After you create a solution, you can’t change its configuration. By default, all new solutions use automatic training. With automatic training, you incur training costs while - * your solution is active. You can't stop automatic training for a solution. To avoid unnecessary costs, make sure to delete the solution when you are finished. For information about training + *
By default, all new solutions use automatic training. With automatic training, you incur training costs while + * your solution is active. To avoid unnecessary costs, when you are finished you can + * update the solution to turn off automatic training. + * For information about training * costs, see Amazon Personalize pricing.
*Creates the configuration for training a model (creating a solution version). This configuration @@ -39,7 +41,7 @@ export interface CreateSolutionCommandOutput extends CreateSolutionResponse, __M *
** By default, new solutions use automatic training to create solution versions every 7 days. You can change the training frequency. - * Automatic solution version creation starts one hour after the solution is ACTIVE. If you manually create a solution version within + * Automatic solution version creation starts within one hour after the solution is ACTIVE. If you manually create a solution version within * the hour, the solution skips the first automatic training. For more information, * see Configuring automatic training.
*@@ -78,6 +80,11 @@ export interface CreateSolutionCommandOutput extends CreateSolutionResponse, __M *
+ * UpdateSolution + *
+ ** ListSolutions *
*Updates an Amazon Personalize solution to use a different automatic training configuration. When you update a solution, + * you can change whether the solution uses + * automatic training, and you can change the training frequency. For more information about updating a solution, see + * Updating a solution.
+ *A solution update can be in one of the + * following states:
+ *CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
+ *To get the status of a solution update, call the
+ * DescribeSolution API operation and find the status
+ * in the latestSolutionUpdate.
Provide a valid value for the field or parameter.
+ * + * @throws {@link LimitExceededException} (client fault) + *The limit on the number of requests per second has been exceeded.
+ * + * @throws {@link ResourceInUseException} (client fault) + *The specified resource is in use.
+ * + * @throws {@link ResourceNotFoundException} (client fault) + *Could not find the specified resource.
+ * + * @throws {@link PersonalizeServiceException} + *Base exception class for all service exceptions from Personalize service.
+ * + * @public + */ +export class UpdateSolutionCommand extends $Command + .classBuilder< + UpdateSolutionCommandInput, + UpdateSolutionCommandOutput, + PersonalizeClientResolvedConfig, + ServiceInputTypes, + ServiceOutputTypes + >() + .ep({ + ...commonParams, + }) + .m(function (this: any, Command: any, cs: any, config: PersonalizeClientResolvedConfig, o: any) { + return [ + getSerdePlugin(config, this.serialize, this.deserialize), + getEndpointPlugin(config, Command.getEndpointParameterInstructions()), + ]; + }) + .s("AmazonPersonalize", "UpdateSolution", {}) + .n("PersonalizeClient", "UpdateSolutionCommand") + .f(void 0, void 0) + .ser(se_UpdateSolutionCommand) + .de(de_UpdateSolutionCommand) + .build() {} diff --git a/clients/client-personalize/src/commands/index.ts b/clients/client-personalize/src/commands/index.ts index 1558cc4b67b7..5eb6c0481e97 100644 --- a/clients/client-personalize/src/commands/index.ts +++ b/clients/client-personalize/src/commands/index.ts @@ -69,3 +69,4 @@ export * from "./UpdateCampaignCommand"; export * from "./UpdateDatasetCommand"; export * from "./UpdateMetricAttributionCommand"; export * from "./UpdateRecommenderCommand"; +export * from "./UpdateSolutionCommand"; diff --git a/clients/client-personalize/src/models/models_0.ts b/clients/client-personalize/src/models/models_0.ts index 9c313e926ba4..e2d88a8bd95b 100644 --- a/clients/client-personalize/src/models/models_0.ts +++ b/clients/client-personalize/src/models/models_0.ts @@ -1766,7 +1766,7 @@ export interface CreateSolutionRequest { * configuration. For more information about automatic training, * see Configuring automatic training. *- * Automatic solution version creation starts one hour after the solution is ACTIVE. If you manually create a solution version within + * Automatic solution version creation starts within one hour after the solution is ACTIVE. If you manually create a solution version within * the hour, the solution skips the first automatic training. *
*@@ -1804,7 +1804,7 @@ export interface CreateSolutionRequest { eventType?: string; /** - *
The configuration to use with the solution. When performAutoML is set to
+ *
The configuration properties for the solution. When performAutoML is set to
* true, Amazon Personalize only evaluates the autoMLConfig section
* of the solution configuration.
The status of the recommender update.
- *A recommender can be in one of the following states:
- *CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
- *STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE
- *DELETE PENDING > DELETE IN_PROGRESS
- *The status of the recommender update. A recommender update can be in one of the following states:
+ *CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
* @public */ status?: string; @@ -3726,6 +3715,62 @@ export interface AutoMLResult { bestRecipeArn?: string; } +/** + *The configuration details of the solution update.
+ * @public + */ +export interface SolutionUpdateConfig { + /** + *The automatic training configuration to use when performAutoTraining is true.
Provides a summary of the properties of a solution update. For a complete listing, call the + * DescribeSolution API.
+ * @public + */ +export interface SolutionUpdateSummary { + /** + *The configuration details of the solution.
+ * @public + */ + solutionUpdateConfig?: SolutionUpdateConfig; + + /** + *The status of the solution update. A solution update can be in one of the following states:
+ *CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
+ * @public + */ + status?: string; + + /** + *Whether the solution automatically creates solution versions.
+ * @public + */ + performAutoTraining?: boolean; + + /** + *The date and time (in Unix format) that the solution update was created.
+ * @public + */ + creationDateTime?: Date; + + /** + *The date and time (in Unix time) that the solution update was last updated.
+ * @public + */ + lastUpdatedDateTime?: Date; + + /** + *If a solution update fails, the reason behind the failure.
+ * @public + */ + failureReason?: string; +} + /** * @public * @enum @@ -3802,8 +3847,10 @@ export interface SolutionVersionSummary { /** *After you create a solution, you can’t change its configuration. By default, all new solutions use automatic training. With automatic training, you incur training costs while - * your solution is active. You can't stop automatic training for a solution. To avoid unnecessary costs, make sure to delete the solution when you are finished. For information about training + *
By default, all new solutions use automatic training. With automatic training, you incur training costs while + * your solution is active. To avoid unnecessary costs, when you are finished you can + * update the solution to turn off automatic training. + * For information about training * costs, see Amazon Personalize pricing.
*An object that provides information about a solution. A solution includes the custom recipe, customized parameters, and @@ -3918,6 +3965,12 @@ export interface Solution { * @public */ latestSolutionVersion?: SolutionVersionSummary; + + /** + *
Provides a summary of the latest updates to the solution.
+ * @public + */ + latestSolutionUpdate?: SolutionUpdateSummary; } /** @@ -5979,6 +6032,53 @@ export interface UpdateRecommenderResponse { recommenderArn?: string; } +/** + * @public + */ +export interface UpdateSolutionRequest { + /** + *The Amazon Resource Name (ARN) of the solution to update.
+ * @public + */ + solutionArn: string | undefined; + + /** + *Whether the solution uses automatic training to create new solution versions (trained models). You can change the training
+ * frequency by specifying a schedulingExpression in the AutoTrainingConfig as part of solution
+ * configuration.
+ * If you turn on automatic training, the first automatic training starts within one hour after the solution update + * completes. If you manually create a solution version within the hour, the solution skips the first automatic training. + * For more information about automatic training, + * see Configuring automatic training. + *
+ *+ * After training starts, you can + * get the solution version's Amazon Resource Name (ARN) with the ListSolutionVersions API operation. + * To get its status, use the DescribeSolutionVersion. + *
+ * @public + */ + performAutoTraining?: boolean; + + /** + *The new configuration details of the solution.
+ * @public + */ + solutionUpdateConfig?: SolutionUpdateConfig; +} + +/** + * @public + */ +export interface UpdateSolutionResponse { + /** + *The same solution Amazon Resource Name (ARN) as given in the request.
+ * @public + */ + solutionArn?: string; +} + /** * @internal */ diff --git a/clients/client-personalize/src/protocols/Aws_json1_1.ts b/clients/client-personalize/src/protocols/Aws_json1_1.ts index 742528090b99..8ae650639eff 100644 --- a/clients/client-personalize/src/protocols/Aws_json1_1.ts +++ b/clients/client-personalize/src/protocols/Aws_json1_1.ts @@ -183,6 +183,7 @@ import { UpdateMetricAttributionCommandOutput, } from "../commands/UpdateMetricAttributionCommand"; import { UpdateRecommenderCommandInput, UpdateRecommenderCommandOutput } from "../commands/UpdateRecommenderCommand"; +import { UpdateSolutionCommandInput, UpdateSolutionCommandOutput } from "../commands/UpdateSolutionCommand"; import { Algorithm, AutoMLConfig, @@ -347,6 +348,8 @@ import { Solution, SolutionConfig, SolutionSummary, + SolutionUpdateConfig, + SolutionUpdateSummary, SolutionVersion, SolutionVersionSummary, StartRecommenderRequest, @@ -363,6 +366,7 @@ import { UpdateDatasetRequest, UpdateMetricAttributionRequest, UpdateRecommenderRequest, + UpdateSolutionRequest, } from "../models/models_0"; import { PersonalizeServiceException as __BaseException } from "../models/PersonalizeServiceException"; @@ -1276,6 +1280,19 @@ export const se_UpdateRecommenderCommand = async ( return buildHttpRpcRequest(context, headers, "/", undefined, body); }; +/** + * serializeAws_json1_1UpdateSolutionCommand + */ +export const se_UpdateSolutionCommand = async ( + input: UpdateSolutionCommandInput, + context: __SerdeContext +): Promise<__HttpRequest> => { + const headers: __HeaderBag = sharedHeaders("UpdateSolution"); + let body: any; + body = JSON.stringify(_json(input)); + return buildHttpRpcRequest(context, headers, "/", undefined, body); +}; + /** * deserializeAws_json1_1CreateBatchInferenceJobCommand */ @@ -2646,6 +2663,26 @@ export const de_UpdateRecommenderCommand = async ( return response; }; +/** + * deserializeAws_json1_1UpdateSolutionCommand + */ +export const de_UpdateSolutionCommand = async ( + output: __HttpResponse, + context: __SerdeContext +): PromiseAfter you create a solution, you can’t change its configuration. By default, all new solutions use automatic training. With automatic training, you incur training costs while\n your solution is active. You can't stop automatic training for a solution. To avoid unnecessary costs, make sure to delete the solution when you are finished. For information about training\n costs, see Amazon Personalize pricing.
\nCreates the configuration for training a model (creating a solution version). This configuration\n includes the recipe to use for model training and optional training configuration, such as columns to use\n in training and feature transformation parameters. For more information about configuring a solution, see Creating and configuring a solution.\n
\n\n By default, new solutions use automatic training to create solution versions every 7 days. You can change the training frequency.\n Automatic solution version creation starts one hour after the solution is ACTIVE. If you manually create a solution version within\n the hour, the solution skips the first automatic training. For more information,\n see Configuring automatic training.
\n\n To turn off automatic training, set performAutoTraining to false. If you turn off automatic training, you must manually create a solution version\n by calling the CreateSolutionVersion operation.
After training starts, you can\n get the solution version's Amazon Resource Name (ARN) with the ListSolutionVersions API operation. \n To get its status, use the DescribeSolutionVersion.\n
\nAfter training completes you can evaluate model accuracy by calling\n GetSolutionMetrics. When you are satisfied with the solution version, you\n deploy it using CreateCampaign. The campaign provides recommendations\n to a client through the\n GetRecommendations API.
\nAmazon Personalize doesn't support configuring the hpoObjective \n for solution hyperparameter optimization at this time.
\n Status\n
\nA solution can be in one of the following states:
\nCREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
\nDELETE PENDING > DELETE IN_PROGRESS
\nTo get the status of the solution, call DescribeSolution. If you use\n manual training, the status must be ACTIVE before you call CreateSolutionVersion.
\n Related APIs\n
\n\n ListSolutions\n
\n\n DescribeSolution\n
\n\n DeleteSolution\n
\n\n ListSolutionVersions\n
\nBy default, all new solutions use automatic training. With automatic training, you incur training costs while\n your solution is active. To avoid unnecessary costs, when you are finished you can \n update the solution to turn off automatic training. \n For information about training\n costs, see Amazon Personalize pricing.
\nCreates the configuration for training a model (creating a solution version). This configuration\n includes the recipe to use for model training and optional training configuration, such as columns to use\n in training and feature transformation parameters. For more information about configuring a solution, see Creating and configuring a solution.\n
\n\n By default, new solutions use automatic training to create solution versions every 7 days. You can change the training frequency.\n Automatic solution version creation starts within one hour after the solution is ACTIVE. If you manually create a solution version within\n the hour, the solution skips the first automatic training. For more information,\n see Configuring automatic training.
\n\n To turn off automatic training, set performAutoTraining to false. If you turn off automatic training, you must manually create a solution version\n by calling the CreateSolutionVersion operation.
After training starts, you can\n get the solution version's Amazon Resource Name (ARN) with the ListSolutionVersions API operation. \n To get its status, use the DescribeSolutionVersion.\n
\nAfter training completes you can evaluate model accuracy by calling\n GetSolutionMetrics. When you are satisfied with the solution version, you\n deploy it using CreateCampaign. The campaign provides recommendations\n to a client through the\n GetRecommendations API.
\nAmazon Personalize doesn't support configuring the hpoObjective \n for solution hyperparameter optimization at this time.
\n Status\n
\nA solution can be in one of the following states:
\nCREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
\nDELETE PENDING > DELETE IN_PROGRESS
\nTo get the status of the solution, call DescribeSolution. If you use\n manual training, the status must be ACTIVE before you call CreateSolutionVersion.
\n Related APIs\n
\n\n UpdateSolution\n
\n\n ListSolutions\n
\n\n DescribeSolution\n
\n\n DeleteSolution\n
\n\n ListSolutionVersions\n
\nWhether the solution uses automatic training to create new solution versions (trained models). The default is\n True and the solution automatically creates new solution versions every 7 days. You can change the training\n frequency by specifying a schedulingExpression in the AutoTrainingConfig as part of solution\n configuration. For more information about automatic training,\n see Configuring automatic training.
\n Automatic solution version creation starts one hour after the solution is ACTIVE. If you manually create a solution version within\n the hour, the solution skips the first automatic training.\n
\n\n After training starts, you can\n get the solution version's Amazon Resource Name (ARN) with the ListSolutionVersions API operation. \n To get its status, use the DescribeSolutionVersion.\n
" + "smithy.api#documentation": "Whether the solution uses automatic training to create new solution versions (trained models). The default is\n True and the solution automatically creates new solution versions every 7 days. You can change the training\n frequency by specifying a schedulingExpression in the AutoTrainingConfig as part of solution\n configuration. For more information about automatic training,\n see Configuring automatic training.
\n Automatic solution version creation starts within one hour after the solution is ACTIVE. If you manually create a solution version within\n the hour, the solution skips the first automatic training.\n
\n\n After training starts, you can\n get the solution version's Amazon Resource Name (ARN) with the ListSolutionVersions API operation. \n To get its status, use the DescribeSolutionVersion.\n
" } }, "recipeArn": { @@ -3172,7 +3175,7 @@ "solutionConfig": { "target": "com.amazonaws.personalize#SolutionConfig", "traits": { - "smithy.api#documentation": "The configuration to use with the solution. When performAutoML is set to\n true, Amazon Personalize only evaluates the autoMLConfig section\n of the solution configuration.
Amazon Personalize doesn't support configuring the hpoObjective \n at this time.
The configuration properties for the solution. When performAutoML is set to\n true, Amazon Personalize only evaluates the autoMLConfig section\n of the solution configuration.
Amazon Personalize doesn't support configuring the hpoObjective \n at this time.
The status of the recommender update.
\nA recommender can be in one of the following states:
\nCREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
\nSTOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE
\nDELETE PENDING > DELETE IN_PROGRESS
\nThe status of the recommender update. A recommender update can be in one of the following states:
\nCREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
" } }, "failureReason": { @@ -8399,10 +8402,16 @@ "traits": { "smithy.api#documentation": "Describes the latest version of the solution, including the status and the ARN.
" } + }, + "latestSolutionUpdate": { + "target": "com.amazonaws.personalize#SolutionUpdateSummary", + "traits": { + "smithy.api#documentation": "Provides a summary of the latest updates to the solution.
" + } } }, "traits": { - "smithy.api#documentation": "After you create a solution, you can’t change its configuration. By default, all new solutions use automatic training. With automatic training, you incur training costs while\n your solution is active. You can't stop automatic training for a solution. To avoid unnecessary costs, make sure to delete the solution when you are finished. For information about training\n costs, see Amazon Personalize pricing.
\nAn object that provides information about a solution. A solution includes the custom recipe, customized parameters, and\n trained models (Solution Versions) that Amazon Personalize uses to generate recommendations.
\nAfter you create a solution, you can’t change its configuration. If you need to make changes, you can clone the solution with the Amazon Personalize console\n or create a new one.
" + "smithy.api#documentation": "By default, all new solutions use automatic training. With automatic training, you incur training costs while\n your solution is active. To avoid unnecessary costs, when you are finished you can \n update the solution to turn off automatic training. \n For information about training\n costs, see Amazon Personalize pricing.
\nAn object that provides information about a solution. A solution includes the custom recipe, customized parameters, and\n trained models (Solution Versions) that Amazon Personalize uses to generate recommendations.
\nAfter you create a solution, you can’t change its configuration. If you need to make changes, you can clone the solution with the Amazon Personalize console\n or create a new one.
" } }, "com.amazonaws.personalize#SolutionConfig": { @@ -8505,6 +8514,61 @@ "smithy.api#documentation": "Provides a summary of the properties of a solution. For a complete listing, call the\n DescribeSolution API.
" } }, + "com.amazonaws.personalize#SolutionUpdateConfig": { + "type": "structure", + "members": { + "autoTrainingConfig": { + "target": "com.amazonaws.personalize#AutoTrainingConfig" + } + }, + "traits": { + "smithy.api#documentation": "The configuration details of the solution update.
" + } + }, + "com.amazonaws.personalize#SolutionUpdateSummary": { + "type": "structure", + "members": { + "solutionUpdateConfig": { + "target": "com.amazonaws.personalize#SolutionUpdateConfig", + "traits": { + "smithy.api#documentation": "The configuration details of the solution.
" + } + }, + "status": { + "target": "com.amazonaws.personalize#Status", + "traits": { + "smithy.api#documentation": "The status of the solution update. A solution update can be in one of the following states:
\nCREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
" + } + }, + "performAutoTraining": { + "target": "com.amazonaws.personalize#PerformAutoTraining", + "traits": { + "smithy.api#documentation": "Whether the solution automatically creates solution versions.
" + } + }, + "creationDateTime": { + "target": "com.amazonaws.personalize#Date", + "traits": { + "smithy.api#documentation": "The date and time (in Unix format) that the solution update was created.
" + } + }, + "lastUpdatedDateTime": { + "target": "com.amazonaws.personalize#Date", + "traits": { + "smithy.api#documentation": "The date and time (in Unix time) that the solution update was last updated.
" + } + }, + "failureReason": { + "target": "com.amazonaws.personalize#FailureReason", + "traits": { + "smithy.api#documentation": "If a solution update fails, the reason behind the failure.
" + } + } + }, + "traits": { + "smithy.api#documentation": "Provides a summary of the properties of a solution update. For a complete listing, call the\n DescribeSolution API.
" + } + }, "com.amazonaws.personalize#SolutionVersion": { "type": "structure", "members": { @@ -9435,6 +9499,73 @@ "traits": { "smithy.api#output": {} } + }, + "com.amazonaws.personalize#UpdateSolution": { + "type": "operation", + "input": { + "target": "com.amazonaws.personalize#UpdateSolutionRequest" + }, + "output": { + "target": "com.amazonaws.personalize#UpdateSolutionResponse" + }, + "errors": [ + { + "target": "com.amazonaws.personalize#InvalidInputException" + }, + { + "target": "com.amazonaws.personalize#LimitExceededException" + }, + { + "target": "com.amazonaws.personalize#ResourceInUseException" + }, + { + "target": "com.amazonaws.personalize#ResourceNotFoundException" + } + ], + "traits": { + "smithy.api#documentation": "Updates an Amazon Personalize solution to use a different automatic training configuration. When you update a solution, \n you can change whether the solution uses\n automatic training, and you can change the training frequency. For more information about updating a solution, see \n Updating a solution.
\nA solution update can be in one of the\n following states:
\nCREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
\nTo get the status of a solution update, call the\n DescribeSolution API operation and find the status\n in the latestSolutionUpdate.
The Amazon Resource Name (ARN) of the solution to update.
", + "smithy.api#required": {} + } + }, + "performAutoTraining": { + "target": "com.amazonaws.personalize#PerformAutoTraining", + "traits": { + "smithy.api#documentation": "Whether the solution uses automatic training to create new solution versions (trained models). You can change the training\n frequency by specifying a schedulingExpression in the AutoTrainingConfig as part of solution\n configuration.
\n If you turn on automatic training, the first automatic training starts within one hour after the solution update\n completes. If you manually create a solution version within the hour, the solution skips the first automatic training. \n For more information about automatic training,\n see Configuring automatic training.\n
\n\n After training starts, you can\n get the solution version's Amazon Resource Name (ARN) with the ListSolutionVersions API operation. \n To get its status, use the DescribeSolutionVersion.\n
" + } + }, + "solutionUpdateConfig": { + "target": "com.amazonaws.personalize#SolutionUpdateConfig", + "traits": { + "smithy.api#documentation": "The new configuration details of the solution.
" + } + } + }, + "traits": { + "smithy.api#input": {} + } + }, + "com.amazonaws.personalize#UpdateSolutionResponse": { + "type": "structure", + "members": { + "solutionArn": { + "target": "com.amazonaws.personalize#Arn", + "traits": { + "smithy.api#documentation": "The same solution Amazon Resource Name (ARN) as given in the request.
" + } + } + }, + "traits": { + "smithy.api#output": {} + } } } }