
LangChain in your Pocket: Beginner's Guide to Building Generative AI Applications using LLMs
KiDimusic
Description
UPDATE:The book has been re-published by Packt and is now available on official website of Packt, O'Reilly and other partners of PacktUnlock the full potential of Generative AI with "LangChain in your Pocket", a hands-on guide that takes you through the robust LangChain framework. This book provides a step-by-step journey into creating powerful applications, from Auto-SQL and NER to custom Agents and Chains, integrating Memory, OutputParsers, RAG for Q&A, Few-Shot Classification, Evaluators, Autonomous AI agents, Advanced Prompt Engineering and many more.NOTE:Drop an email todatasciencepocket@gmail.comwith the transaction receipt for a freePDF version.Key Features:Step-by-step code explanations with expected outputs for each solution.No prerequisites: If you know Python, you're ready to dive in.Practical, hands-on guide with minimal mathematical explanations.Book Description:Since the arrival of ChatGPT in late 2022, the AI landscape has evolved dramatically. "LangChain in your Pocket" invites you to move beyond ChatGPT and explore the versatility of LangChain, a Python/JavaScript framework at the forefront of Large Language Models (LLMs). Whether you're building Classification models, Storyteller, or Internet-enabled GPT, LangChain empowers you to do more.This beginner-friendly introduction covers:Basics of Large Language Models (LLMs) and why LangChain is pivotal.Hello World tutorial for setting up LangChain and creating baseline applications.In-depth chapters on each LangChain module.Advanced problem-solving, including Multi-Document RAG, Hallucinations, NLP chains, and Evaluation for LLMs for supervised and unsupervised ML problems.Dedicated sections for Few-Shot Learning, Advanced Prompt Engineering using ReAct, Autonomous AI agents, and deployment using LangServe.Who should read it?This book is for anyone keen on exploring AI, especially Generative AI. Whether you're a Software Developer, Data Scientist, Student or Content Writer, the focus on diverse use cases in LangChain and GenAI makes it equally valuab
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Episodes (74)
Preface
1.1 What are LLMs?
1.2 Different LLM families
1.5 Book Overview
2.2 Name Generator
2.3 Text Pre-processing
2.4 Storyteller
2.5 LangChain using Local LLMs
Chapter 3: Different LangChain Modules
Chapter 4: Models and Prompts