將個人化 Amazon OpenSearch 服務結果與結果進行比較，

Amazon Personalize 化搜索排名插件根據來自 Amazon Personalize 化的排名和排名重新排列搜索結果。 OpenSearch外掛程式重新排名結果的方式取決於您在管道中設定personalized_search_ranking回應處理器的方式。

若要瞭解結果的排名方式，您可以使用或不使用個人化來執行查詢，並比較結果。您可以使用下面的 Python 代碼來運行兩個不同的查詢，並將結果輸出到兩個JSON文件。第一種方法運行使用插件重新排名結果的查詢。第二個執行的方法會產生結果，而不需要個人化。

import json
import requests
from requests_auth_aws_sigv4 import AWSSigV4


# Returns re-ranked OpenSearch results using the Amazon Personalize Search Ranking plugin.
def get_personalized_results(pipeline_name):
    url = f'{domain}/{index}/_search/'
    auth = AWSSigV4('es')
    headers = {'Content-Type': 'application/json'}
    params = {"search_pipeline": pipeline_name}
    body = {
        "query": {
            "multi_match": {
                "query": "Toyota",
                "fields": ["BRAND"]
            }
        },
        "ext": {
            "personalize_request_parameters": {
                "user_id": "1"
            }
        }
    }
    try:
        response = requests.post(url, auth=auth, params=params, json=body, headers=headers, verify=False)
    except Exception as e:
        return f"Error: {e}"
    return response.text


# Returns OpenSearch results without personalization.
def get_opensearch_results():
    url = f'{domain}/{index}/_search/'
    auth = AWSSigV4('es')
    headers = {'Content-Type': 'application/json'}
    body = {
        "query": {
            "multi_match": {
                "query": "Toyota",
                "fields": ["BRAND"]
            }
        }
    }
    try:
        response = requests.post(url, auth=auth, json=body, headers=headers, verify=False)
    except Exception as e:
        return f"Error: {e}"
    return response.text


def print_results(file_name, results):
    results_file = open(file_name, 'w')
    results_file.write(json.dumps(results, indent=4))
    results_file.close()


# specify domain endpoint
domain = "DOMAIN_ENDPOINT"

# specify the region where you created your Amazon Personalize resources and Amazon OpenSearch domain
aws_region = "REGION"

# specify the name of the pipeline that uses the Amazon Personalize plugin
pipeline_name = "PIPELINE_NAME"

# specify your Amazon OpenSearch index
index = "INDEX"

# specify names for json files for comparison
personalized_results_file = "personalized_results.json"
opensearch_results_file = "opensearch_results.json"

# get personalized results
personalized_results = json.loads(get_personalized_results(pipeline_name))

# get OpenSearch results without personalization
opensearch_results = json.loads(get_opensearch_results())

# print results to files
print_results(personalized_results_file, personalized_results)
print_results(opensearch_results_file, opensearch_results)