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Iterate on a GenAI notebook against the self-hosted stack via the genai-stack CLI (config dirs, auth, subdomains, quantization, GPU/VRAM). Arguments: <notebook|service> [--service comfyui|forge|vllm] [--quant int4|fp8] [--validate] [--bg]
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Detect cell-ordering / enchainement problems in Jupyter notebooks (canonical-order slippage, misplaced or forgotten cells). Arguments: [target] [--severity HIGH|MED|LOW] [--json]
Resume multi-agent coordination session. Reads memory, RooSync inbox, GitHub issues, and produces a situational briefing with recommended actions. Arguments: [--dispatch] [--focus <topic>] [--reply-all]
Train an ML model in the QuantConnect ML-Training-Pipeline with thermal-safe GPU usage and rigorous validation. Arguments: <architecture|script> [--dry-run] [--seeds 0,1,7,42,99] [--folds 5] [--bg]
Execute iterative improvement workflow for QuantConnect strategies. Arguments: [strategy|issue#] [--iterations=N] [--no-backtest] [--commit]
Review and merge student exercise PRs during TP sessions. Arguments: <repo-url> [--class <class-id>] [--timeslot <HH:MM-HH:MM>] [--dry-run]
Analyze PowerPoint slides qualitatively using vision AI. Arguments: <deck_path> [--render] [--slides 1,5,10]
| name | genai-iterate |
| description | Iterate on a GenAI notebook against the self-hosted stack via the genai-stack CLI (config dirs, auth, subdomains, quantization, GPU/VRAM). Arguments: <notebook|service> [--service comfyui|forge|vllm] [--quant int4|fp8] [--validate] [--bg] |
Iterer sur un notebook GenAI (MyIA.AI.Notebooks/GenAI/) contre la stack auto-hebergee, en pilotant le CLI scripts/genai-stack/genai.py. Couvre l'Epic #1385 (GenAI series + hosting). Pour les cycles batch, deleguer a l'agent genai-iterator en async.
<notebook|service> : chemin notebook ou nom de service (comfyui-qwen, forge-turbo, vllm-zimage).--service comfyui|forge|vllm : service cible si ambigu.--quant int4|fp8 : forcer une quantization (Nunchaku INT4 ~4GB / FP8 ~29GB).--validate : lancer la validation stack (genai.py validate + skill validate-genai).--bg : iteration en background..env reel = MyIA.AI.Notebooks/GenAI/.env (gitignored) ; template .env.example (carte sous-domaines)..env. Jamais de literal inline, jamais os.getenv("KEY","<fallback>"), jamais imprimer une valeur de token (cf .claude/rules/secrets-hygiene.md).python genai.py docker # service up ?
python genai.py auth # token present + correct (Bearer comfyui / Basic forge / none vllm) ?
python genai.py gpu # VRAM libre sur le GPU cible ?
python genai.py quant summary # bonne quant chargee ?
COMFYUI_BEARER_TOKEN). forge-turbo : GPU1 ~8GB, Basic (FORGE_USER/FORGE_PASSWORD). vllm-zimage : GPU1 ~15GB, no auth.genai.py quant apply qwen (Nunchaku INT4 ~4GB) obligatoire.genai.py quant apply zimage).genai.py quant apply <service> --dry-run.notebook-modernizer).notebook-executor).notebook-validator).LOCAL_MODE dans les outputs committes (re-executer en remote propre).yourdomain.com — vrai sous-domaine.yourdomain.com dans Image/04-4-Cross-Stitch-Legacy, Texte/10_LocalLlama.02-5-Multi-Model-TTS-Gateway 401.LOCAL_MODE leak dans outputs de 02-4-Z-Image-Lumina2, 02-1-Qwen-Image-Edit-2509.COMFYUI_BEARER_TOKEN vs COMFYUI_AUTH_TOKEN a harmoniser.os.getenv avec fallback secret / imprimer un token.LOCAL_MODE actif ou sans outputs reels.genai.py.