LangChain JS - Practical Guide for Javascript Developers

Name: LangChain JS - Practical Guide for Javascript Developers
Rating: 4.3 (30 reviews)

Getting Started with LangChain for Javascript

Created byFikayo Adepoju

Last updated 11/2024

English

What you'll learn

How to Design powerful prompts to query A.I models
How to ntegrate with powerful models like Gemini models from Google and GPT models from OpenAI
Build conversational chat interactions with A.I models
Use A.I to process images
Load data from local files or specific web pages
Generate results based on information from the web and PDF files

Course content

7 sections • 30 lectures • 4h 33m total length

Welcome1:02

Getting Your API Key10:44
Obtain and manage API keys for OpenAI and Google Gemini to set up LangChain JS model. Build a prompt template, configure an output parser, and run end-to-end hello world chain.
Setting up Your LangChainJS Project9:59
Set up a LangChainJS hello world project by creating a folder, initializing a Node.js project, and installing core, long chain, and Google JNI packages, then configure package.json and overrides.
Your first Prompt Template7:54
Building Your First Chain13:14
build your first chain in LangChain JS by setting up the Gemini model, using an output string parser, and invoking the chain to produce a string result from a prompt.

Understanding Retrieval Augmented Generation [RAG]5:44
RAG Project Setup3:25
Loading Data from a Web Page8:24
Embedding and Storing8:24
Split web page text into 1200-char chunks with 200-char overlap using a recursive character text splitter, generate OpenAI embeddings, and store them in Long Chain's in-memory vector store for search.
Retrieving Context for Prompts4:03
Retrieve context for prompts by pulling a retriever from the store, querying it to fetch relevant documents, and adding those results to your prompt before asking the model.
Generating Responses from our own data14:02
Using PDF files for RAG12:08

Requirements

Basic Programming Skills
Basic Understanding of Javascript
Basic Understanding of Nodejs

Description

The sole purpose of this course is to get your feet wet and your hands building with LangChainJS

LangChainJS gives Web and JavaScript Developers to ability to add A.I-powered features to their web applications using best-in-class Large Language Models from OpenAI, Google, Anthropic and many more LLM vendors out there.

This is the perfect course to get yourself into A.I Engineering and A.I development with LangChain, the biggest A.I software development toolchain in the market today.

By the end of this course, you will have the skills to:

Design powerful prompts to query A.I models
Integrate with powerful models like Gemini 1.5 Flash from Google Generative AI and GPT 4o by OpenAI
Build conversational chat interactions with A.I models
Use A.I to process images
Control the creativity of the model and how much tokens it consumes
Track token consumption
Load data from local files or specific web pages
Generate results based on information from the web
Generate results based on information from your PDF files

So, if anything in the above list sounds fun, let's get started.

Also, feel free to inbox me about any new chapter you will like me to work on. I'll appreciate your suggestions

Who this course is for:

Web Developers who want to add AI-powered features to their applications
Developers who want to transition into A.I Engineering
Developers who want to improve the performance of model-powered features with private data

LangChain JS - Practical Guide for Javascript Developers

What you'll learn

Explore related topics

Course content

Introduction1 lecture • 1min

Concepts and Components4 lectures • 31min

"Hello World" in LangChainJS4 lectures • 42min

Prompt Engineering with Prompt Templates6 lectures • 1hr 27min

Working with Models5 lectures • 41min

Structuring Your Model Output3 lectures • 16min

RAG - Feeding Your Data to A.I Models7 lectures • 56min

Requirements

Description

Who this course is for: