Azure AI Voicelive Py
MicrosoftOfficialCreated by Microsoft
- Skill
- Tool integration
- Software development
- MIT
- Low risk
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The azure-ai-voicelive-py skill provides a Python SDK to facilitate bidirectional WebSocket communication with Azure AI models. It enables developers to integrate voice capabilities into applications, supporting features such as voice assistants, chatbots, speech-to-speech translation, and voice-driven avatars. The SDK includes tools for managing audio buffers, configuring session parameters, handling function calls, and processing real-time events.
What it does
- Establishes bidirectional WebSocket connections for audio streaming.
- Supports Server VAD and manual turn-based conversation control.
- Enables function calling and integration with MCP tools.
- Provides mechanisms for real-time transcription and audio output.
- Offers configuration for various voice models and audio formats.
- Facilitates integration with voice-driven avatars.
When to use it
- When building Python applications that require real-time voice interaction.
- When implementing voice-enabled chatbots or virtual assistants.
- When developing systems requiring speech-to-speech translation.
- When integrating voice-driven avatars into software projects.
Advantages
- Native support for asynchronous Python patterns.
- Flexible authentication options including Entra ID integration.
- Comprehensive event handling for session and audio management.
- Granular control over audio input and output buffers.
Usage examples
- “How do I initialize a connection to the Azure AI Voice Live service?”
- The user receives a code snippet demonstrating the use of the connect() function within an async context manager, including the required endpoint and credential configuration.
- “Show me how to configure a voice assistant with a custom function tool.”
- The user receives an example of using the session.update() method to define a FunctionTool, including its name, description, and parameter schema.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/microsoft/azure-ai-voicelive-py/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip azure-ai-voicelive-py.zip -d .agents/skills
Documentation by Microsoft
Azure AI Voice Live SDK
Build real-time voice AI applications with bidirectional WebSocket communication.
Installation
pip install azure-ai-voicelive aiohttp azure-identityEnvironment Variables
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 belowAuthentication & Lifecycle
🔑 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()
async with DefaultAzureCredential(require_envvar=True) as credential:
async with connect(
endpoint=os.environ["AZURE_COGNITIVE_SERVICES_ENDPOINT"],
credential=credential,
model="gpt-4o-realtime-preview",
credential_scopes=["https://cognitiveservices.azure.com/.default"]
) as conn:
...Legacy: API Key (existing keyed deployments)
New code should use DefaultAzureCredential above. Use AzureKeyCredential only if you have an existing keyed deployment that hasn't been migrated to Entra ID yet — for example, regulated environments still completing their Entra rollout.
import os
from azure.core.credentials import AzureKeyCredential
from azure.ai.voicelive.aio import connect
async with connect(
endpoint=os.environ["AZURE_COGNITIVE_SERVICES_ENDPOINT"],
credential=AzureKeyCredential(os.environ["AZURE_COGNITIVE_SERVICES_KEY"]),
model="gpt-4o-realtime-preview",
) as conn:
...Quick Start
import asyncio
import os
from azure.ai.voicelive.aio import connect
from azure.identity.aio import DefaultAzureCredential
async def main():
async with connect(
endpoint=os.environ["AZURE_COGNITIVE_SERVICES_ENDPOINT"],
credential=DefaultAzureCredential(),
model="gpt-4o-realtime-preview",
credential_scopes=["https://cognitiveservices.azure.com/.default"]
) as conn:
# Update session with instructions
await conn.session.update(session={
"instructions": "You are a helpful assistant.",
"modalities": ["text", "audio"],
"voice": "alloy"
})
# Listen for events
async for event in conn:
print(f"Event: {event.type}")
if event.type == "response.audio_transcript.done":
print(f"Transcript: {event.transcript}")
elif event.type == "response.done":
break
asyncio.run(main())Core Architecture
Connection Resources
The VoiceLiveConnection exposes these resources:
| Resource | Purpose | Key Methods |
|---|---|---|
conn.session | Session configuration | update(session=...) |
conn.response | Model responses | create(), cancel() |
conn.input_audio_buffer | Audio input | append(), commit(), clear() |
conn.output_audio_buffer | Audio output | clear() |
conn.conversation | Conversation state | item.create(), item.delete(), item.truncate() |
conn.transcription_session | Transcription config | update(session=...) |
Session Configuration
from azure.ai.voicelive.models import RequestSession, FunctionTool
await conn.session.update(session=RequestSession(
instructions="You are a helpful voice assistant.",
modalities=["text", "audio"],
voice="alloy", # or "echo", "shimmer", "sage", etc.
input_audio_format="pcm16",
output_audio_format="pcm16",
turn_detection={
"type": "server_vad",
"threshold": 0.5,
"prefix_padding_ms": 300,
"silence_duration_ms": 500
},
tools=[
FunctionTool(
type="function",
name="get_weather",
description="Get current weather",
parameters={
"type": "object",
"properties": {
"location": {"type": "string"}
},
"required": ["location"]
}
)
]
))Audio Streaming
Send Audio (Base64 PCM16)
import base64
# Read audio chunk (16-bit PCM, 24kHz mono)
audio_chunk = await read_audio_from_microphone()
b64_audio = base64.b64encode(audio_chunk).decode()
await conn.input_audio_buffer.append(audio=b64_audio)Receive Audio
async for event in conn:
if event.type == "response.audio.delta":
audio_bytes = base64.b64decode(event.delta)
await play_audio(audio_bytes)
elif event.type == "response.audio.done":
print("Audio complete")Event Handling
async for event in conn:
match event.type:
# Session events
case "session.created":
print(f"Session: {event.session}")
case "session.updated":
print("Session updated")
# Audio input events
case "input_audio_buffer.speech_started":
print(f"Speech started at {event.audio_start_ms}ms")
case "input_audio_buffer.speech_stopped":
print(f"Speech stopped at {event.audio_end_ms}ms")
# Transcription events
case "conversation.item.input_audio_transcription.completed":
print(f"User said: {event.transcript}")
case "conversation.item.input_audio_transcription.delta":
print(f"Partial: {event.delta}")
# Response events
case "response.created":
print(f"Response started: {event.response.id}")
case "response.audio_transcript.delta":
print(event.delta, end="", flush=True)
case "response.audio.delta":
audio = base64.b64decode(event.delta)
case "response.done":
print(f"Response complete: {event.response.status}")
# Function calls
case "response.function_call_arguments.done":
result = handle_function(event.name, event.arguments)
await conn.conversation.item.create(item={
"type": "function_call_output",
"call_id": event.call_id,
"output": json.dumps(result)
})
await conn.response.create()
# Errors
case "error":
print(f"Error: {event.error.message}")Common Patterns
Manual Turn Mode (No VAD)
await conn.session.update(session={"turn_detection": None})
# Manually control turns
await conn.input_audio_buffer.append(audio=b64_audio)
await conn.input_audio_buffer.commit() # End of user turn
await conn.response.create() # Trigger responseInterrupt Handling
async for event in conn:
if event.type == "input_audio_buffer.speech_started":
# User interrupted - cancel current response
await conn.response.cancel()
await conn.output_audio_buffer.clear()Conversation History
# Add system message
await conn.conversation.item.create(item={
"type": "message",
"role": "system",
"content": [{"type": "input_text", "text": "Be concise."}]
})
# Add user message
await conn.conversation.item.create(item={
"type": "message",
"role": "user",
"content": [{"type": "input_text", "text": "Hello!"}]
})
await conn.response.create()Voice Options
| Voice | Description |
|---|---|
alloy | Neutral, balanced |
echo | Warm, conversational |
shimmer | Clear, professional |
sage | Calm, authoritative |
coral | Friendly, upbeat |
ash | Deep, measured |
ballad | Expressive |
verse | Storytelling |
Azure voices: Use AzureStandardVoice, AzureCustomVoice, or AzurePersonalVoice models.
Audio Formats
| Format | Sample Rate | Use Case |
|---|---|---|
pcm16 | 24kHz | Default, high quality |
pcm16-8000hz | 8kHz | Telephony |
pcm16-16000hz | 16kHz | Voice assistants |
g711_ulaw | 8kHz | Telephony (US) |
g711_alaw | 8kHz | Telephony (EU) |
Turn Detection Options
# Server VAD (default)
{"type": "server_vad", "threshold": 0.5, "silence_duration_ms": 500}
# Azure Semantic VAD (smarter detection)
{"type": "azure_semantic_vad"}
{"type": "azure_semantic_vad_en"} # English optimized
{"type": "azure_semantic_vad_multilingual"}Error Handling
from azure.ai.voicelive.aio import ConnectionError, ConnectionClosed
try:
async with connect(...) as conn:
async for event in conn:
if event.type == "error":
print(f"API Error: {event.error.code} - {event.error.message}")
except ConnectionClosed as e:
print(f"Connection closed: {e.code} - {e.reason}")
except ConnectionError as e:
print(f"Connection error: {e}")Best Practices
This SDK is async-only; use the
.aionamespace throughout. Do not try to pair it with sync clients from other Azure SDKs in the same call path — keep the whole request path async.Always use context managers for clients and async credentials. Wrap every connection in
async with connect(...) as conn:. For asyncDefaultAzureCredentialfromazure.identity.aio, also useasync with credential:so tokens and transports are cleaned up.
References
Detailed API Reference: See references/api-reference.md
Complete Examples: See references/examples.md
All Models & Types: See references/models.md
Files
- ATTRIBUTION.mdAdded by AutoGineer974 B
- LICENSELicence file added by AutoGineer1.1 KiB
- SKILL.md11.3 KiB
- references/api-reference.md8.7 KiB
- references/examples.md16.9 KiB
- references/models.md18.0 KiB
LICENSE
MIT License
Copyright (c) Microsoft Corporation.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARERequirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs an API key, Needs Python
Security
What our scanner noticed· Low risk
- Instructions that use the network
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Created by
- Microsoft
- Publisher
- Microsoft (Official)
- Source
- microsoft/skills · .github/plugins/azure-sdk-python/skills/azure-ai-voicelive-py · commit 0696600
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Microsoft or Microsoft.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download azure-ai-voicelive-py.zip