LangGraph: The Framework That Makes AI Agents Actually Work

Description

- Free GenAI Courses - https://www.analyticsvidhya.com/courses/?utm_source=yt_av&utm_medium=video This video introduces the core concepts of LangGraph, exploring its foundations and how it enables the creation of complex LLM workflows. We discuss how LangGraph facilitates robust agent orchestration for AI agents, allowing for sophisticated interactions and applications. Additionally, we touch upon managing state with vector database solutions for efficient long-term memory in large language models. 📂 Get the Code & Notebooks: https://github.com/abhirajsuresh/langraph What you will learn in this LangGraph Tutorial Playlist: ✅ LangGraph Foundations: Understanding graphs, nodes, and edges. ✅ State & Memory Management: How to handle conversation history and trim tokens. ✅ Branching & Routing: Building intent classifiers to route users to the right agent. ✅ Tool Integration: Connecting your agents to external tools (Calculators, Search, etc.). ✅ Capstone Project: Building a LangGraph multi-agent research assistant using FAISS Vector DB and OpenAI. Prerequisites: - Basic Python knowledge. - Familiarity with Jupyter Notebooks. - Foundational understanding of Prompt Engineering and Vector Databases. Whether you are looking for a LangGraph tutorial in English or a hands-on LangGraph agents crash course, this module is designed to help you master the AI agent stack. Timestamps- 0:00 - Introduction & Course Structure 3:40 - What is LangGraph? (Framework Overview) 6:12 - LangGraph vs. LangChain 7:42 - The AI Agent Stack (APIs, Tools, Orchestration) 11:55 - Core Concepts: Graphs, Nodes, Edges, & State 16:54 - Hands-on 1: Building a "Hello World" Workflow 27:09 - Understanding Single Agent Workflows 33:47 - Hands-on 2: Chat Agent with OpenAI Integration 39:58 - State & Memory Management (Stateful Workflows) 46:54 - Hands-on 3: Implementing Memory & History Trimming 52:08 - Branching & Conditional Flows (Intent Classification) 56:00 - Hands-on 4: Routing to Support vs. Chitchat Agents 1:00:08 - Integrating External Tools into LangGraph 1:04:21 - Hands-on 5: Building a Tool-Calling Planner Agent 1:14:07 - Capstone Project: Multi-Agent Research Assistant 1:19:10 - Final Hands-on: Vector DB (FAISS) + Multi-Agent Orchestration 1:31:15 - Conclusion & Next Steps #LangGraphCourse #LangGraphCourseAnalyticsVidhya #LangGraphCrashCourse #LangGraphBeginnerCourse #LangGraphCourseInEnglish #LangGraphCrashCourseByAnalyticsVidhya #LangGraphAgentsCrashCourse #LangGraphTutorialCrashCourse #LangGraphTutorialPlaylist #LangGraphTutorialForBeginners #LangGraphTutorialInEnglish #LangGraphTutorialAnalyticsVidhya #LangGraphTutorialPython #LangGraphMultiAgent #LangGraphAgents #LangGraphEnglish #LangGraphMultiAgentTutorial #LangGraphAnalyticsVidhya #LangGraphMultiAgentProject #LangGraphMemory #LangGraphChatbot #LangGraphPython