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Welcome to another session of the Agentic AI Bootcamp! 🚀 In this video, we’ll get started with LangGraph, the next-generation framework that lets you build, visualize, and control Agentic AI workflows — powered by LangChain. LangGraph combines graph-based reasoning, state management, and tool execution into a single, powerful visual pipeline. You’ll learn how to use LangGraph to orchestrate complex LLM applications — step by step! 💡 What You’ll Learn ✅ What is LangGraph and why it’s important ✅ How LangGraph differs from LangChain ✅ How to build and visualize Agentic workflows ✅ Step-by-step demo: creating and running a LangGraph ✅ How to connect LangGraph with Groq or OpenAI models ⚙️ Topics Covered LangGraph Overview Graph Nodes and Edges Message Passing and State Tracking Tool Invocation Agent Execution Flow Integration with LangChain and LCEL 🧰 Tools & Libraries LangGraph LangChain Core Groq API / OpenAI API Python (Jupyter / VSCode) 📌 GitHub Repository (Code + Notes): 👉 https://github.com/dearnidhi/Agentic-AI-HandsOn-Bootcamp 📩 Connect with Me: ✉️ Email: nidhiyachouhan12@gmail.com 📸 Instagram: @dear_nidhi | @codenidhi 💼 LinkedIn: https://www.linkedin.com/in/nidhi-chouhan-544650b4/ ✨ Don’t forget to LIKE 👍, SHARE 📢 & SUBSCRIBE 🔔 for more LangChain + LangGraph tutorials! LangGraph, Getting Started with LangGraph, LangGraph Tutorial, LangGraph LangChain Integration, LangGraph Python, LangGraph Agents, Agentic AI Workflow, LangChain Agents, LangChain vs LangGraph, LangChain Tutorials, LangGraph State Management, LLM Workflows, Groq LangGraph, OpenAI LangGraph Integration, Nidhi Chouhan LangGraph, CodeNidhi LangChain, Agentic AI Bootcamp, AI Agents Architecture, LangGraph Visual Workflow #LangGraph #LangChain #AgenticAI #AIWorkflow #GroqAPI #LLM #LangChainTutorial #CodeNidhi #NidhiChouhan #ArtificialIntelligence #MachineLearning #GenAI #OpenAI #AIAgent #LangGraphTutorial