English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 82 lectures (6h 59m) | 3.18 GB
Hands-On Practice with OpenAI, ChatGPT and LangChain. Use Pinecone and Huggingface and integrate AI into your Node app
It’s time to add AI to your JavaScript/TypeScript app!
AI for NodeJs devs with OpenAI and LangChain is an advanced course designed to empower developers with the knowledge and skills to integrate artificial intelligence (AI) capabilities into Node.js applications. This course is tailored for developers who are proficient in Node.js and wish to explore the fascinating realm of AI-driven solutions.
Throughout the course, participants will delve into various AI concepts, algorithms, and frameworks, focusing on their practical implementation within Node.js environments.
Key topics covered in this course include:
- Introduction to AI and its applications in Node.js
- OpenAI setup for basic apps
- Understanding models, tokens and roles
- OpenAI request parameters
Practice apps:
- ChatGPT clone in the console
- App features: history, context and token limit
- OpenAI tools app
- OpenAI tools parameters
Key topics for AI development:
- Embeddings – presentation, persistence, load
- Similarity search using cosine or dot product
Vector databases:
- Introduction and setup
- ChromaDB setup
- Building a ChromaDB server with Docker
- Building a ChromaDB client with NodeJS
- Pinecone Vector database setup
- Pinecone indexes and index operations
- Building apps backed by Pinecone
Dedicated section for LangChain, the most popular LLM apps wrapper:
- LangChain introduction and setup
- LangChain prompt templates
- LangChain output parsers
- Building RAG applications with LangChain
- Web and file LangChain loaders
- What if you want to run the AI models yourself on your own machine? This is possible with open source models!
We will explore Hugging face and it’s APIs and open source models for local LLM apps:
- Local embeddings
- Translation models
- Text models
- Voice models
- Image models
Since all the used libraries are build with TypeScript and offer great TS support, the course also contains a TypeScript recap section:
- TypeScript type aliases
- The TypeScript compiler
- Functions, special types, any and unknown
- Enums and the never type
- TypeScript generics
- TypeScript classes
- …and many more features.
Go beyond the theory and learn from an active instructor, aligned with today’s programming demands!
Whether you’re a seasoned NodeJs developer looking to expand your skill set or a newcomer interested in harnessing the power of AI, AI for NodeJS offers an exciting journey into the intersection of artificial intelligence and modern web development. Enroll and unlock the potential to create intelligent, cutting-edge applications with NodeJs!
What you’ll learn
- Integrate OpenAI APIs in JavaScript and TypeScript applications. Use text, speech and Image modes
- Use LangChain, Pinecone, and OpenAI to Build LLM-Powered Applications.
- Translate and transcribe audio files using open source models in NodeJS apps
- Learn the basics of AI with OpenAI and ChatGPT: build a console chat app with NodeJS
- Integrate Tools and Functions into your OpenAI apps and chat with real-time data
- Master crucial AI topics like Embeddings, similarity and Vector databases
- Use ChromaDB as a local DB for your embeddings and run special queries
- Use Pinecone as serverless DB and run special embeddings queries. Use indexes and run similarity searches
- Learn about LangChain components, LLM wrappers, prompt templates, chains, and agents.
Table of Contents
Introduction
1 How to take this course
2 Course experience
3 Tools setup
4 Course resources
OpenAI setup and Introduction
5 Sectio intro
6 NodeJS setup and api key
7 Optional TypeScript setup
8 Understanding an API call
9 OpenAI models
10 Tokens
11 OpenAI roles
12 Other OpenAI parameters
Basic chat project
13 Section intro
14 Project init
15 Basic chat build
16 Context configuration
17 Optional VSCode debug
18 OpenAI token limit
OpenAI tools (functions)
19 Section intro
20 Tool call setup
21 First tool call
22 Tool parameters
23 Practice flight assistant
24 Project solution
Halfway discussion
25 Halfway discussion
Embeddings
26 Section intro
27 Embeddings presentation
28 OpenAI embeddings
29 Saving embeddings
30 Calculating similarity
31 Analizing similarities
32 Project recommandation sysytem
33 Project sollution
Vector databases
34 Section intro
35 Vector dbs presentation
36 ChromaDB presentation
37 ChromaDb installation
38 ChromaDB Client
39 ChromaDB Embedding function
40 Chat with your data App proposal
41 Chat app implementation
42 Pinecone introduction
43 Pinecone indexes
44 Pinecone index operations
45 Pinecone info app
LangChain
46 Section intro
47 What is LangChain
48 LangChain setup
49 First LangChain application
50 LangChain promp templates
51 LangChain output parsers
52 RAG app presentation
53 Basic RAG appication
54 LangChain Web Loader
55 LangChain PDF Loader
56 LangChain and ChromaDB
Escape from OpenAI – other AI models
57 Section intro
58 What is Huggingface
59 Huggingface setup and embeddings
60 Huggingface translation models
61 Huggingface image generation
62 Local model setup
63 Local text generation and speech recognition
Ending section
64 Course conclussions
TypeScript recap
65 Section intro – zzz
66 What is TypeScript
67 Installation and project init
68 Compiler options
69 Primary JavaScript types
70 Type aliases
71 Functions
72 Any and unknown
73 Enums
74 Never
75 TypeScript classes
76 Access modifiers
77 Interfaces
78 Generics
79 Special types
80 Async functions
81 Promises
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