The user chose Microsoft Edge TTS, voice ko-KR-HyunsuMultilingualNeural at rate
+45% (~1.45x), as the natural Korean voice. Wire it into the bridge and make it
the default engine.
- bridge/server.py: _edge_synthesize() calls edge-tts and transcodes the MP3 to
PCM16 mono WAV with the system ffmpeg (temp file for a correct header);
TTS_ENGINE default -> edge; EDGE_TTS_VOICE / EDGE_TTS_RATE env-driven
- requirements-bridge.txt: add edge-tts (lightweight; httpx)
- compose/.env.example/README: TTS_ENGINE=edge + EDGE_TTS_* knobs; note the
online/privacy trade-off (reply text is sent to Microsoft, needs internet)
- drop the now-unused MeloTTS build layer (Dockerfile) and melo-worker
(supervisord) — edge synthesises in-process, no model/worker baked, slimmer
and faster image; settings UI engine list -> edge/piper, restart only bridge
Verified on host: edge-tts -> ffmpeg yields a valid 16-bit mono 24kHz WAV;
envsubst renders tts_engine=edge; docker build --check + 26 tests pass.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
GPU acceleration is now on by default and verified end-to-end on the
Blackwell RTX 5050 (sm_120):
- Ollama offloads 100% to GPU (log: library=CUDA compute=12.0,
BLACKWELL_NATIVE_FP4=1). compose passes GPU via CDI
(devices: nvidia.com/gpu=all) to both ollama and javis.
- Whisper STT on GPU: faster-whisper>=1.1.0 + nvidia-cublas/cudnn cu12,
LD_LIBRARY_PATH baked into the image. Verified float16 transcribe on
sm_120; bridge auto-falls back to CPU when no GPU is present.
- Model: default chat model -> qwen3:8b (best 8GB-VRAM tool-calling,
~5GB Q4). Embed stays nomic-embed-text.
- README documents the host one-time setup (nvidia-container-toolkit +
`nvidia-ctk cdi generate`) and GPU on/off.
Verified: image builds; GPU visible in both containers via compose;
ollama ps = 100% GPU; faster-whisper cuda OK + CPU fallback OK;
bridge /health 200.
`docker compose up -d --build` now brings up the whole thing automatically —
no host setup needed:
- All-in-one javis image: TigerVNC+XFCE desktop, Chrome, Python brain bridge,
Node/bun bot, managed by supervisord (verified: all 6 programs RUNNING).
- ollama service + one-shot ollama-init that auto-pulls chat+embed models
(verified end-to-end; `ollama list` shows pulled models).
- Discord token deferred: without DISCORD_BOT_TOKEN the desktop, bridge,
Ollama and models all run; only the bot waits (no crash loop).
- Slim container deps (bridge/requirements-bridge.txt) drop the unused
PyQt6/torch/chatterbox/sounddevice stack. Piper voice + Whisper models
auto-download into named volumes.
- Configurable host ports (VNC_PORT/NOVNC_PORT/BRIDGE_PORT) to avoid clashing
with a host VNC already on 5901. Bridge binds 0.0.0.0 in-container.
Verified: image builds; brain imports; bridge /health 200; noVNC 200;
X display :1 @1920x1080; auto-pull completes; supervisorctl status all RUNNING.
