get_action_recommendations ¶

def get_action_recommendations(
    self,
    *,
    config_overrides: Optional[PersonalizeRuntimeClientConfig] = None,
    campaign_arn: Optional["capo_personalize_runtime.types.arn.Arn"] = None,
    user_id: Optional["capo_personalize_runtime.types.user_id.UserID"] = None,
    num_results: Optional[
        "capo_personalize_runtime.types.num_results.NumResults"
    ] = None,
    filter_arn: Optional["capo_personalize_runtime.types.arn.Arn"] = None,
    filter_values: Optional[
        "capo_personalize_runtime.types.filter_values.FilterValues"
    ] = None,
) -> "capo_personalize_runtime.types.get_action_recommendations_response.GetActionRecommendationsResponse":
    """<p>Returns a list of recommended actions in sorted in descending order by prediction score. Use the <code>GetActionRecommendations</code> API if you have a custom campaign that deploys a solution version trained with a PERSONALIZED_ACTIONS recipe. </p> <p>For more information about PERSONALIZED_ACTIONS recipes, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/nexts-best-action-recipes.html">PERSONALIZED_ACTIONS recipes</a>. For more information about getting action recommendations, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/get-action-recommendations.html">Getting action recommendations</a>.</p>

    Args:
        campaign_arn: <p>The Amazon Resource Name (ARN) of the campaign to use for getting action recommendations. This campaign must deploy a solution version trained with a PERSONALIZED_ACTIONS recipe.</p>
        user_id: <p>The user ID of the user to provide action recommendations for.</p>
        num_results: <p>The number of results to return. The default is 5. The maximum is 100.</p>
        filter_arn: <p>The ARN of the filter to apply to the returned recommendations. For more information, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/filter.html">Filtering Recommendations</a>.</p> <p>When using this parameter, be sure the filter resource is <code>ACTIVE</code>.</p>
        filter_values: <p>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. </p> <p>For filter expressions that use an <code>INCLUDE</code> element to include actions, you must provide values for all parameters that are defined in the expression. For filters with expressions that use an <code>EXCLUDE</code> element to exclude actions, you can omit the <code>filter-values</code>. In this case, Amazon Personalize doesn't use that portion of the expression to filter recommendations.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/filter.html">Filtering recommendations and user segments</a>.</p>

    Raises:
        capo_personalize_runtime.errors.invalid_input_exception.InvalidInputException: <p>Provide a valid value for the field or parameter.</p>
        capo_personalize_runtime.errors.resource_not_found_exception.ResourceNotFoundException: <p>The specified resource does not exist.</p>
        capo_personalize_runtime.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_personalize_runtime.types.get_action_recommendations_request.GetActionRecommendationsRequest]",
    ) -> OperationResponse[
        "capo_personalize_runtime.types.get_action_recommendations_response.GetActionRecommendationsResponse"
    ]:
        import capo_personalize_runtime._operations.amazon_personalize_runtime.get_action_recommendations

        output, http_response = (
            capo_personalize_runtime._operations.amazon_personalize_runtime.get_action_recommendations.get_action_recommendations(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    def _redact_input(
        input_: "capo_personalize_runtime.types.get_action_recommendations_request.GetActionRecommendationsRequest",
    ) -> dict[str, Any]:
        import capo_personalize_runtime.types.get_action_recommendations_request

        return capo_personalize_runtime.types.get_action_recommendations_request.redact_sensitive(
            input_
        )

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("GetActionRecommendations", redact_input=_redact_input),
    )
    input_: capo_personalize_runtime.types.get_action_recommendations_request.GetActionRecommendationsRequest = {}
    if campaign_arn is not None:
        input_["campaign_arn"] = campaign_arn
    if user_id is not None:
        input_["user_id"] = user_id
    if num_results is not None:
        input_["num_results"] = num_results
    if filter_arn is not None:
        input_["filter_arn"] = filter_arn
    if filter_values is not None:
        input_["filter_values"] = filter_values

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output