Autonomous Agents are agents that designed to be more long running. You give them one or multiple long term goals, and they independently execute towards those goals. The applications combine tool usage and long term memory.
At the moment, Autonomous Agents are fairly experimental and based off of other open-source projects. By implementing these open source projects in LangChain primitives we can get the benefits of LangChain - easy switching and experimenting with multiple LLMs, usage of different vectorstores as memory, usage of LangChain's collection of tools.
This notebook demonstrates an implementation of a Context-Aware AI Sales agent with a Product Knowledge Base.