From 35b20c8f26652e3f1921b25492afbb8dcb1c3b3e Mon Sep 17 00:00:00 2001 From: "open-swe[bot]" Date: Mon, 4 May 2026 10:14:22 +0000 Subject: [PATCH] docs: prominently feature Deep Agents in README --- README.md | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 9ae9e3e181b..5832d3f51be 100644 --- a/README.md +++ b/README.md @@ -43,6 +43,9 @@ result = model.invoke("Hello, world!") If you're looking for more advanced customization or agent orchestration, check out [LangGraph](https://docs.langchain.com/oss/python/langgraph/overview), our framework for building controllable agent workflows. +> [!TIP] +> Building complex, long-horizon agents? Check out **[Deep Agents](https://github.com/langchain-ai/deepagents)** — a higher-level package built on LangChain for agents that can plan, use subagents, and leverage file systems for complex tasks. + > [!TIP] > For developing, debugging, and deploying AI agents and LLM applications, see [LangSmith](https://docs.langchain.com/langsmith/home). @@ -50,7 +53,7 @@ If you're looking for more advanced customization or agent orchestration, check While the LangChain framework can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools when building LLM applications. -- **[Deep Agents](https://github.com/langchain-ai/deepagents)** — Build agents that can plan, use subagents, and leverage file systems for complex tasks +- **[Deep Agents](https://github.com/langchain-ai/deepagents)** *(new!)* — Build agents that can plan, use subagents, and leverage file systems for complex tasks - **[LangGraph](https://docs.langchain.com/oss/python/langgraph/overview)** — Build agents that can reliably handle complex tasks with our low-level agent orchestration framework - **[Integrations](https://docs.langchain.com/oss/python/integrations/providers/overview)** — Chat & embedding models, tools & toolkits, and more - **[LangSmith](https://www.langchain.com/langsmith)** — Agent evals, observability, and debugging for LLM apps