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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).

root = true

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Structure

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

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...

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ignore:

- "guardrails/version.py"

repos:

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

pycache

*.pyc

openaiapikey.txt

pycache

Security

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

Changelog

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

.railsignore

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NVIDIA NeMo Guardrails Library

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.

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

SPDX-License-Identifier: Apache-2.0

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

stages:

repos:

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

.git

.idea

```gitignore

*.pyc

LlamaIndex Integrations

Building LLM applications with LlamaIndex involves building with LlamaIndex

This Pylint rcfile contains a best-effort configuration to uphold the

[MASTER]

English | Español | Français | Deutsch | 中文 | Türkçe | [日本語](./docs/READ

name: pygwalker

channels: