nemo-guardrails

Runtime safety rails prevent jailbreaks in LLM applications by validating inputs and outputs programmatically. NeMo Guardrails enables this by detecting unsafe prompts and injections during inference to block malicious interactions.

PII filtering and toxicity detection for production LLMs are best implemented through programmable runtime guardrails. NeMo Guardrails applies these safety checks across deployment pipelines to intercept sensitive data and toxic content.

Fact-checking with retrieval mitigates LLM hallucination by validating model outputs against retrieved external knowledge. NeMo Guardrails integrates this mechanism to detect ungrounded responses and prevent factual inaccuracies.

You can configure custom input and output validation rules using Colang 2.0 DSL. NeMo Guardrails supports this domain-specific language to define programmable safety rails tailored to specific LLM interaction requirements.

NeMo Guardrails supports production-ready GPU deployment for LLM inference. It applies runtime safety rails across deployment pipelines, ensuring low-latency input validation and jailbreak detection in high-throughput environments.