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LLM Guard - The Security Toolkit for LLM Interactions

LLM Guard by Protect AI is a comprehensive tool designed to fortify the security of Large Language Models (LLMs).

Byte-compiled / optimized / DLL files

pycache/

Contributing

:tada: Thanks for taking the time to contribute! :tada:

.markdownlint.yml

MD004: false # Unordered list style

repos:

- repo: https://github.com/pre-commit/pre-commit-hooks

root = true

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Untitled Skill

Structure

Guardrails docs are served as a docusaurus site. The docs are compiled from various sources

ignore:

- "guardrails/version.py"

Contributing to Guardrails

Welcome and thank you for your interest in contributing to Guardrails! We appreciate all contributions, big or small, from bug fixes to new features. Before diving in, let's go through some guidelines...

openaiapikey.txt

pycache

repos:

- repo: https://github.com/astral-sh/ruff-pre-commit

pycache

*.pyc

Security

NVIDIA is dedicated to the security and trust of our software products and services, including all source code repositories managed through our organization.

SPDX-FileCopyrightText: Copyright (c) 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.

SPDX-License-Identifier: Apache-2.0

.railsignore

No description available.

Changelog

All notable changes to this project will be documented in this file.

Contributing Guidelines

Welcome to NeMo Guardrails. This guide explains the contribution workflow,

Changelog

All notable changes to the Colang language and runtime will be documented in this file.

NVIDIA NeMo Guardrails Library

.git

.idea

repos:

- repo: https://github.com/pre-commit/pre-commit-hooks

```gitignore

*.pyc

You can override the included template(s) by including variable overrides

stages: