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Introduction to LangChain 104

Welcome to LangChain 104! This course builds upon the concepts learned in previous LangChain courses and introduces you to LangGraph, a powerful tool for building complex AI workflows. In this section, we'll explore advanced applications of LangChain and LangGraph.

What You'll Learn​

In this course, we'll cover:

  1. LangGraph RAG Agent: Learn how to combine Retrieval-Augmented Generation (RAG) with LangGraph to create more sophisticated AI agents.

  2. LangGraph Introduction: Get an overview of LangGraph and understand its core concepts and benefits in AI workflow creation.

  3. LangGraph Austin Events Newsletter: Explore a practical application of LangGraph in creating an automated events newsletter.

  4. LangGraph LLM Manufacturing BOM Analyser: Dive into an industry-specific use case, using LangGraph to analyze Bills of Materials (BOM) in manufacturing.

Prerequisites​

Before starting this course, you should have:

  • Completed LangChain 101, 102, and 103 or have equivalent knowledge
  • Solid understanding of Python programming
  • Familiarity with LangChain concepts and large language models

Getting Started​

To begin, make sure you have the necessary environment set up. You'll need Python, LangChain, and LangGraph installed on your system. Detailed setup instructions will be provided in each section.

Let's dive in and explore the advanced capabilities of LangChain and LangGraph!