Performing Text Summarization

from azure.ai.textanalytics import TextAnalyticsClient, ExtractSummaryAction
from azure.core.credentials import AzureKeyCredential
client = TextAnalyticsClient(
            endpoint=text_analytics_endpoint,
            credential = AzureKeyCredential(text_analytics_key)
        )
document = [
    "The extractive summarization feature uses natural language processing techniques to locate key sentences in an unstructured text document. "
    "These sentences collectively convey the main idea of the document. This feature is provided as an API for developers. " 
    "They can use it to build intelligent solutions based on the relevant information extracted to support various use cases. "
    "In the public preview, extractive summarization supports several languages. It is based on pretrained multilingual transformer models, part of our quest for holistic representations. "
    "It draws its strength from transfer learning across monolingual and harness the shared nature of languages to produce models of improved quality and efficiency. "
]
response = client.begin_analyze_actions(document, actions=[ExtractSummaryAction(MaxSentenceCount=4)])
result = response.result()
for res in result:
    for doc_result in range(len(res)):
        print("Document Number: ", doc_result)
        
        extract_summary_result = res[doc_result]
        
        if extract_summary_result.is_error:
            print("Error Code: '{}', Error Message: '{}'".format(
                extract_summary_result.code, extract_summary_result.message))
        else:
            print("Summary extracted: \n{}".format(
                " ".join([sentence.text for sentence in extract_summary_result.sentences])))