
Discover how LangChain agents use GPT models with tools like Wikipedia and math through a zero-shot react agent to plan actions and answer prompts.
Discover how to print chat history using a for loop over a session state 2d array, render it in the app, and address history clearing and features like file uploads.
Create a multi-input LangGraph to collect a name and five transactions, analyze the total, and classify you as saver or spender for budget analysis.
In this short course, we take you on a fun, hands-on and pragmatic journey to learn how to build LLM powered apps using LangChain and LangGraph. You'll start building your first Generative AI app within minutes. Every section is recorded in a bite-sized manner and straight to the point as I don’t want to waste your time (and most certainly mine) on the content you don't need.
In this course, we will cover:
What is LangChain
How does LangChain Work
Installation, Setup and Our First LangChain App
Building a Medium Article Generator App
Connecting to OpenAI LLM
Prompt Templates
Simple Chains
Sequential Chains
Agents
Chat with a Document
Adding Memory (Chat History)
Outputting the Chat History
Uploading Custom Documents
Loading Different Document Types (eg PDF, txt, docs)
Chat with Youtube
* New LangGraph Section!
Multiple Inputs Graph
Conditional Graph
Simple AI Agent Bot
Agent with Conversation History
Reasoning and Acting (ReAct) Agent
Task List Assistant Agent
RAG Agent
and more...
The goal of this course is to teach you LangChain and LangGraph development in a manageable way without overwhelming you. We focus only on the essentials and cover the material in a hands-on practice manner for you to code along.
Working Through This Course
This course is purposely broken down into short sections where the development process of each section will center on different essential topics. The course a practical hands on approach to learning through practice. You learn best when you code along with the examples.