R/personalizeruntime_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 personalizeruntime_service.R
NULL

#' Re-ranks a list of recommended items for the given user
#'
#' @description
#' Re-ranks a list of recommended items for the given user. The first item in the list is deemed the most likely item to be of interest to the user.
#'
#' See [https://www.paws-r-sdk.com/docs/personalizeruntime_get_personalized_ranking/](https://www.paws-r-sdk.com/docs/personalizeruntime_get_personalized_ranking/) for full documentation.
#'
#' @param campaignArn [required] The Amazon Resource Name (ARN) of the campaign to use for generating the
#' personalized ranking.
#' @param inputList [required] A list of items (by `itemId`) to rank. If an item was not included in
#' the training dataset, the item is appended to the end of the reranked
#' list. The maximum is 500.
#' @param userId [required] The user for which you want the campaign to provide a personalized
#' ranking.
#' @param context The contextual metadata to use when getting recommendations. Contextual
#' metadata includes any interaction information that might be relevant
#' when getting a user's recommendations, such as the user's current
#' location or device type.
#' @param filterArn The Amazon Resource Name (ARN) of a filter you created to include items
#' or exclude items from recommendations for a given user. For more
#' information, see [Filtering
#' Recommendations](https://docs.aws.amazon.com/personalize/latest/dg/filter.html).
#' @param filterValues The values to use when filtering recommendations. For each placeholder
#' parameter in your filter expression, provide the parameter name (in
#' matching case) as a key and the filter value(s) as the corresponding
#' value. Separate multiple values for one parameter with a comma.
#' 
#' For filter expressions that use an `INCLUDE` element to include items,
#' you must provide values for all parameters that are defined in the
#' expression. For filters with expressions that use an `EXCLUDE` element
#' to exclude items, you can omit the `filter-values`.In this case, Amazon
#' Personalize doesn't use that portion of the expression to filter
#' recommendations.
#' 
#' For more information, see [Filtering
#' Recommendations](https://docs.aws.amazon.com/personalize/latest/dg/filter.html).
#'
#' @keywords internal
#'
#' @rdname personalizeruntime_get_personalized_ranking
personalizeruntime_get_personalized_ranking <- function(campaignArn, inputList, userId, context = NULL, filterArn = NULL, filterValues = NULL) {
  op <- new_operation(
    name = "GetPersonalizedRanking",
    http_method = "POST",
    http_path = "/personalize-ranking",
    paginator = list()
  )
  input <- .personalizeruntime$get_personalized_ranking_input(campaignArn = campaignArn, inputList = inputList, userId = userId, context = context, filterArn = filterArn, filterValues = filterValues)
  output <- .personalizeruntime$get_personalized_ranking_output()
  config <- get_config()
  svc <- .personalizeruntime$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.personalizeruntime$operations$get_personalized_ranking <- personalizeruntime_get_personalized_ranking

#' Returns a list of recommended items
#'
#' @description
#' Returns a list of recommended items. For campaigns, the campaign's Amazon Resource Name (ARN) is required and the required user and item input depends on the recipe type used to create the solution backing the campaign as follows:
#'
#' See [https://www.paws-r-sdk.com/docs/personalizeruntime_get_recommendations/](https://www.paws-r-sdk.com/docs/personalizeruntime_get_recommendations/) for full documentation.
#'
#' @param campaignArn The Amazon Resource Name (ARN) of the campaign to use for getting
#' recommendations.
#' @param itemId The item ID to provide recommendations for.
#' 
#' Required for `RELATED_ITEMS` recipe type.
#' @param userId The user ID to provide recommendations for.
#' 
#' Required for `USER_PERSONALIZATION` recipe type.
#' @param numResults The number of results to return. The default is 25. The maximum is 500.
#' @param context The contextual metadata to use when getting recommendations. Contextual
#' metadata includes any interaction information that might be relevant
#' when getting a user's recommendations, such as the user's current
#' location or device type.
#' @param filterArn The ARN of the filter to apply to the returned recommendations. For more
#' information, see [Filtering
#' Recommendations](https://docs.aws.amazon.com/personalize/latest/dg/filter.html).
#' 
#' When using this parameter, be sure the filter resource is `ACTIVE`.
#' @param filterValues The values to use when filtering recommendations. For each placeholder
#' parameter in your filter expression, provide the parameter name (in
#' matching case) as a key and the filter value(s) as the corresponding
#' value. Separate multiple values for one parameter with a comma.
#' 
#' For filter expressions that use an `INCLUDE` element to include items,
#' you must provide values for all parameters that are defined in the
#' expression. For filters with expressions that use an `EXCLUDE` element
#' to exclude items, you can omit the `filter-values`.In this case, Amazon
#' Personalize doesn't use that portion of the expression to filter
#' recommendations.
#' 
#' For more information, see [Filtering recommendations and user
#' segments](https://docs.aws.amazon.com/personalize/latest/dg/filter.html).
#' @param recommenderArn The Amazon Resource Name (ARN) of the recommender to use to get
#' recommendations. Provide a recommender ARN if you created a Domain
#' dataset group with a recommender for a domain use case.
#' @param promotions The promotions to apply to the recommendation request. A promotion
#' defines additional business rules that apply to a configurable subset of
#' recommended items.
#'
#' @keywords internal
#'
#' @rdname personalizeruntime_get_recommendations
personalizeruntime_get_recommendations <- function(campaignArn = NULL, itemId = NULL, userId = NULL, numResults = NULL, context = NULL, filterArn = NULL, filterValues = NULL, recommenderArn = NULL, promotions = NULL) {
  op <- new_operation(
    name = "GetRecommendations",
    http_method = "POST",
    http_path = "/recommendations",
    paginator = list()
  )
  input <- .personalizeruntime$get_recommendations_input(campaignArn = campaignArn, itemId = itemId, userId = userId, numResults = numResults, context = context, filterArn = filterArn, filterValues = filterValues, recommenderArn = recommenderArn, promotions = promotions)
  output <- .personalizeruntime$get_recommendations_output()
  config <- get_config()
  svc <- .personalizeruntime$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.personalizeruntime$operations$get_recommendations <- personalizeruntime_get_recommendations