For AI agents: a documentation index is available at the root level at /llms.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.
This page is for version v0.24.0.
For other versions, use one of these documentation indexes:
- Latest (default): https://docs.nvidia.com/nemo/guardrails/latest/llms.txt
- v0.24.1: https://docs.nvidia.com/nemo/guardrails/v0.24.1/llms.txt
- v0.24.0: https://docs.nvidia.com/nemo/guardrails/v0.24.0/llms.txt
- v0.23.0: https://docs.nvidia.com/nemo/guardrails/v0.23.0/llms.txt
- v0.22.0: https://docs.nvidia.com/nemo/guardrails/v0.22.0/llms.txt
The following diagrams illustrate the NeMo Guardrails architecture for each use case.
1. Content Safety
Content safety guardrails check both user inputs and LLM outputs for harmful content.
2. Jailbreak Protection
Jailbreak protection prevents adversarial attempts from bypassing safety measures.
3. Topic Control
Topic control ensures conversations stay within predefined subject boundaries.
4. PII Detection and Masking
PII detection protects user privacy by detecting and masking sensitive data.
5. Agentic Security
Agentic security provides guardrails for LLM agents using tools and external systems.
6. Custom and Third-Party Guardrails
Build custom guardrails using Python actions, LangChain tools, or third-party APIs.
7. Integration Options
Multiple integration options: Python SDK, HTTP Server API, or OpenAI-compatible endpoint.
Combined Architecture Overview
Complete architecture showing all guardrail types and integration options.