Raphael Amorim 30f16f1d4e feat: Add recipe-based one-click model deployment system ...

Introduces a YAML recipe system for simplified model deployment:

- run-recipe.py: Main script handling build, download, and launch
- run-recipe.sh: Bash wrapper for dependency management
- recipes/: Pre-configured recipes for common models
  - glm-4.7-flash-awq.yaml: GLM-4.7-Flash with AWQ quantization
  - glm-4.7-nvfp4.yaml: GLM-4.7 with NVFP4 (cluster-only)
  - minimax-m2-awq.yaml: MiniMax M2 with AWQ
  - openai-gpt-oss-120b.yaml: OpenAI GPT-OSS 120B with MXFP4

Key features:
- Auto-discover cluster nodes with --discover, saves to .env
- Load nodes from .env automatically on subsequent runs
- cluster_only flag for models requiring multi-node setup
- build_args field for Dockerfile selection (--pre-tf, --exp-mxfp4)
- Solo mode auto-strips --distributed-executor-backend ray
- --setup flag for full build + download + run workflow
- --dry-run to preview execution without running

Usage:
  ./run-recipe.sh --discover           # Find and save cluster nodes
  ./run-recipe.sh glm-4.7-flash-awq --solo --setup
  ./run-recipe.sh glm-4.7-nvfp4 --setup  # Uses nodes from .env

2026-02-03 16:09:12 -05:00

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