Building Agentic Workflows with LangGraph: A Deep Dive into ReAct and Memory Management (Part 1)

Author(s): Sai Bhargav Rallapalli

Originally published on Towards AI.

Building Agentic Workflows with LangGraph: A Deep Dive into ReAct and Memory Management (Part 1)

In the world of AI and LLMs, agentic workflows are revolutionizing how we interact with AI systems. These workflows enable LLMs to not just generate text but also reason, take actions, and iterate until they arrive at the correct solution.

This article explores building agentic workflows using LangGraph, focusing on aspects such as tool binding and reasoning, the ReAct framework for implementing actions, and memory management to sustain conversations. It covers the processes involved in tool calling, establishing LLM decisions, and the structured interactions between LLMs and external tools, ultimately providing insights into creating robust multi-step AI agent workflows.

Read the full blog for free on Medium.

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Published via Towards AI