bb60c4db3b
Switch the default TTS engine from online Edge TTS to offline GPU MeloTTS (privacy-first: reply text never leaves the host). Adds a supervisord melo-worker program that runs in full/bot/brain roles and synthesises Korean on the GPU (MELO_DEVICE=cuda, MELO_SPEED=1.5), a baked /opt/melo py3.11 venv layer in the Dockerfile, and compose/env defaults. Edge TTS stays available as an opt-in online fallback via TTS_ENGINE=edge. Verified on the RTX 5050 (Blackwell sm_120): melo-worker logs "ready (lang=KR speed=1.5 device=cuda)", /health returns ok, and a /synth round-trip returns a 177KB WAV. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
162 lines
6.9 KiB
Markdown
162 lines
6.9 KiB
Markdown
# Deployment layouts
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One image, three roles (`JARVIS_ROLE`), selected in `.env`. GPU is added per OS
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via a compose override picked with `COMPOSE_FILE`.
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> `COMPOSE_FILE`'s file separator is OS-specific: Linux/macOS use `:`, Windows
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> uses `;` (a colon collides with the `C:` drive letter). Using `:` on Windows
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> yields `... The system cannot find the file specified`. If in doubt, leave
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> `COMPOSE_FILE` unset and pass the files explicitly:
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> `docker compose -f docker-compose.yml -f docker-compose.gpu-windows.yml up -d`.
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## A. All-in-one (single machine)
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Everything (desktop + Chrome + bridge + bot + TTS) in one container.
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```
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# .env
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JARVIS_ROLE=full
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COMPOSE_FILE=docker-compose.yml:docker-compose.gpu-linux.yml # Ubuntu/macOS (":" )
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# COMPOSE_FILE=docker-compose.yml;docker-compose.gpu-windows.yml # Windows 11 (";" )
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DISCORD_SELFBOT_TOKEN=...
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DISCORD_GUILD_ID=...
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docker compose up -d # Ollama + javis (COMPOSE_FILE adds GPU)
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```
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## B. Split: browser host (LAN) + bot on your PC
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The on-screen Chrome, real mouse/keyboard (xdotool) and screen live on the
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**browser host**. Your PC runs the **bot** and drives that browser over the
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internal network — no auth (internal only).
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### Browser host (the LAN machine that shows Chrome, e.g. 192.168.10.5)
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```
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# .env
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JARVIS_ROLE=browser
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CDP_BIND=0.0.0.0
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BROWSER_CONTROL_BIND=0.0.0.0
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CDP_PUBLISH_BIND=0.0.0.0
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# no GPU needed → leave COMPOSE_FILE unset (base compose only)
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docker compose up -d javis # desktop + Chrome + control-server (port 8777)
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```
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Watch it on this machine’s VNC (`localhost:5901`) / noVNC (`localhost:6080`).
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### Bot host (your PC — Ubuntu or Windows 11)
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```
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# .env
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JARVIS_ROLE=bot
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BROWSER_CONTROL_URL=http://192.168.10.5:8777 # the browser host's LAN IP
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COMPOSE_FILE=docker-compose.yml:docker-compose.gpu-linux.yml # Ubuntu/macOS (":" )
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# COMPOSE_FILE=docker-compose.yml;docker-compose.gpu-windows.yml # Windows 11 (";" )
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DISCORD_SELFBOT_TOKEN=...
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DISCORD_GUILD_ID=...
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docker compose up -d # bot + bridge + TTS + Ollama (GPU per OS)
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```
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The bot’s `controlBrowser` tool posts commands to `BROWSER_CONTROL_URL`, so
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"네이버에서 X 검색", "구글로 돌아가" etc. drive the **browser host’s** Chrome with real
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human-style input (visible on its VNC).
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### External Ollama (LLM on a separate host)
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To run Ollama on a different LAN machine (e.g. a dedicated GPU host at
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`192.168.10.9`) instead of inside this stack:
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```
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# .env on the app host
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OLLAMA_BASE_URL=http://192.168.10.9:11434
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```
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Then start the app WITHOUT the in-stack LLM services: `docker compose up -d javis`
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(do not `docker compose up -d`, which would also start `ollama`/`ollama-init`).
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On the LLM host, make Ollama listen on the LAN (`OLLAMA_HOST=0.0.0.0:11434`) and
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pull the models there (`ollama pull <chat>`, `<intent>`, `<embed>`). The compose
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respects `OLLAMA_BASE_URL`, defaulting to the in-stack `ollama` service when unset.
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## C. GPU split: brain host (.9, GPU) + app host (.5, no GPU)
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All the GPU-heavy compute (Whisper STT, the Ollama LLM, and TTS) runs on the
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**brain host** (a GPU box, e.g. `192.168.10.9`). The **app host** (no GPU, e.g.
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`192.168.10.5`) runs the Discord bot and the on-screen browser, and offloads
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every STT/LLM/TTS call to the brain over the LAN.
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Flow: the bot (app host) POSTs captured voice to the brain's bridge; the brain
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runs STT -> LLM -> TTS on the GPU and returns the reply audio; when the LLM
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drives the browser, the brain's `controlBrowser` tool POSTs to the app host's
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control-server (port 8777), so Chrome moves on the app host's screen.
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### Brain host (.9 — GPU: STT + LLM + TTS)
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```
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# .env
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JARVIS_ROLE=brain
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BRIDGE_HOST=0.0.0.0 # bridge listens on the LAN
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SETTINGS_PUBLISH_BIND=0.0.0.0 # publish bridge port 8765 to the LAN
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OLLAMA_BASE_URL=http://192.168.10.9:11434 # Ollama on this host (bind 0.0.0.0)
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OLLAMA_CHAT_MODEL=qwen2.5:7b
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WHISPER_DEVICE=cuda # STT on the GPU
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WHISPER_COMPUTE_TYPE=float16
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TTS_ENGINE=melo # GPU MeloTTS (offline, privacy-first)
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MELO_DEVICE=cuda # TTS on the GPU (melo-worker)
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BROWSER_CONTROL_URL=http://192.168.10.5:8777 # drive the app host's Chrome
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COMPOSE_FILE=docker-compose.yml:docker-compose.gpu-linux.yml # GPU (":" on Linux)
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# STT (Whisper), LLM (Ollama) and TTS (MeloTTS) all run on this host's GPU.
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# Ollama listens on 0.0.0.0:11434 (systemd or a container).
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docker compose up -d javis # brain bridge + melo-worker only (no bot, no desktop)
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```
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### App host (.5 — bot + browser, no GPU)
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```
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# .env
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JARVIS_ROLE=app
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BRIDGE_URL=http://192.168.10.9:8765 # offload STT/LLM/TTS to the brain
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CDP_PUBLISH_BIND=0.0.0.0 # publish control-server 8777 to the LAN
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STREAM_HW=0 # no NVENC on a no-GPU host
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DISCORD_SELFBOT_TOKEN=...
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DISCORD_GUILD_ID=...
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# no GPU → leave COMPOSE_FILE unset (base compose only)
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docker compose up -d javis # bot + desktop + Chrome + control-server
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```
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The `brain` and `app` roles are backward-compatible additions to `full`/`browser`
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/`bot`; see `docker/run-if-role.sh`.
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## Windows 11 notes
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- Install the NVIDIA driver on Windows and enable GPU in Docker Desktop
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(Settings → Resources → WSL Integration). Use the `gpu-windows.yml` override.
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- Paths: named volumes are cross-platform. The Gemini OAuth login (for
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`GEMINI_AUTH=oauth`) is bind-mounted from the project-local `./docker/gemini-oauth`
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into the container's `~/.gemini`. A project-relative path is used so it resolves
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the same on Windows Docker Desktop and Linux (`${HOME}` is often unset when
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compose runs from PowerShell/cmd). Seed it once from a machine with a browser and
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the logged-in Gemini CLI (`npm i -g @google/gemini-cli`, then `gemini` ->
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"Sign in with Google"), copying the login state:
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(Note: as of 2026-06 Google blocks personal Google accounts on this CLI login
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with "This client is no longer supported for Gemini Code Assist for
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individuals". Workspace/org accounts may still work; personal accounts should
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use `GEMINI_AUTH=apikey` with a key from https://aistudio.google.com/app/apikey
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instead. Real-time search fail-opens to DDG/Brave/Wikipedia either way.)
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`cp -r ~/.gemini/. docker/gemini-oauth/`. The essential file is `oauth_creds.json`
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(it holds the refresh token; `GOOGLE_GENAI_USE_GCA=true` forces OAuth, so that is
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the file the startup readiness check looks for) - copying the whole dir simply also
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carries the cached account/settings. To reuse an existing host login without
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copying, set `GEMINI_OAUTH_DIR=~/.gemini` in `.env`. If unseeded, real-time search
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fail-opens to DDG/Brave and the container logs a `🔑` warning on startup.
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## Known limitation
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Discord Go-Live broadcast of the **browser host's** screen from a **remote** bot
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is not supported (the bot's WebRTC screen capture is local to the bot machine).
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Use the browser host's VNC to view it. A full remote-broadcast path is separate,
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larger work.
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