LangGraph Step-by-Step: Build a Self-Improving AI Agent using Reflexion Architecture (Part 2)

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  • Опубліковано 24 лис 2024

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  • @atefataya
    @atefataya  День тому +1

    💡 Quick Navigation & Resources:
    00:06 Intro
    00:56 Introduction
    02:42 Step 1: Define the Agent State
    04:45 Step 2: Craft the Prompts
    07:19 Step 3: Implement the Agents
    09:51 Step 4: Construct the LangGraph
    13:15 Step 5: Run the Agentic App
    15:12 How to start a career in AI?
    16:21 Final Thoughts
    🔗 Important Links:
    GitHub Repo with Complete Code:
    🔗 tinyurl.com/3ur45mkx
    Part 1 (Theory & Concepts):
    ua-cam.com/video/EWrpnIxPBb8/v-deo.html
    ❓ Common Questions:
    Q: Do I need to watch Part 1 first?
    A: While not strictly required, Part 1 covers the theoretical foundation that will help you better understand the implementation.
    Q: What prerequisites do I need?
    A: Basic Python knowledge and familiarity with LangChain. All required packages and versions are listed in the GitHub repo.
    💬 What kind of AI agent would you like to build? Let me know in the comments!
    ✨ Subscribe and hit the notification bell to catch our upcoming tutorials on AI agents, LangChain, and more advanced implementations!