The article discusses the use of large language models (LLMs) as reasoning engines for powering agent workflows, focusing specifically on ReAct agents. It explains how these agents combine reasoning and action capabilities and provides examples of how they function. Challenges faced while implementing such agents are also mentioned, along with ways to overcome them. Additionally, the integration of open-source models within LangChain is highlighted.
The authors map the landscape of frameworks for abstracting interactions with and between large language models, and suggest two systems of organization for reasoning about the various approaches to, and philosophies of, LLM abstraction.
open-source LLM tools offer transparency, flexibility, cost-effectiveness, and heightened data security.
This is an open source effort to create a similar experience to OpenAI's GPTs and Assistants API. It builds upon LangChain, LangServe and LangSmith. OpenGPTs gives you more control