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Build real-time voice AI applications using Azure AI Voice Live SDK (azure-ai-voicelive).
Passed 22 of 22 test cases with the skill, and 9 of 22 without it.
and 18 more in the full report
13 fixed9 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.
Write an async Python function that accepts raw PCM16 microphone audio bytes and sends them to an active Azure Voice Live connection input buffer.
| Checked | Without skill | With skill |
|---|---|---|
| Encodes raw audio bytes to base64 prior to buffer append | Passed | Passed |
| Calls conn.input_audio_buffer.append with base64 string | Missed | Passed |
The instructions your model reads when the skill loads.
Build real-time voice AI applications with bidirectional WebSocket communication.
pip install azure-ai-voicelive aiohttp azure-identity
AZURE_COGNITIVE_SERVICES_ENDPOINT=https://<region>.api.cognitive.microsoft.com # Required for all auth methods
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production
AZURE_COGNITIVE_SERVICES_KEY=<api-key> # Only required for the legacy API-key auth path below
🔑 Two rules apply to every code sample below:
- Prefer
DefaultAzureCredential. It works locally (Azure CLI / VS Code / Developer CLI) and in Azure (managed identity, workload identity) with no code change. Avoid connection strings, account/API keys — they bypass Entra audit and rotation.
- Local dev:
DefaultAzureCredentialworks as-is.- Production: set
AZURE_TOKEN_CREDENTIALS=prod(orAZURE_TOKEN_CREDENTIALS=<specific_credential>) to constrain the credential chain to production-safe credentials.- Wrap every client in a context manager so HTTP transports, sockets, and token caches are released deterministically:
- Sync:
with <Client>(...) as client:- Async:
async with <Client>(...) as client:andasync with DefaultAzureCredential() as credential:(fromazure.identity.aio)Snippets may abbreviate this setup, but production code should always follow both rules.
import os
from azure.ai.voicelive.aio import connect
from azure.identity.aio import DefaultAzureCredential, ManagedIdentityCredential
# Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
# Or use a specific credential directly in production:
# See https://learn.microsoft.com/python/api/overview/azure/identity-readme?view=azure-python#credential-classes
# credential = ManagedIdentityCredential()
test cases passed, vs 9 / 22 without
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