nemo-guardrails

Preventing prompt injection attacks involves implementing runtime guardrails to intercept and validate user inputs before they reach the LLM. This Skill uses NVIDIA's NeMo Guardrails to detect jailbreaks and filter malicious queries programmatically.

Detecting LLM hallucinations at runtime requires fact-checking mechanisms that verify response accuracy against defined policies. This Skill implements NeMo Guardrails to validate LLM outputs, ensuring factual accuracy and preventing unintended responses in real-time.

Filtering PII from LLM interactions is achievable using programmable rails defined in the Colang 2.0 DSL. This Skill leverages NeMo Guardrails to automatically mask or remove Personally Identifiable Information from user queries and bot replies.

NeMo Guardrails operates effectively on NVIDIA T4 GPUs for low-latency runtime safety filtering. This Skill is production-ready and deploys on T4 hardware to perform real-time input validation, toxicity detection, and jailbreak prevention without significant overhead.

Runtime safety checks are needed for customer service chatbots to prevent the generation of inappropriate responses and protect sensitive information. This Skill implements NeMo Guardrails to filter all user queries and bot replies, ensuring adherence to defined compliance policies.

Setting up input and output validation policies requires defining programmable rules using the Colang 2.0 DSL. This Skill uses NeMo Guardrails to enforce these policies, ensuring both user inputs and LLM outputs adhere strictly to your defined safety and compliance standards.