Amazon Personalize Runtime

{'filterArn': 'string'}

Returns a list of recommended items. The required input depends on the recipe type used to create the solution backing the campaign, as follows:

• RELATED_ITEMS - itemId required, userId not used

• USER_PERSONALIZATION - itemId optional, userId required

See also: AWS API Documentation

Request Syntax

client.get_recommendations(
    campaignArn='string',
    itemId='string',
    userId='string',
    numResults=123,
    context={
        'string': 'string'
    },
    filterArn='string'
)

type campaignArn:

string

param campaignArn:

[REQUIRED]

The Amazon Resource Name (ARN) of the campaign to use for getting recommendations.

type itemId:

string

param itemId:

The item ID to provide recommendations for.

Required for RELATED_ITEMS recipe type.

type userId:

string

param userId:

The user ID to provide recommendations for.

Required for USER_PERSONALIZATION recipe type.

type numResults:

integer

param numResults:

The number of results to return. The default is 25. The maximum is 500.

type context:

dict

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.

• (string) --

  • (string) --

type filterArn:

string

param filterArn:

The ARN of the filter to apply to the returned recommendations. For more information, see Using Filters with Amazon Personalize.

rtype:

dict

returns:

Response Syntax

{
    'itemList': [
        {
            'itemId': 'string',
            'score': 123.0
        },
    ]
}

Response Structure

• (dict) --

  • itemList (list) --

    A list of recommendations sorted in ascending order by prediction score. There can be a maximum of 500 items in the list.

    • (dict) --

      An object that identifies an item.

      The and APIs return a list of ``PredictedItem``s.

      • itemId (string) --

        The recommended item ID.

      • score (float) --

        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.