Guardrails OSS is an open-source framework for enforcing safety, compliance, and policy controls on large language model (LLM) applications. It wraps around LLM-based workflows to validate inputs and outputs in real time before they reach end-users. Core functionality: - Detects and blocks risks such as PII leaks, hallucinations, jailbreak attempts, and policy violations - Provides low-latency, real-time validation that operates as a layer around LLM applications - Includes 65+ community-built guardrails covering risk categories including hallucination, PII, jailbreaks, and content moderation - Allows users to define and enforce custom policies in addition to pre-built guardrails Deployment and compatibility: - Supports any LLM provider (referenced examples include Meta and Anthropic models) - Can be deployed in cloud environments or fully on-premises - Compatible with multiple use case types including chatbots, RAG pipelines, and agentic AI workflows Ecosystem: - Backed by a Guardrails Hub where users can browse and use community-built guardrail components - Accompanied by documentation for integration and operation guidance - Designed for use by enterprises, startups, and government agencies The framework is open source and intended for teams building production AI applications who need structured enforcement of safety and policy requirements across their LLM interactions.