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# coding=utf-8
# ------------------------------------
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# ------------------------------------
"""
FILE: sample_conv_pii_transcript_input.py
DESCRIPTION:
This sample demonstrates how to analyze a conversation for PII (personally identifiable information).
For more info about how to setup a CLU conversation project, see the README.
USAGE:
python sample_conv_pii_transcript_input.py
Set the environment variables with your own values before running the sample:
1) AZURE_CONVERSATIONS_ENDPOINT - endpoint for your CLU resource.
2) AZURE_CONVERSATIONS_KEY - API key for your CLU resource.
"""
def sample_conv_pii_transcript_input():
# [START analyze_conversation_app]
# import libraries
import os
from azure.core.credentials import AzureKeyCredential
from azure.ai.language.conversations import ConversationAnalysisClient
# get secrets
endpoint = os.environ["AZURE_CONVERSATIONS_ENDPOINT"]
key = os.environ["AZURE_CONVERSATIONS_KEY"]
# analyze quey
client = ConversationAnalysisClient(endpoint, AzureKeyCredential(key))
with client:
poller = client.begin_conversation_analysis(
task={
"displayName": "Analyze PII in conversation",
"analysisInput": {
"conversations": [
{
"conversationItems": [
{
"id": "1",
"participantId": "0",
"modality": "transcript",
"text": "It is john doe.",
"lexical": "It is john doe",
"itn": "It is john doe",
"maskedItn": "It is john doe"
},
{
"id": "2",
"participantId": "1",
"modality": "transcript",
"text": "Yes, 633-27-8199 is my phone",
"lexical": "yes six three three two seven eight one nine nine is my phone",
"itn": "yes 633278199 is my phone",
"maskedItn": "yes 633278199 is my phone",
},
{
"id": "3",
"participantId": "1",
"modality": "transcript",
"text": "j.doe@yahoo.com is my email",
"lexical": "j dot doe at yahoo dot com is my email",
"maskedItn": "j.doe@yahoo.com is my email",
"itn": "j.doe@yahoo.com is my email",
}
],
"modality": "transcript",
"id": "1",
"language": "en"
}
]
},
"tasks": [
{
"kind": "ConversationalPIITask",
"parameters": {
"redactionSource": "lexical",
"piiCategories": [
"all"
]
}
}
]
}
)
# view result
result = poller.result()
task_result = result["tasks"]["items"][0]
print("... view task status ...")
print(f"status: {task_result['status']}")
conv_pii_result = task_result["results"]
if conv_pii_result["errors"]:
print("... errors occurred ...")
for error in conv_pii_result["errors"]:
print(error)
else:
conversation_result = conv_pii_result["conversations"][0]
if conversation_result["warnings"]:
print("... view warnings ...")
for warning in conversation_result["warnings"]:
print(warning)
else:
print("... view task result ...")
for conversation in conversation_result["conversationItems"]:
print(f"conversation id: {conversation['id']}")
print("... entities ...")
for entity in conversation["entities"]:
print(f"text: {entity['text']}")
print(f"category: {entity['category']}")
print(f"confidence: {entity['confidenceScore']}")
print(f"offset: {entity['offset']}")
print(f"length: {entity['length']}")
# [END analyze_conversation_app]
if __name__ == '__main__':
sample_conv_pii_transcript_input()
|
