Amazon Bedrock
Describes the API operations for creating, managing, fine-turning, and evaluating Amazon Bedrock models.
bedrock(config = list(), credentials = list(), endpoint = NULL, region = NULL)
config: Optional configuration of credentials, endpoint, and/or region.
credentials :
creds :
profile : The name of a profile to use. If not given, then the default profile is used.
anonymous : Set anonymous credentials.
endpoint : The complete URL to use for the constructed client.
region : The AWS Region used in instantiating the client.
close_connection : Immediately close all HTTP connections.
timeout : The time in seconds till a timeout exception is thrown when attempting to make a connection. The default is 60 seconds.
s3_force_path_style : Set this to true to force the request to use path-style addressing, i.e. http://s3.amazonaws.com/BUCKET/KEY.
sts_regional_endpoint : Set sts regional endpoint resolver to regional or legacy https://docs.aws.amazon.com/sdkref/latest/guide/feature-sts-regionalized-endpoints.html
credentials: Optional credentials shorthand for the config parameter
creds :
profile : The name of a profile to use. If not given, then the default profile is used.
anonymous : Set anonymous credentials.
endpoint: Optional shorthand for complete URL to use for the constructed client.
region: Optional shorthand for AWS Region used in instantiating the client.
A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.
svc <- bedrock(
config = list(
credentials = list(
creds = list(
access_key_id = "string",
secret_access_key = "string",
session_token = "string"
),
profile = "string",
anonymous = "logical"
),
endpoint = "string",
region = "string",
close_connection = "logical",
timeout = "numeric",
s3_force_path_style = "logical",
sts_regional_endpoint = "string"
),
credentials = list(
creds = list(
access_key_id = "string",
secret_access_key = "string",
session_token = "string"
),
profile = "string",
anonymous = "logical"
),
endpoint = "string",
region = "string"
)
| batch_delete_evaluation_job | Deletes a batch of evaluation jobs |
| create_evaluation_job | Creates an evaluation job |
| create_guardrail | Creates a guardrail to block topics and to implement safeguards for your generative AI applications |
| create_guardrail_version | Creates a version of the guardrail |
| create_inference_profile | Creates an application inference profile to track metrics and costs when invoking a model |
| create_marketplace_model_endpoint | Creates an endpoint for a model from Amazon Bedrock Marketplace |
| create_model_copy_job | Copies a model to another region so that it can be used there |
| create_model_customization_job | Creates a fine-tuning job to customize a base model |
| create_model_import_job | Creates a model import job to import model that you have customized in other environments, such as Amazon SageMaker |
| create_model_invocation_job | Creates a batch inference job to invoke a model on multiple prompts |
| create_provisioned_model_throughput | Creates dedicated throughput for a base or custom model with the model units and for the duration that you specify |
| delete_custom_model | Deletes a custom model that you created earlier |
| delete_guardrail | Deletes a guardrail |
| delete_imported_model | Deletes a custom model that you imported earlier |
| delete_inference_profile | Deletes an application inference profile |
| delete_marketplace_model_endpoint | Deletes an endpoint for a model from Amazon Bedrock Marketplace |
| delete_model_invocation_logging_configuration | Delete the invocation logging |
| delete_provisioned_model_throughput | Deletes a Provisioned Throughput |
| deregister_marketplace_model_endpoint | Deregisters an endpoint for a model from Amazon Bedrock Marketplace |
| get_custom_model | Get the properties associated with a Amazon Bedrock custom model that you have created |
| get_evaluation_job | Gets information about an evaluation job, such as the status of the job |
| get_foundation_model | Get details about a Amazon Bedrock foundation model |
| get_guardrail | Gets details about a guardrail |
| get_imported_model | Gets properties associated with a customized model you imported |
| get_inference_profile | Gets information about an inference profile |
| get_marketplace_model_endpoint | Retrieves details about a specific endpoint for a model from Amazon Bedrock Marketplace |
| get_model_copy_job | Retrieves information about a model copy job |
| get_model_customization_job | Retrieves the properties associated with a model-customization job, including the status of the job |
| get_model_import_job | Retrieves the properties associated with import model job, including the status of the job |
| get_model_invocation_job | Gets details about a batch inference job |
| get_model_invocation_logging_configuration | Get the current configuration values for model invocation logging |
| get_prompt_router | Retrieves details about a prompt router |
| get_provisioned_model_throughput | Returns details for a Provisioned Throughput |
| list_custom_models | Returns a list of the custom models that you have created with the CreateModelCustomizationJob operation |
| list_evaluation_jobs | Lists all existing evaluation jobs |
| list_foundation_models | Lists Amazon Bedrock foundation models that you can use |
| list_guardrails | Lists details about all the guardrails in an account |
| list_imported_models | Returns a list of models you've imported |
| list_inference_profiles | Returns a list of inference profiles that you can use |
| list_marketplace_model_endpoints | Lists the endpoints for models from Amazon Bedrock Marketplace in your Amazon Web Services account |
| list_model_copy_jobs | Returns a list of model copy jobs that you have submitted |
| list_model_customization_jobs | Returns a list of model customization jobs that you have submitted |
| list_model_import_jobs | Returns a list of import jobs you've submitted |
| list_model_invocation_jobs | Lists all batch inference jobs in the account |
| list_prompt_routers | Retrieves a list of prompt routers |
| list_provisioned_model_throughputs | Lists the Provisioned Throughputs in the account |
| list_tags_for_resource | List the tags associated with the specified resource |
| put_model_invocation_logging_configuration | Set the configuration values for model invocation logging |
| register_marketplace_model_endpoint | Registers an existing Amazon SageMaker endpoint with Amazon Bedrock Marketplace, allowing it to be used with Amazon Bedrock APIs |
| stop_evaluation_job | Stops an evaluation job that is current being created or running |
| stop_model_customization_job | Stops an active model customization job |
| stop_model_invocation_job | Stops a batch inference job |
| tag_resource | Associate tags with a resource |
| untag_resource | Remove one or more tags from a resource |
| update_guardrail | Updates a guardrail with the values you specify |
| update_marketplace_model_endpoint | Updates the configuration of an existing endpoint for a model from Amazon Bedrock Marketplace |
| update_provisioned_model_throughput | Updates the name or associated model for a Provisioned Throughput |
## Not run: svc <- bedrock() svc$batch_delete_evaluation_job( Foo = 123 ) ## End(Not run)
Useful links