🛠️ Building Iterative AI Agents with LangGraph and Gemini
This tutorial provides a step-by-step guide to building an iterative AI workflow agent using the LangGraph library and Google's Gemini 1.5 Flash model. It explains the core concepts of LangGraph, including State, Nodes, and Edges, highlighting how conditional edges enable cyclical workflows for iterative refinement. The guide details the prerequisites and setup process, such as obtaining a Gemini API key and installing necessary libraries. A significant portion is dedicated to designing and implementing the agent's workflow as a graph with distinct nodes for routing, analysis, research, response generation, and validation. Finally, it covers running, testing, and observing the agent's execution through streaming, and suggests potential extensions for further development.
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