{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/5"}],"enrichment":{"capability":"Adds programmable guardrails to LLM-based conversational applications to control output behavior, prevent unsafe responses, and enforce structured dialog flows.","skillfed_tags":["llm-safety","conversational-ai","prompt-engineering"],"use_cases":["Add fact-checking and output moderation to retrieval-augmented generation (RAG) systems","Build domain-specific chatbots that stay on topic and follow predefined conversation flows","Protect custom LLM endpoints from jailbreaks and prompt injection attacks","Mask sensitive data (PII, credentials) in user input before the LLM sees it","Enforce authentication and support workflows in conversational applications"],"what_it_does":"NeMo Guardrails is an NVIDIA open-source library that inserts a programmable control layer between your application code and an LLM. It lets you define rules\u2014called rails\u2014that shape how the LLM responds: rejecting unsafe inputs, preventing jailbreaks and prompt injections, enforcing topic boundaries, masking sensitive data, and steering conversations along predefined paths. The library supports five rail types (input, dialog, retrieval, execution, output) and works with multiple LLM providers.\n\nYou configure guardrails via YAML and Python files in a standard folder structure, then instantiate an LLMRails object and call generate() or generate_async() instead of the LLM directly. The API mirrors OpenAI's Chat Completions format, so integration requires minimal code changes. It's async-first internally but exposes both sync and async methods, and includes built-in protections against common LLM vulnerabilities like jailbreaks and hallucinations.","worth_installing":"Yes, if you are building LLM-based conversational applications and need safety controls. The library is actively maintained, has no known vulnerabilities, supports current Python versions, and low install friction. The 18 dependencies are standard ecosystem packages. Permissive licensing allows commercial use. Main consideration: evaluate whether the guardrails configuration overhead and async-first design fit your application architecture."},"id":"nemoguardrails","links":{"html":"https://skillfed.io/packages/nemoguardrails","md":"https://skillfed.io/packages/nemoguardrails.md","pypi":"https://pypi.org/project/nemoguardrails/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-01","license_spdx":null,"license_treatment":"permissive","name":"nemoguardrails","python_support":"supports_current","summary":"NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems."},"popularity":{"monthly_downloads":407191,"position":6888,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.23.0"}