LangChainJS For Beginners: A Beginner's Guide to AI Application Development With LangChain, JavaScript, OpenAI/ChatGPT

✍ Scribed by Nathan Sebhastian

• Publisher: Independently Published
• Year: 2024
• Tongue: English
• Leaves: 166
• Category: Library

✦ Synopsis

angChain supports both Python and JavaScript. This book focuses on the JavaScript version of LangChain.Price will increase soon!
Save your time and learn up to 3X faster with a structured learning system that’s carefully crafted for beginners.
LangChainJS For Beginners will help you harness the power of LangChain and JavaScript to develop AI-powered applications.
In this book, I'll be using a step-by-step, practical approach so that you can build cutting-edge AI solutions using LangChain and JavaScript.
By the end of the book, you will understand how to build a Next.js web application that harnesses the power of LLMs such as OpenAI's GPT and Google's Gemini.
What You'll Learn
Understand the benefits of using LangChain.js
Master LangChain features such as chains, agents, and document loader
Integrate open-source LLMs into LangChain
Create prompt templates for specific use cases
Master LCEL, the LangChain Expression Language
Creating chunks and embeddings using a vector database
How to chat with PDF documents using AI
How to chat with YouTube videos using AI
How to send multimodal messages to AI
Use Next.js and LangChain to create AI-powered web applications
Deploying AI-powered web application to production
Who is this for?
Software Engineers and Developers wanting to learn how to build Generative AI applications with LangChain and JavaScript.
JavaScript beginners wanting to explore LangChain and LLM programming

✦ Table of Contents

Preface
Working Through This Book
Requirements
Source Code
Contact
Chapter 1: Introduction to Generative AI Applications
What is a Large Language Model?
What is LangChain?
The Architecture of a Generative AI Application
Development Environment Set Up
Summary
Chapter 2: Your First LangChain Application
Installing LangChain Packages
Creating the Question & Answer Application
Getting Google Gemini API Key
Running the Application
Resource Exhausted Error
Summary
Chapter 3: Using OpenAI LLM in LangChain
Getting Started With OpenAI API
Integrating OpenAI With LangChain
ChatGPT vs Gemini: Which One To Use?
Summary
Chapter 4: Using Open-Source LLMs in LangChain
Ollama Introduction
Using Ollama in LangChain
Again, Which One To Use?
Summary
Chapter 5: Enabling User Input With Prompts
Summary
Chapter 6: LangChain Prompt Templates
Creating a Prompt Template
Prompt Template With Multiple Inputs
Restricting LLM From Answering Unwanted Prompts
Summary
Chapter 7: The LangChain Expression Language (LCEL)
Sequential Chains
Simple Sequential Chain
Using Multiple LLMs in Sequential Chain
Debugging the Sequential Chains
Summary
Chapter 8: Regular Sequential Chains
Format the Output Variables
Summary
Chapter 9: Implementing Chat History in LangChain
Creating a Chat Prompt Template
Saving Messages in LangChain
Summary
Chapter 10: AI Agents and Tools
Creating an AI Agent With LangChain
Asking Different Questions to the Agent
List of Available AI Tools
Types of AI Agents
Summary
Chapter 11: Interacting With Documents in LangChain
Getting the Document
Building the Chat With Document Application
Adding Chat Memory for Context
About The Vector Database
Switching the LLM
Summary
Chapter 12: Uploading Different Document Types
Summary
Chapter 13: Chat With YouTube Videos
Adding The YouTube Loader
Handling Transcript Doesn’t Exist Error
Summary
Chapter 14: Interacting With Images Using Multimodal Messages
Understanding Multimodal Messages
Sending Multimodal Messages in LangChain
Adding Chat History
Ollama Multimodal Message
Summary
Chapter 15: Developing AI-powered Next.js Application
Creating the Next.js Application
Installing Required Packages
Adding the Server Action
Adding Profile Pictures for User and Assistant
Developing React Chat Components
Adding Chat History
Summary
Chapter 16: Deploying Next.js AI Application to Production
Streaming the Response
Creating API Key Input
Adding the setApi() Function
Adding a Chat Sidebar
Running Build Locally
Pushing Code to GitHub
Vercel Deployment
Summary
Wrapping Up
About the author