Mô tả

LAST UPDATE ON FEB 2024- LangChain Version 0.1.7


Welcome to first LangChain Udemy course - Unleashing the Power of LLM!
This comprehensive course is designed to teach you how to QUICKLY harness the power the LangChain library for LLM applications.
This course will equip you with the skills and knowledge necessary to develop cutting-edge LLM solutions for a diverse range of topics.

Please note that this is not a course for beginners. This course assumes that you have a background in software engineering and are proficient in Python. I will be using Pycharm IDE but you can use any editor you'd like since we only use basic feature of the IDE like debugging and running scripts .

In this course, you will embark on a journey from scratch to building a real-world LLM powered application using LangChain.
We are going to do so by build 3 main applications:

  1. Ice Breaker- LangChain agent that given a name, searches in google to find Linkedin and twitter profiles, scrape the internet for information about a name you provide and generate a couple of personalized ice breakers to kick off a conversation with the person.

  2. Documentation Helper- Create chatbot over a python package documentation. (and over any other data you would like)

  3. A slim version of ChatGPT Code-Interpreter



The topics covered in this course include:

  • LangChain

  • History

  • LLMs: Few shots prompting, Chain of Thought, ReAct prompting

  • Chat Models

  • Prompts, PromptTemplates

  • Output Parsers

  • Chains: SequentialChain, LLMChain, RetrievalQA chain

  • Agents, Custom Agents, Python Agents, CSV Agents, Agent Routers

  • OpenAI Functions

  • Tools, Toolkits

  • Memory

  • Vectorstores (Pinecone, FAISS)

  • DocumentLoaders, TextSplitters

  • Streamlit (for UI)


Throughout the course, you will work on hands-on exercises and real-world projects to reinforce your understanding of the concepts and techniques covered. By the end of the course, you will be proficient in using LangChain to create powerful, efficient, and versatile LLM applications for a wide array of usages.


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

  1. Dedicated 1 on 1 troubleshooting support with me

  2. Github links with additional AI resources, FAQ, troubleshooting guides

  3. Access to an exclusive Discord community to connect with other learners (1000+ members)

  4. No extra cost for continuous updates and improvements to the course


DISCLAIMERS

  1. Please note that this is not a course for beginners. This course assumes that you have a background in software engineering and are proficient in Python.
    I will be using Pycharm IDE but you can use any editor you'd like since we only use basic feature of the IDE like debugging and running scripts.

  2. The first project of the course (Ice-Breaker) requires usage of 3rd party APIs-
    ProxyURL, SerpAPI, Twitter API  which are generally paid services.
    All of those 3rd parties have a free tier we will use to create stub responses development and testing.

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12 sections

Introduction

4 lectures
Introduction
03:12
Course Structure + How to get the best of Udemy [PLEASE DO NOT SKIP]
02:20
What is LangChain?
02:14
Course's Discord Server
01:51

The GIST of LangChain- Get started by with your "Hello World" chain

6 lectures
Project Setup (Pycharm) recommend)
06:36
Project Setup (vscode) - optional
08:52
Environment Variables and .env File
01:45
Your First LangChain application - Chaining a simple prompt
11:08
LangChain Version In Course (V0.1.14)
01:43
Quick Check In
00:38

Ice Breaker Real World Generative AI Agent application

9 lectures
Ice Breaker- What are we building here?
01:02
Integrating Linkedin Data Processing - Part 1 - Scraping
15:42
Linkedin Data Processing - Part 2 - Agents Theory
04:22
Linkedin Data Processing- Part 3: Tools, AgentType & initialize_agent
05:23
Linkedin Data Processing- Part 4: Custom Agent Implementation & Testing
23:32
[Optional] Twitter Data Processing- Part 1- Scraping
08:56
[Optional] Twitter Data Processing- Part 2- Agents (Optional)
11:11
Output Parsers- Getting Ready to work with a Frontend
11:23
FullsStack App- Building our LLM powered by LangChain FullStack Application
06:34

Diving Deep Into ReAct Agents- Whats is the magic?

6 lectures
What are we building? ReAct AgentExecutor from scratch
01:51
Environment Setup + ReAct Algorithm overview
05:34
Defining Tools for our ReAct agent
10:47
ReAct prompt, LLM Reasoning Engine, Output Parsing and Tool Execution
14:58
AgentAction, AgentFinish, ReAct Loop
07:40
CallbackHandlers, ReAct Prompt and finalizing the ReAct Agent loop
08:29

The GIST of Embeddings, Vector Databases and, VectorDBQA chain & RetrievalQA

5 lectures
Theoretical Introduction to embeddings, Vectorstores & RetrievalQA chain (RAG)
13:58
LangChain classes review: Pinecone, OpenAIEmbeddings, RetrievalQA, TextLoader
09:47
Medium Analyzer- Boilerplate Project Setup
04:06
Medium Analyzer- Implementation
12:55
Chat With Your PDF- FAISS Local Vectorstore
11:37

Building a documentation assistant (Embeddings, VectorDBs, RetrievalQA, Memory)

5 lectures
What are we building?
02:12
Building an AI LangChain Chat Assistant- Vectorstore Pincone Ingestion
20:17
Building an AI LangChain Chat Assistant- RetrievalQA chain (prompt augmentation)
13:23
Building an AI LangChain Chat Assistant- "Frontend" with Streamlit (UI)
17:08
Building an AI LangChain Chat Assistant- Memory & ConversationalRetrievalChain
11:42

Building a slim ChatGPT Code-Interpreter (Advanced Agents, OpenAI Functions)

5 lectures
What are we building? (A slim Version of GPT Code-Interpreter)
05:32
Project Setup
02:13
Python Agent
08:26
CSV Agent
09:30
Wrapping Everything: Router Agent + OpenAI functions
09:18

LangChain Theory

2 lectures
LangChain Token Limitation Handeling Strategies
11:29
LangChain Memory Deepdive
20:53

Prompt Engineering Theory

7 lectures
The GIST of LLMs
03:52
What is a Prompt? Composition of a formal prompt
02:55
Zero Shot Prompting
02:42
Few Shot Prompting
08:26
Chain of Thought Prompting
08:33
ReAct
07:18
Prompt Engineering Quick Tips
08:59

Troubleshooting Section

4 lectures
Have a technical issue? WATCH THIS FIRST. I Promise this will help!
02:10
Tweet API- tweepy.errors.Forbidden: 403 Forbidden
05:49
Pinecone: AttributeError: init is no longer a top-level attribute of pinecone
01:19
LangChain Version In Course (V0.1.14)
05:04

Wrapping Up

3 lectures
LLM Applications in Production
08:33
LLM Application Development landscape
04:01
Finished course? Whats next!
06:00

Useful tools when developing LLM Applications

3 lectures
LangChain Hub - Downloads prompt from the community
04:08
TextSplitting Playground
03:52
LangChain VS LlamaIndex
02:45

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