The Complete LangChain & LLMs Guide

The Complete LangChain & LLMs Guide

by Paulo Dichone
Released February 2024
Publisher(s): Packt Publishing
ISBN: 9781835885925

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Video description

This comprehensive masterclass takes you on a transformative journey into the realm of LangChain and Large Language Models, equipping you with the skills to build autonomous AI tools.

Starting with the basics, you'll set up your development environment, including OpenAI API and Python, and progress to advanced topics like LangChain's architecture, prompt templates, and parsers. The course meticulously guides you through creating complex chains, memory models, and agents, culminating in the development of practical applications such as PDF extractors, newsletter generators, and multi-document chatbots. With hands-on tutorials, you'll learn to leverage LangChain for tasks ranging from document loading and splitting to embedding vector stores for semantic similarity searches.

By the end, you'll have the knowledge to implement AI in creative and impactful ways, from image-to-text conversion to building interactive chatbots and more, all while navigating the ethical considerations of AI deployment.

What you will learn

  • Configure OpenAI API and Python for AI development
  • Create and manipulate LangChain prompt templates and parsers
  • Implement LangChain memory models and chains for complex AI applications
  • Develop real-world applications, including newsletter generators and chatbots
  • Work with LangChain embeddings and vector stores for semantic searches
  • Navigate the ethical and copyright implications of AI-generated content

Audience

This course is designed for a broad audience interested in artificial intelligence, from data scientists enhancing projects with AI and LangChain, to product managers boosting user experience with AI features. AI enthusiasts, tech innovators, and programmers will deepen their understanding of LangChain, unlocking new opportunities in AI-driven development and pioneering next-gen solutions. While specific knowledge of Python is not necessary, familiarity with programming concepts is essential.

About the Author

Paulo Dichone: Paulo Dichone, a seasoned software engineer and AWS Cloud Practitioner, is renowned for his expertise in Android, Flutter, and AWS, as well as being a best-selling instructor. Paulo has successfully imparted his knowledge to over 200,000 students across 175 countries, specializing in mobile app development for Android and iOS, web development, and AWS Cloud. His teaching philosophy centers on empowering students to excel as developers and AWS cloud practitioners, regardless of their prior experience. Beyond his professional pursuits, Paulo is devoted to his family, enjoys playing the guitar and mandolin, and loves to travel. He is committed to guiding students to achieve their highest potential in the tech industry.

Table of contents

  1. Chapter 1 : Introduction
    1. Welcome
    2. Introduction Course Pre-requisites
    3. What You'll Build in this Course - Demo
    4. Connect with Me
  2. Chapter 2 : Development Environment Setup
    1. Setup OpenAI API - API Key
    2. Install Python - Full Instructions
    3. Setup VS Code and Python Extensions
  3. Chapter 3 : LangChain and LLMs - Deep Dive
    1. What's an LLM
    2. LangChain Deep Dive - How it Works and Benefits
    3. Setup Python Environment VS Code
    4. LangChain Building Blocks - Components - Chains - Agents
    5. LangChain Language Model Types Part 1
    6. LangChain Language Model Types Part 2
  4. Chapter 4 : LangChain Prompts Template
    1. LangChain Prompt Template - Introduction and Motivation
    2. Prompt Templates - Hands-on
  5. Chapter 5 : LangChain Parsers
    1. Parsers - Introduction
    2. Output Parsers - Hands-on
    3. Pydantic Output Parser - Introduction
    4. Pydantic Parser
    5. LangChain Building Blocks Summary
  6. Chapter 6 : LangChain Memory and Chains
    1. LangChain Memory - Introduction
    2. Memory Hands-On - ConversationBufferMemory
    3. LangChain Chains - Introduction
    4. LLMChain Hands-on
    5. LLMChain Input Variables - Hands-on
    6. Sequential Chain Hands-on
    7. Streamlit Application - Lullaby Generator - Demo
    8. Lullaby Application with Streamlit - Hands-on
  7. Chapter 7 : LangChain Routers, Document Loading and Document Splitting
    1. Router Chains - Introduction and Hands-on - Part 1
    2. Router Chains - Hands-on - Part 2
    3. LangChain Document Loading - Loading a PDF File
    4. Document Splitting - An Overview
    5. CharacterTextSplitter - Hands-on
    6. RecursiveCharacterTextSplitter - Hands-on
  8. Chapter 8 : LangChain Embeddings and Vectorstores
    1. Vectorstore Embeddings - Full Overview
    2. Embeddings and Semantic Similarity Test - Hands-on
    3. Saving Embeddings to Chroma DB Similarity Search
    4. LangChain Retrievers
  9. Chapter 9 : LangChain Agents - Deep Dive
    1. Agents - Introduction
    2. Agents - Motivation Creating a Tool for an Agent
    3. Built-in Math Tool Testing an Agent
    4. Adding a General Knowledge Tool for Our Agent
    5. Agents Types
    6. Looking Into the Agents Prompt Template
    7. Conversational Agent and Memory - Hands-on
    8. LangChain Docstore Agent
    9. Self-Ask-with-Search Agent
    10. What We've Learned So far- Recap
  10. Chapter 10 : [REAL-WORLD] App - PDF Extractor
    1. Bill Extractor - Project Introduction and Functions Setup
    2. Front-end Setup and Testing
  11. Chapter 11 : [REAL-WORLD] App - Newsletter Generator
    1. Newsletter Generator Demo
    2. Setup the Search Function with Serper API Key and Testing
    3. Picking the Best Articles Function and Testing
    4. Article Summary
    5. Fixing a Python Libmagic Bug
    6. Generating the Newsletter
    7. Creating the Frontend with Streamlit - Final Result
  12. Chapter 12 : [REAL-WORLD] App - Multi-document Chatbot
    1. Document Chatbot - Resumé Analyzer Bot
    2. Document Chatbot with LangChain QAChain
    3. Multi-Document Chatbot with Streamlit - Full Chatbot
  13. Chapter 13 : [REAL-WORLD] App - Image to Text
    1. Image to Recipe App - Demo
    2. Setup HuggingFace Token Generating Text from an Image
    3. Text to Speech
    4. Generating Recipes from Image - Image Captioning
    5. Adding a Frontend with Streamlit - Text to Recipe Application - Final Result
  14. Chapter 14 : Next Steps
    1. Next Steps

Product information

  • Title: The Complete LangChain & LLMs Guide
  • Author(s): Paulo Dichone
  • Release date: February 2024
  • Publisher(s): Packt Publishing
  • ISBN: 9781835885925