Active filters:
All
Loading video player...
Welcome to LangGraph Components Part 9 – ReAct Agents! 🤖 This video dives deep into the ReAct framework (Reason + Act) — where your LangGraph agent not only calls tools but also reasons before acting, just like a human thought process 🧠. You’ll learn how to build an AI Agent that plans, reasons, calls tools, and reacts — combining LLM reasoning + tool execution in a LangGraph workflow. 💡 What You’ll Learn ✅ What is a ReAct Agent in LangGraph ✅ Difference between Normal Agent and ReAct Agent ✅ How to implement Thought → Action → Observation → Reflection loop ✅ How LangGraph enables multi-step reasoning and decision-making ✅ Build an AI that learns from tool outputs dynamically ⚙️ Key Concepts Covered ReAct Framework (Reason + Act) LLM Thought Generation 🧠 Tool Call Execution 🛠️ Observation & Response Loop 🔁 Graph Nodes for Reasoning Flow 🧰 Tech Stack LangGraph LangChain Core Groq / OpenAI LLMs RunnableLambda Python 3.10+ 📌 GitHub Repository (Code + Notes) 👉 https://github.com/dearnidhi/Agentic-AI-HandsOn-Bootcamp 📩 Connect with Me: ✉️ Email: nidhiyachouhan12@gmail.com 📸 Instagram: @codenidhi 💼 LinkedIn: https://www.linkedin.com/in/nidhi-chouhan-544650b4/ ✨ Don’t forget to LIKE 👍, SHARE 📢 & SUBSCRIBE 🔔 for more LangGraph & Agentic AI tutorials! LangGraph ReAct Agent, LangGraph Reason and Act, LangGraph Components, LangGraph Tutorial, ReAct Agent Example, LangChain ReAct Agent, LangGraph Reasoning Agent, LangGraph Autonomous Agent, LangGraph Workflow, LangGraph LangChain Integration, ReAct Framework AI, Agentic AI Bootcamp, Nidhi Chouhan LangGraph, CodeNidhi LangGraph #LangGraph #LangChain #ReActAgent #AgenticAI #LangGraphAgents #AI #MachineLearning #LangGraphTutorial #LangGraphComponents #AIAgent #CodeNidhi #NidhiChouhan #GenAI #Python #ReasonAndAct