h&`^D      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvw(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-personalize-runtime"An object that identifies an item.The and APIs return a list of  PredictedItems.See:  smart constructor.amazonka-personalize-runtimeThe recommended item ID.amazonka-personalize-runtime;The name of the promotion that included the predicted item.amazonka-personalize-runtimeA numeric representation of the model's certainty that the item will be the next user selection. For more information on scoring logic, see how-scores-work.amazonka-personalize-runtimeCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The recommended item ID., > - The name of the promotion that included the predicted item.,  - A numeric representation of the model's certainty that the item will be the next user selection. For more information on scoring logic, see how-scores-work.amazonka-personalize-runtimeThe recommended item ID.amazonka-personalize-runtime;The name of the promotion that included the predicted item.amazonka-personalize-runtimeA numeric representation of the model's certainty that the item will be the next user selection. For more information on scoring logic, see how-scores-work.  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; amazonka-personalize-runtimeContains information on a promotion. A promotion defines additional business rules that apply to a configurable subset of recommended items.See:  smart constructor.amazonka-personalize-runtimeThe Amazon Resource Name (ARN) of the filter used by the promotion. This filter defines the criteria for promoted items. For more information, see  https://docs.aws.amazon.com/personalize/latest/dg/promoting-items.html#promotion-filtersPromotion filters.amazonka-personalize-runtimeThe values to use when promoting items. For each placeholder parameter in your promotion's 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 on creating filters, see  =https://docs.aws.amazon.com/personalize/latest/dg/filter.html+Filtering recommendations and user segments.amazonka-personalize-runtimeThe name of the promotion.amazonka-personalize-runtime>The percentage of recommended items to apply the promotion to.amazonka-personalize-runtimeCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The Amazon Resource Name (ARN) of the filter used by the promotion. This filter defines the criteria for promoted items. For more information, see  https://docs.aws.amazon.com/personalize/latest/dg/promoting-items.html#promotion-filtersPromotion filters.,  - The values to use when promoting items. For each placeholder parameter in your promotion's 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 on creating filters, see  =https://docs.aws.amazon.com/personalize/latest/dg/filter.html+Filtering recommendations and user segments.,  - The name of the promotion.,  - The percentage of recommended items to apply the promotion to.amazonka-personalize-runtimeThe Amazon Resource Name (ARN) of the filter used by the promotion. This filter defines the criteria for promoted items. For more information, see  https://docs.aws.amazon.com/personalize/latest/dg/promoting-items.html#promotion-filtersPromotion filters.amazonka-personalize-runtimeThe values to use when promoting items. For each placeholder parameter in your promotion's 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 on creating filters, see  =https://docs.aws.amazon.com/personalize/latest/dg/filter.html+Filtering recommendations and user segments.amazonka-personalize-runtimeThe name of the promotion.amazonka-personalize-runtime>The percentage of recommended items to apply the promotion to.  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%!amazonka-personalize-runtime API version  2018-05-225 of the Amazon Personalize Runtime SDK configuration."amazonka-personalize-runtime1Provide a valid value for the field or parameter.#amazonka-personalize-runtime&The specified resource does not exist.!"#!"#(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';?$amazonka-personalize-runtimeSee: > smart constructor.&amazonka-personalize-runtimeA list of recommendations sorted in descending order by prediction score. There can be a maximum of 500 items in the list.'amazonka-personalize-runtimeThe ID of the recommendation.(amazonka-personalize-runtime The response's http status code.)amazonka-personalize-runtimeSee: 4 smart constructor.+amazonka-personalize-runtimeThe Amazon Resource Name (ARN) of the campaign to use for getting recommendations.,amazonka-personalize-runtimeThe 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.-amazonka-personalize-runtimeThe ARN of the filter to apply to the returned recommendations. For more information, see  =https://docs.aws.amazon.com/personalize/latest/dg/filter.htmlFiltering Recommendations.:When using this parameter, be sure the filter resource is ACTIVE..amazonka-personalize-runtimeThe 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  =https://docs.aws.amazon.com/personalize/latest/dg/filter.html+Filtering recommendations and user segments./amazonka-personalize-runtime+The item ID to provide recommendations for. Required for  RELATED_ITEMS recipe type.0amazonka-personalize-runtimeThe number of results to return. The default is 25. The maximum is 500.1amazonka-personalize-runtimeThe promotions to apply to the recommendation request. A promotion defines additional business rules that apply to a configurable subset of recommended items.2amazonka-personalize-runtimeThe 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.3amazonka-personalize-runtime+The user ID to provide recommendations for. Required for USER_PERSONALIZATION recipe type.4amazonka-personalize-runtimeCreate a value of )" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:+, 5 - The Amazon Resource Name (ARN) of the campaign to use for getting recommendations.,, 6 - 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.), 7 - The ARN of the filter to apply to the returned recommendations. For more information, see  =https://docs.aws.amazon.com/personalize/latest/dg/filter.htmlFiltering Recommendations.:When using this parameter, be sure the filter resource is ACTIVE.), 8 - 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  =https://docs.aws.amazon.com/personalize/latest/dg/filter.html+Filtering recommendations and user segments.), 9. - The item ID to provide recommendations for. Required for  RELATED_ITEMS recipe type.0, : - The number of results to return. The default is 25. The maximum is 500.1, ; - The promotions to apply to the recommendation request. A promotion defines additional business rules that apply to a configurable subset of recommended items.2, < - 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.3, =. - The user ID to provide recommendations for. Required for USER_PERSONALIZATION recipe type.5amazonka-personalize-runtimeThe Amazon Resource Name (ARN) of the campaign to use for getting recommendations.6amazonka-personalize-runtimeThe 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.7amazonka-personalize-runtimeThe ARN of the filter to apply to the returned recommendations. For more information, see  =https://docs.aws.amazon.com/personalize/latest/dg/filter.htmlFiltering Recommendations.:When using this parameter, be sure the filter resource is ACTIVE.8amazonka-personalize-runtimeThe 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  =https://docs.aws.amazon.com/personalize/latest/dg/filter.html+Filtering recommendations and user segments.9amazonka-personalize-runtime+The item ID to provide recommendations for. Required for  RELATED_ITEMS recipe type.:amazonka-personalize-runtimeThe number of results to return. The default is 25. The maximum is 500.;amazonka-personalize-runtimeThe promotions to apply to the recommendation request. A promotion defines additional business rules that apply to a configurable subset of recommended items.<amazonka-personalize-runtimeThe 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.=amazonka-personalize-runtime+The user ID to provide recommendations for. Required for USER_PERSONALIZATION recipe type.>amazonka-personalize-runtimeCreate a value of $" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:&, ? - A list of recommendations sorted in descending order by prediction score. There can be a maximum of 500 items in the list.', @ - The ID of the recommendation.(, A# - The response's http status code.?amazonka-personalize-runtimeA list of recommendations sorted in descending order by prediction score. There can be a maximum of 500 items in the list.@amazonka-personalize-runtimeThe ID of the recommendation.Aamazonka-personalize-runtime The response's http status code.>amazonka-personalize-runtime($%&'()*,/-.+0123456789:;<=>?@A)*,/-.+0123456789:;<=$%&'(>?@A(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';[Qamazonka-personalize-runtimeSee: e smart constructor.Samazonka-personalize-runtimeA list of items in order of most likely interest to the user. The maximum is 500.Tamazonka-personalize-runtimeThe ID of the recommendation.Uamazonka-personalize-runtime The response's http status code.Vamazonka-personalize-runtimeSee: ^ smart constructor.Xamazonka-personalize-runtimeThe 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.Yamazonka-personalize-runtimeThe 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  =https://docs.aws.amazon.com/personalize/latest/dg/filter.htmlFiltering Recommendations.Zamazonka-personalize-runtimeThe 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  =https://docs.aws.amazon.com/personalize/latest/dg/filter.htmlFiltering Recommendations.[amazonka-personalize-runtimeThe Amazon Resource Name (ARN) of the campaign to use for generating the personalized ranking.\amazonka-personalize-runtimeA 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.]amazonka-personalize-runtimeThe user for which you want the campaign to provide a personalized ranking.^amazonka-personalize-runtimeCreate a value of V" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:X, _ - 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.V, ` - 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  =https://docs.aws.amazon.com/personalize/latest/dg/filter.htmlFiltering Recommendations.V, a - 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  =https://docs.aws.amazon.com/personalize/latest/dg/filter.htmlFiltering Recommendations.[, b - The Amazon Resource Name (ARN) of the campaign to use for generating the personalized ranking.\, c - 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.], d - The user for which you want the campaign to provide a personalized ranking._amazonka-personalize-runtimeThe 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.`amazonka-personalize-runtimeThe 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  =https://docs.aws.amazon.com/personalize/latest/dg/filter.htmlFiltering Recommendations.aamazonka-personalize-runtimeThe 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  =https://docs.aws.amazon.com/personalize/latest/dg/filter.htmlFiltering Recommendations.bamazonka-personalize-runtimeThe Amazon Resource Name (ARN) of the campaign to use for generating the personalized ranking.camazonka-personalize-runtimeA 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.damazonka-personalize-runtimeThe user for which you want the campaign to provide a personalized ranking.eamazonka-personalize-runtimeCreate a value of Q" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:S, f - A list of items in order of most likely interest to the user. The maximum is 500.T, g - The ID of the recommendation.U, h# - The response's http status code.famazonka-personalize-runtimeA list of items in order of most likely interest to the user. The maximum is 500.gamazonka-personalize-runtimeThe ID of the recommendation.hamazonka-personalize-runtime The response's http status code.^amazonka-personalize-runtime[amazonka-personalize-runtime]eamazonka-personalize-runtimeUQRTUSVWXYZ[]\^_`abcdefghVWXYZ[]\^_`abcdQRTUSefgh(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred\56789:;<=?@A_`abcdfgh_`abcdfgh56789:;<=?@A(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%]}(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred^!"#$%)*4>QRVW^e!"#VW^QRe)*4$%>      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~7amazonka-personalize-runtime-2.0-F3C1CsdiQVG5CxrVfC5dKS/Amazonka.PersonalizeRuntime.Types.PredictedItem+Amazonka.PersonalizeRuntime.Types.Promotion!Amazonka.PersonalizeRuntime.Types.Amazonka.PersonalizeRuntime.GetRecommendations2Amazonka.PersonalizeRuntime.GetPersonalizedRanking Amazonka.PersonalizeRuntime.Lens#Amazonka.PersonalizeRuntime.WaitersAmazonka.PersonalizeRuntime PredictedItemPredictedItem'$sel:itemId:PredictedItem'!$sel:promotionName:PredictedItem'$sel:score:PredictedItem'newPredictedItempredictedItem_itemIdpredictedItem_promotionNamepredictedItem_score$fNFDataPredictedItem$fHashablePredictedItem$fFromJSONPredictedItem$fEqPredictedItem$fReadPredictedItem$fShowPredictedItem$fGenericPredictedItem Promotion Promotion'$sel:filterArn:Promotion'$sel:filterValues:Promotion'$sel:name:Promotion'$$sel:percentPromotedItems:Promotion' newPromotionpromotion_filterArnpromotion_filterValuespromotion_namepromotion_percentPromotedItems$fToJSONPromotion$fNFDataPromotion$fHashablePromotion $fEqPromotion$fShowPromotion$fGenericPromotiondefaultService_InvalidInputException_ResourceNotFoundExceptionGetRecommendationsResponseGetRecommendationsResponse')$sel:itemList:GetRecommendationsResponse'1$sel:recommendationId:GetRecommendationsResponse'+$sel:httpStatus:GetRecommendationsResponse'GetRecommendationsGetRecommendations'$$sel:campaignArn:GetRecommendations' $sel:context:GetRecommendations'"$sel:filterArn:GetRecommendations'%$sel:filterValues:GetRecommendations'$sel:itemId:GetRecommendations'#$sel:numResults:GetRecommendations'#$sel:promotions:GetRecommendations''$sel:recommenderArn:GetRecommendations'$sel:userId:GetRecommendations'newGetRecommendationsgetRecommendations_campaignArngetRecommendations_contextgetRecommendations_filterArngetRecommendations_filterValuesgetRecommendations_itemIdgetRecommendations_numResultsgetRecommendations_promotions!getRecommendations_recommenderArngetRecommendations_userIdnewGetRecommendationsResponse#getRecommendationsResponse_itemList+getRecommendationsResponse_recommendationId%getRecommendationsResponse_httpStatus$fToQueryGetRecommendations$fToPathGetRecommendations$fToJSONGetRecommendations$fToHeadersGetRecommendations$fNFDataGetRecommendations$fHashableGetRecommendations"$fNFDataGetRecommendationsResponse$fAWSRequestGetRecommendations$fEqGetRecommendationsResponse $fReadGetRecommendationsResponse $fShowGetRecommendationsResponse#$fGenericGetRecommendationsResponse$fEqGetRecommendations$fShowGetRecommendations$fGenericGetRecommendationsGetPersonalizedRankingResponseGetPersonalizedRankingResponse'8$sel:personalizedRanking:GetPersonalizedRankingResponse'5$sel:recommendationId:GetPersonalizedRankingResponse'/$sel:httpStatus:GetPersonalizedRankingResponse'GetPersonalizedRankingGetPersonalizedRanking'$$sel:context:GetPersonalizedRanking'&$sel:filterArn:GetPersonalizedRanking')$sel:filterValues:GetPersonalizedRanking'($sel:campaignArn:GetPersonalizedRanking'&$sel:inputList:GetPersonalizedRanking'#$sel:userId:GetPersonalizedRanking'newGetPersonalizedRankinggetPersonalizedRanking_context getPersonalizedRanking_filterArn#getPersonalizedRanking_filterValues"getPersonalizedRanking_campaignArn getPersonalizedRanking_inputListgetPersonalizedRanking_userId!newGetPersonalizedRankingResponse2getPersonalizedRankingResponse_personalizedRanking/getPersonalizedRankingResponse_recommendationId)getPersonalizedRankingResponse_httpStatus$fToQueryGetPersonalizedRanking$fToPathGetPersonalizedRanking$fToJSONGetPersonalizedRanking!$fToHeadersGetPersonalizedRanking$fNFDataGetPersonalizedRanking $fHashableGetPersonalizedRanking&$fNFDataGetPersonalizedRankingResponse"$fAWSRequestGetPersonalizedRanking"$fEqGetPersonalizedRankingResponse$$fReadGetPersonalizedRankingResponse$$fShowGetPersonalizedRankingResponse'$fGenericGetPersonalizedRankingResponse$fEqGetPersonalizedRanking$fShowGetPersonalizedRanking$fGenericGetPersonalizedRanking