If you are building AI and is fed up with dirty logic or hard workflower on a scale, the depth graph makes it easier. It uses a graph to handle dialogue flow, so your boats remain organized despite being more complicated. Support from agents to Multi -Step AI tools is great for anything.
We have just published a full video course on the Frecodecamp.com about the Lang Graph. This is a ferrous framework for building advanced interactions AI workflows. If you want to build chat boats or AI agents that can handle more than just the basic question and answer, this course is for you.
Your instructor, Wahabhao Mahara, goes through everything every step by step. You will learn how to use a graph -based structure to manage the complex dialogue system. From this point of view, the construction of large -scale language models makes the construction of flexible, flexible conversation applications.
Here is a quick drawback of what has been covered:
Basic Things: Start with Lang Graphs, Type Explanations, and Basic Elements.
Agents: Make five different agents from the beginning. Each one contains walkthroughs and coding exercises so that you can follow it and try yourself.
AI Agent: Go deeper with AI -driven agents. These modules cover key design patterns and show you how to build more intelligent, adaptive system.
RAG (Born over retrieval): Learn how to integrate the vein into your own depth graphwork flu, to react to a smart, context.
Wrapped up: Recover what you have learned and see how all the pieces come together.
This is a hands -on course, so expect many codes and create examples of real work. Whether you are new to the Lang Graph or just want to accelerate your abilities, this course will help you go to zero production applications.
See it now Freecodecamp.org YouTube channel (3 hours clock)