Critical frontend bugs: - Add TrackSubscribed/attach() for agent audio playback - Fix decodeToString TypeError with TextDecoder - XSS fix: innerHTML -> textContent in addMessage - Fresh token on reconnect retry Agent fixes: - GemmaLLM subclass with reasoning_content fallback wrapper - Disable Gemma 4 thinking mode via chat_template_kwargs (6.8s -> 0.5s) - Remove duplicate session-level LLM - Replace global _active_session with closure-based handler - asyncio.create_task instead of deprecated get_event_loop - Explicit silero VAD, topic filter on voice-control Infra: - supervisord: all programs log to /dev/stdout - Dockerfile: uv sync --frozen with committed uv.lock - nginx config moved to real file, token_server.py no longer served - entrypoint.sh: cert persisted, only regenerated on IP change - compose: healthcheck + cert volume - token_server: CORS removed, room pinned to voice-room UI upgrade: - Orb UI with state machine (idle/connecting/listening/thinking/speaking) - Streaming transcripts via lk.transcription text streams - Barge-in hint, thinking chip, audio visualizer - Glassmorphism, chat bubbles, settings sheet, light mode - PWA manifest, favicon, wake-lock, safe-area insets - localStorage conversation history Docs: AGENTS.md drift fixed
139 lines
7.6 KiB
Markdown
139 lines
7.6 KiB
Markdown
# Voice — Real-time Voice Assistant
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A single-container voice assistant built on LiveKit Agents. Speaks and listens in real time using Azure Speech (STT + TTS) with a local Gemma LLM for reasoning.
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## Architecture
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One Docker container runs three processes via supervisord:
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1. **LiveKit server** — open-source WebRTC media transport (port 7880 TCP, 7882 UDP muxed media)
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2. **Voice agent** — Python LiveKit Agents pipeline: Azure STT → Gemma LLM → Azure TTS
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3. **Web frontend** — static HTML served by a tiny HTTP server (port 8090)
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```
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Browser ──WebRTC──► LiveKit Server ──audio──► Agent
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▲ │
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└────────── audio ◄────────────────────────────┘
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Azure STT → Gemma LLM → Azure TTS
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```
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## Quick Start
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```bash
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# 1. Set your Azure Speech key (already in ~/.hermes/.env as AZURE_SPEECH)
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export AZURE_SPEECH_KEY=$(grep '^AZURE_SPEECH=' ~/.hermes/.env | cut -d= -f2)
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# 2. Build and start
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docker compose up --build -d
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# 3. Open the web UI (self-signed cert: accept the browser warning once)
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# https://<host-ip>:8090
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```
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LAN access requires ufw rules: `8090/tcp` (UI + signaling), `7882/udp`
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(WebRTC media), `7881/tcp` (media TCP fallback).
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## Ports
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| Port | Protocol | Service | Access |
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|-------|----------|----------------------|--------------|
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| 7880 | TCP | LiveKit HTTP/WS | internal only (proxied via nginx at /livekit/) |
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| 7881 | TCP | LiveKit RTC media (TCP fallback) | LAN |
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| 7882 | UDP | LiveKit RTC media (muxed) | LAN |
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| 8090 | TCP | Web frontend (HTTPS) | LAN |
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## Configuration
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All config lives in `.env` (git-ignored). See `.env.example` for the full list.
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Key variables:
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- `AZURE_SPEECH_KEY` — Azure Speech resource key
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- `AZURE_SPEECH_REGION` — default `eastus`
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- `AZURE_TTS_VOICE` — default voice (e.g. `en-US-AvaNeural`)
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- `GEMMA_BASE_URL` — LLM endpoint (default `http://192.168.86.2:8023/v1`)
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- `GEMMA_MODEL` — model name (default `gemma-4-e4b`)
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## Voice Selection
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The web UI includes a voice picker that sends the selected voice to the agent via LiveKit data channel. The agent updates its TTS voice in real time without restarting.
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Supported voices: any Azure Neural voice. See https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=en-us#neural-voices
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## SSML / Expressive Speech
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The TTS layer uses full SSML with `<mstts:express-as>` for style and `<prosody>` for rate/volume/pitch. The agent's system prompt instructs the LLM to write in a conversational, spoken style (short sentences, natural phrasing) so the output sounds like speech, not text.
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## Agent Prompt
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The LLM is instructed to:
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- Speak as if talking to someone, not writing for them to read
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- Keep responses to 1-3 sentences
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- Use contractions, natural fillers sparingly
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- Never use markdown, lists, or formatting
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- Spell out numbers and abbreviations
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## Testing
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```bash
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# Verify the container is running
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docker compose ps
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# Check all logs (single service: "voice")
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docker compose logs -f voice
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# Tail individual process logs via supervisord stdout
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docker exec voice tail -f /dev/stdout
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# Test TTS directly (outside the agent)
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curl -s "https://eastus.tts.speech.microsoft.com/cognitiveservices/v1" \
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-H "Ocp-Apim-Subscription-Key: $AZURE_SPEECH_KEY" \
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-H "Content-Type: application/ssml+xml" \
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-H "X-Microsoft-OutputFormat: audio-24khz-48kbitrate-mono-mp3" \
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--data-binary '<speak version="1.0" xmlns="http://www.w3.org/2001/10/synthesis" xml:lang="en-US"><voice name="en-US-AvaNeural">Test</voice></speak>' > /tmp/test.mp3
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```
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## File Layout
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```
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~/dev/voice/
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├── AGENTS.md ← you are here
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├── .env.example ← config template (copy to .env)
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├── .gitignore
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├── docker-compose.yml ← single container
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├── Dockerfile ← multi-stage build
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├── entrypoint.sh ← regenerates self-signed cert with LAN IP at start
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├── livekit.yaml ← LiveKit server config
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├── nginx.conf ← HTTPS UI + /livekit/ WS proxy
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├── supervisord.conf ← process manager (livekit, agent, nginx, token-server)
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├── certs/ ← persisted self-signed cert (volume mount)
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├── agent/
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│ ├── agent.py ← LiveKit Agents voice pipeline
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│ ├── pyproject.toml ← Python deps (uv)
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│ └── uv.lock ← locked dependency versions
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└── web/
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├── index.html ← single-page voice UI
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├── app.js ← LiveKit client logic
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├── manifest.json ← PWA manifest
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├── favicon.svg ← site icon
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├── livekit-client.umd.js ← vendored LiveKit JS SDK (no CDN)
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└── style.css ← minimal dark theme
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```
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## Conventions
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- **Single container.** All services (LiveKit, agent, web, token endpoint) run in one Docker container via supervisord. No multi-service compose.
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- **No published UDP ports in compose.** LiveKit binds its media ports directly on the host network (`network_mode: host`). This avoids the docker-proxy process explosion that hit hope-webui.
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- **Agent dispatch via roomConfig token claim.** LiveKit only dispatches agents to rooms that request them; a room auto-created by a participant join gets none. The token endpoint embeds `roomConfig.agents` in every JWT so the agent is dispatched when the browser joins. Do not pre-create rooms instead — if the agent worker isn't registered yet (first ~15s after container start), the dispatch silently fails and never retries; joining later re-fires it. The token server now pins the room name to "voice-room" server-side and no longer accepts arbitrary room names.
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- **Interruption mode must be "vad".** `interruption={"mode": "adaptive"}` requires the LiveKit Cloud barge-in service (agent-gateway.livekit.cloud) and spams 401 retries on self-hosted setups.
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- **Mic requires HTTPS.** Browsers block getUserMedia outside a secure context. nginx serves the UI on 8090 over HTTPS with a self-signed cert whose SAN includes the detected LAN IP (generated by entrypoint.sh at container start). The cert is persisted in `./certs/` (mounted as a volume) and only regenerated when the LAN IP changes, not on every container start. The LiveKit WS is proxied through nginx at `/livekit/` so everything stays on one origin (no mixed content).
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- **No CDN dependencies.** livekit-client UMD bundle is vendored into `web/`; LAN devices may have no internet access.
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- **Transcripts flow over the data channel.** The agent publishes `{type: "transcript", role, text}` JSON on topic "transcript"; the UI renders them. Voice changes flow the other way as `{type: "set_voice", voice}` on topic "voice-control".
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- **Gemma is a reasoning model.** It sometimes spends tokens on hidden reasoning before producing content. The agent implements this with `max_completion_tokens=1000` and a `GemmaLLM` subclass that wraps the LLM stream, falling back to `reasoning_content` if `content` is empty.
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- **Azure TTS uses SSML, not JSON.** The REST endpoint requires `Content-Type: application/ssml+xml`. The LiveKit Azure plugin handles this internally.
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- **Voice changes are live.** The web UI sends a data message to the agent; the agent calls `tts.update_options(voice=...)` without restarting. The agent filters data messages by topic ("voice-control") before processing.
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- **All supervisord programs log to /dev/stdout** so `docker compose logs -f voice` shows everything. Individual process logs are no longer written to files.
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## Git
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Commit frequently. Conventional commits (`feat:`, `fix:`, `chore:`).
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