Services or capabilities described in Amazon Web Services documentation might vary by Region. To see the differences applicable to the China Regions, see Getting Started with Amazon Web Services in China (PDF).

Getting real-time item recommendations

You can get real-time item recommendations from an Amazon Personalize recommender or custom campaign with the Amazon Personalize console, Amazon Command Line Interface (Amazon CLI), or Amazon SDKs.

Getting item recommendations (console)

To get recommendations with the Amazon Personalize console, you provide the request information on the details page of either a recommender (Domain dataset group) or a custom campaign.

Getting item recommendations (Amazon CLI)

Use the following code to get recommendations from a campaign. To get recommendations from a recommender, replace the campaign-arn parameter with the recommender-arn.

Specify the ID of the user you want to get recommendations for, and the Amazon Resource Name (ARN) of your campaign or recommender. A list of the top 10 recommended items for the user displays. If you use User-Personalization-v2, each recommended item includes a list of reasons for why the item was included in recommendations. For more information, see Recommendation reasons with User-Personalization-v2.

To change the number of recommended items, change the value for numResults. The default is 25 items. The maximum is 500 items. If you used a RELATED_ITEMS recipe to train the solution version backing the campaign, replace the user-id parameter with item-id and specify the item ID.

If you recorded events for a user before they logged in (an anonymous user), you can get recommendations for this user by providing the sessionId from those events as if it is their userId. For more information about recording events for anonymous users, see Recording events for anonymous users.

aws personalize-runtime get-recommendations \
--campaign-arn campaign arn \
--user-id User ID \
--num-results 10

Getting item recommendations (Amazon SDKs)

The following code shows how to get Amazon Personalize recommendations for a user from a campaign with the Amazon SDKs. To get recommendations from a recommender, replace the campaignArn parameter with the recommenderArn.

Specify the ID of the user you want to get recommendations for, and the Amazon Resource Name (ARN) of your campaign or recommender. A list of the top 10 recommended items for the user displays. If you use User-Personalization-v2, each recommended item includes a list of reasons for why the item was included in recommendations. For more information, see Recommendation reasons with User-Personalization-v2.

To change the number of recommended items, change the value for numResults. The default is 25 items. The maximum is 500 items. If you used a RELATED_ITEMS recipe to train the solution version backing the campaign, replace the userId parameter with itemId and specify the item ID.

If you enabled metadata in recommendations for your campaign or recommender, you can specify the Items dataset metadata columns to include in the response. For a code sample, see Including item metadata with recommendations (Amazon SDKs). For information about enabling metadata, see Item metadata in recommendations.

If you recorded events for a user before they logged in (an anonymous user), you can get recommendations for this user by providing the sessionId from those events as if it is their userId. For more information about recording events for anonymous users, see Recording events for anonymous users.

SDK for Python (Boto3)

import boto3

personalizeRt = boto3.client('personalize-runtime')

response = personalizeRt.get_recommendations(
    campaignArn = 'Campaign ARN',
    userId = 'User ID',
    numResults = 10
)

print("Recommended items")
for item in response['itemList']:
    print (item['itemId'])

SDK for Java 2.x

    public static void getRecs(PersonalizeRuntimeClient personalizeRuntimeClient, String campaignArn, String userId) {

        try {
            GetRecommendationsRequest recommendationsRequest = GetRecommendationsRequest.builder()
                    .campaignArn(campaignArn)
                    .numResults(20)
                    .userId(userId)
                    .build();

            GetRecommendationsResponse recommendationsResponse = personalizeRuntimeClient
                    .getRecommendations(recommendationsRequest);
            List<PredictedItem> items = recommendationsResponse.itemList();
            for (PredictedItem item : items) {
                System.out.println("Item Id is : " + item.itemId());
                System.out.println("Item score is : " + item.score());
            }

        } catch (AwsServiceException e) {
            System.err.println(e.awsErrorDetails().errorMessage());
            System.exit(1);
        }
    }

SDK for JavaScript v3

// Get service clients module and commands using ES6 syntax.
import { GetRecommendationsCommand } from
  "@aws-sdk/client-personalize-runtime";

import { personalizeRuntimeClient } from "./libs/personalizeClients.js";
// Or, create the client here.
// const personalizeRuntimeClient = new PersonalizeRuntimeClient({ region: "REGION"});

// Set the recommendation request parameters.
export const getRecommendationsParam = {
  campaignArn: 'CAMPAIGN_ARN', /* required */
  userId: 'USER_ID',      /* required */
  numResults: 15    /* optional */
}

export const run = async () => {
  try {
    const response = await personalizeRuntimeClient.send(new GetRecommendationsCommand(getRecommendationsParam));
    console.log("Success!", response);
    return response; // For unit tests.
  } catch (err) {
    console.log("Error", err);
  }
};
run();