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 This project demonstrates a fullstack application using a React frontend and a LangGraph-powered backend agent. The agent is designed to perform comprehensive research on a user's query by dynamically generating search terms, querying the web using Google Search, reflecting on the results to identify knowledge gaps, and iteratively refining its search until it can provide a well-supported answer with citations. This application serves as an example of building research-augmented conversational AI using LangGraph and Google's Gemini models.
 
+![Gemini Fullstack LangGraph](./app.png)
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 ## Features
 
 - 💬 Fullstack application with a React frontend and LangGraph backend.
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