) {
  op <- new_operation(
    name = "GetModelCustomizationJob",
    http_method = "GET",
    http_path = "/model-customization-jobs/{jobIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_model_customization_job_input(jobIdentifier = jobIdentifier)
  output <- .bedrock$get_model_customization_job_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_model_customization_job <- bedrock_get_model_customization_job

#' Retrieves the properties associated with import model job, including the
#' status of the job
#'
#' @description
#' Retrieves the properties associated with import model job, including the status of the job. For more information, see [Import a customized model](https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-import-model.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_model_import_job/](https://www.paws-r-sdk.com/docs/bedrock_get_model_import_job/) for full documentation.
#'
#' @param jobIdentifier &#91;required&#93; The identifier of the import job.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_model_import_job
bedrock_get_model_import_job <- function(jobIdentifier) {
  op <- new_operation(
    name = "GetModelImportJob",
    http_method = "GET",
    http_path = "/model-import-jobs/{jobIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_model_import_job_input(jobIdentifier = jobIdentifier)
  output <- .bedrock$get_model_import_job_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_model_import_job <- bedrock_get_model_import_job

#' Gets details about a batch inference job
#'
#' @description
#' Gets details about a batch inference job. For more information, see [Monitor batch inference jobs](https://docs.aws.amazon.com/bedrock/latest/userguide/batch-inference-monitor.html)
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_model_invocation_job/](https://www.paws-r-sdk.com/docs/bedrock_get_model_invocation_job/) for full documentation.
#'
#' @param jobIdentifier &#91;required&#93; The Amazon Resource Name (ARN) of the batch inference job.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_model_invocation_job
bedrock_get_model_invocation_job <- function(jobIdentifier) {
  op <- new_operation(
    name = "GetModelInvocationJob",
    http_method = "GET",
    http_path = "/model-invocation-job/{jobIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_model_invocation_job_input(jobIdentifier = jobIdentifier)
  output <- .bedrock$get_model_invocation_job_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_model_invocation_job <- bedrock_get_model_invocation_job

#' Get the current configuration values for model invocation logging
#'
#' @description
#' Get the current configuration values for model invocation logging.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_model_invocation_logging_configuration/](https://www.paws-r-sdk.com/docs/bedrock_get_model_invocation_logging_configuration/) for full documentation.
#'

#'
#' @keywords internal
#'
#' @rdname bedrock_get_model_invocation_logging_configuration
bedrock_get_model_invocation_logging_configuration <- function() {
  op <- new_operation(
    name = "GetModelInvocationLoggingConfiguration",
    http_method = "GET",
    http_path = "/logging/modelinvocations",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_model_invocation_logging_configuration_input()
  output <- .bedrock$get_model_invocation_logging_configuration_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_model_invocation_logging_configuration <- bedrock_get_model_invocation_logging_configuration

#' Retrieves details about a prompt router
#'
#' @description
#' Retrieves details about a prompt router.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_prompt_router/](https://www.paws-r-sdk.com/docs/bedrock_get_prompt_router/) for full documentation.
#'
#' @param promptRouterArn &#91;required&#93; The prompt router's ARN
#'
#' @keywords internal
#'
#' @rdname bedrock_get_prompt_router
bedrock_get_prompt_router <- function(promptRouterArn) {
  op <- new_operation(
    name = "GetPromptRouter",
    http_method = "GET",
    http_path = "/prompt-routers/{promptRouterArn}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_prompt_router_input(promptRouterArn = promptRouterArn)
  output <- .bedrock$get_prompt_router_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_prompt_router <- bedrock_get_prompt_router

#' Returns details for a Provisioned Throughput
#'
#' @description
#' Returns details for a Provisioned Throughput. For more information, see [Provisioned Throughput](https://docs.aws.amazon.com/bedrock/latest/userguide/prov-throughput.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_provisioned_model_throughput/](https://www.paws-r-sdk.com/docs/bedrock_get_provisioned_model_throughput/) for full documentation.
#'
#' @param provisionedModelId &#91;required&#93; The Amazon Resource Name (ARN) or name of the Provisioned Throughput.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_provisioned_model_throughput
bedrock_get_provisioned_model_throughput <- function(provisionedModelId) {
  op <- new_operation(
    name = "GetProvisionedModelThroughput",
    http_method = "GET",
    http_path = "/provisioned-model-throughput/{provisionedModelId}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_provisioned_model_throughput_input(provisionedModelId = provisionedModelId)
  output <- .bedrock$get_provisioned_model_throughput_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_provisioned_model_throughput <- bedrock_get_provisioned_model_throughput

#' Gets the resource policy document for a Bedrock resource
#'
#' @description
#' Gets the resource policy document for a Bedrock resource
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_resource_policy/](https://www.paws-r-sdk.com/docs/bedrock_get_resource_policy/) for full documentation.
#'
#' @param resourceArn &#91;required&#93; The ARN of the Bedrock resource to which this resource policy applies.
#'
#' @keywords internal
#'
#' @rdname bedrock_get_resource_policy
bedrock_get_resource_policy <- function(resourceArn) {
  op <- new_operation(
    name = "GetResourcePolicy",
    http_method = "GET",
    http_path = "/resource-policy/{resourceArn}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_resource_policy_input(resourceArn = resourceArn)
  output <- .bedrock$get_resource_policy_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_resource_policy <- bedrock_get_resource_policy

#' Get usecase for model access
#'
#' @description
#' Get usecase for model access.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_get_use_case_for_model_access/](https://www.paws-r-sdk.com/docs/bedrock_get_use_case_for_model_access/) for full documentation.
#'

#'
#' @keywords internal
#'
#' @rdname bedrock_get_use_case_for_model_access
bedrock_get_use_case_for_model_access <- function() {
  op <- new_operation(
    name = "GetUseCaseForModelAccess",
    http_method = "GET",
    http_path = "/use-case-for-model-access",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$get_use_case_for_model_access_input()
  output <- .bedrock$get_use_case_for_model_access_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$get_use_case_for_model_access <- bedrock_get_use_case_for_model_access

#' Lists all advanced prompt optimization jobs for the account
#'
#' @description
#' Lists all advanced prompt optimization jobs for the account.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_advanced_prompt_optimization_jobs/](https://www.paws-r-sdk.com/docs/bedrock_list_advanced_prompt_optimization_jobs/) for full documentation.
#'
#' @param maxResults Maximum number of results to return.
#' @param nextToken Pagination token for the next page of results.
#' @param sortBy Field to sort by in the returned list of jobs.
#' @param sortOrder Sort order for the results.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_advanced_prompt_optimization_jobs
bedrock_list_advanced_prompt_optimization_jobs <- function(maxResults = NULL, nextToken = NULL, sortBy = NULL, sortOrder = NULL) {
  op <- new_operation(
    name = "ListAdvancedPromptOptimizationJobs",
    http_method = "GET",
    http_path = "/advanced-prompt-optimization-jobs",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", limit_key = "maxResults", result_key = "jobSummaries"),
    stream_api = FALSE
  )
  input <- .bedrock$list_advanced_prompt_optimization_jobs_input(maxResults = maxResults, nextToken = nextToken, sortBy = sortBy, sortOrder = sortOrder)
  output <- .bedrock$list_advanced_prompt_optimization_jobs_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_advanced_prompt_optimization_jobs <- bedrock_list_advanced_prompt_optimization_jobs

#' Lists all Automated Reasoning policies in your account, with optional
#' filtering by policy ARN
#'
#' @description
#' Lists all Automated Reasoning policies in your account, with optional filtering by policy ARN. This helps you manage and discover existing policies.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_automated_reasoning_policies/](https://www.paws-r-sdk.com/docs/bedrock_list_automated_reasoning_policies/) for full documentation.
#'
#' @param policyArn Optional filter to list only the policy versions with the specified Amazon Resource Name (ARN). If not provided, the DRAFT versions for all policies are listed.
#' @param nextToken The pagination token from a previous request to retrieve the next page of results.
#' @param maxResults The maximum number of policies to return in a single call.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_automated_reasoning_policies
bedrock_list_automated_reasoning_policies <- function(policyArn = NULL, nextToken = NULL, maxResults = NULL) {
  op <- new_operation(
    name = "ListAutomatedReasoningPolicies",
    http_method = "GET",
    http_path = "/automated-reasoning-policies",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", limit_key = "maxResults", result_key = "automatedReasoningPolicySummaries"),
    stream_api = FALSE
  )
  input <- .bedrock$list_automated_reasoning_policies_input(policyArn = policyArn, nextToken = nextToken, maxResults = maxResults)
  output <- .bedrock$list_automated_reasoning_policies_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_automated_reasoning_policies <- bedrock_list_automated_reasoning_policies

#' Lists all build workflows for an Automated Reasoning policy, showing the
#' history of policy creation and modification attempts
#'
#' @description
#' Lists all build workflows for an Automated Reasoning policy, showing the history of policy creation and modification attempts.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_automated_reasoning_policy_build_workflows/](https://www.paws-r-sdk.com/docs/bedrock_list_automated_reasoning_policy_build_workflows/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy whose build workflows you want to list.
#' @param nextToken A pagination token from a previous request to continue listing build workflows from where the previous request left off.
#' @param maxResults The maximum number of build workflows to return in a single response. Valid range is 1-100.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_automated_reasoning_policy_build_workflows
bedrock_list_automated_reasoning_policy_build_workflows <- function(policyArn, nextToken = NULL, maxResults = NULL) {
  op <- new_operation(
    name = "ListAutomatedReasoningPolicyBuildWorkflows",
    http_method = "GET",
    http_path = "/automated-reasoning-policies/{policyArn}/build-workflows",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", limit_key = "maxResults", result_key = "automatedReasoningPolicyBuildWorkflowSummaries"),
    stream_api = FALSE
  )
  input <- .bedrock$list_automated_reasoning_policy_build_workflows_input(policyArn = policyArn, nextToken = nextToken, maxResults = maxResults)
  output <- .bedrock$list_automated_reasoning_policy_build_workflows_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_automated_reasoning_policy_build_workflows <- bedrock_list_automated_reasoning_policy_build_workflows

#' Lists tests for an Automated Reasoning policy
#'
#' @description
#' Lists tests for an Automated Reasoning policy. We recommend using pagination to ensure that the operation returns quickly and successfully.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_automated_reasoning_policy_test_cases/](https://www.paws-r-sdk.com/docs/bedrock_list_automated_reasoning_policy_test_cases/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy for which to list tests.
#' @param nextToken The pagination token from a previous request to retrieve the next page of results.
#' @param maxResults The maximum number of tests to return in a single call.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_automated_reasoning_policy_test_cases
bedrock_list_automated_reasoning_policy_test_cases <- function(policyArn, nextToken = NULL, maxResults = NULL) {
  op <- new_operation(
    name = "ListAutomatedReasoningPolicyTestCases",
    http_method = "GET",
    http_path = "/automated-reasoning-policies/{policyArn}/test-cases",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", limit_key = "maxResults", result_key = "testCases"),
    stream_api = FALSE
  )
  input <- .bedrock$list_automated_reasoning_policy_test_cases_input(policyArn = policyArn, nextToken = nextToken, maxResults = maxResults)
  output <- .bedrock$list_automated_reasoning_policy_test_cases_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_automated_reasoning_policy_test_cases <- bedrock_list_automated_reasoning_policy_test_cases

#' Lists test results for an Automated Reasoning policy, showing how the
#' policy performed against various test scenarios and validation checks
#'
#' @description
#' Lists test results for an Automated Reasoning policy, showing how the policy performed against various test scenarios and validation checks.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_automated_reasoning_policy_test_results/](https://www.paws-r-sdk.com/docs/bedrock_list_automated_reasoning_policy_test_results/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy whose test results you want to list.
#' @param buildWorkflowId &#91;required&#93; The unique identifier of the build workflow whose test results you want to list.
#' @param nextToken A pagination token from a previous request to continue listing test results from where the previous request left off.
#' @param maxResults The maximum number of test results to return in a single response. Valid range is 1-100.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_automated_reasoning_policy_test_results
bedrock_list_automated_reasoning_policy_test_results <- function(policyArn, buildWorkflowId, nextToken = NULL, maxResults = NULL) {
  op <- new_operation(
    name = "ListAutomatedReasoningPolicyTestResults",
    http_method = "GET",
    http_path = "/automated-reasoning-policies/{policyArn}/build-workflows/{buildWorkflowId}/test-results",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", limit_key = "maxResults", result_key = "testResults"),
    stream_api = FALSE
  )
  input <- .bedrock$list_automated_reasoning_policy_test_results_input(policyArn = policyArn, buildWorkflowId = buildWorkflowId, nextToken = nextToken, maxResults = maxResults)
  output <- .bedrock$list_automated_reasoning_policy_test_results_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_automated_reasoning_policy_test_results <- bedrock_list_automated_reasoning_policy_test_results

#' Lists custom model deployments in your account
#'
#' @description
#' 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.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_custom_model_deployments/](https://www.paws-r-sdk.com/docs/bedrock_list_custom_model_deployments/) for full documentation.
#'
#' @param createdBefore Filters deployments created before the specified date and time.
#' @param createdAfter Filters deployments created after the specified date and time.
#' @param nameContains Filters deployments whose names contain the specified string.
#' @param maxResults The maximum number of results to return in a single call.
#' @param nextToken The token for the next set of results. Use this token to retrieve additional results when the response is truncated.
#' @param sortBy The field to sort the results by. The only supported value is `CreationTime`.
#' @param sortOrder The sort order for the results. Valid values are `Ascending` and `Descending`. Default is `Descending`.
#' @param statusEquals Filters deployments by status. Valid values are `CREATING`, `ACTIVE`, and `FAILED`.
#' @param modelArnEquals Filters deployments by the Amazon Resource Name (ARN) of the associated custom model.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_custom_model_deployments
bedrock_list_custom_model_deployments <- function(createdBefore = NULL, createdAfter = NULL, nameContains = NULL, maxResults = NULL, nextToken = NULL, sortBy = NULL, sortOrder = NULL, statusEquals = NULL, modelArnEquals = NULL) {
  op <- new_operation(
    name = "ListCustomModelDeployments",
    http_method = "GET",
    http_path = "/model-customization/custom-model-deployments",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", limit_key = "maxResults", result_key = "modelDeploymentSummaries"),
    stream_api = FALSE
  )
  input <- .bedrock$list_custom_model_deployments_input(createdBefore = createdBefore, createdAfter = createdAfter, nameContains = nameContains, maxResults = maxResults, nextToken = nextToken, sortBy = sortBy, sortOrder = sortOrder, statusEquals = statusEquals, modelArnEquals = modelArnEquals)
  output <- .bedrock$list_custom_model_deployments_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_custom_model_deployments <- bedrock_list_custom_model_deployments

#' Returns a list of the custom models that you have created with the
#' CreateModelCustomizationJob operation
#'
#' @description
#' Returns a list of the custom models that you have created with the [`create_model_customization_job`][bedrock_create_model_customization_job] operation.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_custom_models/](https://www.paws-r-sdk.com/docs/bedrock_list_custom_models/) for full documentation.
#'
#' @param creationTimeBefore Return custom models created before the specified time.
#' @param creationTimeAfter Return custom models created after the specified time.
#' @param nameContains Return custom models only if the job name contains these characters.
#' @param baseModelArnEquals Return custom models only if the base model Amazon Resource Name (ARN) matches this parameter.
#' @param foundationModelArnEquals Return custom models only if the foundation model Amazon Resource Name (ARN) matches this parameter.
#' @param maxResults The maximum number of results to return in the response. If the total number of results is greater than this value, use the token returned in the response in the `nextToken` field when making another request to return the next batch of results.
#' @param nextToken If the total number of results is greater than the `maxResults` value provided in the request, enter the token returned in the `nextToken` field in the response in this field to return the next batch of results.
#' @param sortBy The field to sort by in the returned list of models.
#' @param sortOrder The sort order of the results.
#' @param isOwned Return custom models depending on if the current account owns them (`true`) or if they were shared with the current account (`false`).
#' @param modelStatus The status of them model to filter results by. Possible values include:
#' 
#' -   `Creating` - Include only models that are currently being created and validated.
#' 
#' -   `Active` - Include only models that have been successfully created and are ready for use.
#' 
#' -   `Failed` - Include only models where the creation process failed.
#' 
#' If you don't specify a status, the API returns models in all states.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_custom_models
bedrock_list_custom_models <- function(creationTimeBefore = NULL, creationTimeAfter = NULL, nameContains = NULL, baseModelArnEquals = NULL, foundationModelArnEquals = NULL, maxResults = NULL, nextToken = NULL, sortBy = NULL, sortOrder = NULL, isOwned = NULL, modelStatus = NULL) {
  op <- new_operation(
    name = "ListCustomModels",
    http_method = "GET",
    http_path = "/custom-models",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", limit_key = "maxResults", result_key = "modelSummaries"),
    stream_api = FALSE
  )
  input <- .bedrock$list_custom_models_input(creationTimeBefore = creationTimeBefore, creationTimeAfter = creationTimeAfter, nameContains = nameContains, baseModelArnEquals = baseModelArnEquals, foundationModelArnEquals = foundationModelArnEquals, maxResults = maxResults, nextToken = nextToken, sortBy = sortBy, sortOrder = sortOrder, isOwned = isOwned, modelStatus = modelStatus)
  output <- .bedrock$list_custom_models_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_custom_models <- bedrock_list_custom_models

#' Lists the account-level enforced guardrail configurations
#'
#' @description
#' Lists the account-level enforced guardrail configurations.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_enforced_guardrails_configuration/](https://www.paws-r-sdk.com/docs/bedrock_list_enforced_guardrails_configuration/) for full documentation.
#'
#' @param nextToken Opaque continuation token of previous paginated response.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_enforced_guardrails_configuration
bedrock_list_enforced_guardrails_configuration <- function(nextToken = NULL) {
  op <- new_operation(
    name = "ListEnforcedGuardrailsConfiguration",
    http_method = "GET",
    http_path = "/enforcedGuardrailsConfiguration",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", result_key = "guardrailsConfig"),
    stream_api = FALSE
  )
  input <- .bedrock$list_enforced_guardrails_configuration_input(nextToken = nextToken)
  output <- .bedrock$list_enforced_guardrails_configuration_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_enforced_guardrails_configuration <- bedrock_list_enforced_guardrails_configuration

#' Lists all existing evaluation jobs
#'
#' @description
#' Lists all existing evaluation jobs.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_evaluation_jobs/](https://www.paws-r-sdk.com/docs/bedrock_list_evaluation_jobs/) for full documentation.
#'
#' @param creationTimeAfter A filter to only list evaluation jobs created after a specified time.
#' @param creationTimeBefore A filter to only list evaluation jobs created before a specified time.
#' @param statusEquals A filter to only list evaluation jobs that are of a certain status.
#' @param applicationTypeEquals A filter to only list evaluation jobs that are either model evaluations or knowledge base evaluations.
#' @param nameContains A filter to only list evaluation jobs that contain a specified string in the job name.
#' @param maxResults The maximum number of results to return.
#' @param nextToken Continuation token from the previous response, for Amazon Bedrock to list the next set of results.
#' @param sortBy Specifies a creation time to sort the list of evaluation jobs by when they were created.
#' @param sortOrder Specifies whether to sort the list of evaluation jobs by either ascending or descending order.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_evaluation_jobs
bedrock_list_evaluation_jobs <- function(creationTimeAfter = NULL, creationTimeBefore = NULL, statusEquals = NULL, applicationTypeEquals = NULL, nameContains = NULL, maxResults = NULL, nextToken = NULL, sortBy = NULL, sortOrder = NULL) {
  op <- new_operation(
    name = "ListEvaluationJobs",
    http_method = "GET",
    http_path = "/evaluation-jobs",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", limit_key = "maxResults", result_key = "jobSummaries"),
    stream_api = FALSE
  )
  input <- .bedrock$list_evaluation_jobs_input(creationTimeAfter = creationTimeAfter, creationTimeBefore = creationTimeBefore, statusEquals = statusEquals, applicationTypeEquals = applicationTypeEquals, nameContains = nameContains, maxResults = maxResults, nextToken = nextToken, sortBy = sortBy, sortOrder = sortOrder)
  output <- .bedrock$list_evaluation_jobs_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_evaluation_jobs <- bedrock_list_evaluation_jobs

#' Get the offers associated with the specified model
#'
#' @description
#' Get the offers associated with the specified model.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_foundation_model_agreement_offers/](https://www.paws-r-sdk.com/docs/bedrock_list_foundation_model_agreement_offers/) for full documentation.
#'
#' @param modelId &#91;required&#93; Model Id of the foundation model.
#' @param offerType Type of offer associated with the model.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_foundation_model_agreement_offers
bedrock_list_foundation_model_agreement_offers <- function(modelId, offerType = NULL) {
  op <- new_operation(
    name = "ListFoundationModelAgreementOffers",
    http_method = "GET",
    http_path = "/list-foundation-model-agreement-offers/{modelId}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$list_foundation_model_agreement_offers_input(modelId = modelId, offerType = offerType)
  output <- .bedrock$list_foundation_model_agreement_offers_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_foundation_model_agreement_offers <- bedrock_list_foundation_model_agreement_offers

#' Lists Amazon Bedrock foundation models that you can use
#'
#' @description
#' Lists Amazon Bedrock foundation models that you can use. You can filter the results with the request parameters. For more information, see [Foundation models](https://docs.aws.amazon.com/bedrock/latest/userguide/) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_foundation_models/](https://www.paws-r-sdk.com/docs/bedrock_list_foundation_models/) for full documentation.
#'
#' @param byProvider Return models belonging to the model provider that you specify.
#' @param byCustomizationType Return models that support the customization type that you specify. For more information, see [Custom models](https://docs.aws.amazon.com/bedrock/latest/userguide/custom-models.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#' @param byOutputModality Return models that support the output modality that you specify.
#' @param byInferenceType Return models that support the inference type that you specify. For more information, see [Provisioned Throughput](https://docs.aws.amazon.com/bedrock/latest/userguide/prov-throughput.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' @keywords internal
#'
#' @rdname bedrock_list_foundation_models
bedrock_list_foundation_models <- function(byProvider = NULL, byCustomizationType = NULL, byOutputModality = NULL, byInferenceType = NULL) {
  op <- new_operation(
    name = "ListFoundationModels",
    http_method = "GET",
    http_path = "/foundation-models",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$list_foundation_models_input(byProvider = byProvider, byCustomizationType = byCustomizationType, byOutputModality = byOutputModality, byInferenceType = byInferenceType)
  output <- .bedrock$list_foundation_models_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_foundation_models <- bedrock_list_foundation_models

#' Lists details about all the guardrails in an account
#'
#' @description
#' 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.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_guardrails/](https://www.paws-r-sdk.com/docs/bedrock_list_guardrails/) for full documentation.
#'
#' @param guardrailIdentifier The unique identifier of the guardrail. This can be an ID or the ARN.
#' @param maxResults The maximum number of results to return in the response.
#' @param nextToken If there are more results than were returned in the response, the response returns a `nextToken` that you can send in another [`list_guardrails`][bedrock_list_guardrails] request to see the next batch of results.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_guardrails
bedrock_list_guardrails <- function(guardrailIdentifier = NULL, maxResults = NULL, nextToken = NULL) {
  op <- new_operation(
    name = "ListGuardrails",
    http_method = "GET",
    http_path = "/guardrails",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", limit_key = "maxResults", result_key = "guardrails"),
    stream_api = FALSE
  )
  input <- .bedrock$list_guardrails_input(guardrailIdentifier = guardrailIdentifier, maxResults = maxResults, nextToken = nextToken)
  output <- .bedrock$list_guardrails_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_guardrails <- bedrock_list_guardrails

#' Returns a list of models you've imported
#'
#' @description
#' 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](https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-import-model.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_imported_models/](https://www.paws-r-sdk.com/docs/bedrock_list_imported_models/) for full documentation.
#'
#' @param creationTimeBefore Return imported models that created before the specified time.
#' @param creationTimeAfter Return imported models that were created after the specified time.
#' @param nameContains Return imported models only if the model name contains these characters.
#' @param maxResults The maximum number of results to return in the response. If the total number of results is greater than this value, use the token returned in the response in the `nextToken` field when making another request to return the next batch of results.
#' @param nextToken If the total number of results is greater than the `maxResults` value provided in the request, enter the token returned in the `nextToken` field in the response in this field to return the next batch of results.
#' @param sortBy The field to sort by in the returned list of imported models.
#' @param sortOrder Specifies whetehr to sort the results in ascending or descending order.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_imported_models
bedrock_list_imported_models <- function(creationTimeBefore = NULL, creationTimeAfter = NULL, nameContains = NULL, maxResults = NULL, nextToken = NULL, sortBy = NULL, sortOrder = NULL) {
  op <- new_operation(
    name = "ListImportedModels",
    http_method = "GET",
    http_path = "/imported-models",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", limit_key = "maxResults", result_key = "modelSummaries"),
    stream_api = FALSE
  )
  input <- .bedrock$list_imported_models_input(creationTimeBefore = creationTimeBefore, creationTimeAfter = creationTimeAfter, nameContains = nameContains, maxResults = maxResults, nextToken = nextToken, sortBy = sortBy, sortOrder = sortOrder)
  output <- .bedrock$list_imported_models_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_imported_models <- bedrock_list_imported_models

#' Returns a list of inference profiles that you can use
#'
#' @description
#' 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](https://docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference.html). in the Amazon Bedrock User Guide.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_inference_profiles/](https://www.paws-r-sdk.com/docs/bedrock_list_inference_profiles/) for full documentation.
#'
#' @param maxResults The maximum number of results to return in the response. If the total number of results is greater than this value, use the token returned in the response in the `nextToken` field when making another request to return the next batch of results.
#' @param nextToken If the total number of results is greater than the `maxResults` value provided in the request, enter the token returned in the `nextToken` field in the response in this field to return the next batch of results.
#' @param typeEquals Filters for inference profiles that match the type you specify.
#' 
#' -   `SYSTEM_DEFINED` – The inference profile is defined by Amazon Bedrock. You can route inference requests across regions with these inference profiles.
#' 
#' -   `APPLICATION` – The inference profile was created by a user. This type of inference profile can track metrics and costs when invoking the model in it. The inference profile may route requests to one or multiple regions.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_inference_profiles
bedrock_list_inference_profiles <- function(maxResults = NULL, nextToken = NULL, typeEquals = NULL) {
  op <- new_operation(
    name = "ListInferenceProfiles",
    http_method = "GET",
    http_path = "/inference-profiles",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", limit_key = "maxResults", result_key = "inferenceProfileSummaries"),
    stream_api = FALSE
  )
  input <- .bedrock$list_inference_profiles_input(maxResults = maxResults, nextToken = nextToken, typeEquals = typeEquals)
  output <- .bedrock$list_inference_profiles_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_inference_profiles <- bedrock_list_inference_profiles

#' Lists the endpoints for models from Amazon Bedrock Marketplace in your
#' Amazon Web Services account
#'
#' @description
#' Lists the endpoints for models from Amazon Bedrock Marketplace in your Amazon Web Services account.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_marketplace_model_endpoints/](https://www.paws-r-sdk.com/docs/bedrock_list_marketplace_model_endpoints/) for full documentation.
#'
#' @param maxResults The maximum number of results to return in a single call. If more results are available, the operation returns a `NextToken` value.
#' @param nextToken The token for the next set of results. You receive this token from a previous [`list_marketplace_model_endpoints`][bedrock_list_marketplace_model_endpoints] call.
#' @param modelSourceEquals If specified, only endpoints for the given model source identifier are returned.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_marketplace_model_endpoints
bedrock_list_marketplace_model_endpoints <- function(maxResults = NULL, nextToken = NULL, modelSourceEquals = NULL) {
  op <- new_operation(
    name = "ListMarketplaceModelEndpoints",
    http_method = "GET",
    http_path = "/marketplace-model/endpoints",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", limit_key = "maxResults", result_key = "marketplaceModelEndpoints"),
    stream_api = FALSE
  )
  input <- .bedrock$list_marketplace_model_endpoints_input(maxResults = maxResults, nextToken = nextToken, modelSourceEquals = modelSourceEquals)
  output <- .bedrock$list_marketplace_model_endpoints_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_marketplace_model_endpoints <- bedrock_list_marketplace_model_endpoints

#' Returns a list of model copy jobs that you have submitted
#'
#' @description
#' 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](https://docs.aws.amazon.com/bedrock/latest/userguide/copy-model.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_model_copy_jobs/](https://www.paws-r-sdk.com/docs/bedrock_list_model_copy_jobs/) for full documentation.
#'
#' @param creationTimeAfter Filters for model copy jobs created after the specified time.
#' @param creationTimeBefore Filters for model copy jobs created before the specified time.
#' @param statusEquals Filters for model copy jobs whose status matches the value that you specify.
#' @param sourceAccountEquals Filters for model copy jobs in which the account that the source model belongs to is equal to the value that you specify.
#' @param sourceModelArnEquals Filters for model copy jobs in which the Amazon Resource Name (ARN) of the source model to is equal to the value that you specify.
#' @param targetModelNameContains Filters for model copy jobs in which the name of the copied model contains the string that you specify.
#' @param maxResults The maximum number of results to return in the response. If the total number of results is greater than this value, use the token returned in the response in the `nextToken` field when making another request to return the next batch of results.
#' @param nextToken If the total number of results is greater than the `maxResults` value provided in the request, enter the token returned in the `nextToken` field in the response in this field to return the next batch of results.
#' @param sortBy The field to sort by in the returned list of model copy jobs.
#' @param sortOrder Specifies whether to sort the results in ascending or descending order.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_model_copy_jobs
bedrock_list_model_copy_jobs <- function(creationTimeAfter = NULL, creationTimeBefore = NULL, statusEquals = NULL, sourceAccountEquals = NULL, sourceModelArnEquals = NULL, targetModelNameContains = NULL, maxResults = NULL, nextToken = NULL, sortBy = NULL, sortOrder = NULL) {
  op <- new_operation(
    name = "ListModelCopyJobs",
    http_method = "GET",
    http_path = "/model-copy-jobs",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", limit_key = "maxResults", result_key = "modelCopyJobSummaries"),
    stream_api = FALSE
  )
  input <- .bedrock$list_model_copy_jobs_input(creationTimeAfter = creationTimeAfter, creationTimeBefore = creationTimeBefore, statusEquals = statusEquals, sourceAccountEquals = sourceAccountEquals, sourceModelArnEquals = sourceModelArnEquals, targetModelNameContains = targetModelNameContains, maxResults = maxResults, nextToken = nextToken, sortBy = sortBy, sortOrder = sortOrder)
  output <- .bedrock$list_model_copy_jobs_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_model_copy_jobs <- bedrock_list_model_copy_jobs

#' Returns a list of model customization jobs that you have submitted
#'
#' @description
#' Returns a list of model customization jobs that you have submitted. You can filter the jobs to return based on one or more criteria.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_model_customization_jobs/](https://www.paws-r-sdk.com/docs/bedrock_list_model_customization_jobs/) for full documentation.
#'
#' @param creationTimeAfter Return customization jobs created after the specified time.
#' @param creationTimeBefore Return customization jobs created before the specified time.
#' @param statusEquals Return customization jobs with the specified status.
#' @param nameContains Return customization jobs only if the job name contains these characters.
#' @param maxResults The maximum number of results to return in the response. If the total number of results is greater than this value, use the token returned in the response in the `nextToken` field when making another request to return the next batch of results.
#' @param nextToken If the total number of results is greater than the `maxResults` value provided in the request, enter the token returned in the `nextToken` field in the response in this field to return the next batch of results.
#' @param sortBy The field to sort by in the returned list of jobs.
#' @param sortOrder The sort order of the results.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_model_customization_jobs
bedrock_list_model_customization_jobs <- function(creationTimeAfter = NULL, creationTimeBefore = NULL, statusEquals = NULL, nameContains = NULL, maxResults = NULL, nextToken = NULL, sortBy = NULL, sortOrder = NULL) {
  op <- new_operation(
    name = "ListModelCustomizationJobs",
    http_method = "GET",
    http_path = "/model-customization-jobs",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", limit_key = "maxResults", result_key = "modelCustomizationJobSummaries"),
    stream_api = FALSE
  )
  input <- .bedrock$list_model_customization_jobs_input(creationTimeAfter = creationTimeAfter, creationTimeBefore = creationTimeBefore, statusEquals = statusEquals, nameContains = nameContains, maxResults = maxResults, nextToken = nextToken, sortBy = sortBy, sortOrder = sortOrder)
  output <- .bedrock$list_model_customization_jobs_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_model_customization_jobs <- bedrock_list_model_customization_jobs

#' Returns a list of import jobs you've submitted
#'
#' @description
#' 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](https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-import-model.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_model_import_jobs/](https://www.paws-r-sdk.com/docs/bedrock_list_model_import_jobs/) for full documentation.
#'
#' @param creationTimeAfter Return import jobs that were created after the specified time.
#' @param creationTimeBefore Return import jobs that were created before the specified time.
#' @param statusEquals Return imported jobs with the specified status.
#' @param nameContains Return imported jobs only if the job name contains these characters.
#' @param maxResults The maximum number of results to return in the response. If the total number of results is greater than this value, use the token returned in the response in the `nextToken` field when making another request to return the next batch of results.
#' @param nextToken If the total number of results is greater than the `maxResults` value provided in the request, enter the token returned in the `nextToken` field in the response in this field to return the next batch of results.
#' @param sortBy The field to sort by in the returned list of imported jobs.
#' @param sortOrder Specifies whether to sort the results in ascending or descending order.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_model_import_jobs
bedrock_list_model_import_jobs <- function(creationTimeAfter = NULL, creationTimeBefore = NULL, statusEquals = NULL, nameContains = NULL, maxResults = NULL, nextToken = NULL, sortBy = NULL, sortOrder = NULL) {
  op <- new_operation(
    name = "ListModelImportJobs",
    http_method = "GET",
    http_path = "/model-import-jobs",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", limit_key = "maxResults", result_key = "modelImportJobSummaries"),
    stream_api = FALSE
  )
  input <- .bedrock$list_model_import_jobs_input(creationTimeAfter = creationTimeAfter, creationTimeBefore = creationTimeBefore, statusEquals = statusEquals, nameContains = nameContains, maxResults = maxResults, nextToken = nextToken, sortBy = sortBy, sortOrder = sortOrder)
  output <- .bedrock$list_model_import_jobs_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_model_import_jobs <- bedrock_list_model_import_jobs

#' Lists all batch inference jobs in the account
#'
#' @description
#' Lists all batch inference jobs in the account. For more information, see [View details about a batch inference job](https://docs.aws.amazon.com/bedrock/latest/userguide/batch-inference-monitor.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_model_invocation_jobs/](https://www.paws-r-sdk.com/docs/bedrock_list_model_invocation_jobs/) for full documentation.
#'
#' @param submitTimeAfter Specify a time to filter for batch inference jobs that were submitted after the time you specify.
#' @param submitTimeBefore Specify a time to filter for batch inference jobs that were submitted before the time you specify.
#' @param statusEquals Specify a status to filter for batch inference jobs whose statuses match the string you specify.
#' 
#' The following statuses are possible:
#' 
#' -   Submitted – This job has been submitted to a queue for validation.
#' 
#' -   Validating – This job is being validated for the requirements described in [Format and upload your batch inference data](https://docs.aws.amazon.com/bedrock/latest/userguide/batch-inference-data.html). The criteria include the following:
#' 
#'     -   Your IAM service role has access to the Amazon S3 buckets containing your files.
#' 
#'     -   Your files are .jsonl files and each individual record is a JSON object in the correct format. Note that validation doesn't check if the `modelInput` value matches the request body for the model.
#' 
#'     -   Your files fulfill the requirements for file size and number of records. For more information, see [Quotas for Amazon Bedrock](https://docs.aws.amazon.com/bedrock/latest/userguide/quotas.html).
#' 
#' -   Scheduled – This job has been validated and is now in a queue. The job will automatically start when it reaches its turn.
#' 
#' -   Expired – This job timed out because it was scheduled but didn't begin before the set timeout duration. Submit a new job request.
#' 
#' -   InProgress – This job has begun. You can start viewing the results in the output S3 location.
#' 
#' -   Completed – This job has successfully completed. View the output files in the output S3 location.
#' 
#' -   PartiallyCompleted – This job has partially completed. Not all of your records could be processed in time. View the output files in the output S3 location.
#' 
#' -   Failed – This job has failed. Check the failure message for any further details. For further assistance, reach out to the Amazon Web Services Support Center.
#' 
#' -   Stopped – This job was stopped by a user.
#' 
#' -   Stopping – This job is being stopped by a user.
#' @param nameContains Specify a string to filter for batch inference jobs whose names contain the string.
#' @param maxResults The maximum number of results to return. If there are more results than the number that you specify, a `nextToken` value is returned. Use the `nextToken` in a request to return the next batch of results.
#' @param nextToken If there were more results than the value you specified in the `maxResults` field in a previous [`list_model_invocation_jobs`][bedrock_list_model_invocation_jobs] request, the response would have returned a `nextToken` value. To see the next batch of results, send the `nextToken` value in another request.
#' @param sortBy An attribute by which to sort the results.
#' @param sortOrder Specifies whether to sort the results by ascending or descending order.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_model_invocation_jobs
bedrock_list_model_invocation_jobs <- function(submitTimeAfter = NULL, submitTimeBefore = NULL, statusEquals = NULL, nameContains = NULL, maxResults = NULL, nextToken = NULL, sortBy = NULL, sortOrder = NULL) {
  op <- new_operation(
    name = "ListModelInvocationJobs",
    http_method = "GET",
    http_path = "/model-invocation-jobs",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", limit_key = "maxResults", result_key = "invocationJobSummaries"),
    stream_api = FALSE
  )
  input <- .bedrock$list_model_invocation_jobs_input(submitTimeAfter = submitTimeAfter, submitTimeBefore = submitTimeBefore, statusEquals = statusEquals, nameContains = nameContains, maxResults = maxResults, nextToken = nextToken, sortBy = sortBy, sortOrder = sortOrder)
  output <- .bedrock$list_model_invocation_jobs_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_model_invocation_jobs <- bedrock_list_model_invocation_jobs

#' Retrieves a list of prompt routers
#'
#' @description
#' Retrieves a list of prompt routers.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_prompt_routers/](https://www.paws-r-sdk.com/docs/bedrock_list_prompt_routers/) for full documentation.
#'
#' @param maxResults The maximum number of prompt routers to return in one page of results.
#' @param nextToken Specify the pagination token from a previous request to retrieve the next page of results.
#' @param type The type of the prompt routers, such as whether it's default or custom.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_prompt_routers
bedrock_list_prompt_routers <- function(maxResults = NULL, nextToken = NULL, type = NULL) {
  op <- new_operation(
    name = "ListPromptRouters",
    http_method = "GET",
    http_path = "/prompt-routers",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", limit_key = "maxResults", result_key = "promptRouterSummaries"),
    stream_api = FALSE
  )
  input <- .bedrock$list_prompt_routers_input(maxResults = maxResults, nextToken = nextToken, type = type)
  output <- .bedrock$list_prompt_routers_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_prompt_routers <- bedrock_list_prompt_routers

#' Lists the Provisioned Throughputs in the account
#'
#' @description
#' Lists the Provisioned Throughputs in the account. For more information, see [Provisioned Throughput](https://docs.aws.amazon.com/bedrock/latest/userguide/prov-throughput.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_provisioned_model_throughputs/](https://www.paws-r-sdk.com/docs/bedrock_list_provisioned_model_throughputs/) for full documentation.
#'
#' @param creationTimeAfter A filter that returns Provisioned Throughputs created after the specified time.
#' @param creationTimeBefore A filter that returns Provisioned Throughputs created before the specified time.
#' @param statusEquals A filter that returns Provisioned Throughputs if their statuses matches the value that you specify.
#' @param modelArnEquals A filter that returns Provisioned Throughputs whose model Amazon Resource Name (ARN) is equal to the value that you specify.
#' @param nameContains A filter that returns Provisioned Throughputs if their name contains the expression that you specify.
#' @param maxResults THe maximum number of results to return in the response. If there are more results than the number you specified, the response returns a `nextToken` value. To see the next batch of results, send the `nextToken` value in another list request.
#' @param nextToken If there are more results than the number you specified in the `maxResults` field, the response returns a `nextToken` value. To see the next batch of results, specify the `nextToken` value in this field.
#' @param sortBy The field by which to sort the returned list of Provisioned Throughputs.
#' @param sortOrder The sort order of the results.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_provisioned_model_throughputs
bedrock_list_provisioned_model_throughputs <- function(creationTimeAfter = NULL, creationTimeBefore = NULL, statusEquals = NULL, modelArnEquals = NULL, nameContains = NULL, maxResults = NULL, nextToken = NULL, sortBy = NULL, sortOrder = NULL) {
  op <- new_operation(
    name = "ListProvisionedModelThroughputs",
    http_method = "GET",
    http_path = "/provisioned-model-throughputs",
    host_prefix = "",
    paginator = list(input_token = "nextToken", output_token = "nextToken", limit_key = "maxResults", result_key = "provisionedModelSummaries"),
    stream_api = FALSE
  )
  input <- .bedrock$list_provisioned_model_throughputs_input(creationTimeAfter = creationTimeAfter, creationTimeBefore = creationTimeBefore, statusEquals = statusEquals, modelArnEquals = modelArnEquals, nameContains = nameContains, maxResults = maxResults, nextToken = nextToken, sortBy = sortBy, sortOrder = sortOrder)
  output <- .bedrock$list_provisioned_model_throughputs_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_provisioned_model_throughputs <- bedrock_list_provisioned_model_throughputs

#' List the tags associated with the specified resource
#'
#' @description
#' List the tags associated with the specified resource.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_list_tags_for_resource/](https://www.paws-r-sdk.com/docs/bedrock_list_tags_for_resource/) for full documentation.
#'
#' @param resourceARN &#91;required&#93; The Amazon Resource Name (ARN) of the resource.
#'
#' @keywords internal
#'
#' @rdname bedrock_list_tags_for_resource
bedrock_list_tags_for_resource <- function(resourceARN) {
  op <- new_operation(
    name = "ListTagsForResource",
    http_method = "POST",
    http_path = "/listTagsForResource",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$list_tags_for_resource_input(resourceARN = resourceARN)
  output <- .bedrock$list_tags_for_resource_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$list_tags_for_resource <- bedrock_list_tags_for_resource

#' Sets the account-level enforced guardrail configuration
#'
#' @description
#' Sets the account-level enforced guardrail configuration.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_put_enforced_guardrail_configuration/](https://www.paws-r-sdk.com/docs/bedrock_put_enforced_guardrail_configuration/) for full documentation.
#'
#' @param configId Unique ID for the account enforced configuration.
#' @param guardrailInferenceConfig &#91;required&#93; Account-level enforced guardrail input configuration.
#'
#' @keywords internal
#'
#' @rdname bedrock_put_enforced_guardrail_configuration
bedrock_put_enforced_guardrail_configuration <- function(configId = NULL, guardrailInferenceConfig) {
  op <- new_operation(
    name = "PutEnforcedGuardrailConfiguration",
    http_method = "PUT",
    http_path = "/enforcedGuardrailsConfiguration",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$put_enforced_guardrail_configuration_input(configId = configId, guardrailInferenceConfig = guardrailInferenceConfig)
  output <- .bedrock$put_enforced_guardrail_configuration_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$put_enforced_guardrail_configuration <- bedrock_put_enforced_guardrail_configuration

#' Set the configuration values for model invocation logging
#'
#' @description
#' Set the configuration values for model invocation logging.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_put_model_invocation_logging_configuration/](https://www.paws-r-sdk.com/docs/bedrock_put_model_invocation_logging_configuration/) for full documentation.
#'
#' @param loggingConfig &#91;required&#93; The logging configuration values to set.
#'
#' @keywords internal
#'
#' @rdname bedrock_put_model_invocation_logging_configuration
bedrock_put_model_invocation_logging_configuration <- function(loggingConfig) {
  op <- new_operation(
    name = "PutModelInvocationLoggingConfiguration",
    http_method = "PUT",
    http_path = "/logging/modelinvocations",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$put_model_invocation_logging_configuration_input(loggingConfig = loggingConfig)
  output <- .bedrock$put_model_invocation_logging_configuration_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$put_model_invocation_logging_configuration <- bedrock_put_model_invocation_logging_configuration

#' Adds a resource policy for a Bedrock resource
#'
#' @description
#' Adds a resource policy for a Bedrock resource.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_put_resource_policy/](https://www.paws-r-sdk.com/docs/bedrock_put_resource_policy/) for full documentation.
#'
#' @param resourceArn &#91;required&#93; The ARN of the Bedrock resource to which this resource policy applies.
#' @param resourcePolicy &#91;required&#93; The JSON string representing the Bedrock resource policy.
#'
#' @keywords internal
#'
#' @rdname bedrock_put_resource_policy
bedrock_put_resource_policy <- function(resourceArn, resourcePolicy) {
  op <- new_operation(
    name = "PutResourcePolicy",
    http_method = "POST",
    http_path = "/resource-policy",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$put_resource_policy_input(resourceArn = resourceArn, resourcePolicy = resourcePolicy)
  output <- .bedrock$put_resource_policy_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$put_resource_policy <- bedrock_put_resource_policy

#' Put usecase for model access
#'
#' @description
#' Put usecase for model access.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_put_use_case_for_model_access/](https://www.paws-r-sdk.com/docs/bedrock_put_use_case_for_model_access/) for full documentation.
#'
#' @param formData &#91;required&#93; Put customer profile Request.
#'
#' @keywords internal
#'
#' @rdname bedrock_put_use_case_for_model_access
bedrock_put_use_case_for_model_access <- function(formData) {
  op <- new_operation(
    name = "PutUseCaseForModelAccess",
    http_method = "POST",
    http_path = "/use-case-for-model-access",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$put_use_case_for_model_access_input(formData = formData)
  output <- .bedrock$put_use_case_for_model_access_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$put_use_case_for_model_access <- bedrock_put_use_case_for_model_access

#' Registers an existing Amazon SageMaker endpoint with Amazon Bedrock
#' Marketplace, allowing it to be used with Amazon Bedrock APIs
#'
#' @description
#' Registers an existing Amazon SageMaker endpoint with Amazon Bedrock Marketplace, allowing it to be used with Amazon Bedrock APIs.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_register_marketplace_model_endpoint/](https://www.paws-r-sdk.com/docs/bedrock_register_marketplace_model_endpoint/) for full documentation.
#'
#' @param endpointIdentifier &#91;required&#93; The ARN of the Amazon SageMaker endpoint you want to register with Amazon Bedrock Marketplace.
#' @param modelSourceIdentifier &#91;required&#93; The ARN of the model from Amazon Bedrock Marketplace that is deployed on the endpoint.
#'
#' @keywords internal
#'
#' @rdname bedrock_register_marketplace_model_endpoint
bedrock_register_marketplace_model_endpoint <- function(endpointIdentifier, modelSourceIdentifier) {
  op <- new_operation(
    name = "RegisterMarketplaceModelEndpoint",
    http_method = "POST",
    http_path = "/marketplace-model/endpoints/{endpointIdentifier}/registration",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$register_marketplace_model_endpoint_input(endpointIdentifier = endpointIdentifier, modelSourceIdentifier = modelSourceIdentifier)
  output <- .bedrock$register_marketplace_model_endpoint_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$register_marketplace_model_endpoint <- bedrock_register_marketplace_model_endpoint

#' Starts a new build workflow for an Automated Reasoning policy
#'
#' @description
#' 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.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_start_automated_reasoning_policy_build_workflow/](https://www.paws-r-sdk.com/docs/bedrock_start_automated_reasoning_policy_build_workflow/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy for which to start the build workflow.
#' @param buildWorkflowType &#91;required&#93; The type of build workflow to start (e.g., DOCUMENT_INGESTION for processing new documents, POLICY_REPAIR for fixing existing policies).
#' @param clientRequestToken A unique, case-sensitive identifier to ensure that the operation completes no more than once. If this token matches a previous request, Amazon Bedrock ignores the request but doesn't return an error.
#' @param sourceContent &#91;required&#93; The source content for the build workflow, such as documents to analyze or repair instructions for existing policies.
#'
#' @keywords internal
#'
#' @rdname bedrock_start_automated_reasoning_policy_build_workflow
bedrock_start_automated_reasoning_policy_build_workflow <- function(policyArn, buildWorkflowType, clientRequestToken = NULL, sourceContent) {
  op <- new_operation(
    name = "StartAutomatedReasoningPolicyBuildWorkflow",
    http_method = "POST",
    http_path = "/automated-reasoning-policies/{policyArn}/build-workflows/{buildWorkflowType}/start",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$start_automated_reasoning_policy_build_workflow_input(policyArn = policyArn, buildWorkflowType = buildWorkflowType, clientRequestToken = clientRequestToken, sourceContent = sourceContent)
  output <- .bedrock$start_automated_reasoning_policy_build_workflow_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$start_automated_reasoning_policy_build_workflow <- bedrock_start_automated_reasoning_policy_build_workflow

#' Initiates a test workflow to validate Automated Reasoning policy tests
#'
#' @description
#' Initiates a test workflow to validate Automated Reasoning policy tests. The workflow executes the specified tests against the policy and generates validation results.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_start_automated_reasoning_policy_test_workflow/](https://www.paws-r-sdk.com/docs/bedrock_start_automated_reasoning_policy_test_workflow/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy to test.
#' @param buildWorkflowId &#91;required&#93; The build workflow identifier. The build workflow must show a `COMPLETED` status before running tests.
#' @param testCaseIds The list of test identifiers to run. If not provided, all tests for the policy are run.
#' @param clientRequestToken A unique, case-sensitive identifier to ensure that the operation completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request but doesn't return an error.
#'
#' @keywords internal
#'
#' @rdname bedrock_start_automated_reasoning_policy_test_workflow
bedrock_start_automated_reasoning_policy_test_workflow <- function(policyArn, buildWorkflowId, testCaseIds = NULL, clientRequestToken = NULL) {
  op <- new_operation(
    name = "StartAutomatedReasoningPolicyTestWorkflow",
    http_method = "POST",
    http_path = "/automated-reasoning-policies/{policyArn}/build-workflows/{buildWorkflowId}/test-workflows",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$start_automated_reasoning_policy_test_workflow_input(policyArn = policyArn, buildWorkflowId = buildWorkflowId, testCaseIds = testCaseIds, clientRequestToken = clientRequestToken)
  output <- .bedrock$start_automated_reasoning_policy_test_workflow_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$start_automated_reasoning_policy_test_workflow <- bedrock_start_automated_reasoning_policy_test_workflow

#' Stops an in-progress advanced prompt optimization job
#'
#' @description
#' Stops an in-progress advanced prompt optimization job.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_stop_advanced_prompt_optimization_job/](https://www.paws-r-sdk.com/docs/bedrock_stop_advanced_prompt_optimization_job/) for full documentation.
#'
#' @param jobIdentifier &#91;required&#93; ARN or ID of the advanced prompt optimization job to stop.
#'
#' @keywords internal
#'
#' @rdname bedrock_stop_advanced_prompt_optimization_job
bedrock_stop_advanced_prompt_optimization_job <- function(jobIdentifier) {
  op <- new_operation(
    name = "StopAdvancedPromptOptimizationJob",
    http_method = "POST",
    http_path = "/advanced-prompt-optimization-jobs/{jobIdentifier}/stop",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$stop_advanced_prompt_optimization_job_input(jobIdentifier = jobIdentifier)
  output <- .bedrock$stop_advanced_prompt_optimization_job_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$stop_advanced_prompt_optimization_job <- bedrock_stop_advanced_prompt_optimization_job

#' Stops an evaluation job that is current being created or running
#'
#' @description
#' Stops an evaluation job that is current being created or running.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_stop_evaluation_job/](https://www.paws-r-sdk.com/docs/bedrock_stop_evaluation_job/) for full documentation.
#'
#' @param jobIdentifier &#91;required&#93; The Amazon Resource Name (ARN) of the evaluation job you want to stop.
#'
#' @keywords internal
#'
#' @rdname bedrock_stop_evaluation_job
bedrock_stop_evaluation_job <- function(jobIdentifier) {
  op <- new_operation(
    name = "StopEvaluationJob",
    http_method = "POST",
    http_path = "/evaluation-job/{jobIdentifier}/stop",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$stop_evaluation_job_input(jobIdentifier = jobIdentifier)
  output <- .bedrock$stop_evaluation_job_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$stop_evaluation_job <- bedrock_stop_evaluation_job

#' Stops an active model customization job
#'
#' @description
#' Stops an active model customization job. For more information, see [Custom models](https://docs.aws.amazon.com/bedrock/latest/userguide/custom-models.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_stop_model_customization_job/](https://www.paws-r-sdk.com/docs/bedrock_stop_model_customization_job/) for full documentation.
#'
#' @param jobIdentifier &#91;required&#93; Job identifier of the job to stop.
#'
#' @keywords internal
#'
#' @rdname bedrock_stop_model_customization_job
bedrock_stop_model_customization_job <- function(jobIdentifier) {
  op <- new_operation(
    name = "StopModelCustomizationJob",
    http_method = "POST",
    http_path = "/model-customization-jobs/{jobIdentifier}/stop",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$stop_model_customization_job_input(jobIdentifier = jobIdentifier)
  output <- .bedrock$stop_model_customization_job_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$stop_model_customization_job <- bedrock_stop_model_customization_job

#' Stops a batch inference job
#'
#' @description
#' Stops a batch inference job. You're only charged for tokens that were already processed. For more information, see [Stop a batch inference job](https://docs.aws.amazon.com/bedrock/latest/userguide/batch-inference-stop.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_stop_model_invocation_job/](https://www.paws-r-sdk.com/docs/bedrock_stop_model_invocation_job/) for full documentation.
#'
#' @param jobIdentifier &#91;required&#93; The Amazon Resource Name (ARN) of the batch inference job to stop.
#'
#' @keywords internal
#'
#' @rdname bedrock_stop_model_invocation_job
bedrock_stop_model_invocation_job <- function(jobIdentifier) {
  op <- new_operation(
    name = "StopModelInvocationJob",
    http_method = "POST",
    http_path = "/model-invocation-job/{jobIdentifier}/stop",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$stop_model_invocation_job_input(jobIdentifier = jobIdentifier)
  output <- .bedrock$stop_model_invocation_job_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$stop_model_invocation_job <- bedrock_stop_model_invocation_job

#' Associate tags with a resource
#'
#' @description
#' Associate tags with a resource. For more information, see [Tagging resources](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_tag_resource/](https://www.paws-r-sdk.com/docs/bedrock_tag_resource/) for full documentation.
#'
#' @param resourceARN &#91;required&#93; The Amazon Resource Name (ARN) of the resource to tag.
#' @param tags &#91;required&#93; Tags to associate with the resource.
#'
#' @keywords internal
#'
#' @rdname bedrock_tag_resource
bedrock_tag_resource <- function(resourceARN, tags) {
  op <- new_operation(
    name = "TagResource",
    http_method = "POST",
    http_path = "/tagResource",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$tag_resource_input(resourceARN = resourceARN, tags = tags)
  output <- .bedrock$tag_resource_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$tag_resource <- bedrock_tag_resource

#' Remove one or more tags from a resource
#'
#' @description
#' Remove one or more tags from a resource. For more information, see [Tagging resources](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_untag_resource/](https://www.paws-r-sdk.com/docs/bedrock_untag_resource/) for full documentation.
#'
#' @param resourceARN &#91;required&#93; The Amazon Resource Name (ARN) of the resource to untag.
#' @param tagKeys &#91;required&#93; Tag keys of the tags to remove from the resource.
#'
#' @keywords internal
#'
#' @rdname bedrock_untag_resource
bedrock_untag_resource <- function(resourceARN, tagKeys) {
  op <- new_operation(
    name = "UntagResource",
    http_method = "POST",
    http_path = "/untagResource",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$untag_resource_input(resourceARN = resourceARN, tagKeys = tagKeys)
  output <- .bedrock$untag_resource_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$untag_resource <- bedrock_untag_resource

#' Updates an existing Automated Reasoning policy with new rules,
#' variables, or configuration
#'
#' @description
#' 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.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_update_automated_reasoning_policy/](https://www.paws-r-sdk.com/docs/bedrock_update_automated_reasoning_policy/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy to update. This must be the ARN of a draft policy.
#' @param policyDefinition &#91;required&#93; The updated policy definition containing the formal logic rules, variables, and types.
#' @param name The updated name for the Automated Reasoning policy.
#' @param description The updated description for the Automated Reasoning policy.
#'
#' @keywords internal
#'
#' @rdname bedrock_update_automated_reasoning_policy
bedrock_update_automated_reasoning_policy <- function(policyArn, policyDefinition, name = NULL, description = NULL) {
  op <- new_operation(
    name = "UpdateAutomatedReasoningPolicy",
    http_method = "PATCH",
    http_path = "/automated-reasoning-policies/{policyArn}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$update_automated_reasoning_policy_input(policyArn = policyArn, policyDefinition = policyDefinition, name = name, description = description)
  output <- .bedrock$update_automated_reasoning_policy_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$update_automated_reasoning_policy <- bedrock_update_automated_reasoning_policy

#' Updates the annotations for an Automated Reasoning policy build workflow
#'
#' @description
#' Updates the annotations for an Automated Reasoning policy build workflow. This allows you to modify extracted rules, variables, and types before finalizing the policy.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_update_automated_reasoning_policy_annotations/](https://www.paws-r-sdk.com/docs/bedrock_update_automated_reasoning_policy_annotations/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy whose annotations you want to update.
#' @param buildWorkflowId &#91;required&#93; The unique identifier of the build workflow whose annotations you want to update.
#' @param annotations &#91;required&#93; The updated annotations containing modified rules, variables, and types for the policy.
#' @param lastUpdatedAnnotationSetHash &#91;required&#93; The hash value of the annotation set that you're updating. This is used for optimistic concurrency control to prevent conflicting updates.
#'
#' @keywords internal
#'
#' @rdname bedrock_update_automated_reasoning_policy_annotations
bedrock_update_automated_reasoning_policy_annotations <- function(policyArn, buildWorkflowId, annotations, lastUpdatedAnnotationSetHash) {
  op <- new_operation(
    name = "UpdateAutomatedReasoningPolicyAnnotations",
    http_method = "PATCH",
    http_path = "/automated-reasoning-policies/{policyArn}/build-workflows/{buildWorkflowId}/annotations",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$update_automated_reasoning_policy_annotations_input(policyArn = policyArn, buildWorkflowId = buildWorkflowId, annotations = annotations, lastUpdatedAnnotationSetHash = lastUpdatedAnnotationSetHash)
  output <- .bedrock$update_automated_reasoning_policy_annotations_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$update_automated_reasoning_policy_annotations <- bedrock_update_automated_reasoning_policy_annotations

#' Updates an existing Automated Reasoning policy test
#'
#' @description
#' Updates an existing Automated Reasoning policy test. You can modify the content, query, expected result, and confidence threshold.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_update_automated_reasoning_policy_test_case/](https://www.paws-r-sdk.com/docs/bedrock_update_automated_reasoning_policy_test_case/) for full documentation.
#'
#' @param policyArn &#91;required&#93; The Amazon Resource Name (ARN) of the Automated Reasoning policy that contains the test.
#' @param testCaseId &#91;required&#93; The unique identifier of the test to update.
#' @param guardContent &#91;required&#93; The updated content to be validated by the Automated Reasoning policy.
#' @param queryContent The updated input query or prompt that generated the content.
#' @param lastUpdatedAt &#91;required&#93; The timestamp when the test was last updated. This is used as a concurrency token to prevent conflicting modifications.
#' @param expectedAggregatedFindingsResult &#91;required&#93; The updated expected result of the Automated Reasoning check.
#' @param confidenceThreshold The updated minimum confidence level for logic validation. If null is provided, the threshold will be removed.
#' @param clientRequestToken A unique, case-sensitive identifier to ensure that the operation completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error.
#'
#' @keywords internal
#'
#' @rdname bedrock_update_automated_reasoning_policy_test_case
bedrock_update_automated_reasoning_policy_test_case <- function(policyArn, testCaseId, guardContent, queryContent = NULL, lastUpdatedAt, expectedAggregatedFindingsResult, confidenceThreshold = NULL, clientRequestToken = NULL) {
  op <- new_operation(
    name = "UpdateAutomatedReasoningPolicyTestCase",
    http_method = "PATCH",
    http_path = "/automated-reasoning-policies/{policyArn}/test-cases/{testCaseId}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$update_automated_reasoning_policy_test_case_input(policyArn = policyArn, testCaseId = testCaseId, guardContent = guardContent, queryContent = queryContent, lastUpdatedAt = lastUpdatedAt, expectedAggregatedFindingsResult = expectedAggregatedFindingsResult, confidenceThreshold = confidenceThreshold, clientRequestToken = clientRequestToken)
  output <- .bedrock$update_automated_reasoning_policy_test_case_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$update_automated_reasoning_policy_test_case <- bedrock_update_automated_reasoning_policy_test_case

#' Updates a custom model deployment with a new custom model
#'
#' @description
#' Updates a custom model deployment with a new custom model. This allows you to deploy updated models without creating new deployment endpoints.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_update_custom_model_deployment/](https://www.paws-r-sdk.com/docs/bedrock_update_custom_model_deployment/) for full documentation.
#'
#' @param modelArn &#91;required&#93; ARN of the new custom model to deploy. This replaces the currently deployed model.
#' @param customModelDeploymentIdentifier &#91;required&#93; Identifier of the custom model deployment to update with the new custom model.
#'
#' @keywords internal
#'
#' @rdname bedrock_update_custom_model_deployment
bedrock_update_custom_model_deployment <- function(modelArn, customModelDeploymentIdentifier) {
  op <- new_operation(
    name = "UpdateCustomModelDeployment",
    http_method = "PATCH",
    http_path = "/model-customization/custom-model-deployments/{customModelDeploymentIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$update_custom_model_deployment_input(modelArn = modelArn, customModelDeploymentIdentifier = customModelDeploymentIdentifier)
  output <- .bedrock$update_custom_model_deployment_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$update_custom_model_deployment <- bedrock_update_custom_model_deployment

#' Updates a guardrail with the values you specify
#'
#' @description
#' Updates a guardrail with the values you specify.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_update_guardrail/](https://www.paws-r-sdk.com/docs/bedrock_update_guardrail/) for full documentation.
#'
#' @param guardrailIdentifier &#91;required&#93; The unique identifier of the guardrail. This can be an ID or the ARN.
#' @param name &#91;required&#93; A name for the guardrail.
#' @param description A description of the guardrail.
#' @param topicPolicyConfig The topic policy to configure for the guardrail.
#' @param contentPolicyConfig The content policy to configure for the guardrail.
#' @param wordPolicyConfig The word policy to configure for the guardrail.
#' @param sensitiveInformationPolicyConfig The sensitive information policy to configure for the guardrail.
#' @param contextualGroundingPolicyConfig The contextual grounding policy configuration used to update a guardrail.
#' @param automatedReasoningPolicyConfig Updated configuration for Automated Reasoning policies associated with the guardrail.
#' @param crossRegionConfig The system-defined guardrail profile that you're using with your guardrail. Guardrail profiles define the destination Amazon Web Services Regions where guardrail inference requests can be automatically routed.
#' 
#' For more information, see the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/guardrails-cross-region.html).
#' @param blockedInputMessaging &#91;required&#93; The message to return when the guardrail blocks a prompt.
#' @param blockedOutputsMessaging &#91;required&#93; The message to return when the guardrail blocks a model response.
#' @param kmsKeyId The ARN of the KMS key with which to encrypt the guardrail.
#'
#' @keywords internal
#'
#' @rdname bedrock_update_guardrail
bedrock_update_guardrail <- function(guardrailIdentifier, name, description = NULL, topicPolicyConfig = NULL, contentPolicyConfig = NULL, wordPolicyConfig = NULL, sensitiveInformationPolicyConfig = NULL, contextualGroundingPolicyConfig = NULL, automatedReasoningPolicyConfig = NULL, crossRegionConfig = NULL, blockedInputMessaging, blockedOutputsMessaging, kmsKeyId = NULL) {
  op <- new_operation(
    name = "UpdateGuardrail",
    http_method = "PUT",
    http_path = "/guardrails/{guardrailIdentifier}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$update_guardrail_input(guardrailIdentifier = guardrailIdentifier, name = name, description = description, topicPolicyConfig = topicPolicyConfig, contentPolicyConfig = contentPolicyConfig, wordPolicyConfig = wordPolicyConfig, sensitiveInformationPolicyConfig = sensitiveInformationPolicyConfig, contextualGroundingPolicyConfig = contextualGroundingPolicyConfig, automatedReasoningPolicyConfig = automatedReasoningPolicyConfig, crossRegionConfig = crossRegionConfig, blockedInputMessaging = blockedInputMessaging, blockedOutputsMessaging = blockedOutputsMessaging, kmsKeyId = kmsKeyId)
  output <- .bedrock$update_guardrail_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$update_guardrail <- bedrock_update_guardrail

#' Updates the configuration of an existing endpoint for a model from
#' Amazon Bedrock Marketplace
#'
#' @description
#' Updates the configuration of an existing endpoint for a model from Amazon Bedrock Marketplace.
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_update_marketplace_model_endpoint/](https://www.paws-r-sdk.com/docs/bedrock_update_marketplace_model_endpoint/) for full documentation.
#'
#' @param endpointArn &#91;required&#93; The Amazon Resource Name (ARN) of the endpoint you want to update.
#' @param endpointConfig &#91;required&#93; The new configuration for the endpoint, including the number and type of instances to use.
#' @param clientRequestToken A unique, case-sensitive identifier that you provide to ensure the idempotency of the request. This token is listed as not required because Amazon Web Services SDKs automatically generate it for you and set this parameter. If you're not using the Amazon Web Services SDK or the CLI, you must provide this token or the action will fail.
#'
#' @keywords internal
#'
#' @rdname bedrock_update_marketplace_model_endpoint
bedrock_update_marketplace_model_endpoint <- function(endpointArn, endpointConfig, clientRequestToken = NULL) {
  op <- new_operation(
    name = "UpdateMarketplaceModelEndpoint",
    http_method = "PATCH",
    http_path = "/marketplace-model/endpoints/{endpointArn}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$update_marketplace_model_endpoint_input(endpointArn = endpointArn, endpointConfig = endpointConfig, clientRequestToken = clientRequestToken)
  output <- .bedrock$update_marketplace_model_endpoint_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$update_marketplace_model_endpoint <- bedrock_update_marketplace_model_endpoint

#' Updates the name or associated model for a Provisioned Throughput
#'
#' @description
#' Updates the name or associated model for a Provisioned Throughput. For more information, see [Provisioned Throughput](https://docs.aws.amazon.com/bedrock/latest/userguide/prov-throughput.html) in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
#'
#' See [https://www.paws-r-sdk.com/docs/bedrock_update_provisioned_model_throughput/](https://www.paws-r-sdk.com/docs/bedrock_update_provisioned_model_throughput/) for full documentation.
#'
#' @param provisionedModelId &#91;required&#93; The Amazon Resource Name (ARN) or name of the Provisioned Throughput to update.
#' @param desiredProvisionedModelName The new name for this Provisioned Throughput.
#' @param desiredModelId The Amazon Resource Name (ARN) of the new model to associate with this Provisioned Throughput. You can't specify this field if this Provisioned Throughput is associated with a base model.
#' 
#' If this Provisioned Throughput is associated with a custom model, you can specify one of the following options:
#' 
#' -   The base model from which the custom model was customized.
#' 
#' -   Another custom model that was customized from the same base model as the custom model.
#'
#' @keywords internal
#'
#' @rdname bedrock_update_provisioned_model_throughput
bedrock_update_provisioned_model_throughput <- function(provisionedModelId, desiredProvisionedModelName = NULL, desiredModelId = NULL) {
  op <- new_operation(
    name = "UpdateProvisionedModelThroughput",
    http_method = "PATCH",
    http_path = "/provisioned-model-throughput/{provisionedModelId}",
    host_prefix = "",
    paginator = list(),
    stream_api = FALSE
  )
  input <- .bedrock$update_provisioned_model_throughput_input(provisionedModelId = provisionedModelId, desiredProvisionedModelName = desiredProvisionedModelName, desiredModelId = desiredModelId)
  output <- .bedrock$update_provisioned_model_throughput_output()
  config <- get_config()
  svc <- .bedrock$service(config, op)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.bedrock$operations$update_provisioned_model_throughput <- bedrock_update_provisioned_model_throughput