# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: MIT-0 """ Amazon SageMaker resolver that invokes an inference endpoint for a SageMaker model """ import boto3 import json import codecs from typing import Dict, List, Union from http import HTTPStatus from aws_lambda_powertools import Logger, Tracer from personalization_error import SageMakerError from personalization_constants import ACTION_RECOMMEND_ITEMS, ACTION_RELATED_ITEMS, ACTION_RERANK_ITEMS tracer = Tracer() logger = Logger(child=True) PAYLOAD_VERSION = '1.0' class SageMakerResolver(): def __init__( self, sagemaker = boto3.client('sagemaker-runtime') ): self.sagemaker = sagemaker def _invoke_endpoint(self, endpoint_name: str, context: Dict, payload: Dict) -> Dict: if context: if isinstance(context, str): context = json.loads(context) payload['context'] = context response = self.sagemaker.invoke_endpoint( EndpointName = endpoint_name, ContentType = 'application/json', Accept = 'application/json', Body = codecs.encode(json.dumps(payload)) ) logger.debug(response) return json.load(response.get('Body')) @tracer.capture_method def get_recommend_items(self, recommender_path: str, recommender_config: Dict, variation_config: Dict, user_id: str, num_results: int = 25, context: Union[str,Dict] = None) -> Dict: endpoint_name = variation_config.get('endpointName') if not endpoint_name: raise SageMakerError(HTTPStatus.NOT_FOUND, 'EndpointNameNotConfigured', 'Endpoint name has not been configured for this namespace and recommender name') logger.debug('Invoking SageMaker endpoint %s for recommend-items recommendation type', endpoint_name) payload = { 'version': PAYLOAD_VERSION, 'action': ACTION_RECOMMEND_ITEMS, 'recommender': { 'path': recommender_path, 'config': recommender_config }, 'variation': variation_config, 'userId': user_id, 'numResults': num_results } return self._invoke_endpoint(endpoint_name, context, payload) @tracer.capture_method def get_related_items(self, recommender_path: str, recommender_config: Dict, variation_config: Dict, item_id: str, num_results: int = 25, user_id: str = None, context: Union[str,Dict] = None) -> Dict: endpoint_name = variation_config.get('endpointName') if not endpoint_name: raise SageMakerError(HTTPStatus.NOT_FOUND, 'EndpointNameNotConfigured', 'Endpoint name has not been configured for this namespace and recommender name') logger.debug('Invoking SageMaker endpoint %s for related-items recommendation type', endpoint_name) payload = { 'version': PAYLOAD_VERSION, 'action': ACTION_RELATED_ITEMS, 'recommender': { 'path': recommender_path, 'config': recommender_config }, 'variation': variation_config, 'itemId': item_id, 'userId': (user_id if user_id else ''), 'numResults': num_results } return self._invoke_endpoint(endpoint_name, context, payload) @tracer.capture_method def rerank_items(self, recommender_path: str, recommender_config: Dict, variation_config: Dict, user_id: str, input_list: List[str], context: Union[str,Dict] = None) -> Dict: endpoint_name = variation_config.get('endpointName') if not endpoint_name: raise SageMakerError(HTTPStatus.NOT_FOUND, 'EndpointNameNotConfigured', 'Endpoint name has not been configured for this namespace and recommender name') logger.debug('Invoking SageMaker endpoint %s for rerank-items recommendation type', endpoint_name) payload = { 'version': PAYLOAD_VERSION, 'action': ACTION_RERANK_ITEMS, 'recommender': { 'path': recommender_path, 'config': recommender_config }, 'variation': variation_config, 'userId': user_id, 'itemList': input_list } return self._invoke_endpoint(endpoint_name, context, payload)