Langchain v0.3 Agents P4: LangGraph Build & Visualize Graph Run a Chatbot Understand Agent Workflow
🚀 *Langchain v0.3 Agents P4: LangGraph Build & Visualize Graph | Run a Chatbot & Understand Agent Workflow*
In this video, we dive deep into *Langchain v0.3* and explore the new *LangGraph* feature for building and visualizing AI agents. This is *Part 1* of a 2-part mini-series within my main series on *Modern AI Agents**. We focus on the workflow of creating **LangGraph Agents**, visualizing their structure, and building our first chatbot using **LangGraph* in **Google Colab**.
🔥 **What’s Covered in This Video**:
1. **LangGraph Agent Workflow**:
Understand the agent workflow through an easy-to-follow explanation and detailed diagram (check out the image for the visualization).
Learn how *LangGraph* makes building and managing AI agents more streamlined and powerful in **Langchain v0.3**.
2. **Building Our First Graph**:
Walk through the step-by-step process of building a graph using *LangGraph* methods and classes.
Explore how you can create a structured agent that can handle complex tasks by visualizing the graph in both *ASCII* and *image* formats.
3. **Running the Graph: Create a Chatbot**:
Once the graph is built, we implement it by running the *LangGraph Agent* to create a fully functional *chatbot* in **Google Colab**.
Understand how each node in the graph plays a critical role in handling the user input and generating responses, showcasing the potential of modern agents.
4. **Part 1 of a 2-Part Series**:
This video sets the stage for Part 2, where we will enhance the chatbot by adding a *Tavily search-based Tool node* and integrating *SQLite-based chat memory* to make the bot smarter and more efficient.
Stay tuned for more advanced tools and agent optimizations in the next video!
🌟 **Why Watch This Video**:
If you are looking to master **Langchain v0.3**, **LangGraph**, and **AI agents**, this is the perfect series for you.
Learn how to visually map out and build complex agent workflows using *LangGraph* and integrate them with real-world tools to build powerful AI solutions.
This hands-on tutorial provides detailed code walk-throughs and practical examples using **Google Colab**, making it easy to follow along.
👨💻 **Who Should Watch**:
*AI Developers**: If you're working with AI agents and looking to take advantage of **Langchain’s* latest features, this tutorial is packed with actionable insights.
**Python Developers**: Get hands-on experience with **Langchain v0.3**, **LangGraph**, and learn how to build and visualize modern agents using Python.
**AI Enthusiasts**: Whether you're new to AI or an experienced developer, this series will help you understand the latest advancements in agent building and how to implement them step-by-step.
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💡 **Keywords & Tags**:
Langchain v0.3, LangGraph, Langchain Agents, AI Agent Workflow, Chatbot, LangGraph Visualization, Langchain Tutorial, Google Colab, Python AI, Modern AI Agents, LangGraph Chatbot, Langchain v0.3 Agents, AI Tools, LangSmith, LangGraph Build, AI Agent Development
#Langchain #LangGraph #AIAgent #LangchainTutorial #PythonAI #GoogleColab #LangchainV0_3 #LangSmith #AIWorkflow #ChatbotDevelopment #AIVisualization #LangchainGraph
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Stay tuned for Part 2 where we enhance the bot with *Tavily search* and *SQLite chat memory* for smarter interactions! 💻
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