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javis_bot/.env.example
javis-bot b17961e9e3 feat(tts): add MeloTTS Korean voice via warm worker with offline-baked cache 
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>
2026-06-12 19:01:54 +09:00

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# ============================================================================
# Javis Bot — environment configuration
# Copy to `.env` and fill in. Never commit your real `.env`.
# ============================================================================
# ---------------------------------------------------------------------------
# Discord bot (normal bot account) — voice I/O + slash commands
# ---------------------------------------------------------------------------
# From https://discord.com/developers/applications → your app
DISCORD_BOT_TOKEN=
DISCORD_APP_ID=
# The (single) server this bot serves. Guild-scoped commands appear instantly.
DISCORD_GUILD_ID=
# Voice channel used by the stream-test scripts (bot/scripts/stream-test).
DISCORD_VOICE_CHANNEL_ID=
# ---------------------------------------------------------------------------
# Brain bridge (Python service in bridge/) — STT + reply engine + TTS
# ---------------------------------------------------------------------------
BRIDGE_URL=http://127.0.0.1:8765
BRIDGE_HOST=127.0.0.1
BRIDGE_PORT=8765
JARVIS_BRAIN_ENABLED=1
JARVIS_TTS_ENABLED=1
# faster-whisper device/compute. GPU by default (RTX 5050 / sm_120, verified).
# Falls back to CPU automatically if no GPU is passed to the container.
WHISPER_DEVICE=cuda
WHISPER_COMPUTE_TYPE=float16
# Optional explicit Piper voice model (.onnx). If empty, the jarvis default is used.
TTS_PIPER_MODEL_PATH=
# TTS engine: "melo" (default) uses the MeloTTS Korean voice served by the warm
# melo-worker (Korean speaker, speed 1.5). Set to "piper" to use Piper directly.
TTS_ENGINE=melo
# Melo-only by default: if MeloTTS synthesis fails the bridge returns no audio
# rather than speaking Korean through the English Piper voice (which mangles it).
# Set to 1 only if you explicitly want the Piper fallback.
MELO_FALLBACK_PIPER=0
# Where the bridge reaches the in-container MeloTTS worker, and how long it
# waits for a synthesis. Speaking rate is set on the worker via MELO_SPEED.
MELO_WORKER_URL=http://127.0.0.1:8770
MELO_TIMEOUT=30
MELO_SPEED=1.5
# ---------------------------------------------------------------------------
# Jarvis brain (Ollama-backed). In Docker these populate the rendered
# config (docker/jarvis-config.template.json). See src/jarvis/config.py.
# ---------------------------------------------------------------------------
# In docker-compose this is overridden to http://ollama:11434 automatically.
OLLAMA_BASE_URL=http://127.0.0.1:11434
# qwen3:8b — best 8GB-VRAM pick: strongest tool-calling, ~5GB Q4, fits the RTX 5050.
OLLAMA_CHAT_MODEL=qwen3:8b
OLLAMA_EMBED_MODEL=nomic-embed-text
WHISPER_MODEL=small
# ---------------------------------------------------------------------------
# Docker desktop (VNC) — used only by the container image
# ---------------------------------------------------------------------------
# VNC viewer password (max 8 chars effective). Watch the screen at localhost:5901.
# Also used by the broadcast keepalive: TigerVNC only refreshes its framebuffer
# while a VNC client is attached, so the stream keeps a tiny client connected to
# avoid a choppy (~1.5 fps) capture. Must match the VNC server's password. If
# unset, the keepalive falls back to the obfuscated passwd file (VNC_PASSWD_FILE,
# default ~/.config/tigervnc/passwd).
VNC_PASSWORD=javis123
# VNC_PASSWD_FILE=/home/claude/.config/tigervnc/passwd
# Auto-opened page in the in-container Chrome.
CHROME_START_URL=about:blank
# ---------------------------------------------------------------------------
# Screen-share + browser mode.
# true = the bot may go Live (screen-share the VNC desktop) and drive the
# on-screen browser for real-time info (search / play / read screen).
# false = no screen share; voice only, real-time info via the Gemini API.
STREAM_BROWSER=true
# Gemini auth for real-time info when STREAM_BROWSER=false.
# oauth = use the Gemini CLI with a Google-account login (no API key).
# Install once: npm i -g @google/gemini-cli ; then run `gemini` and
# "Sign in with Google". Uses the CLI's built-in web-search grounding.
# apikey = legacy REST path; needs GEMINI_API_KEY below
# (get one at https://aistudio.google.com/app/apikey).
GEMINI_AUTH=oauth
GEMINI_API_KEY=
GEMINI_MODEL=gemini-2.0-flash
# ---------------------------------------------------------------------------
# VNC screen broadcast
# selfbot = real live "Go Live" stream (needs a USER/burner token; ToS risk)
# novnc = share a noVNC browser link (safe, real-time, not native)
# screenshot = periodic screenshots to the channel (safe, low fps)
# none = disabled
# ---------------------------------------------------------------------------
STREAM_BACKEND=selfbot
# The VNC desktop runs on X display :1 (see docs/vnc-xfce-setup.md)
VNC_DISPLAY=:1
VNC_RESOLUTION=1920x1080
# 1080p60 broadcast. 8 Mbps suits 60fps (YouTube-style 1080p60 sits ~8-12 Mbps);
# drop to 30/4000 for a lighter stream. Max bitrate is 1.5x this value.
VNC_FRAMERATE=60
VNC_BITRATE_KBPS=8000
# --- selfbot backend ---
# A THROWAWAY/burner Discord user account token. NEVER your main account.
# Using a selfbot violates Discord ToS and can get the account banned.
DISCORD_SELFBOT_TOKEN=
# Hardware (NVENC) encode for the stream. 1 = use the GPU (recommended for
# 1080p60), 0 = software x264. Requires an NVIDIA GPU + ffmpeg built with nvenc.
STREAM_HW=1
# Capture desktop audio into the broadcast so the stream has sound. 1 = on,
# 0 = mute. Pulls the PipeWire/Pulse monitor of the default sink; override the
# source with STREAM_AUDIO_SOURCE (e.g. a specific "<sink>.monitor").
STREAM_AUDIO=1
STREAM_AUDIO_SOURCE=@DEFAULT_MONITOR@
# --- novnc backend ---
# e.g. http://192.168.10.9:6080/vnc.html (websockify --web=/usr/share/novnc 6080 localhost:5901)
NOVNC_URL=
# --- screenshot backend ---
SCREENSHOT_INTERVAL_SEC=5
# ---------------------------------------------------------------------------
# Voice behaviour
# ---------------------------------------------------------------------------
# Silence (ms) that marks the end of an utterance before sending to the brain.
VOICE_SILENCE_MS=800
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