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LangGraph - managing AI Agents: A Beginner's Guide
AI agents are here to stay, and LangGraph makes it easy to build them and harness their capabilities!
Today’s Large Language Models (LLMs) are impressive, but let’s be real. These LLMs are still primarily just sophisticated text processors.
So, how can we evolve these text processors into autonomous problem solvers that can understand and interact with the world around them?
Enter AI Agents. Simply put, AI agents are LLMs that operate in a loop to accomplish specific goals.
You can assign them tasks such calendar manager to schedule and manage appointments, send reminders, and suggest optimal meeting timesa personal AI Agent assistant to organize trips, book hotels and plane tickets for a destination in a given budget.These are much closer to the capabilities we expect from real AI.
AI Agents are LLMs on steroids. The anatomy of an agent consists
AI_AGENT = LLM + MEMORY + TOOLS + PLANNING + DO_WHILE_LOOP
The LangGraph framework is an excellent tool for implementing and orchestrating all of these components.
AI Agents can solve very complex situations thus clear communication is essential to achieve the desired results.
This is where LangGraph excels. Communicating with LLMs via code leads to far more reliable results than using only natural language (prompt engineering).
In this book, we’ll take you on a fun, hands-on journey where each chapter will focus on essential concepts like tool management or human in the loop validation, while also coding practical implementations of these elements using LangGraph.
You can see this book as your launchpad. You'll build your first AI Agent within minutes, and slowly become competent and knowledgeable in this technology, with each chapter featuring a full practical example.
Let's start learning!
Today’s Large Language Models (LLMs) are impressive, but let’s be real. These LLMs are still primarily just sophisticated text processors.
So, how can we evolve these text processors into autonomous problem solvers that can understand and interact with the world around them?
Enter AI Agents. Simply put, AI agents are LLMs that operate in a loop to accomplish specific goals.
You can assign them tasks such calendar manager to schedule and manage appointments, send reminders, and suggest optimal meeting timesa personal AI Agent assistant to organize trips, book hotels and plane tickets for a destination in a given budget.These are much closer to the capabilities we expect from real AI.
AI Agents are LLMs on steroids. The anatomy of an agent consists
AI_AGENT = LLM + MEMORY + TOOLS + PLANNING + DO_WHILE_LOOP
The LangGraph framework is an excellent tool for implementing and orchestrating all of these components.
AI Agents can solve very complex situations thus clear communication is essential to achieve the desired results.
This is where LangGraph excels. Communicating with LLMs via code leads to far more reliable results than using only natural language (prompt engineering).
In this book, we’ll take you on a fun, hands-on journey where each chapter will focus on essential concepts like tool management or human in the loop validation, while also coding practical implementations of these elements using LangGraph.
You can see this book as your launchpad. You'll build your first AI Agent within minutes, and slowly become competent and knowledgeable in this technology, with each chapter featuring a full practical example.
Let's start learning!
93 pages, Paperback
Published November 13, 2024
32 people are currently reading
4 people want to read
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