So langchain's agents are lightweight implementation of existing liberaries. Superagi on the other hand is focussed on real world production deployment
Goal of SuperAGI is to build useful autonomous agents and to do that there are bunch of things I have included in the project which is not there in autogpt etc, like agent trajectory fine tuning, running concurrent agents or agent clusters, configurable workflows for each iteration of agent
This project came out of building an autonomous marketing app, so faced some of the challenges of using autogpt , babyagi etc in the prod
Currently, there is support for GPT3.5, GPT3.5 16k and GPT4, but there are some open prs for opensource models like GPT4All and Vicuna. Going forward idea is to integrate with as many models as possible and philosophically it is model agnostic