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LangChain Academy
academy.langchain.com › courses › intro-to-langgraph
Foundation: Introduction to LangGraph - Python
Learn the basics of LangGraph - our framework for building agentic and multi-agent applications. Separate from the LangChain package, LangGraph helps developers add better precision and control into agentic workflows.
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Langchain
docs.langchain.com › oss › python › langgraph › overview
LangGraph overview - Docs by LangChain
LangGraph is very low-level, and focused entirely on agent orchestration. Before using LangGraph, we recommend you familiarize yourself with some of the components used to build agents, starting with models and tools. We will commonly use LangChain components throughout the documentation to integrate models and tools, but you don’t need to use LangChain to use LangGraph.
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Medium
medium.com › @ashutoshsharmaengg › getting-started-with-langgraph-a-beginners-guide-to-building-intelligent-workflows-67eeee0899d0
Getting Started with LangGraph: A Beginner’s Guide to Building Intelligent Workflows
June 15, 2025 - A comprehensive guide to LangGraph, covering core concepts, graph construction, and tool calling. Learn to build advanced AI agent workflows from scratch.
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GitHub
github.com › langchain-ai › langgraph-101
GitHub - langchain-ai/langgraph-101: Learn about the fundamentals of LangGraph through a series of notebooks · GitHub
Welcome to LangGraph 101! This repository contains hands-on tutorials for learning LangChain, LangGraph, and Deep Agents, organized into two learning tracks:
Starred by 394 users
Forked by 88 users
Languages   Jupyter Notebook 80.0% | Python 20.0%
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Codecademy
codecademy.com › article › building-ai-workflow-with-langgraph
LangGraph Tutorial: Complete Guide to Building AI Workflows | Codecademy
Learn LangGraph, a Python library for AI workflows. Step-by-step tutorial with code examples and best practices.
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Reddit
reddit.com › r/langchain › tutorial for langgraph , any source will help .
r/LangChain on Reddit: Tutorial for Langgraph , any source will help .
September 28, 2024 -

I've been trying to make a project using Langgraph by connecting agents via concepts of graphs . But the thing is that the documentation is not very friendly to understand , nor the tutorials that i found were focusing on the functionality of the classes and modules . Can you gyus suggest some resources to refer so as to get an idea of how things work in langgraph .

TL;DR : Need some good resource/Tutorial to understand langgraph apart form documentation .

Find elsewhere
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Hugging Face
huggingface.co › learn › agents-course › unit2 › langgraph › introduction
Introduction to LangGraph · Hugging Face
Welcome to this next part of our journey, where you’ll learn how to build applications using the LangGraph framework designed to help you structure and orchestrate complex LLM workflows.
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Latenode
community.latenode.com › other questions › langchain
New to LangChain & LangGraph - Need Study Path Suggestions - langchain - Latenode Official Community
August 22, 2025 - Hey folks! I just started exploring LangChain and LangGraph but feeling a bit overwhelmed with where to begin. There seems to be so much content out there and I’m not sure what order to tackle things in. Can someone po…
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GeeksforGeeks
geeksforgeeks.org › machine learning › what-is-langgraph
What is LangGraph - GeeksforGeeks
2 weeks ago - Tutorials · Interview Prep · ... Updated : 14 Apr, 2026 · LangGraph is an open-source framework from LangChain designed to build and manage AI agent workflows using graph-based structures....
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DataCamp
datacamp.com › tutorial › langgraph-tutorial
LangGraph Tutorial: What Is LangGraph and How to Use It? | DataCamp
June 26, 2024 - LangGraph Studio is a visual ... inside data pipelines and applications. This tutorial provides an overview of what you can do with LangChain, including the problems that LangChain solves and examples of data use cases....
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OpenAI
blog.gopenai.com › langgraph-tutorial-part-1-build-a-simple-agent-workflow-in-python-18a5c6b8e34a
LangGraph Tutorial (Part 1): Build a Simple Agent Workflow in Python | by Nishan Jain | GoPenAI
July 5, 2025 - In this article, you will learn about key LangGraph terminologies — including State, Nodes, and Edges — and see how to build a basic agent workflow in 5 simple steps.
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DeepLearning.AI
deeplearning.ai › home › courses › ai agents in langgraph
AI Agents in LangGraph - DeepLearning.AI
September 11, 2025 - In this course you will learn to build an agent from scratch using Python and an LLM, and then you will rebuild it using LangGraph, learning about its components and how to combine them to build flow-based applications.
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Aiproduct
aiproduct.engineer › tutorials › langgraph-tutorial-building-your-first-graph-unit-11-exercise-3
LangGraph Tutorial: Building Your First Graph - Unit 1.1 Exercise 3 - AI Product Engineer
Discover the basics of StateGraph, node creation, edge configuration, and graph execution to kickstart your journey into graph-based conversation flows. ... This tutorial introduces the core components of LangGraph: StateGraph, nodes, and edges.
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Data Science Dojo
datasciencedojo.com › home › blog › llm › langgraph tutorial to revolutionize ai agent workflows
LangGraph Tutorial to Build a Basic and Smart Chatbot
LangGraph tutorial: Learn to design smarter AI workflows with state-aware, cyclical graphs for dynamic chatbots and advanced agents.
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LangChain
langchain.com › langgraph
LangGraph: Agent Orchestration Framework for Reliable AI Agents
LangGraph sets the foundation for how we can build and scale AI workloads — from conversational agents, complex task automation, to custom LLM-backed experiences that 'just work'. The next chapter in building complex production-ready features with LLMs is agentic, and with LangGraph and LangSmith, LangChain delivers an out-of-the-box solution to iterate quickly, debug immediately, and scale effortlessly.”
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DataCouch
datacouch.io › home › artificial intelligence › langgraph tutorial – build smart ai workflows easily
LangGraph Tutorial - Build Smart AI Workflows Easily
August 20, 2025 - Learn LangGraph to create powerful AI workflows with stateful agents, error handling, RAG, and ReAct agents using Gemini LLM and LangChain tools.
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Stackademic
blog.stackademic.com › simple-tutorial-to-understand-langgraph-part-1-55fbffa0405d
LangGraph Made Easy: A Beginner's Guide (Part 1)
December 4, 2024 - Stackademic is a learning hub for programmers, devs, coders, and engineers. Our goal is to democratize free coding education for the world.
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YouTube
youtube.com › playlist
Agentic AI using LangGraph - YouTube
Welcome to the ultimate Agentic AI using LangGraph playlist! In this series, we’ll take you from the fundamentals of Agentic AI — understanding how it differ...
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Reddit
reddit.com › r/langchain › struggling to understand the langgraph tutorial (build a basic chatbot)
r/LangChain on Reddit: struggling to understand the langgraph tutorial (build a basic chatbot)
December 15, 2024 -

link: https://langchain-ai.github.io/langgraph/tutorials/introduction/#part-1-build-a-basic-chatbot

So far I am able to follow this tutorial for the "build chatbot section" - what I don't understand is the logic in the "while True" statement below - specifically on how the excelption logic is invoked:

while True:
try:
user_input = input("User: ")
if user_input.lower() in ["quit", "exit", "q"]:
print("Goodbye!")
break

stream_graph_updates(user_input)
except:
# fallback if input() is not available
user_input = "What do you know about LangGraph?"
print("User: " + user_input)
stream_graph_updates(user_input)
break

Question : exception logic trigger - how does it get triggered?

If you look at the tutorial, it is showing the results of executing the exception logic -

Assistant: LangGraph is a library designed to help build stateful multi-agent applications using language models. It provides tools for creating workflows and state machines to coordinate multiple AI agents or language model interactions. LangGraph is built on top of LangChain, leveraging its components while adding graph-based coordination capabilities. It's particularly useful for developing more complex, stateful AI applications that go beyond simple query-response interactions.
Goodbye!

How does the execution logic get triggered?