Adds a dedicated MeloTTS Korean voice (speed 1.5) as the primary TTS engine,
served by a long-lived in-container worker so each Discord turn pays only
inference cost, not model-load cost.
- bridge/melo_worker.py: tiny HTTP service in its own /opt/melo py3.11 venv,
keeps the KR model warm, returns PCM16 WAV on POST /synth.
- bridge/server.py: synthesize() routes to the melo worker first; Piper stays
as an opt-in fallback (MELO_FALLBACK_PIPER, default off so Korean is never
mangled through the English voice). /health reports tts_engine.
- docker/setup-melo.sh: builds the isolated venv (pinned torch 2.12.0 /
torchaudio 2.11.0 CPU, MeloTTS pinned to a commit for reproducible rebuilds),
pre-fetches mecab-ko, and warms a dedicated HF cache (/opt/melo-cache) with a
real KR synth so all BERT + KR checkpoint assets are baked into the image.
- docker/supervisord.conf: runs melo-worker before the bridge with
HF_HOME=/opt/melo-cache (the whisper_cache volume shadows the default HF
cache) plus HF_HUB_OFFLINE/TRANSFORMERS_OFFLINE so it reads the baked cache
and never retries the network on load.
- Dockerfile/.env.example: wire the melo build layer and config knobs.
Verified: offline synth passes with --network none and the prod volume mounted;
prod container recreated, all supervisord services up, bot logged in, and an
end-to-end /tts call returns a 44.1kHz mono PCM16 WAV.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Completes the STREAM_BROWSER=true behaviour:
- handleJoin auto-starts the broadcast on voice join and wires the session to
the guild streamer; each turn reports the live state to the brain so search
routes Chrome (live) vs Gemini (off).
- New setBroadcast tool lets the user toggle the broadcast by voice ("방송
켜줘/꺼줘") via the LLM (no hardcoded phrases); it refuses when
STREAM_BROWSER=false. The directive flows brain -> bridge (broadcast_action)
-> bot streamer.start/stop, guarded by isActive() so it's idempotent.
- Per-turn IPC uses a thread-local (reply/turn_state.py) instead of threading
params through the whole engine chain: bridge sets broadcasting in, tool
records the directive out; Tool.execute exposes broadcasting on ToolContext.
Bot typecheck clean; brain covered by tests/test_set_broadcast.py (+ existing
routing tests). Specs + docs updated.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
- voice.ts: reply playback is now a FIFO queue (AudioPlayerStatus.Idle drains
it) so concurrent speakers no longer cut each other's replies off.
- selfbot.ts: rewritten against the REAL @dank074/discord-video-stream v6 API
(verified from its d.ts): prepareStream(input, opts, signal)->{command,output},
playStream(output, streamer, {type:"go-live"}, signal), Streamer.joinVoice.
x11grab via customInputOptions; optional NVENC encode (RTX 5050) via exported
`nvenc`. package.json pinned to ^6.0.0 (was a wrong ^4.2.1).
- Dockerfile: dropped the hardcoded python3.12 LD_LIBRARY_PATH. faster-whisper
>=1.1 self-locates the pip CUDA libs; ldconfig (full path, glob) registers
them as a robust fallback. Verified: ld.so cache lists libcublas/libcudnn and
GPU whisper works with LD_LIBRARY_PATH empty.
- bridge: STT resample 48k->16k upgraded from nearest-neighbor to linear
(np.interp).
Verified: tsc clean, image builds, GPU whisper OK via ldconfig, compose valid.
Code review of the bridge/bot/docker work found:
- TTS bug: bridge called PiperVoice.synthesize(text, wav) but that method
returns AudioChunks and takes a SynthesisConfig as its 2nd arg, not a wav
file -> TTS would fail. Switched to synthesize_wav(text, wav_file).
Verified: produces a valid 22050Hz mono WAV.
- run-bot.sh now waits if ANY of DISCORD_BOT_TOKEN/APP_ID/GUILD_ID is missing
(config.ts throws on a missing one), preventing a supervisor crash-loop.
Verified clean: discord.js Events.ClientReady == 'clientReady' (existing
handler correct); image rebuilds.
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.
