Enforce runtime safety rails for LLM applications using Colang 2.0 DSL.
npx skills add https://github.com/ovachiever/droid-tings --skill nemo-guardrails
Please help me install this Agent Skill. Skill: nemo-guardrails Source: https://github.com/ovachiever/droid-tings/tree/main/skills/nemo-guardrails Command: npx skills add https://github.com/ovachiever/droid-tings --skill nemo-guardrails
NVIDIA's NeMo Guardrails for real-time jailbreak prevention, input/output validation, and fact-checking in LLM apps, with Colang 2.0 DSL for programmable rails.
Install guardrails, define rails with Colang DSL, and apply to LLM calls to enforce safety policies.
High-intent search queries and answers about installing and using this skill.
Jailbreak detection identifies malicious prompts designed to bypass LLM safety constraints. NeMo Guardrails provides runtime jailbreak detection and prompt-injection guardrails using the Colang 2.0 DSL to define and enforce configurable safety policies on GPU-accelerated deployments.
Yes. NeMo Guardrails enables PII filtering and toxicity detection across both user inputs and LLM outputs. Define filtering rules with Colang 2.0 DSL and apply them in real time to enforce production-grade safety compliance.
Fact-checking and retrieval integration in NeMo Guardrails allow you to validate LLM responses against external knowledge sources. Use Colang 2.0 DSL to wire guardrails that cross-reference outputs with fact databases and flag hallucinations or unsupported claims.
NeMo Guardrails provides the Colang 2.0 DSL, a programmable domain-specific language for defining safety rails. Deploy on NVIDIA GPUs for real-time input/output validation, jailbreak detection, and hallucination prevention without modifying your existing LLM pipeline.
NeMo Guardrails is designed for NVIDIA GPU-accelerated execution to handle runtime safety filtering at scale. GPU deployment enables efficient real-time enforcement of guardrails in production LLM applications.
Yes. NeMo Guardrails supports bidirectional validation through input/output validation components. Define safety policies in Colang 2.0 DSL that govern both incoming prompts and outgoing LLM responses within a single integrated framework.
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