damjan_savicandClaude Opus 4.5
43484c5023
- Add 100 blog posts covering AI, development, and tech topics - Add .env.example for environment configuration - Add accessibility and lighthouse audit scripts - Remove obsolete SEO reports and temporary files - Remove dev-dist build artifacts and backup files - Remove unused portrait images (moved/consolidated elsewhere) - Update contact form and component improvements Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
602 lines
17 KiB
Markdown
602 lines
17 KiB
Markdown
# WebSockets für Voice AI: Real-Time Streaming Architekturen
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**Meta-Description:** WebSocket-basierte Architekturen für Voice AI Systeme. Audio-Streaming, Bidirektionale Kommunikation und Low-Latency Patterns für Sprachassistenten.
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**Keywords:** WebSocket, Voice AI, Real-Time Streaming, Audio WebSocket, Voice Agent Architecture, Low Latency, Bidirectional Communication
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---
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## Einführung
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WebSockets sind das Rückgrat moderner Voice AI. Anders als HTTP ermöglichen sie **persistente, bidirektionale Verbindungen** – essentiell für Echtzeit-Audio-Streaming mit Sub-500ms Latenz.
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> "WebSockets bieten JSON-basierte Protokolle statt komplexem WebRTC-Signaling – einfacher zu debuggen, universell unterstützt."
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---
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## Warum WebSockets für Voice AI?
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### HTTP vs. WebSocket vs. WebRTC
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| Aspekt | HTTP | WebSocket | WebRTC |
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|--------|------|-----------|--------|
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| **Verbindung** | Request/Response | Persistent | Persistent |
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| **Latenz** | Hoch (neue Verbindung) | Niedrig | Sehr niedrig |
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| **Bidirektional** | Nein | Ja | Ja |
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| **Komplexität** | Einfach | Mittel | Hoch |
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| **Audio-Streaming** | Schlecht | Gut | Exzellent |
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| **Debugging** | Einfach | Einfach | Schwer |
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**Fazit:** WebSockets sind der Sweet Spot zwischen Einfachheit und Performance.
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---
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## Voice AI Pipeline über WebSocket
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```
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┌─────────────────────────────────────────────────────────────┐
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│ VOICE AI WEBSOCKET ARCHITECTURE │
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├─────────────────────────────────────────────────────────────┤
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│ │
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│ Client (Browser/App) │
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│ ┌─────────────────────────────────────────────────────┐ │
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│ │ Microphone → AudioWorklet → WebSocket Send │ │
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│ │ │ │
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│ │ WebSocket Receive → AudioContext → Speaker │ │
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│ └─────────────────────────────────────────────────────┘ │
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│ │ │
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│ ▼ │
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│ Server │
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│ ┌─────────────────────────────────────────────────────┐ │
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│ │ WebSocket Handler │ │
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│ │ │ │ │
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│ │ ▼ │ │
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│ │ Audio Buffer → STT → LLM → TTS → Audio Stream │ │
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│ │ │ │ │ │ │ │
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│ │ └───────────┴──────┴──────┘ │ │
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│ │ Event-Driven Pipeline │ │
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│ └─────────────────────────────────────────────────────┘ │
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│ │
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└─────────────────────────────────────────────────────────────┘
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```
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---
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## Server-Side Implementation
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```typescript
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// src/server/voice-websocket.ts
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import { WebSocketServer, WebSocket } from 'ws';
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import { createClient } from '@deepgram/sdk';
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import { ElevenLabsClient } from 'elevenlabs';
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import Anthropic from '@anthropic-ai/sdk';
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interface VoiceSession {
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ws: WebSocket;
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deepgramConnection: any;
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conversationHistory: Message[];
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isProcessing: boolean;
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}
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const sessions = new Map<string, VoiceSession>();
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export function createVoiceWebSocketServer(server: any) {
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const wss = new WebSocketServer({ server, path: '/voice' });
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wss.on('connection', async (ws, req) => {
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const sessionId = crypto.randomUUID();
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console.log(`New voice session: ${sessionId}`);
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// Session initialisieren
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const session: VoiceSession = {
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ws,
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deepgramConnection: null,
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conversationHistory: [],
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isProcessing: false
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};
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sessions.set(sessionId, session);
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// Deepgram Streaming Connection
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const deepgram = createClient(process.env.DEEPGRAM_API_KEY!);
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session.deepgramConnection = deepgram.listen.live({
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model: 'nova-2',
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language: 'de',
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smart_format: true,
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interim_results: true,
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endpointing: 500,
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vad_events: true
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});
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// STT Events
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session.deepgramConnection.on('Results', async (data: any) => {
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const transcript = data.channel.alternatives[0].transcript;
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if (data.is_final && transcript.trim()) {
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await processUserInput(session, transcript);
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} else if (transcript) {
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// Interim results für UI
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ws.send(JSON.stringify({
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type: 'transcript_interim',
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text: transcript
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}));
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}
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});
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session.deepgramConnection.on('UtteranceEnd', async () => {
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// User hat aufgehört zu sprechen
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ws.send(JSON.stringify({ type: 'user_speech_end' }));
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});
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// Client Events
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ws.on('message', async (data: Buffer) => {
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const message = parseMessage(data);
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switch (message.type) {
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case 'audio':
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// Audio an Deepgram weiterleiten
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if (session.deepgramConnection) {
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session.deepgramConnection.send(message.audio);
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}
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break;
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case 'interrupt':
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// User unterbricht
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session.isProcessing = false;
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ws.send(JSON.stringify({ type: 'interrupted' }));
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break;
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case 'config':
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// Session-Konfiguration
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break;
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}
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});
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ws.on('close', () => {
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console.log(`Session closed: ${sessionId}`);
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if (session.deepgramConnection) {
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session.deepgramConnection.finish();
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}
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sessions.delete(sessionId);
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});
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// Ready-Signal senden
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ws.send(JSON.stringify({ type: 'ready', sessionId }));
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});
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return wss;
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}
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async function processUserInput(session: VoiceSession, text: string) {
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if (session.isProcessing) return;
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session.isProcessing = true;
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const { ws } = session;
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// User-Nachricht an Client
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ws.send(JSON.stringify({
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type: 'transcript_final',
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text
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}));
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// Conversation History updaten
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session.conversationHistory.push({
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role: 'user',
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content: text
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});
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// LLM Response generieren
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const anthropic = new Anthropic();
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const stream = await anthropic.messages.stream({
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model: 'claude-3-haiku-20240307',
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max_tokens: 500,
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system: 'Du bist ein hilfreicher Sprachassistent. Antworte kurz und prägnant.',
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messages: session.conversationHistory
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});
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let fullResponse = '';
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let sentenceBuffer = '';
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// Sentence-by-sentence TTS
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const elevenlabs = new ElevenLabsClient();
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for await (const event of stream) {
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if (!session.isProcessing) break; // Interruption Check
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if (event.type === 'content_block_delta') {
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const text = event.delta.text;
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fullResponse += text;
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sentenceBuffer += text;
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// Satz-Ende erkennen
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const sentenceEnd = sentenceBuffer.match(/[.!?]\s/);
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if (sentenceEnd) {
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const sentence = sentenceBuffer.substring(0, sentenceEnd.index! + 1);
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sentenceBuffer = sentenceBuffer.substring(sentenceEnd.index! + 2);
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// TTS für Satz
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await streamTTSToClient(ws, sentence, elevenlabs);
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}
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}
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}
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// Restlichen Buffer sprechen
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if (sentenceBuffer.trim() && session.isProcessing) {
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await streamTTSToClient(ws, sentenceBuffer, elevenlabs);
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}
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// History updaten
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session.conversationHistory.push({
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role: 'assistant',
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content: fullResponse
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});
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session.isProcessing = false;
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ws.send(JSON.stringify({ type: 'response_complete' }));
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}
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async function streamTTSToClient(
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ws: WebSocket,
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text: string,
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elevenlabs: ElevenLabsClient
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) {
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const audioStream = await elevenlabs.textToSpeech.convertAsStream(
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'onwK4e9ZLuTAKqWW03F9',
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{
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text,
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model_id: 'eleven_turbo_v2_5',
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voice_settings: {
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stability: 0.5,
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similarity_boost: 0.75
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},
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optimize_streaming_latency: 2
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}
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);
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for await (const chunk of audioStream) {
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if (ws.readyState === WebSocket.OPEN) {
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ws.send(JSON.stringify({
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type: 'audio',
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data: Buffer.from(chunk).toString('base64')
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}));
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}
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}
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}
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function parseMessage(data: Buffer): any {
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try {
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return JSON.parse(data.toString());
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} catch {
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// Binary audio data
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return { type: 'audio', audio: data };
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}
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}
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```
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---
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## Client-Side Implementation
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```typescript
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// src/client/voice-client.ts
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class VoiceWebSocketClient {
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private ws: WebSocket | null = null;
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private audioContext: AudioContext | null = null;
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private mediaStream: MediaStream | null = null;
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private audioWorklet: AudioWorkletNode | null = null;
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private audioQueue: AudioBuffer[] = [];
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private isPlaying = false;
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async connect(url: string) {
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this.ws = new WebSocket(url);
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this.ws.onopen = () => {
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console.log('Connected to voice server');
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this.startAudioCapture();
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};
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this.ws.onmessage = async (event) => {
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const message = JSON.parse(event.data);
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await this.handleMessage(message);
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};
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this.ws.onclose = () => {
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console.log('Disconnected');
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this.stopAudioCapture();
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};
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}
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private async handleMessage(message: any) {
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switch (message.type) {
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case 'ready':
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console.log(`Session: ${message.sessionId}`);
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break;
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case 'transcript_interim':
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this.onInterimTranscript?.(message.text);
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break;
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case 'transcript_final':
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this.onFinalTranscript?.(message.text);
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break;
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case 'audio':
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await this.playAudio(message.data);
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break;
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case 'response_complete':
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this.onResponseComplete?.();
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break;
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}
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}
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private async startAudioCapture() {
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this.audioContext = new AudioContext({ sampleRate: 16000 });
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this.mediaStream = await navigator.mediaDevices.getUserMedia({
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audio: {
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channelCount: 1,
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sampleRate: 16000,
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echoCancellation: true,
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noiseSuppression: true
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}
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});
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// AudioWorklet für effizientes Audio-Processing
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await this.audioContext.audioWorklet.addModule('/audio-processor.js');
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const source = this.audioContext.createMediaStreamSource(this.mediaStream);
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this.audioWorklet = new AudioWorkletNode(
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this.audioContext,
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'audio-processor'
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);
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this.audioWorklet.port.onmessage = (event) => {
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if (this.ws?.readyState === WebSocket.OPEN) {
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// Audio als Base64 senden
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const audioData = event.data;
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this.ws.send(JSON.stringify({
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type: 'audio',
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audio: this.float32ToInt16Base64(audioData)
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}));
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}
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};
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source.connect(this.audioWorklet);
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}
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private async playAudio(base64Data: string) {
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if (!this.audioContext) return;
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const audioData = Uint8Array.from(atob(base64Data), c => c.charCodeAt(0));
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const audioBuffer = await this.audioContext.decodeAudioData(
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audioData.buffer
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);
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this.audioQueue.push(audioBuffer);
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if (!this.isPlaying) {
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this.playNextInQueue();
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}
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}
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private playNextInQueue() {
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if (this.audioQueue.length === 0) {
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this.isPlaying = false;
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return;
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}
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this.isPlaying = true;
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const buffer = this.audioQueue.shift()!;
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const source = this.audioContext!.createBufferSource();
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source.buffer = buffer;
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source.connect(this.audioContext!.destination);
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source.onended = () => {
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this.playNextInQueue();
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};
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source.start();
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}
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interrupt() {
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// Audio-Queue leeren und Server informieren
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this.audioQueue = [];
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this.isPlaying = false;
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this.ws?.send(JSON.stringify({ type: 'interrupt' }));
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}
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private stopAudioCapture() {
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this.mediaStream?.getTracks().forEach(track => track.stop());
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this.audioWorklet?.disconnect();
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this.audioContext?.close();
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}
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private float32ToInt16Base64(float32Array: Float32Array): string {
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const int16Array = new Int16Array(float32Array.length);
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for (let i = 0; i < float32Array.length; i++) {
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int16Array[i] = Math.max(-32768, Math.min(32767,
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Math.round(float32Array[i] * 32767)
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));
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}
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return btoa(String.fromCharCode(...new Uint8Array(int16Array.buffer)));
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}
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// Event Callbacks
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onInterimTranscript?: (text: string) => void;
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onFinalTranscript?: (text: string) => void;
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onResponseComplete?: () => void;
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}
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```
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---
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## Audio Worklet für Browser
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```javascript
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// public/audio-processor.js
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class AudioProcessor extends AudioWorkletProcessor {
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constructor() {
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super();
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this.bufferSize = 4096;
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this.buffer = new Float32Array(this.bufferSize);
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this.bufferIndex = 0;
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}
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process(inputs, outputs, parameters) {
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const input = inputs[0];
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if (input.length > 0) {
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const channelData = input[0];
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for (let i = 0; i < channelData.length; i++) {
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this.buffer[this.bufferIndex++] = channelData[i];
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if (this.bufferIndex >= this.bufferSize) {
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// Buffer voll - an Main Thread senden
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this.port.postMessage(this.buffer.slice());
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this.bufferIndex = 0;
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}
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}
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}
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return true;
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}
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}
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registerProcessor('audio-processor', AudioProcessor);
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```
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---
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## Message Protocol
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```typescript
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// src/types/voice-protocol.ts
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type ClientMessage =
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| { type: 'audio'; audio: string } // Base64 Audio
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| { type: 'interrupt' }
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| { type: 'config'; language?: string; voice?: string };
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type ServerMessage =
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| { type: 'ready'; sessionId: string }
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| { type: 'transcript_interim'; text: string }
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| { type: 'transcript_final'; text: string }
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| { type: 'audio'; data: string } // Base64 Audio
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| { type: 'user_speech_end' }
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| { type: 'response_complete' }
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| { type: 'interrupted' }
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| { type: 'error'; message: string };
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```
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---
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## Latenz-Optimierungen
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### 1. Audio Chunk Size
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```typescript
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// Kleinere Chunks = niedrigere Latenz, mehr Overhead
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const CHUNK_SIZES = {
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lowLatency: 1024, // ~64ms bei 16kHz
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balanced: 4096, // ~256ms bei 16kHz
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efficiency: 8192 // ~512ms bei 16kHz
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};
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```
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### 2. Connection Keep-Alive
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```typescript
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// Ping/Pong für Connection Health
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setInterval(() => {
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if (ws.readyState === WebSocket.OPEN) {
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ws.ping();
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}
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}, 30000);
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ws.on('pong', () => {
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// Connection alive
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});
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```
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### 3. Audio Codec Optimization
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```typescript
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// Opus für niedrige Bandbreite
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const mediaConstraints = {
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audio: {
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channelCount: 1,
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sampleRate: 16000,
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// Für Opus Encoding (wenn verfügbar)
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// echoCancellation: true,
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// noiseSuppression: true,
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// autoGainControl: true
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}
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};
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```
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---
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## Error Handling & Reconnection
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```typescript
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class ResilientVoiceClient extends VoiceWebSocketClient {
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private reconnectAttempts = 0;
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private maxReconnectAttempts = 5;
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async connect(url: string) {
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try {
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await super.connect(url);
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this.reconnectAttempts = 0;
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} catch (error) {
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await this.handleConnectionError(error);
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}
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}
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private async handleConnectionError(error: Error) {
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if (this.reconnectAttempts < this.maxReconnectAttempts) {
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this.reconnectAttempts++;
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const delay = Math.min(1000 * 2 ** this.reconnectAttempts, 30000);
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console.log(`Reconnecting in ${delay}ms (attempt ${this.reconnectAttempts})`);
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await new Promise(resolve => setTimeout(resolve, delay));
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await this.connect(this.url);
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} else {
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console.error('Max reconnection attempts reached');
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this.onConnectionFailed?.();
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}
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}
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onConnectionFailed?: () => void;
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}
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```
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||
---
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||
|
||
## Fazit
|
||
|
||
WebSockets für Voice AI erfordern:
|
||
|
||
1. **Bidirektionales Streaming**: Audio rein, Audio raus
|
||
2. **Event-Driven Architecture**: Asynchrone Pipeline-Verarbeitung
|
||
3. **Chunk-basiertes Audio**: Balance zwischen Latenz und Effizienz
|
||
4. **Robuste Reconnection**: Graceful Degradation bei Verbindungsproblemen
|
||
|
||
Die 500ms-Grenze ist mit WebSockets erreichbar – aber nur mit sorgfältiger Architektur.
|
||
|
||
---
|
||
|
||
## Bildprompts
|
||
|
||
1. "Two-way data stream between client and server, glowing WebSocket connection, technical visualization"
|
||
2. "Audio waveform traveling through network tunnel, real-time streaming concept"
|
||
3. "Voice AI architecture diagram with WebSocket at center, clean technical illustration"
|
||
|
||
---
|
||
|
||
## Quellen
|
||
|
||
- [TEN Framework: Building Real-Time Voice AI with WebSockets](https://theten.ai/blog/building-real-time-voice-ai-with-websockets)
|
||
- [Telnyx: Media Streaming WebSocket](https://telnyx.com/resources/media-streaming-websocket)
|
||
- [VideoSDK: WebSockets for Voice Streaming](https://www.videosdk.live/developer-hub/ai-voice-agent/WebSockets-for-voice-streaming)
|
||
- [AssemblyAI: Real-Time Speech Recognition APIs 2026](https://www.assemblyai.com/blog/best-api-models-for-real-time-speech-recognition-and-transcription)
|