nemo-guardrails

You can implement guardrails for LLM security using the NeMo Guardrails framework to define programmable safety policies with the Colang 2.0 DSL, preventing harmful outputs at runtime.

The best way to detect prompt injections and filter PII is by integrating a runtime safety framework that validates inputs and outputs, blocking inappropriate requests and sensitive information automatically.

You can configure hallucination detection and toxicity detection by defining content moderation rules using the Colang 2.0 DSL, ensuring LLM responses are factual and non-toxic before reaching the user.

Yes, NeMo Guardrails can run on NVIDIA T4 GPUs to deliver production-ready performance for runtime safety and LLM security tasks like fact-checking and jailbreak detection.

To set up NeMo Guardrails, install the library via 'pip install nemoguardrails', then use Colang 2.0 to define your safety policies for input validation and output filtering.

Using Colang 2.0 for programmable guardrails requires learning the domain-specific language to define policies, adding a configuration layer that must be maintained alongside your LLM application logic.