bedrockagent: Agents for Amazon Bedrock

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

Agents for Amazon Bedrock

Description

Describes the API operations for creating and managing Amazon Bedrock agents.

Usage

bedrockagent(
  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 <- bedrockagent(
  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

associate_agent_collaborator	Makes an agent a collaborator for another agent
associate_agent_knowledge_base	Associates a knowledge base with an agent
create_agent	Creates an agent that orchestrates interactions between foundation models, data sources, software applications, user conversations, and APIs to carry out tasks to help customers
create_agent_action_group	Creates an action group for an agent
create_agent_alias	Creates an alias of an agent that can be used to deploy the agent
create_data_source	Connects a knowledge base to a data source
create_flow	Creates a prompt flow that you can use to send an input through various steps to yield an output
create_flow_alias	Creates an alias of a flow for deployment
create_flow_version	Creates a version of the flow that you can deploy
create_knowledge_base	Creates a knowledge base
create_prompt	Creates a prompt in your prompt library that you can add to a flow
create_prompt_version	Creates a static snapshot of your prompt that can be deployed to production
delete_agent	Deletes an agent
delete_agent_action_group	Deletes an action group in an agent
delete_agent_alias	Deletes an alias of an agent
delete_agent_version	Deletes a version of an agent
delete_data_source	Deletes a data source from a knowledge base
delete_flow	Deletes a flow
delete_flow_alias	Deletes an alias of a flow
delete_flow_version	Deletes a version of a flow
delete_knowledge_base	Deletes a knowledge base
delete_knowledge_base_documents	Deletes documents from a data source and syncs the changes to the knowledge base that is connected to it
delete_prompt	Deletes a prompt or a version of it, depending on whether you include the promptVersion field or not
disassociate_agent_collaborator	Disassociates an agent collaborator
disassociate_agent_knowledge_base	Disassociates a knowledge base from an agent
get_agent	Gets information about an agent
get_agent_action_group	Gets information about an action group for an agent
get_agent_alias	Gets information about an alias of an agent
get_agent_collaborator	Retrieves information about an agent's collaborator
get_agent_knowledge_base	Gets information about a knowledge base associated with an agent
get_agent_version	Gets details about a version of an agent
get_data_source	Gets information about a data source
get_flow	Retrieves information about a flow
get_flow_alias	Retrieves information about a flow
get_flow_version	Retrieves information about a version of a flow
get_ingestion_job	Gets information about a data ingestion job
get_knowledge_base	Gets information about a knoweldge base
get_knowledge_base_documents	Retrieves specific documents from a data source that is connected to a knowledge base
get_prompt	Retrieves information about the working draft (DRAFT version) of a prompt or a version of it, depending on whether you include the promptVersion field or not
ingest_knowledge_base_documents	Ingests documents directly into the knowledge base that is connected to the data source
list_agent_action_groups	Lists the action groups for an agent and information about each one
list_agent_aliases	Lists the aliases of an agent and information about each one
list_agent_collaborators	Retrieve a list of an agent's collaborators
list_agent_knowledge_bases	Lists knowledge bases associated with an agent and information about each one
list_agents	Lists the agents belonging to an account and information about each agent
list_agent_versions	Lists the versions of an agent and information about each version
list_data_sources	Lists the data sources in a knowledge base and information about each one
list_flow_aliases	Returns a list of aliases for a flow
list_flows	Returns a list of flows and information about each flow
list_flow_versions	Returns a list of information about each flow
list_ingestion_jobs	Lists the data ingestion jobs for a data source
list_knowledge_base_documents	Retrieves all the documents contained in a data source that is connected to a knowledge base
list_knowledge_bases	Lists the knowledge bases in an account
list_prompts	Returns either information about the working draft (DRAFT version) of each prompt in an account, or information about of all versions of a prompt, depending on whether you include the promptIdentifier field or not
list_tags_for_resource	List all the tags for the resource you specify
prepare_agent	Creates a DRAFT version of the agent that can be used for internal testing
prepare_flow	Prepares the DRAFT version of a flow so that it can be invoked
start_ingestion_job	Begins a data ingestion job
stop_ingestion_job	Stops a currently running data ingestion job
tag_resource	Associate tags with a resource
untag_resource	Remove tags from a resource
update_agent	Updates the configuration of an agent
update_agent_action_group	Updates the configuration for an action group for an agent
update_agent_alias	Updates configurations for an alias of an agent
update_agent_collaborator	Updates an agent's collaborator
update_agent_knowledge_base	Updates the configuration for a knowledge base that has been associated with an agent
update_data_source	Updates the configurations for a data source connector
update_flow	Modifies a flow
update_flow_alias	Modifies the alias of a flow
update_knowledge_base	Updates the configuration of a knowledge base with the fields that you specify
update_prompt	Modifies a prompt in your prompt library
validate_flow_definition	Validates the definition of a flow

Examples

## Not run: 
svc <- bedrockagent()
svc$associate_agent_collaborator(
  Foo = 123
)

## End(Not run)

paws.machine.learning documentation built on April 3, 2025, 8:41 p.m.