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Getting Started with LLM Agents using LangGraph

Published by O'Reilly Media, Inc.

Beginner content levelBeginner

How to build AI agents using LangChain

Course outcomes

  • Learn the basics of working with LLM-based agents
  • Gain proficiency in working with modern LLM agent frameworks
  • Gain the ability to build apps powered by LLM agents with complex functionalities like browsing the internet, researching information, producing reports, and more

Course description

Join expert Lucas Soares to explore the capabilities of AI agents to perform complex tasks like browsing the internet, creating complex research workflows, generating automatic reports, and even making commits to a GitHub repository. You'll learn the essential building blocks of creating AI agents through presentations, hands-on exercises in Jupyter notebooks, and demo apps with Streamlit. You'll also develop the practical skills to integrate LLM-based automation powered by agents into personal and enterprise use cases.

What you’ll learn and how you can apply it

  • Gain foundational and practical knowledge to build LLM-based agents using LangChain
  • Learn to build LLM-powered apps that leverage agents to perform tasks like web browsing and research
  • Learn the necessary skills to build complex agent applications that can manage GitHub repositories, write code, and solve desktop tasks
  • Acquire the basic skills to deploy LLM-based LangChain agents with frameworks such as LangServe and FastAPI

This live event is for you because...

  • You’re a software or machine learning engineer, data scientist, or a software developer (AI engineer) who wants to learn how LLM-based agents work and how to build them using the best current frameworks.

Prerequisites

  • An OpenAI API key
  • Familiarity with Python programming
  • Some knowledge of large language models
  • A simple working understanding of NLP

Recommended preparation:

Recommended follow-up:

Schedule

The time frames are only estimates and may vary according to how the class is progressing.

Agent systems and current frameworks (60 minutes)

  • Presentation: Agents overview; general framework for building agents
  • Demonstration: Building a web browsing agent
  • Hands-on exercise: Build a web browsing agent
  • Break

LangChain core concepts and workflow (60 minutes)

  • Presentation: Building agents with LangChain; building agents with LangChain and OpenAI function calling
  • Hands-on exercises: Build a simple GitHub agent with LangChain; build a basic personal assistant agent with LangChain and OpenAI function calling
  • Q&A
  • Break

LangChain deployment and case studies (60 minutes)

  • Presentation: Building a planner agent with LangChain; deploying a LangChain agent (options and frameworks)
  • Hands-on exercises: Build a desktop productivity agent with LangChain; deploy a researcher agent with LangChain using BentoML and OpenLLM
  • Q&A

Your Instructor

  • Lucas Soares

    Lucas Soares is a machine learning engineer who has worked at K1 Digital and Biometrid, where he developed computer vision and NLP models for applications such as document verification, OCR-based applications, and recommender systems. Lucas has also developed various ML models, including neural networks, Siamese networks, convolutional neural networks, LSTMs, and genetic algorithms.

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Skill covered

Large Language Models (LLMs)