Awesome

<h1> <img src="plexiglass/assets/plexiglass_safellama.png" width="100" height="100"><br> Plexiglass</h1>

Quickstart | Installation | Documentation | Code of Conduct

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Plexiglass is a toolkit for detecting and protecting against vulnerabilities in Large Language Models (LLMs).

It is a simple command line interface (CLI) tool which allows users to quickly test LLMs against adversarial attacks such as prompt injection, jailbreaking and more.

Plexiglass also allows security, bias and toxicity benchmarking of multiple LLMs by scraping latest adversarial prompts such as jailbreakchat.com and wiki_toxic. See more at modes.

Quickstart

Please follow this quickstart guide in the documentation.

Installation

The first experimental release is version 0.0.1.

To download the package from PyPi:

pip install --upgrade plexiglass

Modes

Plexiglass has two modes: llm-chat and llm-scan.

llm-chat allows you to converse with the LLM and measure predefined metrics, such as toxicity, from its responses. It currently supports the following metrics:

toxicity
pii_detection

llm-scan runs benchmarks using open-source datasets to identify and assess various vulnerabilities in the LLM.

Feature Request

To request new features, please submit an issue

Development Roadmap

implement adversarial prompt templates in llm-chat mode
security, bias and toxicity benchmarking with llm-scan mode
generate html report in llm-scan and llm-chat modes
standalone python module
production-ready API

Join us in #plexiglass on Discord.

Contributors

<a href="https://github.com/kortex-labs/plexiglass/graphs/contributors"> <img src="https://contrib.rocks/image?repo=kortex-labs/plexiglass" /> </a>

Code of Conduct

Read our Code of Conduct.

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