About Configuring Guardrails

Prepare LLM endpoints, NemoGuard NIMs, and knowledge base documents before configuration.

Learn to write config.yml, Colang flows, and custom actions for guardrails.

Define models, guardrails, prompts, and tracing settings in the config.yml file.

Reference for all config.yml options including models, rails, prompts, and advanced settings.

Reference for pre-built guardrails including content safety, jailbreak detection, and PII handling.

Learn Colang, the event-driven language for defining guardrails flows and bot behavior.

Create Python actions to extend guardrails with external APIs and validation logic.

Use config.py to register custom LLM providers, embedding providers, and shared resources at startup.

Additional configuration topics including knowledge base setup and embedding search providers.

Configure in-memory caching for LLM calls and KV cache reuse to improve performance and reduce latency.

Raise and handle exceptions in guardrails flows to control error behavior and custom responses.