Enable GPU: LLM + Whisper on the RTX 5050, pick qwen3:8b

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/entrypoint.sh

@@ -8,11 +8,11 @@ set -euo pipefail
 : "${VNC_PASSWORD:=javis123}"
 : "${VNC_RESOLUTION:=1920x1080}"
 : "${OLLAMA_BASE_URL:=http://ollama:11434}"
-: "${OLLAMA_CHAT_MODEL:=llama3.1:8b}"
+: "${OLLAMA_CHAT_MODEL:=qwen3:8b}"
 : "${OLLAMA_EMBED_MODEL:=nomic-embed-text}"
 : "${WHISPER_MODEL:=small}"
-: "${WHISPER_DEVICE:=cpu}"
-: "${WHISPER_COMPUTE_TYPE:=int8}"
+: "${WHISPER_DEVICE:=cuda}"
+: "${WHISPER_COMPUTE_TYPE:=float16}"
 : "${JARVIS_DB_PATH:=/data/jarvis.db}"
 : "${BRIDGE_HOST:=0.0.0.0}"
 : "${BRIDGE_PORT:=8765}"