MR
Mayur Rathi
@mayurrathi
⭐ 40.7k GitHub stars

Azure Ai Voicelive Ts

Azure Ai Voicelive Ts is an data AI skill with a core value of |. It helps developers solve real-world problems in the data domain, boosting efficiency, automating repetitive tasks, and optimizing workflows.

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Last verified on: 2026-07-08

Quick Facts

Category data
Works With Claude
Source sickn33/antigravity-awesome-skills
Stars ⭐ 40.7k
Last Verified 2026-07-08
Risk Level Low
mkdir -p ./skills/azure-ai-voicelive-ts && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/azure-ai-voicelive-ts/SKILL.md -o ./skills/azure-ai-voicelive-ts/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# @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


text
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

🎯 Best For

  • Claude users
  • Data professionals
  • Analytics teams
  • Researchers

💡 Use Cases

  • Data pipeline auditing
  • Query optimization

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply Azure Ai Voicelive Ts to Your Work

    Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.

  4. 4

    Review and Refine

    Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.

❓ Frequently Asked Questions

How do I install Azure Ai Voicelive Ts?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/azure-ai-voicelive-ts/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Ignoring data quality

AI analysis inherits all data quality issues — profile your data first.

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