docs: add Chat LangChain link and highlight Deep Agents (#34858)

README.md

@@ -36,6 +36,7 @@ If you're looking for more advanced customization or agent orchestration, check
 
 - [docs.langchain.com](https://docs.langchain.com/oss/python/langchain/overview) – Comprehensive documentation, including conceptual overviews and guides
 - [reference.langchain.com/python](https://reference.langchain.com/python) – API reference docs for LangChain packages
+- [Chat LangChain](https://chat.langchain.com/) – Chat with the LangChain documentation and get answers to your questions
 
 **Discussions**: Visit the [LangChain Forum](https://forum.langchain.com) to connect with the community and share all of your technical questions, ideas, and feedback.
 
@@ -61,11 +62,11 @@ While the LangChain framework can be used standalone, it also integrates seamles
 
 To improve your LLM application development, pair LangChain with:
 
+- [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 LangGraph, our low-level agent orchestration framework. LangGraph offers customizable architecture, long-term memory, and human-in-the-loop workflows – and is trusted in production by companies like LinkedIn, Uber, Klarna, and GitLab.
 - [Integrations](https://docs.langchain.com/oss/python/integrations/providers/overview) – List of LangChain integrations, including chat & embedding models, tools & toolkits, and more
 - [LangSmith](https://www.langchain.com/langsmith) – Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
 - [LangSmith Deployment](https://docs.langchain.com/langsmith/deployments) – Deploy and scale agents effortlessly with a purpose-built deployment platform for long-running, stateful workflows. Discover, reuse, configure, and share agents across teams – and iterate quickly with visual prototyping in [LangSmith Studio](https://docs.langchain.com/langsmith/studio).
-- [Deep Agents](https://github.com/langchain-ai/deepagents) *(new!)* – Build agents that can plan, use subagents, and leverage file systems for complex tasks
 
 ## Additional resources