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# coding=utf-8
# ------------------------------------
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# ------------------------------------
"""
FILE: sample_conversation_summarization_async.py
DESCRIPTION:
This sample demonstrates how to summarize a conversation using CLU's conversation
summarization capability (async).
USAGE:
python sample_conversation_summarization_async.py
REQUIRED ENV VARS (for AAD / DefaultAzureCredential):
AZURE_CONVERSATIONS_ENDPOINT
AZURE_CLIENT_ID
AZURE_TENANT_ID
AZURE_CLIENT_SECRET
NOTE:
If you want to use AzureKeyCredential instead, set:
- AZURE_CONVERSATIONS_ENDPOINT
- AZURE_CONVERSATIONS_KEY
"""
# [START conversation_summarization_async]
import os
import asyncio
from azure.identity.aio import DefaultAzureCredential
from azure.ai.language.conversations.aio import ConversationAnalysisClient
from azure.ai.language.conversations.models import (
TextConversationItem,
TextConversation,
ParticipantRole,
MultiLanguageConversationInput,
SummarizationOperationAction,
ConversationSummarizationActionContent,
SummaryAspect,
AnalyzeConversationOperationInput,
SummarizationOperationResult,
ConversationError,
)
async def sample_conversation_summarization_async():
# settings
endpoint = os.environ["AZURE_CONVERSATIONS_ENDPOINT"]
credential = DefaultAzureCredential()
# Build conversation input
conversation_items = [
TextConversationItem(
id="1", participant_id="Agent_1", text="Hello, how can I help you?", role=ParticipantRole.AGENT
),
TextConversationItem(
id="2",
participant_id="Customer_1",
text="How to upgrade Office? I am getting error messages the whole day.",
role=ParticipantRole.CUSTOMER,
),
TextConversationItem(
id="3",
participant_id="Agent_1",
text="Press the upgrade button please. Then sign in and follow the instructions.",
role=ParticipantRole.AGENT,
),
]
conversation_input = MultiLanguageConversationInput(
conversations=[TextConversation(id="1", language="en", conversation_items=conversation_items)]
)
# Build the operation input and inline actions
operation_input = AnalyzeConversationOperationInput(
conversation_input=conversation_input,
actions=[
SummarizationOperationAction(
name="Issue task",
action_content=ConversationSummarizationActionContent(summary_aspects=[SummaryAspect.ISSUE]),
),
SummarizationOperationAction(
name="Resolution task",
action_content=ConversationSummarizationActionContent(summary_aspects=[SummaryAspect.RESOLUTION]),
),
],
)
async with ConversationAnalysisClient(endpoint, credential=credential) as client:
poller = await client.begin_analyze_conversation_job(body=operation_input)
# Operation ID
op_id = poller.details.get("operation_id")
if op_id:
print(f"Operation ID: {op_id}")
# Wait for result
paged_actions = await 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
async for actions_page in paged_actions:
print(
f"Completed: {actions_page.completed}, "
f"In Progress: {actions_page.in_progress}, "
f"Failed: {actions_page.failed}, "
f"Total: {actions_page.total}"
)
for action_result in actions_page.task_results or []:
if isinstance(action_result, SummarizationOperationResult):
for conversation in action_result.results.conversations or []:
print(f" Conversation ID: {conversation.id}")
print(" Summaries:")
for summary in conversation.summaries or []:
print(f" Aspect: {summary.aspect}")
print(f" Text: {summary.text}")
if conversation.warnings:
print(" Warnings:")
for warning in conversation.warnings:
print(f" Code: {warning.code}, Message: {warning.message}")
else:
print(" [No supported results to display for this action type]")
# Errors
if d.get("errors"):
print("\nErrors:")
for error in d["errors"]:
if isinstance(error, ConversationError):
print(f" Code: {error.code} - {error.message}")
# [END conversation_summarization_async]
async def main():
await sample_conversation_summarization_async()
if __name__ == "__main__":
loop = asyncio.get_event_loop()
loop.run_until_complete(main())
|
