Instantly deploy and chat with local or Hugging Face models directly from your workspace using vLLM.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install modelready
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 modelready 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 ModelReady?
ModelReady is a high-performance utility designed to streamline the deployment of Large Language Models (LLMs) from local storage or the Hugging Face hub. By leveraging the vLLM engine, it transforms complex model repositories into accessible, OpenAI-compatible endpoints within seconds, allowing for immediate interaction within your development environment.
As a versatile component of Openclaw Skills, ModelReady bridges the gap between raw model files and interactive chat interfaces. It allows developers to maintain full control over their model infrastructure while benefiting from a simplified command-line interface for management and testing.
ModelReady Use Cases
- Rapidly prototyping applications with specific Hugging Face model variants without manual setup.
- Running sensitive or proprietary models locally to ensure data privacy and security.
- Testing different quantization levels or tensor parallelism configurations on the fly for performance tuning.
- Integrating local model endpoints into larger automated workflows powered by Openclaw Skills.
How ModelReady Works
- Initialize the model server by specifying the local file path or the Hugging Face repository ID.
- Configure performance parameters such as tensor parallelism and data types to match your hardware.
- The skill utilizes vLLM to host an OpenAI-compatible API on a designated port.
- Interact with the model directly via the chat command or send requests from external applications to the local endpoint.
- Monitor server health or stop the process once the task is complete to free up system resources.
ModelReady Setup
Ensure you have bash and curl installed on your system. To add this to your environment, use the standard installation command for Openclaw Skills:
openclaw install modelready
Configure your environment variables if you are targeting a remote host:
export URL="http://your-server-ip"
ModelReady Data Schema & Taxonomy
The skill manages model execution and connectivity through a structured set of parameters:
| Parameter | Description | Default/Options |
|---|---|---|
| repo | The source path or Hugging Face ID of the model. | Required |
| port | The network port for the OpenAI-compatible API server. | Required |
| tp | Tensor Parallelism degree for multi-GPU scaling. | Integer (e.g., 2, 4) |
| dtype | Weight and activation data type. | e.g., bfloat16, float16 |
| ip | The host IP address for the server instance. | Localhost by default |
ModelReady Advanced Features
- Seamless Hugging Face Hub integration for automatic model downloading and caching.
- Multi-GPU support via configurable Tensor Parallelism (TP) for large-scale model inference.
- Dynamic endpoint generation that follows the OpenAI API format for broad compatibility.
- Persistent configuration of default host IPs and ports to accelerate repetitive development tasks within Openclaw Skills.
- Low-latency inference powered by the vLLM backend for production-grade testing.
SKILL.md
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