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OpenClaw

nim

Invoke various LLMs (GLM-5, Kimi-k2.5, Llama 3.1, etc.) via NVIDIA NIM API to save main agent tokens and leverage specialized model capabilities.

d-wwei0 来源安装数☆ 0 仓库 Stars

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 d-wwei/openclaw-nim-skill

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

NVIDIA NIM Skill for OpenClaw

This skill allows OpenClaw to delegate tasks to external models hosted on the NVIDIA NIM platform.

Setup

  1. Get API Key: Register at build.nvidia.com and get your nvapi-... key.
  2. Set Environment Variable:
    export NVIDIA_API_KEY="your_api_key_here"
    

Usage

Direct Command
python3 scripts/nim_call.py <model_alias> "<prompt>"
Supported Aliases
  • glm5: Zhipu AI GLM-5
  • kimi: Moonshot Kimi-k2.5
  • r1: DeepSeek R1 (Llama-8B Distill)
  • llama: Llama 3.1 405B
  • phi: Microsoft Phi-4

Integration with CLAUDE.md

Add this to your project's CLAUDE.md:

- /nim <model> <prompt>: Call NVIDIA NIM models.

来源信息

Source
github
Repository
openclaw/skills
Path
skills/d-wwei/openclaw-nim-skill
Version
—
Commit
050b6a49fe4522f3c3241cff7708f05c10f01df0
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。

README

OpenClaw NVIDIA NIM Skill

🚀 Token-Saving Superpower for OpenClaw/Claude Code

This skill integrates the NVIDIA NIM (Inference Microservices) platform into your OpenClaw environment. It allows you to "outsource" heavy tasks like summarization, long-form explanation, or deep reasoning to specialized models (GLM-5, Kimi-k2.5, DeepSeek R1, etc.) for FREE, saving up to 90%+ of your main agent's context tokens.

🌟 Features

  • Multi-Model Support: Switch between top Chinese and Global models instantly.
  • Zero Dependencies: Pure Python implementation using urllib.
  • Token Efficiency: Keeps your main conversation lean by handling long inputs/outputs externally.

📦 Installation

  1. Clone this repo into your skills/ directory.
  2. Get your free API Key from NVIDIA Build.
  3. Add export NVIDIA_API_KEY="your-key" to your .zshrc or .bashrc.

🛠 Usage

In your OpenClaw session:

"Use /nim with kimi to summarize this long file: [path]"

Or via CLI:

python3 scripts/nim_call.py kimi "Summarize the history of AI"

📜 License

MIT

来源内容

SKILL.md
# NVIDIA NIM Skill for OpenClaw

This skill allows OpenClaw to delegate tasks to external models hosted on the NVIDIA NIM platform.

## Setup

1. **Get API Key**: Register at [build.nvidia.com](https://build.nvidia.com) and get your `nvapi-...` key.
2. **Set Environment Variable**:
   ```bash
   export NVIDIA_API_KEY="your_api_key_here"
   ```

## Usage

### Direct Command
```bash
python3 scripts/nim_call.py <model_alias> "<prompt>"
```

### Supported Aliases
- `glm5`: Zhipu AI GLM-5
- `kimi`: Moonshot Kimi-k2.5
- `r1`: DeepSeek R1 (Llama-8B Distill)
- `llama`: Llama 3.1 405B
- `phi`: Microsoft Phi-4

## Integration with CLAUDE.md
Add this to your project's `CLAUDE.md`:
```markdown
- /nim <model> <prompt>: Call NVIDIA NIM models.
```
README
# OpenClaw NVIDIA NIM Skill

🚀 **Token-Saving Superpower for OpenClaw/Claude Code**

This skill integrates the **NVIDIA NIM (Inference Microservices)** platform into your OpenClaw environment. It allows you to "outsource" heavy tasks like summarization, long-form explanation, or deep reasoning to specialized models (GLM-5, Kimi-k2.5, DeepSeek R1, etc.) for FREE, saving up to 90%+ of your main agent's context tokens.

## 🌟 Features

- **Multi-Model Support**: Switch between top Chinese and Global models instantly.
- **Zero Dependencies**: Pure Python implementation using `urllib`.
- **Token Efficiency**: Keeps your main conversation lean by handling long inputs/outputs externally.

## 📦 Installation

1. Clone this repo into your `skills/` directory.
2. Get your free API Key from [NVIDIA Build](https://build.nvidia.com/).
3. Add `export NVIDIA_API_KEY="your-key"` to your `.zshrc` or `.bashrc`.

## 🛠 Usage

In your OpenClaw session:
> "Use /nim with kimi to summarize this long file: [path]"

Or via CLI:
```bash
python3 scripts/nim_call.py kimi "Summarize the history of AI"
```

## 📜 License
MIT

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