Building ReAct agents with Memory using LangGraph
Last Updated on August 28, 2025 by Editorial Team
Author(s): Aayushi_Sharma
Originally published on Towards AI.
“How do AI agents decide when to think, when to act, and when to stop?”
Welcome to the world of ReAct Agents — powerful AI workflows that combine reasoning and actions. If you’ve ever wondered how AI systems like ChatGPT plan, decide, and call tools dynamically, this guide is for you.
This article explores the concept of ReAct agents, highlighting their ability to merge reasoning with action using LangGraph, an open-source library. It details how to implement these agents, starting from core principles and progressing to creating simple workflows, integrating tools, and establishing memory mechanisms to enhance decision-making processes. The guide concludes with suggestions for further enhancements and real-world applications of these intelligent workflows.
Read the full blog for free on Medium.
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