OpenClaw

mlops-automation-cn

Task automation, containerization, CI/CD, and experiment tracking

guohongbin-git0 来源安装数☆ 0 仓库 Starsv1.0.0

查看来源 ↗安装与使用 SKILL.md ↗

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。

SkillHub CLI

skillhub install guohongbin-git/mlops-automation-cn

打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

MLOps Automation 🤖

Automate tasks, containers, CI/CD, and ML experiments.

Features

1. Task Runner (just) ⚡

Copy justfile:

cp references/justfile ../your-project/

Tasks:

just check - Run all checks
just test - Run tests
just build - Build package
just clean - Remove artifacts
just train - Run training

2. Docker 🐳

Multi-stage build:

cp references/Dockerfile ../your-project/
docker build -t my-model .
docker run my-model

Optimizations:

Layer caching (uv sync before copy src/)
Minimal runtime image
Non-root user

3. CI/CD (GitHub Actions) 🔄

Automated pipeline:

cp references/ci-workflow.yml ../your-project/.github/workflows/ci.yml

Runs on push/PR:

Lint (Ruff + MyPy)
Test (pytest + coverage)
Build (package + Docker)

Quick Start

# Setup task runner
cp references/justfile ./

# Setup CI
mkdir -p .github/workflows
cp references/ci-workflow.yml .github/workflows/ci.yml

# Setup Docker
cp references/Dockerfile ./

# Test locally
just check
docker build -t test .

MLflow Tracking

import mlflow

mlflow.autolog()
with mlflow.start_run():
    mlflow.log_param("lr", 0.001)
    model.fit(X, y)
    mlflow.log_metric("accuracy", acc)

Author

Converted from MLOps Coding Course

Changelog

v1.0.0 (2026-02-18)

Initial OpenClaw conversion
Added justfile template
Added Dockerfile
Added CI workflow

来源信息

Source: github
Repository: openclaw/skills
Path: skills/guohongbin-git/mlops-automation-cn
Version: 1.0.0
Commit: a5bde140dc312c06c020b757100b583932ae5490
分类来源: rules
状态: active
可见性: public

这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。

来源内容

SKILL.md

# MLOps Automation 🤖

Automate tasks, containers, CI/CD, and ML experiments.

## Features

### 1. Task Runner (just) ⚡

Copy justfile:

```bash
cp references/justfile ../your-project/
```

Tasks:
- `just check` - Run all checks
- `just test` - Run tests
- `just build` - Build package
- `just clean` - Remove artifacts
- `just train` - Run training

### 2. Docker 🐳

Multi-stage build:

```bash
cp references/Dockerfile ../your-project/
docker build -t my-model .
docker run my-model
```

Optimizations:
- Layer caching (uv sync before copy src/)
- Minimal runtime image
- Non-root user

### 3. CI/CD (GitHub Actions) 🔄

Automated pipeline:

```bash
cp references/ci-workflow.yml ../your-project/.github/workflows/ci.yml
```

Runs on push/PR:
- Lint (Ruff + MyPy)
- Test (pytest + coverage)
- Build (package + Docker)

## Quick Start

```bash
# Setup task runner
cp references/justfile ./

# Setup CI
mkdir -p .github/workflows
cp references/ci-workflow.yml .github/workflows/ci.yml

# Setup Docker
cp references/Dockerfile ./

# Test locally
just check
docker build -t test .
```

## MLflow Tracking

```python
import mlflow

mlflow.autolog()
with mlflow.start_run():
    mlflow.log_param("lr", 0.001)
    model.fit(X, y)
    mlflow.log_metric("accuracy", acc)
```

## Author

Converted from [MLOps Coding Course](https://github.com/MLOps-Courses/mlops-coding-skills)

## Changelog

### v1.0.0 (2026-02-18)
- Initial OpenClaw conversion
- Added justfile template
- Added Dockerfile
- Added CI workflow

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