router: Bildgenerierung mit FLUX.2 [klein] 4B Base (GPU-Hotswap)

- POST /v1/images/generations (OpenAI-kompatibel, prompt/size/n/seed/quality)
- quality: standard=30 Steps (Default), high=50 Steps
- Größen: 1024x1024, 1536x1024, 1024x1536, 1920x1088, 1088x1920
- GPU-Hotswap: Qwen stoppen -> FLUX laden -> Bild -> FLUX entladen -> Qwen
  wiederherstellen (exakt vorheriges Profil)
- Zentrales GPU/Modell-Lock (Profilwechsel und Bild teilen sich das Lock)
- Chat-Requests warten während Bild-Job (kein 502), Timeout CHAT_WAIT_TIMEOUT
- Robuste Recovery: try/finally, Worker-Beendigung, VRAM-Check, Qwen-Readiness
- /status: image.phase, image.worker, image.model_loaded, qwen.available,
  qwen.active_chats
- GET /images, GET /images/<datei> (validiert, nur images/-Verzeichnis)
- image_worker.py: FLUX-Worker (eigener Prozess, JSON-Protokoll, bf16 +
  enable_model_cpu_offload)
- deploy: venv (torch/diffusers/transformers/accelerate), Modell-Download,
  Image-Dir, systemd-Unit mit Image-Umgebungsvariablen
- dev: Mock-Worker, fake-systemctl, Benchmarks (GPU-Resident, Offload, Steps,
  Quality-Compare), 32 lokale Tests
- README: Bildgenerierung, Hotswap, Recovery, Benchmarks (RTX 5080),
  Python-Pakete

Benchmarks (RTX 5080, 16 GB, CPU-Offload):
- 512x512 / 10 Steps: ~9.3 s
- 1024x1024 / 30 Steps: ~31.3 s
- 1024x1024 / 50 Steps: ~45.3 s
- 1920x1088 / 50 Steps: ~91 s
- Peak-VRAM: ~8.4-8.9 GB
- Hotswap-Gesamtzeit: ~41-42 s (1024x1024 / 30 Steps)

deploy/deploy.sh

@@ -9,7 +9,7 @@ SSH_KEY="${SSH_KEY:-$HOME/.ssh/lmstudio_unraid}"
 STAGE="/tmp/ai-profile-router-$$"
 
 mkdir -p "$STAGE"
-cp router/ai_profile_router.py deploy/install.sh deploy/mike-ai-profile-router.service "$STAGE/"
+cp router/ai_profile_router.py router/image_worker.py deploy/install.sh deploy/mike-ai-profile-router.service "$STAGE/"
 
 echo "== Übertrage Dateien nach ${TARGET}:/tmp/ai-profile-router/"
 ssh -i "$SSH_KEY" "$TARGET" 'mkdir -p /tmp/ai-profile-router'