Skip to main content Skills Marktplatz Entdecken und erkunden Sie KI-Skills, die von der Community erstellt wurden.
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Prompt-Details anzeigen Ein direkter Befehl überspringt den Prüf-Prompt. Prüfen Sie die Quelle, bevor Sie ihn ausführen.
npx skills add https://github.com/BEKO2210/Firstbrain --skill azure-ai-voicelive-pyDer Befehl bleibt in einer Zeile. Scrollen Sie horizontal, um ihn vor dem Kopieren vollständig zu prüfen.
Sie bevorzugen eine lokale Kopie? Laden Sie die Dateien herunter, die SkillsMP derzeit vorliegen.
ZIP herunterladen Herunterladen... Mehr aus diesem Repository Verwandte Berufe SOC
Basierend auf der SOC-Berufsklassifikation
name azure-ai-voicelive-py description Build real-time voice AI applications with bidirectional WebSocket communication. type skill created 2026-02-27T00:00:00.000Z domain cloud-infrastructure category azure risk unknown source community tags ["skill","cloud-infrastructure","azure","voicelive"]
Azure AI Voice Live SDK
Build real-time voice AI applications with bidirectional WebSocket communication.
Installation
pip install azure-ai-voicelive aiohttp azure-identity
Environment Variables
AZURE_COGNITIVE_SERVICES_ENDPOINT=https://<region>.api.cognitive.microsoft.com
AZURE_COGNITIVE_SERVICES_KEY=<api-key>
Authentication
DefaultAzureCredential (preferred) :
from azure.ai.voicelive.aio import connect
from azure.identity.aio import DefaultAzureCredential
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:
...
API Key :
from azure.ai.voicelive.aio import connect
from azure.core.credentials import AzureKeyCredential
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
"AZURE_COGNITIVE_SERVICES_ENDPOINT"
"gpt-4o-realtime-preview"
"https://cognitiveservices.azure.com/.default"
as
await
"instructions"
"You are a helpful assistant."
"modalities"
"text"
"audio"
"voice"
"alloy"
async
for
in
print
f"Event: {event.type } "
if
type
"response.audio_transcript.done"
print
f"Transcript: {event.transcript} "
elif
type
"response.done"
break
Core Architecture
Connection Resources The VoiceLiveConnection exposes these resources:
Resource Purpose Key Methods conn.sessionSession configuration update(session=...)conn.responseModel responses create(), cancel()conn.input_audio_bufferAudio input append(), commit(), clear()conn.output_audio_bufferAudio output clear()conn.conversationConversation state item.create(), item.delete(), item.truncate()conn.transcription_sessionTranscription 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" ,
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
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 :
case "session.created" :
print (f"Session: {event.session} " )
case "session.updated" :
print ("Session updated" )
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" )
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} " )
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} " )
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()
case "error" :
print (f"Error: {event.error.message} " )
Common Patterns
Manual Turn Mode (No VAD) await conn.session.update(session={"turn_detection" : None })
await conn.input_audio_buffer.append(audio=b64_audio)
await conn.input_audio_buffer.commit()
await conn.response.create()
Interrupt Handling async for event in conn:
if event.type == "input_audio_buffer.speech_started" :
await conn.response.cancel()
await conn.output_audio_buffer.clear()
Conversation History
await conn.conversation.item.create(item={
"type" : "message" ,
"role" : "system" ,
"content" : [{"type" : "input_text" , "text" : "Be concise." }]
})
await conn.conversation.item.create(item={
"type" : "message" ,
"role" : "user" ,
"content" : [{"type" : "input_text" , "text" : "Hello!" }]
})
await conn.response.create()
Voice Options Voice Description alloyNeutral, balanced echoWarm, conversational shimmerClear, professional sageCalm, authoritative coralFriendly, upbeat ashDeep, measured balladExpressive verseStorytelling
Azure voices: Use AzureStandardVoice, AzureCustomVoice, or AzurePersonalVoice models.
Audio Formats Format Sample Rate Use Case pcm1624kHz Default, high quality pcm16-8000hz8kHz Telephony pcm16-16000hz16kHz Voice assistants g711_ulaw8kHz Telephony (US) g711_alaw8kHz Telephony (EU)
Turn Detection Options
{"type" : "server_vad" , "threshold" : 0.5 , "silence_duration_ms" : 500 }
{"type" : "azure_semantic_vad" }
{"type" : "azure_semantic_vad_en" }
{"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} " )
References
Detailed API Reference : See references/api-reference.mdComplete Examples : See references/examples.mdAll Models & Types : See references/models.md
When to Use This skill is applicable to execute the workflow or actions described in the overview.
Connections
Domain: [[Cloud & Infrastruktur]]Kategorie: [[Microsoft Azure]]Navigation: [[Skills Uebersicht]], [[Home]] 