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sample_dynamic_classification_async.py
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sample_dynamic_classification_async.py
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# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
"""
FILE: sample_dynamic_classification_async.py
DESCRIPTION:
This sample demonstrates how to dynamically classify documents into one or multiple categories.
No model training is required to use dynamic classification.
The dynamic classification feature is part of a gated preview. Request access here:
https://aka.ms/applyforgatedlanguagefeature
USAGE:
python sample_dynamic_classification_async.py
Set the environment variables with your own values before running the sample:
1) AZURE_LANGUAGE_ENDPOINT - the endpoint to your Language resource.
2) AZURE_LANGUAGE_KEY - your Language subscription key
"""
import asyncio
async def sample_dynamic_classification_async() -> None:
# [START dynamic_classification_async]
import os
from azure.core.credentials import AzureKeyCredential
from azure.ai.textanalytics.aio import TextAnalyticsClient
endpoint = os.environ["AZURE_LANGUAGE_ENDPOINT"]
key = os.environ["AZURE_LANGUAGE_KEY"]
text_analytics_client = TextAnalyticsClient(
endpoint=endpoint,
credential=AzureKeyCredential(key),
)
documents = [
"The WHO is issuing a warning about Monkey Pox.",
"Mo Salah plays in Liverpool FC in England.",
]
async with text_analytics_client:
results = await text_analytics_client.dynamic_classification(
documents,
categories=["Health", "Politics", "Music", "Sports"],
classification_type="Multi"
)
for doc, classification_result in zip(documents, results):
if classification_result.kind == "DynamicClassification":
classifications = classification_result.classifications
print(f"\n'{doc}' classifications:\n")
for classification in classifications:
print("Category '{}' with confidence score {}.".format(
classification.category, classification.confidence_score
))
elif classification_result.is_error is True:
print("Document '{}' has an error with code '{}' and message '{}'".format(
doc, classification_result.error.code, classification_result.error.message
))
# [END dynamic_classification_async]
if __name__ == "__main__":
asyncio.run(sample_dynamic_classification_async())