guardrails-ai/guardrails

Adding guardrails to large language models.

70
/ 100
Verified

This tool helps developers build reliable AI applications by ensuring the output from large language models (LLMs) is safe, compliant, and correctly formatted. It takes an LLM's raw output and applies predefined 'guards' or validation rules to it, flagging or correcting issues like toxic language, competitor mentions, or incorrect data formats. The end user is an AI developer or engineer responsible for integrating LLMs into applications and maintaining their quality and safety.

6,534 stars. Actively maintained with 62 commits in the last 30 days.

Use this if you are building an application with a large language model and need to guarantee its outputs are structured correctly and free from specific risks like toxicity or unwanted information.

Not ideal if you are looking for a general-purpose data validation tool not specifically designed for large language model outputs or if you need to fine-tune an LLM model itself.

AI application development LLM output validation AI safety data structuring AI engineering
No Package No Dependents
Maintenance 25 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 19 / 25

How are scores calculated?

Stars

6,534

Forks

543

Language

Python

License

Apache-2.0

Last pushed

Mar 12, 2026

Commits (30d)

62

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