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# coding=utf-8
# ------------------------------------
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# ------------------------------------
"""
FILE: sample_detect_language.py
DESCRIPTION:
This sample demonstrates how to run **language detection** over text.
USAGE:
python sample_detect_language.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 detect_language]
import os
from azure.identity import DefaultAzureCredential
from azure.ai.textanalytics import TextAnalysisClient
from azure.ai.textanalytics.models import (
TextLanguageDetectionInput,
LanguageDetectionTextInput,
LanguageInput,
AnalyzeTextLanguageDetectionResult,
)
def sample_detect_language():
# get settings
endpoint = os.environ["AZURE_TEXT_ENDPOINT"]
credential = DefaultAzureCredential()
client = TextAnalysisClient(endpoint, credential=credential)
# Build input
text_a = "Sentences in different languages."
body = TextLanguageDetectionInput(
text_input=LanguageDetectionTextInput(language_inputs=[LanguageInput(id="A", text=text_a)])
)
# Sync (non-LRO) call
result = client.analyze_text(body=body)
# Validate and print results
if not isinstance(result, AnalyzeTextLanguageDetectionResult):
print("Unexpected result type.")
return
if not result.results or not result.results.documents:
print("No documents in the response.")
return
for doc in result.results.documents:
print(f"\nDocument ID: {doc.id}")
if doc.detected_language:
dl = doc.detected_language
print(f"Detected language: {dl.name} ({dl.iso6391_name})")
print(f"Confidence score: {dl.confidence_score}")
else:
print("No detected language returned for this document.")
# [END detect_language]
def main():
sample_detect_language()
if __name__ == "__main__":
main()
|
