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# coding=utf-8
# ------------------------------------
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# ------------------------------------
"""
FILE: sample_conversation_pii_async.py
DESCRIPTION:
This sample demonstrates how to run a PII detection action over a conversation (async).
USAGE:
python sample_conversation_pii_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_pii_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 (
MultiLanguageConversationInput,
TextConversation,
TextConversationItem,
ParticipantRole,
AnalyzeConversationOperationInput,
PiiOperationAction,
ConversationPiiActionContent,
AnalyzeConversationOperationResult,
ConversationPiiOperationResult,
InputWarning,
ConversationError,
)
async def sample_conversation_pii_async():
# get settings
endpoint = os.environ["AZURE_CONVERSATIONS_ENDPOINT"]
credential = DefaultAzureCredential()
entities_detected = []
async with ConversationAnalysisClient(endpoint, credential=credential) as client:
# build input
ml_input = MultiLanguageConversationInput(
conversations=[
TextConversation(
id="1",
language="en",
conversation_items=[
TextConversationItem(
id="1",
participant_id="Agent_1",
role=ParticipantRole.AGENT,
text="Can you provide your name?",
),
TextConversationItem(
id="2",
participant_id="Customer_1",
role=ParticipantRole.CUSTOMER,
text="Hi, my name is John Doe.",
),
TextConversationItem(
id="3",
participant_id="Agent_1",
role=ParticipantRole.AGENT,
text="Thank you John, that has been updated in our system.",
),
],
)
]
)
pii_action = PiiOperationAction(
action_content=ConversationPiiActionContent(),
name="Conversation PII",
)
operation_input = AnalyzeConversationOperationInput(
conversation_input=ml_input,
actions=[pii_action],
)
# start async long-running operation
poller = await client.begin_analyze_conversation_job(body=operation_input)
# operation metadata
print(f"Operation ID: {poller.details.get('operation_id')}")
# wait for completion
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 []:
print(f"\nAction Name: {action_result.name}")
print(f"Action Status: {action_result.status}")
print(f"Kind: {action_result.kind}")
if isinstance(action_result, ConversationPiiOperationResult):
for conversation in action_result.results.conversations or []:
print(f"Conversation: #{conversation.id}")
print("Detected Entities:")
for item in conversation.conversation_items or []:
for entity in item.entities or []:
print(f" Category: {entity.category}")
print(f" Subcategory: {entity.subcategory}")
print(f" Text: {entity.text}")
print(f" Offset: {entity.offset}")
print(f" Length: {entity.length}")
print(f" Confidence score: {entity.confidence_score}\n")
entities_detected.append(entity)
if conversation.warnings:
print("Warnings:")
for warning in conversation.warnings:
if isinstance(warning, InputWarning):
print(f" Code: {warning.code}")
print(f" Message: {warning.message}")
print()
else:
print(" [No supported results to display for this action type]")
# errors
if d.get("errors"):
print("\nErrors:")
for err in d["errors"]:
print(f" Code: {err.code} - {err.message}")
# [END conversation_pii_async]
async def main():
await sample_conversation_pii_async()
if __name__ == "__main__":
loop = asyncio.get_event_loop()
loop.run_until_complete(main())
|
