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AI Agents are becoming the go‑to solution for handling complex workflows—and LangGraph’s ReAct agent pattern makes it feel effortless. In this video, I will walk through a practical demo of analysing several reviews of a product in an e-commerce setup and extract meaningful insights, so that the users can make informed decisions. What You'll Learn: 1. Setting up a ReAct agent with LangGraph 2. Setting up tools for fetching, deduplicating, and filtering reviews 3. Creating an agent that chains multiple processing steps Why is this helpful? Instead of reading hundreds of reviews, this agent automates the analysis and delivers actionable insights in seconds. Perfect for e-commerce platforms, product research, or any scenario where you need to process large volumes of text data intelligently. GitHub repo: https://github.com/digitalocean-labs/product_review_summarizer LangGraph Docs: https://langchain-ai.github.io/langgraph/ // TIMESTAMPS ⏱️ 0:00 - Intro 0:22 - Product Reviews Analyser code walk through 3:46 - Demo 4:31 - Closing 🚀 Join the Developer Cloud: https://cloud.digitalocean.com/registrations/new?utm_source=youtube&utm_medium=organic_video&utm_campaign=digitalocean&utm_content=MJGRImUXTqU // STAY CONNECTED 🌏 Follow our blog for the latest updates: https://www.digitalocean.com/blog 🦈 Join our Developer Community on Discord: https://discord.com/invite/digitalocean 🐥 Follow us on X/Twitter: https://x.com/digitalocean 👩💻 We're Hiring! See open roles: http://grnh.se/aicoph1