Ross ROSS = Recommend OSS · open-source software intelligence for agents

NVIDIA-NeMo/Guardrails

NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems. observed · 2026-08-28

github.com/NVIDIA-NeMo/Guardrails · homepage · Python · NOASSERTION (other) observed · 2026-08-28

Health v2 · maintenance only

93/100

  • Activity 99
  • Release rhythm 87
  • Longevity 88

Flags: no_license

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 39
  • age_days: 1233
  • days_rel: 7
  • days_push: 7
  • n_releases_24m: 18

Full methodology

Adoption not part of the score

7017 stars · 812 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

NVIDIA NeMo Guardrails is an open-source Python toolkit for adding programmable guardrails to LLM-based conversational applications. It sits between your application and the LLM, validating inputs, filtering retrieved context, steering dialog flows, and blocking or transforming unsafe or policy-violating outputs using YAML configs, Colang flows, and custom actions.

Use cases

  • add guardrails to my llm chatbot
  • block prompt injection and jailbreak attempts
  • keep the llm from talking about off-topic subjects
  • detect and mask PII in user inputs and model outputs
  • enforce a predefined conversation flow for a support bot
  • validate retrieved documents before passing them to the llm
  • scan llm outputs for safety and policy violations
  • secure tool-calling in my ai agent workflow

When to choose

  • you need input, output, retrieval, and dialog rails around an LLM application
  • you want declarative YAML/Colang configuration plus custom Python actions
  • you need defense against prompt injection, jailbreaks, and PII leakage
  • you want observability, evaluation, and vulnerability scanning for your rails
  • you use LangChain or multiple LLM providers and need a provider-agnostic safety layer

When to avoid

  • you need a fully managed commercial content-moderation service rather than a self-hosted library
  • your application does not involve LLMs or conversational AI
  • you want zero-latency filtering, since rails add LLM calls and processing overhead
  • you need non-Python runtimes, as the library is Python-only

Facets

library · maturity active

security middleware llm-inference agent-framework chatbot prompt-engineering cli api-framework large-language-models security chatbots developer-tools python windows self-hosted cli guardrails llm-safety colang prompt-injection jailbreak-protection pii-detection content-moderation conversation-flow langchain-integration nvidia ai-agents natural-language-processing linux macos docker

10 sources

Member repositories

RepositoryRoleHealth v2
NVIDIA-NeMo/Guardrailsmain93

For agents

markdown · JSON · MCP: product_card(name="NVIDIA-NeMo/Guardrails")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem