1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
|
# coding=utf-8
# ------------------------------------
# Copyright (c) Microsoft.
# Licensed under the MIT License.
# ------------------------------------
"""
FILE: sample_recognize_pii_entities_async.py
DESCRIPTION:
This sample demonstrates how to run **PII entity recognition** over text (async).
USAGE:
python sample_recognize_pii_entities_async.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 recognize_pii_entities_async]
import os
import asyncio
from azure.identity.aio import DefaultAzureCredential
from azure.ai.textanalytics.aio import TextAnalysisClient
from azure.ai.textanalytics.models import (
MultiLanguageTextInput,
MultiLanguageInput,
TextPiiEntitiesRecognitionInput,
AnalyzeTextPiiResult,
)
async def sample_recognize_pii_entities_async():
# settings
endpoint = os.environ["AZURE_TEXT_ENDPOINT"]
credential = DefaultAzureCredential()
async with TextAnalysisClient(endpoint, credential=credential) as client:
# input
text_a = (
"Parker Doe has repaid all of their loans as of 2020-04-25. Their SSN is 859-98-0987. "
"To contact them, use their phone number 800-102-1100. They are originally from Brazil and "
"have document ID number 998.214.865-68."
)
body = TextPiiEntitiesRecognitionInput(
text_input=MultiLanguageTextInput(
multi_language_inputs=[MultiLanguageInput(id="A", text=text_a, language="en")]
)
)
# Async (non-LRO) call
result = await client.analyze_text(body=body)
# Print results
if isinstance(result, AnalyzeTextPiiResult) and result.results and result.results.documents:
for doc in result.results.documents:
print(f"\nDocument ID: {doc.id}")
if doc.entities:
print("PII Entities:")
for entity in doc.entities:
print(f" Text: {entity.text}")
print(f" Category: {entity.category}")
if entity.subcategory:
print(f" Subcategory: {entity.subcategory}")
print(f" Offset: {entity.offset}")
print(f" Length: {entity.length}")
print(f" Confidence score: {entity.confidence_score}\n")
else:
print("No PII entities found for this document.")
else:
print("No documents in the response or unexpected result type.")
# [END recognize_pii_entities_async]
async def main():
await sample_recognize_pii_entities_async()
if __name__ == "__main__":
loop = asyncio.get_event_loop()
loop.run_until_complete(main())
|
