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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 installations selon la source☆ 0 Étoiles du dépôt

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install d-wwei/openclaw-nim-skill

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

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.

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/d-wwei/openclaw-nim-skill
Version
—
Commit
050b6a49fe4522f3c3241cff7708f05c10f01df0
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

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

Contenu extrait

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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