Dive deep into LangGraph, an agent framework from LangChain that enables the development of AI agents using graphs. Learn how to build a sophisticated AI research agent capable of producing in-depth reports on various topics through multiple steps. Explore the integration of GPT-4, Pinecone, LangGraph, arXiv, and Google via SerpAPI to create a powerful research tool. Gain insights into the evolution of AI agents, understand the concept of agents as graphs, and master the components of a research agent. Follow along as the video guides you through building a RAG pipeline, implementing custom agent tools, and constructing the LangGraph graph. Witness the testing of the research agent and grasp the potential of agentic graphs in AI development. Perfect for developers and AI enthusiasts looking to enhance their skills in creating advanced, multi-step AI agents.
Overview
Syllabus
LangGraph Agents
LangGraph Agent Overview
Short History of Agents and ReAct
Agents as Graphs
LangGraph
Research Agent Components
Building the RAG Pipeline
LangGraph Graph State
Custom Agent Tools
ArXiv Paper Fetch Tool
Web Search Tool
RAG Tools
Final Answer Tool
Agent Decision Making
LangGraph Router and Nodes
Building the LangGraph Graph
Building the Research Agent Report
Testing the Research Agent
Final Notes on Agentic Graphs
Taught by
James Briggs
