README.md
December 25, 2023 ยท View on GitHub

Plexiglass
Quickstart | Installation | Documentation | Code of Conduct
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:
toxicitypii_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-chatmode - security, bias and toxicity benchmarking with
llm-scanmode - generate html report in
llm-scanandllm-chatmodes - standalone python module
- production-ready API
Join us in #plexiglass on Discord.
Contributors
Code of Conduct
Read our Code of Conduct.
Made with contrib.rocks.