Skip to main content

No project description provided

Project description

Project logo

any-guardrail

Docs Linting Unit Tests Integration Tests

Python 3.11+ PyPI Discord

A single interface to use different guardrail models.

any-guardrail provides a unified interface for AI safety guardrails, for example, letting you detect toxic content, jailbreak attempts, and other risks in LLM inputs and outputs. Switch between different guardrail providers, both encoder-based (discriminative) and decoder-based (generative) models like Llama Guard and ShieldGemma, without changing your code.

Some guardrails are extremely customizable, which any-guardrail fully exposes. See the complete list of supported providers and customization examples in our docs.

Why any-guardrail?

  • Unified API: Switch between evergrowing list of guardrail providers
  • Production-ready: Built for real-world LLM applications
  • Flexible: Use encoder-based (fast) or decoder-based (customizable) models

Quickstart

Requirements

  • Python 3.11 or newer

Installation

Install with pip:

pip install any-guardrail

Basic Usage

AnyGuardrail provides a seamless interface for interacting with the guardrail models. It allows you to see a list of all the supported guardrails, and to instantiate each supported guardrail. Here is a full example:

from any_guardrail import AnyGuardrail, GuardrailName, GuardrailOutput

# Initialize guardrail
guardrail = AnyGuardrail.create(GuardrailName.DEEPSET)

# Validate input before sending to your LLM
result: GuardrailOutput = guardrail.validate("How do I hack into a system?")

if not result.valid:
    print(f"Blocked: {result.explanation}")
else:
    # Safe to proceed with LLM call
    response = your_llm(user_input)

Documentation

Full guides at docs link

Troubleshooting

Some of the models on HuggingFace require extra permissions to use. To do this, you'll need to create a HuggingFace profile and manually go through the permissions. Then, you'll need to download the HuggingFace Hub and login. One way to do this is:

pip install --upgrade huggingface_hub

hf auth login

More information can be found here: HuggingFace Hub

Contributing to any-guardrail

The guardrail space is ever growing. If there is a guardrail that you'd like us to support, please see our CONTRIBUTING.md for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

any_guardrail-0.5.0.tar.gz (221.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

any_guardrail-0.5.0-py3-none-any.whl (71.5 kB view details)

Uploaded Python 3

File details

Details for the file any_guardrail-0.5.0.tar.gz.

File metadata

  • Download URL: any_guardrail-0.5.0.tar.gz
  • Upload date:
  • Size: 221.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for any_guardrail-0.5.0.tar.gz
Algorithm Hash digest
SHA256 fc925c3f680171a38023ea3515e8e0d2e5ac80b6b0a093b0eba365d0fdcdd507
MD5 5f11dd1f72ff318fcf18e64cf0a73ac1
BLAKE2b-256 8a10099d620bb6adc69b50fb24cde3703dc3c2c87f4a01b33c6be97ed692c9f5

See more details on using hashes here.

Provenance

The following attestation bundles were made for any_guardrail-0.5.0.tar.gz:

Publisher: release.yaml on mozilla-ai/any-guardrail

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file any_guardrail-0.5.0-py3-none-any.whl.

File metadata

  • Download URL: any_guardrail-0.5.0-py3-none-any.whl
  • Upload date:
  • Size: 71.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for any_guardrail-0.5.0-py3-none-any.whl
Algorithm Hash digest
SHA256 d2315949424047ab39967b89ea1aa0629515e626bad560909b1b83af52df3bcc
MD5 b6b8f07288585a6955d28e40aa61f499
BLAKE2b-256 29086eb47360e695f749298c9231710092879a912b4f2979ad1130357ffdbc01

See more details on using hashes here.

Provenance

The following attestation bundles were made for any_guardrail-0.5.0-py3-none-any.whl:

Publisher: release.yaml on mozilla-ai/any-guardrail

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page