The voice interface connects to your running OpenClaw gateway's OpenAI-compatible endpoint. It's the same agent with all its context, tools, and memory — just with a voice.

## Quick Start

## Supported Providers

### STT (Speech-to-Text)
| Provider   | Model            | Latency  | Notes                        |
|-----------|------------------|----------|------------------------------|
| Deepgram  | nova-2 (streaming) | ~200-300ms | WebSocket streaming, best accuracy/speed |
| ElevenLabs | Scribe v1        | ~300-500ms | REST-based, good multilingual |

### TTS (Text-to-Speech)
| Provider    | Model        | Latency  | Notes                          |
|------------|--------------|----------|--------------------------------|
| Deepgram   | aura-2       | ~200ms   | WebSocket streaming, low cost  |
| ElevenLabs | Turbo v2.5   | ~300ms   | Best voice quality, streaming   |

## Configuration

All configuration is via environment variables in `.env`:

## Provider Combinations

| Setup                              | Best For                        |
|------------------------------------|---------------------------------|
| Deepgram STT + ElevenLabs TTS     | Best quality voice output        |
| Deepgram STT + Deepgram TTS       | Lowest latency, single vendor    |
| ElevenLabs STT + ElevenLabs TTS   | Best multilingual support        |

## How It Works

1. **Browser captures mic audio** via Web Audio API and streams raw PCM over a WebSocket
2. **Server receives audio** and pipes it to the configured STT provider's streaming endpoint
3. **STT returns partial transcripts** in real-time; on end-of-utterance the full text is sent to the OpenClaw gateway
4. **OpenClaw gateway streams** the LLM response token-by-token via SSE (Server-Sent Events)
5. **Tokens are accumulated** into sentence-sized chunks and streamed to the TTS provider
6. **TTS returns audio chunks** that are immediately forwarded to the browser over the same WebSocket
7. **Browser plays audio** using the Web Audio API with a jitter buffer for smooth playback

## Interruption Handling (Barge-In)

When the user starts speaking while the agent is still talking:
- Current TTS audio is immediately cancelled
- The agent stops its current response
- New STT session begins capturing the user's interruption

## Usage Examples

Browser Mic → WebSocket → STT (Deepgram / ElevenLabs) → Text
  → OpenClaw Gateway (/v1/chat/completions, streaming) → Response Text
  → TTS (Deepgram Aura / ElevenLabs) → Audio chunks → Browser Speaker

cd {baseDir}
cp .env.example .env
# Fill in your API keys and gateway URL
uv run scripts/server.py
# Open http://localhost:7860 and click the mic

# === Required ===
OPENCLAW_GATEWAY_URL=http://localhost:4141/v1    # Your OpenClaw gateway
OPENCLAW_MODEL=claude-sonnet-4-5-20250929        # Model your gateway routes to

# === STT Provider (pick one) ===
VOICE_STT_PROVIDER=deepgram                      # "deepgram" or "elevenlabs"
DEEPGRAM_API_KEY=your-key-here                   # Required if STT=deepgram
ELEVENLABS_API_KEY=your-key-here                 # Required if STT=elevenlabs

# === TTS Provider (pick one) ===
VOICE_TTS_PROVIDER=elevenlabs                    # "deepgram" or "elevenlabs"
# Uses the same API keys as above

# === Optional Tuning ===
VOICE_TTS_VOICE=rachel                           # ElevenLabs voice name/ID
VOICE_TTS_VOICE_DG=aura-2-theia-en              # Deepgram Aura voice
VOICE_VAD_SILENCE_MS=400                         # Silence before end-of-turn (ms)
VOICE_SAMPLE_RATE=16000                          # Audio sample rate
VOICE_SERVER_PORT=7860                           # Server port
VOICE_SYSTEM_PROMPT=""                           # Optional system prompt override

User: "Hey, set up my voice assistant"
→ OpenClaw runs: cd {baseDir} && cp .env.example .env
→ Opens .env for the user to fill in API keys
→ Runs: uv run scripts/server.py

User: "Start a voice chat"
→ Opens http://localhost:7860 in the browser

User: "Switch TTS to Deepgram"
→ Updates VOICE_TTS_PROVIDER=deepgram in .env
→ Restarts the server