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# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
"""
FILE: sample_transcribe_from_url_async.py
DESCRIPTION:
This sample demonstrates how to asynchronously transcribe audio from a publicly
accessible URL using the Azure AI Transcription client.
USAGE:
python sample_transcribe_from_url_async.py
Set the environment variables with your own values before running the sample:
1) AZURE_SPEECH_ENDPOINT - the endpoint to your Speech resource.
2) AZURE_SPEECH_API_KEY - your Speech API key.
"""
import asyncio
import os
async def sample_transcribe_from_url_async():
# [START transcribe_from_url_async]
from azure.core.credentials import AzureKeyCredential
from azure.ai.transcription.aio import TranscriptionClient
from azure.ai.transcription.models import TranscriptionOptions
# Get configuration from environment variables
endpoint = os.environ["AZURE_SPEECH_ENDPOINT"]
api_key = os.environ["AZURE_SPEECH_API_KEY"]
# Create the transcription client
async with TranscriptionClient(endpoint=endpoint, credential=AzureKeyCredential(api_key)) as client:
# URL to your audio file (must be publicly accessible)
audio_url = "https://example.com/path/to/audio.wav"
# Configure transcription options
options = TranscriptionOptions(locales=["en-US"])
# Transcribe the audio from URL
# The service will access and transcribe the audio directly from the URL
result = await client.transcribe_from_url(audio_url, options=options)
# Print the transcription result
print(f"Transcription: {result.combined_phrases[0].text}")
# Print duration information
if result.duration_milliseconds:
print(f"Audio duration: {result.duration_milliseconds / 1000:.2f} seconds")
# [END transcribe_from_url_async]
if __name__ == "__main__":
asyncio.run(sample_transcribe_from_url_async())
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