LangGraph Mastery: Develop LLM Agents with LangGraph

Posted By: naag

LangGraph Mastery: Develop LLM Agents with LangGraph
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | 2 hours 56 minutes | 50 lectures | 1.22 GB
Genre: eLearning | Language: English

Unleash the Power of AI Agents with LangChain and LangGraph - the New Frontier in AI

Welcome to this brand new course on
LangGraph
, which allows us to build agentic LLM applications!
By the end of this course, you will be equipped with the skills to seamlessly integrate LLM agents into your applications, opening up new possibilities and horizons.
We are witnessing a rapid ascent in AI capabilities, with groundbreaking advancements occurring annually. This swift progress has the potential to significantly reshape our world in the coming years.
Three pivotal advancements are poised to make a profound impact:
Infinite Context Windows, Text to Action, and Agents.
Agents: The New Frontier in AI
Agents
are autonomous intelligent entities designed to perform tasks, process information, and interact within a language-based framework. These agents are significantly expanding the potential of AI across various domains.
Agentic AI is revolutionizing industries
, offering enhanced applications in fields such as legal document analysis, medical diagnostics, and software development
. Imagine an army of skilled programmers working around the clock to develop software solutions for you.
In this course,
we will delve into LangGraph
, an extension of LangChain specifically designed for agent and multi-agent workflows.
LangGraph enables highly customizable and controllable agent flows, ideal for complex scenarios.
We will also explore
LangSmith
, a platform for tracing and debugging your production-grade LLM applications.
Course Highlights:
Building a Simple ReAct Agent from Scratch
Introduction to Agents and ReAct
LangGraph concepts and core components
Nodes, edges, conditional edges, and state management
Visualizing the graph
Agentic search using Tavily AI
Enhancing agents with tool observation
Adding memory to agents
Patterns: reflection and reflexion
Setting up LangSmith
Debugging and tracing LLM apps with LangSmith
Hands-On Projects:
Create a ReAct agent from scratch.
Develop a ChatBot app using LangGraph.
Build a Tweet generator using the reflection pattern.
Create an essay writer using reflexion, Tavily AI, and tool observation.
Are you ready to dive into this exciting new world of AI? Enroll in this LangGraph mastery course and transform the way you integrate AI into your applications!
Looking forward to seeing you in the course!