PentestGPT VS trex

Compare PentestGPT vs trex and see what are their differences.

trex

Enforce structured output from LLMs 100% of the time (by automorphic-ai)
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PentestGPT trex
18 3
6,361 238
- 0.4%
8.2 6.6
13 days ago 8 months ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

PentestGPT

Posts with mentions or reviews of PentestGPT. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-02.

trex

Posts with mentions or reviews of trex. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-10-03.

What are some alternatives?

When comparing PentestGPT and trex you can also consider the following projects:

llama.cpp - LLM inference in C/C++

graph-of-thoughts - Official Implementation of "Graph of Thoughts: Solving Elaborate Problems with Large Language Models"

ChatGLM2-6B - ChatGLM2-6B: An Open Bilingual Chat LLM | εΌ€ζΊεŒθ―­ε―Ήθ―θ―­θ¨€ζ¨‘εž‹

sycamore - 🍁 Sycamore is an LLM-powered search and analytics platform for unstructured data.

deepdoctection - A Repo For Document AI

autolabel - Label, clean and enrich text datasets with LLMs.

langcorn - ⛓️ Serving LangChain LLM apps and agents automagically with FastApi. LLMops

developer - the first library to let you embed a developer agent in your own app!

JSON-Schema Faker - JSON-Schema + fake data generators

vocode-python - πŸ€– Build voice-based LLM agents. Modular + open source.

safe-rlhf - Safe RLHF: Constrained Value Alignment via Safe Reinforcement Learning from Human Feedback