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azure-ai-voicelive-ts

Azure AI Voice Live SDK for JavaScript/TypeScript. Build real-time voice AI applications with bidirectional WebSocket communication. Use for voice assistants, conversational AI, real-time speech-to-speech, and voice-enabled chatbots in Node.js or browser environments.

Install / Use

npx skills add microsoft/skills --skill azure-ai-voicelive-ts

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

95/100

Supported Platforms

Universal

Our assessment of azure-ai-voicelive-ts

azure-ai-voicelive-ts scores 95/100 on our quality scale, 37th of 225 Customer Support skills we index (top 17%).

Its SKILL.md is 13 KB long, well organised into 24 sections with 13 code examples: a thorough specification that gives an agent plenty to work with.

With 3,051 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
15/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 5 days ago, so azure-ai-voicelive-ts is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

azure-ai-voicelive-ts compared with similar skills

All 4 of these similar skills score higher than azure-ai-voicelive-ts; compare them before choosing.

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Frequently asked questions

How do I install azure-ai-voicelive-ts?
Run npx skills add microsoft/skills --skill azure-ai-voicelive-ts. The install tabs above show the steps for each supported agent.
Which AI agents does azure-ai-voicelive-ts work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is azure-ai-voicelive-ts safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is azure-ai-voicelive-ts still maintained?
The repository was last updated 5 days ago, so azure-ai-voicelive-ts is actively maintained.

name: azure-ai-voicelive-ts description: | Azure AI Voice Live SDK for JavaScript/TypeScript. Build real-time voice AI applications with bidirectional WebSocket communication. Use for voice assistants, conversational AI, real-time speech-to-speech, and voice-enabled chatbots in Node.js or browser environments. Triggers: "voice live", "real-time voice", "VoiceLiveClient", "VoiceLiveSession", "voice assistant TypeScript", "bidirectional audio", "speech-to-speech JavaScript". license: MIT metadata: author: Microsoft version: "1.0.0" package: '@azure/ai-voicelive'

@azure/ai-voicelive (JavaScript/TypeScript)

Real-time voice AI SDK for building bidirectional voice assistants with Azure AI in Node.js and browser environments.

Installation

npm install @azure/ai-voicelive @azure/identity
# TypeScript users
npm install @types/node

Current Version: 1.0.0-beta.3

Supported Environments:

  • Node.js LTS versions (20+)
  • Modern browsers (Chrome, Firefox, Safari, Edge)

Environment Variables

AZURE_VOICELIVE_ENDPOINT=https://<resource>.cognitiveservices.azure.com
# Optional: API key if not using Entra ID
AZURE_VOICELIVE_API_KEY=<your-api-key>
# Optional: Logging
AZURE_LOG_LEVEL=info
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production

Authentication

Microsoft Entra Token Credential (Recommended)

import { DefaultAzureCredential, ManagedIdentityCredential } from "@azure/identity";
import { VoiceLiveClient } from "@azure/ai-voicelive";

// Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
const credential = new DefaultAzureCredential({requiredEnvVars: ["AZURE_TOKEN_CREDENTIALS"]});
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/javascript/api/overview/azure/identity-readme?view=azure-node-latest#credential-classes
// const credential = new ManagedIdentityCredential();
const endpoint = "https://your-resource.cognitiveservices.azure.com";

const client = new VoiceLiveClient(endpoint, credential);

API Key

import { AzureKeyCredential } from "@azure/core-auth";
import { VoiceLiveClient } from "@azure/ai-voicelive";

const endpoint = "https://your-resource.cognitiveservices.azure.com";
const credential = new AzureKeyCredential("your-api-key");

const client = new VoiceLiveClient(endpoint, credential);

Client Hierarchy

VoiceLiveClient
└── VoiceLiveSession (WebSocket connection)
    ├── updateSession()      → Configure session options
    ├── subscribe()          → Event handlers (Azure SDK pattern)
    ├── sendAudio()          → Stream audio input
    ├── addConversationItem() → Add messages/function outputs
    └── sendEvent()          → Send raw protocol events

Quick Start

import { DefaultAzureCredential } from "@azure/identity";
import { VoiceLiveClient } from "@azure/ai-voicelive";

const credential = new DefaultAzureCredential({requiredEnvVars: ["AZURE_TOKEN_CREDENTIALS"]});
const endpoint = process.env.AZURE_VOICELIVE_ENDPOINT!;

// Create client and start session
const client = new VoiceLiveClient(endpoint, credential);
const session = await client.startSession("gpt-4o-mini-realtime-preview");

// Configure session
await session.updateSession({
  modalities: ["text", "audio"],
  instructions: "You are a helpful AI assistant. Respond naturally.",
  voice: {
    type: "azure-standard",
    name: "en-US-AvaNeural",
  },
  turnDetection: {
    type: "server_vad",
    threshold: 0.5,
    prefixPaddingMs: 300,
    silenceDurationMs: 500,
  },
  inputAudioFormat: "pcm16",
  outputAudioFormat: "pcm16",
});

// Subscribe to events
const subscription = session.subscribe({
  onResponseAudioDelta: async (event, context) => {
    // Handle streaming audio output
    const audioData = event.delta;
    playAudioChunk(audioData);
  },
  onResponseTextDelta: async (event, context) => {
    // Handle streaming text
    process.stdout.write(event.delta);
  },
  onInputAudioTranscriptionCompleted: async (event, context) => {
    console.log("User said:", event.transcript);
  },
});

// Send audio from microphone
function sendAudioChunk(audioBuffer: ArrayBuffer) {
  session.sendAudio(audioBuffer);
}

Session Configuration

await session.updateSession({
  // Modalities
  modalities: ["audio", "text"],
  
  // System instructions
  instructions: "You are a customer service representative.",
  
  // Voice selection
  voice: {
    type: "azure-standard",  // or "azure-custom", "openai"
    name: "en-US-AvaNeural",
  },
  
  // Turn detection (VAD)
  turnDetection: {
    type: "server_vad",      // or "azure_semantic_vad"
    threshold: 0.5,
    prefixPaddingMs: 300,
    silenceDurationMs: 500,
  },
  
  // Audio formats
  inputAudioFormat: "pcm16",
  outputAudioFormat: "pcm16",
  
  // Tools (function calling)
  tools: [
    {
      type: "function",
      name: "get_weather",
      description: "Get current weather",
      parameters: {
        type: "object",
        properties: {
          location: { type: "string" }
        },
        required: ["location"]
      }
    }
  ],
  toolChoice: "auto",
});

Event Handling (Azure SDK Pattern)

The SDK uses a subscription-based event handling pattern:

const subscription = session.subscribe({
  // Connection lifecycle
  onConnected: async (args, context) => {
    console.log("Connected:", args.connectionId);
  },
  onDisconnected: async (args, context) => {
    console.log("Disconnected:", args.code, args.reason);
  },
  onError: async (args, context) => {
    console.error("Error:", args.error.message);
  },
  
  // Session events
  onSessionCreated: async (event, context) => {
    console.log("Session created:", context.sessionId);
  },
  onSessionUpdated: async (event, context) => {
    console.log("Session updated");
  },
  
  // Audio input events (VAD)
  onInputAudioBufferSpeechStarted: async (event, context) => {
    console.log("Speech started at:", event.audioStartMs);
  },
  onInputAudioBufferSpeechStopped: async (event, context) => {
    console.log("Speech stopped at:", event.audioEndMs);
  },
  
  // Transcription events
  onConversationItemInputAudioTranscriptionCompleted: async (event, context) => {
    console.log("User said:", event.transcript);
  },
  onConversationItemInputAudioTranscriptionDelta: async (event, context) => {
    process.stdout.write(event.delta);
  },
  
  // Response events
  onResponseCreated: async (event, context) => {
    console.log("Response started");
  },
  onResponseDone: async (event, context) => {
    console.log("Response complete");
  },
  
  // Streaming text
  onResponseTextDelta: async (event, context) => {
    process.stdout.write(event.delta);
  },
  onResponseTextDone: async (event, context) => {
    console.log("\n--- Text complete ---");
  },
  
  // Streaming audio
  onResponseAudioDelta: async (event, context) => {
    const audioData = event.delta;
    playAudioChunk(audioData);
  },
  onResponseAudioDone: async (event, context) => {
    console.log("Audio complete");
  },
  
  // Audio transcript (what assistant said)
  onResponseAudioTranscriptDelta: async (event, context) => {
    process.stdout.write(event.delta);
  },
  
  // Function calling
  onResponseFunctionCallArgumentsDone: async (event, context) => {
    if (event.name === "get_weather") {
      const args = JSON.parse(event.arguments);
      const result = await getWeather(args.location);
      
      await session.addConversationItem({
        type: "function_call_output",
        callId: event.callId,
        output: JSON.stringify(result),
      });
      
      await session.sendEvent({ type: "response.create" });
    }
  },
  
  // Catch-all for debugging
  onServerEvent: async (event, context) => {
    console.log("Event:", event.type);
  },
});

// Clean up when done
await subscription.close();

Function Calling

// Define tools in session config
await session.updateSession({
  modalities: ["audio", "text"],
  instructions: "Help users with weather information.",
  tools: [
    {
      type: "function",
      name: "get_weather",
      description: "Get current weather for a location",
      parameters: {
        type: "object",
        properties: {
          location: {
            type: "string",
            description: "City and state or country",
          },
        },
        required: ["location"],
      },
    },
  ],
  toolChoice: "auto",
});

// Handle function calls
const subscription = session.subscribe({
  onResponseFunctionCallArgumentsDone: async (event, context) => {
    if (event.name === "get_weather") {
      const args = JSON.parse(event.arguments);
      const weatherData = await fetchWeather(args.location);
      
      // Send function result
      await session.addConversationItem({
        type: "function_call_output",
        callId: event.callId,
        output: JSON.stringify(weatherData),
      });
      
      // Trigger response generation
      await session.sendEvent({ type: "response.create" });
    }
  },
});

Voice Options

| Voice Type | Config | Example | |------------|--------|---------| | Azure Standard | { type: "azure-standard", name: "..." } | "en-US-AvaNeural" | | Azure Custom | { type: "azure-custom", name: "...", endpointId: "..." } | Custom voice endpoint | | Azure Personal | { type: "azure-personal", speakerProfileId: "..." } | Personal voice clone | | OpenAI | { type: "openai", name: "..." } | "alloy", "echo", "shimmer" |

Supported Models

| Model | Description | Use Case | |-------|-------------|----------| | gpt-4o-realtime-preview | GPT-4o with real-time audio | High-quality conversational AI | | gpt-4o-mini-realtime-preview | Lightweight GPT-4o | Fast, efficient interactions | | phi4-mm-realtime | Phi multimodal | Cost-effective applications |

Turn Detection Options

// Server VAD (default)
turnDetection: {
  type: "server_vad",
  threshold: 0.5,
  prefixPaddingMs: 300,
  silenceDurationMs: 500,
}

// Azure Semantic VAD (smarter detection)
turnDetection: {
  type: "azure_semantic_vad",
}

// Azure Semantic VAD (English optimized)
turnDetection: {
  type: "azure_semantic_vad_en",
}

// Azure Semantic VAD (Multilingual)
turnDetection: {
  type: "azure_semantic_vad_multilingual",
}

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) |

Key Types Reference

| Type | Purpose | |------|---------| | VoiceLiveClient | Main client for creating sessions | | VoiceLiveSession | Active WebSocket session | | VoiceLiveSessionHandlers | Event handler interface | | VoiceLiveSubscription | Active event subscription | | ConnectionContext | Context for connection events | | SessionContext | Context for session events | | ServerEventUnion | Union of all server events |

Error Handling

import {
  VoiceLiveError,
  VoiceLiveConnectionError,
  VoiceLiveAuthenticationError,
  VoiceLiveProtocolError,
} from "@azure/ai-voicelive";

const subscription = session.subscribe({
  onError: async (args, context) => {
    const { error } = args;
    
    if (error instanceof VoiceLiveConnectionError) {
      console.error("Connection error:", error.message);
    } else if (error instanceof VoiceLiveAuthenticationError) {
      console.error("Auth error:", error.message);
    } else if (error instanceof VoiceLiveProtocolError) {
      console.error("Protocol error:", error.message);
    }
  },
  
  onServerError: async (event, context) => {
    console.error("Server error:", event.error?.message);
  },
});

Logging

`

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars3.1k
CategoryCustomer
Updated5d ago
Forks349

Languages

TypeScript

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions