# coding=utf-8 # ------------------------------------ # Copyright (c) Microsoft Corporation. # Licensed under the MIT License. # ------------------------------------ """ FILE: sample_text_extractive_summarization.py DESCRIPTION: This sample demonstrates how to run an **extractive summarization** action over text. USAGE: python sample_text_extractive_summarization.py REQUIRED ENV VARS (for AAD / DefaultAzureCredential): AZURE_TEXT_ENDPOINT AZURE_CLIENT_ID AZURE_TENANT_ID AZURE_CLIENT_SECRET NOTE: If you want to use AzureKeyCredential instead, set: - AZURE_TEXT_ENDPOINT - AZURE_TEXT_KEY """ # [START text_extractive_summarization] import os from azure.identity import DefaultAzureCredential from azure.ai.textanalytics import TextAnalysisClient from azure.ai.textanalytics.models import ( MultiLanguageTextInput, MultiLanguageInput, ExtractiveSummarizationOperationAction, ExtractiveSummarizationOperationResult, ) def sample_text_extractive_summarization(): # get settings endpoint = os.environ["AZURE_TEXT_ENDPOINT"] credential = DefaultAzureCredential() client = TextAnalysisClient(endpoint, credential=credential) # Build input text_a = ( "Windows 365 was in the works before COVID-19 sent companies around the world on a scramble to secure " "solutions to support employees suddenly forced to work from home, but “what really put the " "firecracker behind it was the pandemic, it accelerated everything,” McKelvey said. She explained " "that customers were asking, “How do we create an experience for people that makes them still feel " "connected to the company without the physical presence of being there?” In this new world of " "Windows 365, remote workers flip the lid on their laptop, boot up the family workstation or clip a " "keyboard onto a tablet, launch a native app or modern web browser and login to their Windows 365 " "account. From there, their Cloud PC appears with their background, apps, settings and content just " "as they left it when they last were last there – in the office, at home or a coffee shop. And " "then, when you’re done, you’re done. You won’t have any issues around security because you’re not " "saving anything on your device,” McKelvey said, noting that all the data is stored in the cloud. " "The ability to login to a Cloud PC from anywhere on any device is part of Microsoft’s larger " "strategy around tailoring products such as Microsoft Teams and Microsoft 365 for the post-pandemic " "hybrid workforce of the future, she added. It enables employees accustomed to working from home to " "continue working from home; it enables companies to hire interns from halfway around the world; it " "allows startups to scale without requiring IT expertise. “I think this will be interesting for " "those organizations who, for whatever reason, have shied away from virtualization. This is giving " "them an opportunity to try it in a way that their regular, everyday endpoint admin could manage,” " "McKelvey said. The simplicity of Windows 365 won over Dean Wells, the corporate chief information " "officer for the Government of Nunavut. His team previously attempted to deploy a traditional " "virtual desktop infrastructure and found it inefficient and unsustainable given the limitations of " "low-bandwidth satellite internet and the constant need for IT staff to manage the network and " "infrastructure. We didn’t run it for very long,” he said. “It didn’t turn out the way we had " "hoped. So, we actually had terminated the project and rolled back out to just regular PCs.” He " "re-evaluated this decision after the Government of Nunavut was hit by a ransomware attack in " "November 2019 that took down everything from the phone system to the government’s servers. " "Microsoft helped rebuild the system, moving the government to Teams, SharePoint, OneDrive and " "Microsoft 365. Manchester’s team recruited the Government of Nunavut to pilot Windows 365. Wells " "was intrigued, especially by the ability to manage the elastic workforce securely and seamlessly. " "“The impact that I believe we are finding, and the impact that we’re going to find going forward, " "is being able to access specialists from outside the territory and organizations outside the " "territory to come in and help us with our projects, being able to get people on staff with us to " "help us deliver the day-to-day expertise that we need to run the government,” he said. “Being able " "to improve healthcare, being able to improve education, economic development is going to improve " "the quality of life in the communities.”" ) text_input = MultiLanguageTextInput(multi_language_inputs=[MultiLanguageInput(id="A", text=text_a, language="en")]) action = ExtractiveSummarizationOperationAction(name="Extractive Summarization") # Start long-running operation (sync) poller = client.begin_analyze_text_job( text_input=text_input, actions=[action], ) # Operation metadata (pre-final) print(f"Operation ID: {poller.details.get('operation_id')}") # Wait for completion and get pageable of TextActions paged_actions = poller.result() # Final-state metadata d = poller.details print(f"Job ID: {d.get('job_id')}") print(f"Status: {d.get('status')}") print(f"Created: {d.get('created_date_time')}") print(f"Last Updated: {d.get('last_updated_date_time')}") if d.get("expiration_date_time"): print(f"Expires: {d.get('expiration_date_time')}") if d.get("display_name"): print(f"Display Name: {d.get('display_name')}") # Iterate results (sync pageable) for actions_page in paged_actions: # Page-level counts (if available) print( f"Completed: {actions_page.completed}, " f"In Progress: {actions_page.in_progress}, " f"Failed: {actions_page.failed}, " f"Total: {actions_page.total}" ) # Items are the individual operation results for op_result in actions_page.items_property or []: if isinstance(op_result, ExtractiveSummarizationOperationResult): print(f"\nAction Name: {op_result.task_name}") print(f"Action Status: {op_result.status}") print(f"Kind: {op_result.kind}") result = op_result.results for doc in result.documents or []: print(f"\nDocument ID: {doc.id}") for sent in doc.sentences or []: # Each sentence is part of the extractive summary print(f" Sentence: {sent.text}") print(f" Rank score: {sent.rank_score}") print(f" Offset: {sent.offset}") print(f" Length: {sent.length}") else: # Other action kinds, if present try: print( f"\n[Non-extractive action] name={op_result.task_name}, " f"status={op_result.status}, kind={op_result.kind}" ) except Exception: print("\n[Non-extractive action present]") # [END text_extractive_summarization] def main(): sample_text_extractive_summarization() if __name__ == "__main__": main()