azure-ai-voicelive-ts — Голосовые помощники в реальном времени для Node.js

--- name: azure-ai-voicelive-ts description: Azure AI Voice Live SDK for JavaScript/TypeScript. Build real-time voice AI applications with bidirectional WebSocket communication. risk: unknown source: community date_added: '2026-02-27' --- # @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 | ## When to Use This skill is applicable to execute the workflow or actions described in the overview.