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Intent judging, tool routing and arg extraction are classification/JSON calls, not the spoken answer, yet the stack aliased OLLAMA_INTENT_MODEL back to the big chat model — so each command paid the big model's cost 2-3 times for routing before the reply even ran. With the GPU on, that round-trip stacking is the main remaining per-turn latency. Default OLLAMA_INTENT_MODEL to qwen2.5:3b (the project's reference small model, clean Korean on classification) and have ollama-init pull it. The reply engine already routes these calls through intent_judge_model, so answer quality is untouched; set OLLAMA_INTENT_MODEL = OLLAMA_CHAT_MODEL to fold back onto one resident model. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
95 lines
4.6 KiB
Bash
Executable File
95 lines
4.6 KiB
Bash
Executable File
#!/usr/bin/env bash
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# Container entrypoint: render config from env, set the VNC password, ensure the
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# Piper voice exists, then hand off to supervisord (which runs the desktop,
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# bridge, and bot).
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set -euo pipefail
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# --- Defaults (override via .env / compose) ---
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: "${VNC_PASSWORD:=javis123}"
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: "${VNC_RESOLUTION:=1920x1080}"
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: "${OLLAMA_BASE_URL:=http://ollama:11434}"
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: "${OLLAMA_CHAT_MODEL:=qwen3:8b}"
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# Auxiliary small-model calls (intent judge, tool router, weather place
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# extraction, query decomposition). Default to a small fast model so the big
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# chat model only runs for the actual spoken answer — the main per-turn latency
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# win once the GPU is in use, since the 2-3 routing/extraction calls per command
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# no longer pay the big model's cost. ollama-init pulls this model. Set it equal
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# to OLLAMA_CHAT_MODEL to fold everything back onto one resident model.
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: "${OLLAMA_INTENT_MODEL:=qwen2.5:3b}"
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# Cap chat-model output tokens per turn (worst-case latency guard). Spoken
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# answers are 1-2 sentences; 512 is safe headroom above tool-call JSON. 0 = off.
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: "${OLLAMA_NUM_PREDICT:=512}"
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: "${OLLAMA_EMBED_MODEL:=nomic-embed-text}"
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: "${WHISPER_MODEL:=small}"
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: "${WHISPER_DEVICE:=cuda}"
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: "${WHISPER_COMPUTE_TYPE:=float16}"
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: "${JARVIS_DB_PATH:=/data/jarvis.db}"
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: "${BRIDGE_HOST:=127.0.0.1}"
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: "${BRIDGE_PORT:=8765}"
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: "${PIPER_VOICE:=en_GB-alan-medium}"
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: "${PIPER_VOICE_DIR:=/opt/piper-voices}"
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: "${TTS_PIPER_MODEL_PATH:=${PIPER_VOICE_DIR}/${PIPER_VOICE}.onnx}"
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# Audio: shared PulseAudio socket so Chrome (playback) and the selfbot ffmpeg
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# (capture of @DEFAULT_MONITOR@) reach the same headless daemon (run-pulse.sh).
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: "${XDG_RUNTIME_DIR:=/run/user/0}"
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: "${PULSE_SERVER:=unix:${XDG_RUNTIME_DIR}/pulse/native}"
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export VNC_RESOLUTION OLLAMA_BASE_URL OLLAMA_CHAT_MODEL OLLAMA_NUM_PREDICT OLLAMA_INTENT_MODEL OLLAMA_EMBED_MODEL \
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WHISPER_MODEL WHISPER_DEVICE WHISPER_COMPUTE_TYPE JARVIS_DB_PATH \
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PIPER_VOICE PIPER_VOICE_DIR TTS_PIPER_MODEL_PATH BRIDGE_HOST BRIDGE_PORT \
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XDG_RUNTIME_DIR PULSE_SERVER
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mkdir -p /data /app/config "$(dirname "$JARVIS_DB_PATH")"
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# --- VNC password file ---
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mkdir -p /root/.vnc
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echo "$VNC_PASSWORD" | tigervncpasswd -f > /root/.vnc/passwd
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chmod 600 /root/.vnc/passwd
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# --- Render jarvis brain config from template ---
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envsubst < /app/docker/jarvis-config.template.json > /app/config/jarvis.json
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export JARVIS_CONFIG_PATH=/app/config/jarvis.json
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# Merge persistent settings from the settings UI (on the /data volume) on top of
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# the env-rendered config, so changes survive container recreate.
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if [ -f /data/jarvis-settings.json ]; then
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python3 - <<'PY' || true
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import json, os
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try:
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base = json.load(open("/app/config/jarvis.json"))
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ov = json.load(open("/data/jarvis-settings.json"))
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if isinstance(base, dict) and isinstance(ov, dict):
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base.update(ov)
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# A stale persisted tts_engine from an earlier voice (melo/xtts, no
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# longer built into the image) would override the configured engine and
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# leave the bot silent. Reset those to the env-configured engine.
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if base.get("tts_engine") in ("melo", "xtts"):
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base["tts_engine"] = os.environ.get("TTS_ENGINE", "edge")
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print(f"[entrypoint] reset stale tts_engine -> {base['tts_engine']}")
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json.dump(base, open("/app/config/jarvis.json", "w"), ensure_ascii=False, indent=2)
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print("[entrypoint] merged persistent settings overrides")
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except Exception as e:
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print(f"[entrypoint] settings merge skipped: {e}")
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PY
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fi
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# --- Ensure the Piper voice exists (best effort) ---
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bash /app/docker/download-piper.sh || echo "[entrypoint] piper download failed; TTS may be unavailable"
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# --- Gemini OAuth login check (GEMINI_AUTH=oauth real-time search) ---
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# The browser-only role never runs the reply engine / web search, so skip the
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# check there. Otherwise warn (don't fail) when oauth is selected but no login
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# has been seeded into the mounted ~/.gemini, since the path silently degrades
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# to the DDG/Brave cascade.
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if [ "${JARVIS_ROLE:-full}" != "browser" ] \
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&& [ "${GEMINI_AUTH:-oauth}" = "oauth" ] \
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&& [ ! -f /root/.gemini/oauth_creds.json ]; then
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echo "[entrypoint] 🔑 GEMINI_AUTH=oauth but no Gemini login at /root/.gemini/oauth_creds.json"
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echo "[entrypoint] Real-time search will fall back to DDG/Brave until you seed the login."
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echo "[entrypoint] Seed it: copy a logged-in ~/.gemini into the host's gemini-oauth dir"
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echo "[entrypoint] (default ./docker/gemini-oauth, or set GEMINI_OAUTH_DIR). See docs/DEPLOY.md."
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fi
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echo "[entrypoint] display=$DISPLAY ollama=$OLLAMA_BASE_URL whisper=$WHISPER_MODEL/$WHISPER_DEVICE"
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exec supervisord -c /app/docker/supervisord.conf
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