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site_name: LLM Guard

site_author: Protect AI, Inc.

Byte-compiled / optimized / DLL files

pycache/

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).

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

[*]

ignore:

- "guardrails/version.py"

Structure

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

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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

pycache

*.pyc

repos:

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

Security

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

.railsignore

No description available.

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

SPDX-License-Identifier: Apache-2.0

Changelog

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

Changelog

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

NVIDIA NeMo Guardrails Library

Contributing Guidelines

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

repos:

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

.git

.idea

```gitignore

*.pyc