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. Triggers: "voice live", "real-time voice", "VoiceLiveClient", "VoiceLiveSession", "voice assistant TypeScript", "bidirectional audio", "speech-to-speech JavaScript".
Best use case
azure-ai-voicelive-ts is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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".
Teams using azure-ai-voicelive-ts should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/azure-ai-voicelive-ts/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How azure-ai-voicelive-ts Compares
| Feature / Agent | azure-ai-voicelive-ts | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# @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
```bash
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
```bash
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
```
## Authentication
### Microsoft Entra ID (Recommended)
```typescript
import { DefaultAzureCredential } from "@azure/identity";
import { VoiceLiveClient } from "@azure/ai-voicelive";
const credential = new DefaultAzureCredential();
const endpoint = "https://your-resource.cognitiveservices.azure.com";
const client = new VoiceLiveClient(endpoint, credential);
```
### API Key
```typescript
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
```typescript
import { DefaultAzureCredential } from "@azure/identity";
import { VoiceLiveClient } from "@azure/ai-voicelive";
const credential = new DefaultAzureCredential();
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
```typescript
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:
```typescript
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
```typescript
// 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
```typescript
// 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
```typescript
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
```typescript
import { setLogLevel } from "@azure/logger";
// Enable verbose logging
setLogLevel("info");
// Or via environment variable
// AZURE_LOG_LEVEL=info
```
## Browser Usage
```typescript
// Browser requires bundler (Vite, webpack, etc.)
import { VoiceLiveClient } from "@azure/ai-voicelive";
import { InteractiveBrowserCredential } from "@azure/identity";
// Use browser-compatible credential
const credential = new InteractiveBrowserCredential({
clientId: "your-client-id",
tenantId: "your-tenant-id",
});
const client = new VoiceLiveClient(endpoint, credential);
// Request microphone access
const stream = await navigator.mediaDevices.getUserMedia({ audio: true });
const audioContext = new AudioContext({ sampleRate: 24000 });
// Process audio and send to session
// ... (see samples for full implementation)
```
## Best Practices
1. **Always use `DefaultAzureCredential`** — Never hardcode API keys
2. **Set both modalities** — Include `["text", "audio"]` for voice assistants
3. **Use Azure Semantic VAD** — Better turn detection than basic server VAD
4. **Handle all error types** — Connection, auth, and protocol errors
5. **Clean up subscriptions** — Call `subscription.close()` when done
6. **Use appropriate audio format** — PCM16 at 24kHz for best quality
## Reference Links
| Resource | URL |
|----------|-----|
| npm Package | https://www.npmjs.com/package/@azure/ai-voicelive |
| GitHub Source | https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/ai/ai-voicelive |
| Samples | https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/ai/ai-voicelive/samples |
| API Reference | https://learn.microsoft.com/javascript/api/@azure/ai-voicelive |Related Skills
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