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LangChain: Develop AI web-apps with JavaScript and LangChain

Name: LangChain: Develop AI web-apps with JavaScript and LangChain
Rating: 3.9 (339 reviews)

Create LLM applications with LangChain, OpenAI API, NextJS, and TailwindCSS

Created byShawn Esquivel

Last updated 6/2024

English

What you'll learn

Chat With Anything - use AI to chat with books, videos, etc.
Supercharge Your Work - create autonomous AI agents that can "think" through complex tasks
Launch Your Product - display your AI projects for potential employers/customers to see
Troubleshoot Anything - how to use AI tools beyond ChatGPT to become the "10x developer"

Course content

9 sections • 86 lectures • 6h 28m total length

1.1 • Developer Environment Setup3:24
Note: Node Version0:21
1.2 Cloning the Repository4:00
(Optional) Downloading the Course Materials Manually2:05
1.3 • Extensions to Make Life Easier5:49
1.4 • Extensions to Make Life Easier (Cont.)1:02
1.5 • Troubleshooting Guide4:32
The most helpful resource here is the LangChain KapaAI.

You can ask your questions to an AI assistant that is trained on AI!
1.6 • API Keys Needed4:31
1.7 • Add API Keys to Environment (Cont.)1:31
This step is crucial so that we'll have API keys in the NodeJS runtime environment.
1.7 • Set API Usage Limits (Optional)1:04
IMPORTANT: 1.8 Setting API Keys In Terminal0:24
(OPTIONAL FOR WINDOWS USERS) Setting API keys in the Terminal2:33
1.8 Course Resources2:16
1.9 LangChain Quick Start Guide30:03
NPM Issues (npm install, npm run dev)? – TRY THIS!6:48
(Optional) NextJS/React/Tailwind Crash Course Part 10:40
(Optional) NextJS/React/Tailwind Crash Course Part 210:29
(Optional) NextJS/React/Tailwind Crash Course Part 327:21
(Optional) NextJS/React/Tailwind Crash Course Part 44:29

3.0 • Streaming Demo0:32
LangChain provides a streaming API that allows you to get words streamed back to you as they are generated. This is useful for chatbots, where you want to show the user what is being generated as it is being generated. You can find an example of how to use the streaming API in the LangChain documentation.
3.1 • Set up the Frontend9:42
3.2 • Stream Responses from Backend5:36
3.3 • Streaming Conclusion0:16

DISCLAIMER0:15
⚠️ WARNING/DISCLAIMER ⚠️
This lecture was created in July 2023 prior to major changes to the LangChain-JS repository.
There may be bugs!
For an updated repository using the latest LangChain packages from June 2024, please skip to Section 9: PDF Chatbot V2.

Need Help?
To get the latest course updates, join the Discord and post on the #troubleshooting channel.
https://discord.gg/DPydvGb7
4.0 • PDF Chatbot Demo1:02
4.1 • Set Up Pinecone2:31
4.2 • Quick Review of Frontend1:15
4.3 • Using PDFLoader (pdf-upload.js)4:00
4.4 • Character Text Splitter (pdf-upload.js)6:24
4.5 • How do Embeddings Work? (pdf-upload.js)5:29
4.6 • Initialize Pinecone (pdf-query.js)0:55
4.7 • Vector Database Question Answer Chain (pdf-query.js)5:47
The VectorDBQAChain is a tool that allows you to interact with a vector store in an agentic manner. It is created by combining an LLM with a vector store, and can be used to answer questions about the data in the vector store. To use the VectorDBQAChain, you first need to create a vector store with your data, and then create the chain using the OpenAI LLM and the vector store. Once you have the chain, you can create a tool to use it, and then use the tool just like any other tool.
4.8 • Conclusion2:19
Review1:07
Lecture 40A (Optional): Namespaces in Pinecone Part 11:02
Lecture 40B (Optional): Namespaces in Pinecone Part 21:33
Lecture 40C (Optional): Namespaces in Pinecone Part 3: Upload0:49
Lecture 40D (Optional): Namespaces in Pinecone Part 4: Query0:23
Lecture 40E (Optional): Namespaces in Pinecone Part 5: Demo2:32

5.0 • YouTube Chatbot Demo3:07
5.1 • Frontend Setup2:08
5.2 • YouTube Transcript API7:09
5.3 • Initialize ChatOpenAI1:47
ChatOpenAI is a chat model provided by LangChain. It allows you to get chat completions by passing one or more messages to the chat model. The response will also be a message. The types of messages currently supported in LangChain are AIChatMessage, HumanChatMessage, SystemChatMessage, and a generic ChatMessage. Most of the time, you'll just be dealing with HumanChatMessage, AIChatMessage, and SystemChatMessage. You can also use the streaming API to get words streamed back to you as they are generated. This is useful for chatbots, where you want to show the user what is being generated as it is being generated.
5.4 • Configure HNSWLib and ConversationalRetrievalQAChain7:01
HNSWLib is an in-memory vector store that can be saved to a file and is only available on Node.js. It is used for similarity search and uses HNSWLib. You can create a new index from texts or a loader, save an index to a file and load it again, and filter documents.
5.5 • Handling Follow Up Questions to the Chain4:04
5.6 • Conclusion4:36

6.0 • AI Content Generator Demo0:32
6.1 • Overview of Project4:02
6.2 • Transcript API8:51
6.3 • Video Metadata10:11
6.4.1 • SerpAPI Tool5:25
6.4.2 • Web Browser Tool and Prompt Template4:01
The Web Browser Tool allows an agent to visit a website and extract information. It has two modes of operation:
When called with only a URL, it produces a summary of the website contents.
When called with a URL and a description of what to find, it uses an in-memory Vector Store to find the most relevant snippets and summarize those.
To use the Web Browser Tool, you need to install the dependencies cheerio and axios. The tool can be used standalone or in an agent.
6.4.3 • Zero Shot Agent3:53
The "zero-shot-react-description" agent is a type of agent that can be used with text LLMs. It is a stateless wrapper around an agent prompt chain, such as MRKL, that formats tools into the prompt and parses responses obtained from the chat model. This agent is recommended for use with small tasks.
6.4.4 • Connecting it to the Handler5:29
6.5.1 Summary2:07
6.5.2 LLM Chain Prompt Template6:30
6.6.1 Follow Up Questions2:32
6.6.2 Conclusion2:37

7.0 • RoboHR Demo1:45
7.1 • High Level Overview1:36
7.2 • File Overview2:58
7.3 • Convert Resumes to Embeddings3:37
7.4 • Resume Upload Section10:58
7.7 • Load Summary Chain10:03
The SummaryChain is a chain provided by LangChain that can be used to generate a summary of a given input text. To use it, you can import it from langchain/chains and create an instance of it. Once you have created the chain, you can call its call method with a text input to get a summary of the text.
7.8 • Upload to Pinecone (recommended)9:29
7.8.1 Supabase Part 1: Uploading (alternative, if waitlisted on Pinecone)6:01
7.8.2 Supabase Part 2: Querying (alternative, if waitlisted on Pinecone)15:06
7.8.3 If you're enjoying, please consider leaving a review!1:04
7.9 • Vector Database Question Answer Chain10:59
7.10 • Conclusion1:31

Requirements

Some experience in JavaScript (or a similar programming language) is helpful
No experience in AI, NextJS, TailwindCSS necessary
A desire to build your own AI applications!
Some experience in React is helpful

Description

Welcome to the LangChain AI JavaScript course!

As we stand here in 2023, AI is transforming our world at the speed of light. It's not just a buzzword - it's a reality shaping industries, from finance to healthcare, logistics, and entertainment. And you, as a developer, are in a prime position to ride the wave.

Dive into the innovative world of building Large Language Models (LLM) with LangChain, a groundbreaking tool for rapidly building AI powered applications.

In this course, we place an equal emphasis on theory and practice. We’ll start easy, and increase the complexity with each project. Additionally, you'll have starter templates for each project, so that you spend most of your time learning about AI, and less time worrying about setting up your code environment.

In 2023 alone, we’ve seen a rise in AI products making hundreds to thousands of dollars a month built by solo developers. At the end of the course, you will have built SIX stunning full-stack AI applications that will give you the skills to build your own AI products from scratch.

The world is moving fast, and AI is leading the charge. Don't be left behind, wishing you had started learning AI sooner. So secure your spot in the course, and take the first step towards your AI journey today.

In this course, we use cutting edge technologies to create a seamless developer experience:

LangChain, an AI framework for rapidly building LLM applications with OpenAI, HuggingFace, and more.
NextJS - Allows you to build the frontend and backend in one language, JavaScript.
Vercel - You'll know how to deploy your LLM application to users, without pulling your hair out.
TailwindCSS - Each project comes with a pre-styled template, so you don't need to worry about styling.

By the end of the course you will the skills to:

Chat With Anything - use AI to chat with books, videos, etc.
Supercharge Your Work - create autonomous AI agents that can "think" through complex tasks
Launch Your Product - display your AI projects for potential employers/customers to see
Troubleshoot Anything - how to use AI tools beyond ChatGPT to become the "10x developer"

Course Pre-Requisites:

Some experience in JavaScript (or a similar programming language) is helpful
Some experience in React is helpful
No experience in AI, NextJS, TailwindCSS necessary
A desire to build your own AI applications!

This is not just a course, it's a community. Along with lifetime access to the course, you'll get:

Dedicated 1 on 1 troubleshooting support with me
Notion Course Textbook with additional AI resources, FAQ, troubleshooting guides
Access to an exclusive Discord community to connect with other learners
No extra cost for continuous updates and improvements to the course

Who this course is for:

Beginner to intermediate developers who are curious about OpenAI and Langchain
React developers who are interested in creating LangChain projects in NextJS

LangChain: Develop AI web-apps with JavaScript and LangChain

What you'll learn

Explore related topics

Course content

Environment Setup & Quick Start to LangChain/NextJS19 lectures • 1hr 53min

Memory (Project) + NextJS Intro8 lectures • 36min

Streaming (Project)4 lectures • 16min

PDF Chatbot (Project)16 lectures • 37min

YouTube Chatbot (Project)7 lectures • 30min

AI Content Generator (Project)12 lectures • 56min

RoboHR (Project)12 lectures • 1hr 15min

Deployment (Optional)3 lectures • 12min

PDF Chatbot V25 lectures • 13min

Requirements

Description

Who this course is for: