> This page is for version v0.24.1. > 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 > For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.nvidia.com/nemo/guardrails/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/guardrails/_mcp/server. # NVIDIA NeMo Guardrails Library > Add programmable guardrails to LLM applications with an open-source Python library. The NeMo Guardrails library is an open-source Python package for adding programmable guardrails to LLM-based applications. It intercepts inputs and outputs, applies configurable safety checks, and blocks or modifies content based on defined policies. ## Get Started Use the starter prompt with your AI coding agent to help it install the NVIDIA NeMo Guardrails library, choose the right docs, or follow contributor guidance. #### Copy Starter Prompt # NVIDIA NeMo Guardrails Library Agent Instructions You are helping me get started with the NVIDIA NeMo Guardrails library from this AI coding agent. Use the official documentation as the source of truth instead of relying on memory. 1. Ask whether I am a developer using the library or a contributor changing the Guardrails repository, then ask what I want to accomplish. 2. Before using installation or tutorial instructions, check whether `nemoguardrails` is installed and determine its version when possible. 3. Discover the stable package releases and published documentation versions from official sources. Use `https://docs.nvidia.com/nemo/guardrails/llms.txt` to find documentation when needed. Do not rely on a hardcoded version list. 4. If the installed version has matching documentation, recommend that version and ask whether to keep it, upgrade, or choose another version. 5. For a first-time installation, present the available versions as a numbered list, newest first. Mark the most recent stable release as "Recommended for first-time installation," include older releases with published documentation, and let me specify another exact version for an existing setup. 6. If the selected package version has no matching documentation, explain the mismatch and ask which published version to use. Do not silently fall back to Latest. 7. Set `DOCS_BASE` to the selected documentation version, load `DOCS_BASE/get-started/use-with-ai-agent.md`, and follow that canonical agent guidance. Prefer the documentation MCP server when available. 8. If I am contributing, clone the repository when needed and follow its `AGENTS.md`, `CONTRIBUTING.md`, and `AI_POLICY.md` files. Never ask me to paste real credentials into chat. Use placeholders and let me set secrets through my local environment or secret manager. Begin by asking which role applies and what I want to do. Browse the following introductory guides to learn more about the NVIDIA NeMo Guardrails library. #### [Overview](/nemo/guardrails/overview) Overview of the NVIDIA NeMo Guardrails library, including its capabilities, architecture, and supported LLMs. Concept #### [Installation](/nemo/guardrails/v0.24.1/get-started/installation-guide) Install NeMo Guardrails with pip, configure your environment, and verify the installation. Get Started #### [Use with AI Agents](/nemo/guardrails/v0.24.1/get-started/use-with-ai-agent) Connect Cursor, Claude Code, Codex, or another AI agent to the documentation MCP server or starter prompt. Get Started #### [Tutorials](/nemo/guardrails/v0.24.1/get-started/tutorials) Follow hands-on tutorials to deploy Nemotron Content Safety, Nemotron Topic Control, and Nemotron Jailbreak Detect Tutorial #### [Guardrail Catalog](/nemo/guardrails/v0.24.1/configure-guardrails/guardrail-catalog) Reference for pre-built guardrails including content safety, jailbreak detection, topic control, PII handling, agentic security, and third party APIs. Reference ## Next Steps Once you've completed the get-started tutorials, explore the following areas to deepen your understanding. #### [Configuring Guardrails](/nemo/guardrails/v0.24.1/configure-guardrails/configure-rails) Configure YAML files, Colang flows, custom actions, and other components to control LLM behavior. Concept #### [Running Guardrailed Inference](/nemo/guardrails/v0.24.1/run-guardrailed-inference/run-rails) Run guardrailed inference using the Python API or Guardrails API server. Get Started #### [Evaluating Guardrails](/nemo/guardrails/v0.24.1/evaluation/evaluate-guardrails) Measure accuracy and performance of dialog, fact-checking, moderation, and hallucination rails. How To #### [Logging](/nemo/guardrails/v0.24.1/observability/logging) Debug guardrails with verbose mode, explain method, and generation log options. How To #### [Observability](/nemo/guardrails/v0.24.1/observability/observability) Use OpenTelemetry to trace requests, forward Python logs, and emit metrics for end-to-end visibility into guardrails. How To #### [Deployment Options](/nemo/guardrails/v0.24.1/more-deployment-options/deployment) Deploy guardrails using the local API server, Docker containers, or production microservices. How To #### [LangChain Frameworks](/nemo/guardrails/v0.24.1/integration-with-third-party-libraries/langchain) Integrate NeMo Guardrails with LangChain chains, runnables, and LangGraph workflows. How To