#5050th of 70 in Agent frameworks and SDKs
guardrails
Python framework for validating LLM inputs and outputs and generating structured data
Documentation ↗
(opens in a new tab)Website ↗
(opens in a new tab)Repository on GitHub ↗
(opens in a new tab)
- Stars
- 7.6k
- License
- Apache-2.0
- Last commit
- Aug 2026
- Last release
- Aug 2026
- Language
- Python
6,573 on 1 Apr 20267,552 on 21 Oct 2026
From GitHub's daily star counts.
Checked on GitHub.
Overview
Guardrails is a Python library that wraps LLM calls with input and output guards built from validators, such as regex match, competitor check and toxic language. It also produces structured output from Pydantic models, using function calling or a schema added to the prompt. Guards run in-process or behind a Flask REST server started with `guardrails start`, which exposes an OpenAI SDK-compatible endpoint.
Who it is for: Python developers adding validation and structured output to LLM apps
Strengths
- Several validators combine in one Guard, each with its own on_fail action
- Structured output from Pydantic models via function calling or prompt schema
- Guard server exposes an OpenAI SDK-compatible base URL for existing clients
- Custom validators supported; works with proprietary and open-source LLMs
Weaknesses
- Hosted remote inferencing is being discontinued, planned cutoff August 25, 2026
- Validators are moving to separate PyPI packages, so existing installs need migration
- Hub validators need separate installs and `guardrails configure` setup
- README examples use the legacy OpenAI completions API; one sample output is malformed
What it needs
- Needs Guardrails Hub validators (pip packages), LLM provider API (e.g. OpenAI)
- Models: OpenAI, any LLM, proprietary or open-source
- port 8000
Also in Agent frameworks and SDKs
See all 70| Rank | Project | Score |
|---|---|---|
| 1 | ppt-masterAgent skill that turns documents into natively editable PowerPoint decks | 94 out of 100 |
| 2 | langchainPython framework for building LLM agents and apps from interoperable components | 89 out of 100 |
| 3 | browser-usePython library that lets an LLM agent control a web browser | 89 out of 100 |
| #4 | openai-agents-pythonPython SDK for multi-agent workflows with handoffs, guardrails and tracing | 89 out of 100 |
| #5 | mastraTypeScript framework for building AI agents and workflows | 89 out of 100 |