🤖
MLOps Industrialization
Transform prototypes into distributable Python packages
安全通过
💬Prompt
技能说明
name: mlops-industrialization-cn version: 1.0.0 description: Transform prototypes into distributable Python packages license: MIT
MLOps Industrialization 🏭
Convert notebooks to production packages.
Features
1. Package Structure Generator 📦
Create src/ layout:
./scripts/create-package.sh my_package
Creates:
src/my_package/
├── __init__.py
├── io/ # I/O operations
├── domain/ # Pure business logic
└── application/ # Orchestration
2. Three-Layer Architecture 🏗️
Domain (Pure)
- No I/O, no side effects
- Feature transformations
- Pure functions or immutable objects
I/O (Impure)
- External interactions
- Load data, save models
- Classes for state management
Application
- Wire Domain + I/O
- Training loops, inference
Quick Start
# Create package structure
./scripts/create-package.sh my_ml_package
# Add CLI entrypoint to pyproject.toml:
# [project.scripts]
# train = "my_ml_package.application.train:main"
Key Files
Generated files:
src/my_package/domain/features.py- Feature engineeringsrc/my_package/io/data.py- Data loading/savingsrc/my_package/application/train.py- Training pipeline
Author
Converted from MLOps Coding Course
Changelog
v1.0.0 (2026-02-18)
- Initial OpenClaw conversion
- Added package generator
如何使用「MLOps Industrialization」?
- 打开小龙虾AI(Web 或 iOS App)
- 点击上方「立即使用」按钮,或在对话框中输入任务描述
- 小龙虾AI 会自动匹配并调用「MLOps Industrialization」技能完成任务
- 结果即时呈现,支持继续对话优化