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from openclaw-nim-skill12
Call NVIDIA NIM-hosted LLMs from OpenClaw to offload heavy model work and conserve main-agent tokens.
This skill integrates OpenClaw with NVIDIA's NIM platform, allowing the agent to call external models (GLM-5, Kimi, Llama 3.1, etc.) via an nvapi key. It wraps usage patterns for listing available models and invoking them with a prompt, helping agents delegate specific tasks to specialty models while preserving main-agent token budgets.
Use when you need to run inference on models hosted on NVIDIA NIM—for tasks that require specific model capabilities (e.g., code generation, multilingual reasoning, large-context jobs) or when you want to distribute load away from the primary agent. Suitable for batch inference, ad-hoc model calls, or when testing different model aliases.
python3 scripts/nim_call.py list and python3 scripts/nim_call.py <model_alias> "<prompt>".Agents that can run Python helper scripts or shell commands (OpenClaw main, CLI agents). Likely compatible with any agent that can execute subprocesses or call external HTTP-based model APIs.
NVIDIA NIM skill lets OpenClaw delegate LLM calls to NVIDIA-hosted models. The script ran cleanly, showing usage help when invoked without full args. SSL verification is disabled in the HTTP client, which is a security concern. Documentation mixes Chinese and English, limiting accessibility.
Disabling SSL verification is the main security issue. No hardcoded secrets, no destructive commands, no exfiltration. The skill is functional but rough — bare urllib, no logging, minimal error handling. Architecture is flat with no separation of concerns.
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