By Nuno Campos and Vadym Barda
Over the past year, we’ve invested heavily in making LangGraph the go-to framework for building AI agents. With companies like Replit, Klarna, LinkedIn and Uber choosing to build on top of LangGraph, we have more conviction than ever that we are on the right path.
A core principle of LangGraph is to be as low level as possible. There are no hidden prompts or no enforced “cognitive architectures” in LangGraph. This has served to make it production ready and also distinguishes itself from all other frameworks.
At the same, we do see the value in higher level abstractions. They make it easy to get started, easy to try out new cognitive architectures, and provide a nice entrypoint to the field.
Up to this point, we’ve had one higher level abstraction and it’s lived in the main langgraph package. It was create_react_agent, a wrapper for creating a simple tool calling agent. Today, we are splitting that out of langgraph as part of a 0.3 release, and moving it into langgraph-prebuilt.
We are also introducing a new set of prebuilt agents built on top of LangGraph, in both Python and JavaScript.
Over the past three weeks, we’ve already released a few of these:
- Trustcall: for doing reliable structured extraction
- LangGraph Supervisor: for getting started with a supervisor multi-agent architecture
- LangMem: for long term memory
- LangGraph Swarm: for getting started with a swarm multi-agent architecture
We believe that these prebuilt libraries can combine the best of both worlds:
- They make it easy to get started with common agent patterns
- They are built on top of LangGraph, so if you want to modify them it’s easy and familiar
We hope that this will foster a large collection of prebuilt agents built by the community. To that end, we have added instructions for creating your own prebuilt package and adding it to our registry of agents. We have seen this work well with LangChain integrations. We have over 700 integrations, a large amount maintained by the community in third party packages. We hope the same will happen with LangGraph prebuilt agents.