lexmodelbuildingservice: Amazon Lex Model Building Service

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

Amazon Lex Model Building Service

Description

Amazon Lex Build-Time Actions

Amazon Lex is an AWS service for building conversational voice and text interfaces. Use these actions to create, update, and delete conversational bots for new and existing client applications.

Usage

lexmodelbuildingservice(
  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 <- lexmodelbuildingservice(
  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

create_bot_version	Creates a new version of the bot based on the $LATEST version
create_intent_version	Creates a new version of an intent based on the $LATEST version of the intent
create_slot_type_version	Creates a new version of a slot type based on the $LATEST version of the specified slot type
delete_bot	Deletes all versions of the bot, including the $LATEST version
delete_bot_alias	Deletes an alias for the specified bot
delete_bot_channel_association	Deletes the association between an Amazon Lex bot and a messaging platform
delete_bot_version	Deletes a specific version of a bot
delete_intent	Deletes all versions of the intent, including the $LATEST version
delete_intent_version	Deletes a specific version of an intent
delete_slot_type	Deletes all versions of the slot type, including the $LATEST version
delete_slot_type_version	Deletes a specific version of a slot type
delete_utterances	Deletes stored utterances
get_bot	Returns metadata information for a specific bot
get_bot_alias	Returns information about an Amazon Lex bot alias
get_bot_aliases	Returns a list of aliases for a specified Amazon Lex bot
get_bot_channel_association	Returns information about the association between an Amazon Lex bot and a messaging platform
get_bot_channel_associations	Returns a list of all of the channels associated with the specified bot
get_bots	Returns bot information as follows:
get_bot_versions	Gets information about all of the versions of a bot
get_builtin_intent	Returns information about a built-in intent
get_builtin_intents	Gets a list of built-in intents that meet the specified criteria
get_builtin_slot_types	Gets a list of built-in slot types that meet the specified criteria
get_export	Exports the contents of a Amazon Lex resource in a specified format
get_import	Gets information about an import job started with the StartImport operation
get_intent	Returns information about an intent
get_intents	Returns intent information as follows:
get_intent_versions	Gets information about all of the versions of an intent
get_migration	Provides details about an ongoing or complete migration from an Amazon Lex V1 bot to an Amazon Lex V2 bot
get_migrations	Gets a list of migrations between Amazon Lex V1 and Amazon Lex V2
get_slot_type	Returns information about a specific version of a slot type
get_slot_types	Returns slot type information as follows:
get_slot_type_versions	Gets information about all versions of a slot type
get_utterances_view	Use the GetUtterancesView operation to get information about the utterances that your users have made to your bot
list_tags_for_resource	Gets a list of tags associated with the specified resource
put_bot	Creates an Amazon Lex conversational bot or replaces an existing bot
put_bot_alias	Creates an alias for the specified version of the bot or replaces an alias for the specified bot
put_intent	Creates an intent or replaces an existing intent
put_slot_type	Creates a custom slot type or replaces an existing custom slot type
start_import	Starts a job to import a resource to Amazon Lex
start_migration	Starts migrating a bot from Amazon Lex V1 to Amazon Lex V2
tag_resource	Adds the specified tags to the specified resource
untag_resource	Removes tags from a bot, bot alias or bot channel

Examples

## Not run: 
svc <- lexmodelbuildingservice()
# This example shows how to get configuration information for a bot.
svc$get_bot(
  name = "DocOrderPizza",
  versionOrAlias = "$LATEST"
)

## End(Not run)

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