AmazonPersonalize#
- class langchain_experimental.recommenders.amazon_personalize.AmazonPersonalize(campaign_arn: str | None = None, recommender_arn: str | None = None, client: Any | None = None, credentials_profile_name: str | None = None, region_name: str | None = None)[source]#
Amazon Personalize Runtime wrapper for executing real-time operations.
See [this link for more details](https://docs.aws.amazon.com/personalize/latest/dg/API_Operations_Amazon_Personalize_Runtime.html).
- Parameters:
campaign_arn (str | None) β str, Optional: The Amazon Resource Name (ARN) of the campaign to use for getting recommendations.
recommender_arn (str | None) β str, Optional: The Amazon Resource Name (ARN) of the recommender to use to get recommendations
client (Any | None) β Optional: boto3 client
credentials_profile_name (str | None) β str, Optional :AWS profile name
region_name (str | None) β str, Optional: AWS region, e.g., us-west-2
Example
- personalize_client = AmazonPersonalize (
campaignArn=β<my-campaign-arn>β )
Methods
__init__
([campaign_arn,Β recommender_arn,Β ...])get_personalized_ranking
(user_id,Β input_list)Re-ranks a list of recommended items for the given user.
get_recommendations
([user_id,Β item_id,Β ...])Get recommendations from Amazon Personalize service.
- __init__(campaign_arn: str | None = None, recommender_arn: str | None = None, client: Any | None = None, credentials_profile_name: str | None = None, region_name: str | None = None)[source]#
- Parameters:
campaign_arn (str | None) β
recommender_arn (str | None) β
client (Any | None) β
credentials_profile_name (str | None) β
region_name (str | None) β
- get_personalized_ranking(user_id: str, input_list: List[str], filter_arn: str | None = None, filter_values: Mapping[str, str] | None = None, context: Mapping[str, str] | None = None, metadata_columns: Mapping[str, Sequence[str]] | None = None, **kwargs: Any) Mapping[str, Any] [source]#
Re-ranks a list of recommended items for the given user.
https://docs.aws.amazon.com/personalize/latest/dg/API_RS_GetPersonalizedRanking.html
- Parameters:
user_id (str) β str, Required: The user identifier for which to retrieve recommendations
input_list (List[str]) β List[str], Required: A list of items (by itemId) to rank
filter_arn (str | None) β str, Optional: The ARN of the filter to apply
filter_values (Mapping[str, str] | None) β Mapping, Optional: The values to use when filtering recommendations.
context (Mapping[str, str] | None) β Mapping, Optional: The contextual metadata to use when getting recommendations
metadata_columns (Mapping[str, Sequence[str]] | None) β Mapping, Optional: The metadata Columns to be returned as part of the response.
kwargs (Any) β
- Returns:
- Mapping[str, Any]: Returns personalizedRanking
and recommendationId.
- Return type:
response
Example
personalize_client = AmazonPersonalize(campaignArn=β<my-campaign-arn>β )
- response = personalize_client.get_personalized_ranking(user_id=β1β,
input_list=[β123,β256β])
- get_recommendations(user_id: str | None = None, item_id: str | None = None, filter_arn: str | None = None, filter_values: Mapping[str, str] | None = None, num_results: int | None = 10, context: Mapping[str, str] | None = None, promotions: Sequence[Mapping[str, Any]] | None = None, metadata_columns: Mapping[str, Sequence[str]] | None = None, **kwargs: Any) Mapping[str, Any] [source]#
Get recommendations from Amazon Personalize service.
See more details at: https://docs.aws.amazon.com/personalize/latest/dg/API_RS_GetRecommendations.html
- Parameters:
user_id (str | None) β str, Optional: The user identifier for which to retrieve recommendations
item_id (str | None) β str, Optional: The item identifier for which to retrieve recommendations
filter_arn (str | None) β str, Optional: The ARN of the filter to apply to the returned recommendations
filter_values (Mapping[str, str] | None) β Mapping, Optional: The values to use when filtering recommendations.
num_results (int | None) β int, Optional: Default=10: The number of results to return
context (Mapping[str, str] | None) β Mapping, Optional: The contextual metadata to use when getting recommendations
promotions (Sequence[Mapping[str, Any]] | None) β Sequence, Optional: The promotions to apply to the recommendation request.
metadata_columns (Mapping[str, Sequence[str]] | None) β Mapping, Optional: The metadata Columns to be returned as part of the response.
kwargs (Any) β
- Returns:
Mapping[str, Any]: Returns an itemList and recommendationId.
- Return type:
response
Example
personalize_client = AmazonPersonalize(campaignArn=β<my-campaign-arn>β )
response = personalize_client.get_recommendations(user_id=β1β)