A comprehensive command-line framework for managing the lifecycle of machine learning experiments, training jobs, and inference services.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install luban-cli
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install luban-cli using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Luban CLI?
The Luban CLI is a specialized Openclaw Skills framework designed to bridge the gap between model development and production deployment. It provides a unified interface for MLOps practitioners to manage three critical pillars: experiment environments, training task orchestration, and the deployment of online services. By using this tool, teams can ensure consistent environments across the development lifecycle.
Built with extensibility in mind, this Openclaw Skills asset includes structural templates that allow developers to build or customize their own MLOps interfaces. It simplifies complex resource management tasks, allowing data scientists to focus on model logic rather than infrastructure configuration.
Luban CLI Use Cases
- Orchestrating distributed model training workloads with specific GPU requirements.
- Provisioning standardized development environments for data science teams using Openclaw Skills.
- Deploying and autoscaling inference services for real-time model serving.
- Automating the lifecycle management of MLOps resources through a unified CLI.
How Luban CLI Works
- Initialize the CLI project using the provided Python boilerplate within the Openclaw Skills directory.
- Define MLOps commands for environments, jobs, and services based on the provided reference guides.
- Implement the required CRUD operations to ensure each entity can be created, read, updated, and deleted.
- Execute commands via the terminal to interact with the MLOps backend for resource provisioning and job tracking.
Luban CLI Setup
To get started with the Luban CLI using Openclaw Skills, follow these installation steps:
- Access the skill templates:
cd skills/luban-cli/templates
- Initialize your project using the boilerplate:
python cli_boilerplate.py --init
- Verify the installation by listing available environments:
luban env list
Luban CLI Data Schema & Taxonomy
The Luban CLI organizes MLOps entities according to a strict schema within the Openclaw Skills framework:
| Entity | Description | Key Attributes |
|---|---|---|
| env | Experiment Environments | Name, Docker Image, Workspace Path |
| job | Training Tasks | Script Entrypoint, GPU Count, Job ID |
| svc | Online Services | Model Path, Replicas, Service ID |
All metadata for these entities is tracked through the Openclaw Skills reference guide to ensure cross-team compatibility.
Luban CLI Advanced Features
- Scalable service management allowing for dynamic replica adjustments of inference nodes.
- Standardized boilerplate structures for rapid CLI extension and customization within Openclaw Skills.
- Comprehensive resource lifecycle tracking from initial provisioning to final cleanup.
- Support for complex training task orchestration with dedicated hardware allocation.
SKILL.md
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