Guardrails AI

What is Guardrails AI?

Guardrails AI is an open-source framework for validating and correcting LLM outputs at runtime — enforcing structured formats, catching hallucinations, and blocking unsafe content before it reaches an end user or downstream system.

Key features

• Runtime validation of LLM outputs against defined rules
• Pre-built validators for common issues like PII leaks and toxicity
• Automatic re-asking or correction when output fails validation
• Structured output enforcement (like valid JSON) for app integrations
• Open-source core with a hub of community-contributed validators

How to get started

1. Install the Guardrails AI Python package
2. Define a spec for the output format and rules you require
3. Wrap your LLM calls with Guardrails validation
4. Configure automatic re-asking or fallback behavior on failure

Use cases

• Enforcing structured, valid JSON output from an LLM
• Blocking PII leaks or toxic content before it reaches users
• Adding a safety layer to a production LLM application
• Reducing hallucination-related errors in critical workflows

Guardrails AI vs. alternatives

FAQ

Is Guardrails AI free to use?

Guardrails AI's plans: Free, open-source; paid enterprise plans. Pricing and free-tier limits change over time, so check the official site above for the latest details.

What is Guardrails AI used for?

Validation framework for safer, structured LLM output.

Who is Guardrails AI best for?

Guardrails AI is a good fit for enforcing structured, valid JSON output from an LLM, or blocking PII leaks or toxic content before it reaches users.

What are the alternatives to Guardrails AI?

Commonly compared alternatives include Promptfoo and Hive Moderation, see the comparison above for how they differ.