bedrockruntime: Amazon Bedrock Runtime

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

Amazon Bedrock Runtime

Description

Describes the API operations for running inference using Amazon Bedrock models.

Usage

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

Arguments

config	Optional configuration of credentials, endpoint, and/or region. credentials: creds: access_key_id: AWS access key ID secret_access_key: AWS secret access key session_token: AWS temporary session token profile: The name of a profile to use. If not given, then the default profile is used. anonymous: Set anonymous credentials. endpoint: The complete URL to use for the constructed client. region: The AWS Region used in instantiating the client. close_connection: Immediately close all HTTP connections. timeout: The time in seconds till a timeout exception is thrown when attempting to make a connection. The default is 60 seconds. s3_force_path_style: Set this to true to force the request to use path-style addressing, i.e. ⁠http://s3.amazonaws.com/BUCKET/KEY⁠. sts_regional_endpoint: Set sts regional endpoint resolver to regional or legacy https://docs.aws.amazon.com/sdkref/latest/guide/feature-sts-regionalized-endpoints.html
credentials	Optional credentials shorthand for the config parameter creds: access_key_id: AWS access key ID secret_access_key: AWS secret access key session_token: AWS temporary session token profile: The name of a profile to use. If not given, then the default profile is used. anonymous: Set anonymous credentials.
endpoint	Optional shorthand for complete URL to use for the constructed client.
region	Optional shorthand for AWS Region used in instantiating the client.

Value

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

Service syntax

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

Operations

apply_guardrail	The action to apply a guardrail
converse	Sends messages to the specified Amazon Bedrock model
converse_stream	Sends messages to the specified Amazon Bedrock model and returns the response in a stream
invoke_model	Invokes the specified Amazon Bedrock model to run inference using the prompt and inference parameters provided in the request body
invoke_model_with_response_stream	Invoke the specified Amazon Bedrock model to run inference using the prompt and inference parameters provided in the request body

Examples

## Not run: 
svc <- bedrockruntime()
svc$apply_guardrail(
  Foo = 123
)

## End(Not run)

paws.machine.learning documentation built on Sept. 12, 2024, 6:23 a.m.