Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs

12 reviews for Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs

1. Samuel de Zoete

   Rated 5 out of 5

   May 21, 2024

   No need to look any further

   This book is a well written and comprehensive guide into langchain, the essential library to setup your Generative AI pipelines. The many and easy to ...More

   This book is a well written and comprehensive guide into langchain, the essential library to setup your Generative AI pipelines. The many and easy to follow examples ensures a good grasp of the power of langchain as well how to develop a generative ai application. The problem with YouTube and other media to learn about langchain is that it only handles a small part and it's then hard to find the 'missing pieces'. In this book it all hangs together and by just scrolling through the pages you find easily what you need. I also enjoyed the way the book is written.

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   Rajesh Sathya Kumar

   Rated 5 out of 5

   April 4, 2024

   Excellent Intro to Langchain

   "Generative AI with Langchain" comprehensively explores building Generative AI software and individual components using Langchain. From understanding ...More

   "Generative AI with Langchain" comprehensively explores building Generative AI software and individual components using Langchain. From understanding the fundamentals of generative models to practical applications in various sectors, the book navigates through topics such as enhancing language models with external knowledge, developing AI-driven assistants, and deploying generative AI in real-world scenarios. It addresses critical concerns like misinformation, ethical deployment, and the future societal impacts of AI technologies.
   
   With insights into LLM customization techniques, and deployment strategies, the book offers a roadmap for harnessing Langchain's potential in the Gen AI landscape.

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   Heena Chouhan

   Rated 5 out of 5

   March 24, 2024

   Must have book for LLM and Generative AI

   "Generative AI with LangChain" offers a timely exploration of the evolving landscape of language models, particularly in the context of LangChain's tr...More

   "Generative AI with LangChain" offers a timely exploration of the evolving landscape of language models, particularly in the context of LangChain's transformative potential. Auffarth adeptly navigates the complexities of LLM-powered applications, providing a comprehensive guide for both beginners and seasoned developers alike.
   
   The book demystifies key LangChain developments by abstracting LLM complexities while empowering readers with advanced customization options. From fundamental concepts to intricate techniques like agents and chains, Auffarth equips readers with the tools necessary to enhance applications and navigate production deployment effectively.
   
   What sets this book apart is its multifaceted approach, bridging theory with hands-on examples across diverse domains like information extraction and chatbots. By combining conceptual foundations with real-world implementations, Auffarth ensures readers gain not only a deep understanding of LangChain but also the skills to tailor it to their specific applications.
   
   "Generative AI with LangChain" stands out among existing resources by offering a comprehensive, well-rounded exploration of LangChain's capabilities. Auffarth's expertise shines through in his intuitive explanations and applied case studies, making this book an invaluable resource for anyone looking to harness the power of language models in their projects.

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   Bipin Chadha

   Rated 5 out of 5

   February 19, 2024

   A good intro to turn your LLM project into a working application

   This is a very timely book that builds upon other books that discuss GenAI and LLMs and GenAI apps. Key idea that this book brings forward is that LLM...More

   This is a very timely book that builds upon other books that discuss GenAI and LLMs and GenAI apps. Key idea that this book brings forward is that LLM powered applications will need to overcome many of the drawbacks (hallucinations, bias, potential for misuse, poor reasoning capabilities, etc.) of LLMs. These can be overcome (though not completely) by using frameworks like LangChain that can tie LLMs with other data sources, vector stores, chains, agents, and tools. The author then describes in detail how to use these capabilities to create intelligent assistants, chatbots, code copilots, and data science assistants. I really liked the chapters that go into operationalizing these applications including testing, evaluation, cost analysis, moderation, observability, monitoring, bias analysis, and ethical safeguards.
   If you are already familiar with many of the basics of LLMs, then this is a good next step to learn how to turn them into useful applications that can be deployed.

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   Thomas M.

   Rated 5 out of 5

   February 3, 2024

   Excellent one-stop-shop for all things practical and theoretical related to LLMs

   Generative AI with LangChain is an invaluable resource for anyone interested in the revolutionary topic of LLMs and transformer architecture. With lim...More

   Generative AI with LangChain is an invaluable resource for anyone interested in the revolutionary topic of LLMs and transformer architecture. With limited quality resources available in this nascent field, this book stands out in providing a deep dive into the capabilities, limitations, and practical applications of LLMs, with hands-on examples using the groundbreaking ChatGPT and Bard models.
   
   Auffarth does an exceptional job of breaking down complex concepts into digestible content, making it accessible to both beginners and experienced developers. The book starts with an introduction to LLMs and their legal implications, before delving into the intricacies of transformer models and different attention mechanisms.
   
   One of the standout features of this book is its practical approach. The author guides readers on how to use the LangChain framework to implement production-ready applications, such as agents and personal assistants. The book also provides insights into integrating these applications with other tools such as web searches and code execution. The book also covers the critical process of training and fine-tuning LLMs, providing readers with a comprehensive understanding of data-driven decision-making, automated analysis, and visualization using familiar libraries like pandas.
   
   By the end of this book, I feel like I not only have a deep understanding of LLMs but am also equipped with the knowledge to build and deploy actual applications using the LangChain framework. The book is a must-read for developers, researchers, and anyone interested in staying ahead of the curve in the LLMs and LangChain arena. We'll see how long the concepts stand the test of time in this rapidly evolving field, but there is no doubt that the book's blend of theoretical knowledge and practical application makes it a valuable addition to any tech enthusiast's library.

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   Saksham

   Rated 5 out of 5

   February 1, 2024

   A much required practical book

   Overall, "Generative AI with LangChain" is a commendable resource that bridges the gap between theory and practical implementation, making it an essen...More

   Overall, "Generative AI with LangChain" is a commendable resource that bridges the gap between theory and practical implementation, making it an essential read for anyone looking to explore and leverage the capabilities of large language models in their projects.

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   H. Gibbs Bauer

   Rated 5 out of 5

   January 25, 2024

   AI Toolbox

   I am impressed by the thoroughness and level of detail presented. My guess is that this and future editions of this compendium of useful AI tools wil...More

   I am impressed by the thoroughness and level of detail presented. My guess is that this and future editions of this compendium of useful AI tools will always have a place in my AI library.
   
   Cheers!
   
   HGB 💥🐎🎶

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   hawkinflight

   Rated 5 out of 5

   January 5, 2024

   Great for getting started w/LLM apps

   I have not used LangChain before, and I am looking at this book to learn how to create an LLM app. I am really looking forward to trying it out for al...More

   I have not used LangChain before, and I am looking at this book to learn how to create an LLM app. I am really looking forward to trying it out for all three types of apps covered in the book - assistants/chatbot, code generation, and data science. The book is clear and straight to the point, so I expect to be able to try these out fairly quickly. I have gotten through the "setting up the dependencies" section. I cloned the book's github repo, and I tried three methods for variety's sake to create a python environment: pip, conda, and Docker, all on Windows, and I believe I have them all set up. I hit some bumps, but I was able to follow the onscreen error messages and get past them. For pip, I needed to install MSFT Build Tools to get C++. For the conda case, I had to modify the yaml file for two of the packages - ncurses and readline, which have different names for Windows. In Chapter 2 there is a comparison of LangChain with other frameworks, from which you get a feel that choosing LangChain at this moment is the best choice. I am happy to have found this book, and I can't wait to proceed w/the next steps. It's a lot of fun to be able to interact w/LLMs.

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   MZ

   Rated 5 out of 5

   January 1, 2024

   Great Book!

   This book has substance and interesting material, best book so far in the market covering langchain. The author knows his stuff!

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   Stephan Miller

   Rated 5 out of 5

   December 30, 2023

   Great book for creating your own generative AI solutions

   I played around with Langchain before I read this book, trying to piece together various agents to create a custom chatbot, but the results were not q...More

   I played around with Langchain before I read this book, trying to piece together various agents to create a custom chatbot, but the results were not quite what expected. But that is what happens sometimes when you are depending on short online blog posts and articles. This book filled in the gaps and helped me understand where I messed up in my first try.
   
   But it is more than just a "How to use Langchain" book. It explains what LLMs and GPTs are, how they work, how they are trained, and how they are conditioned, so when you get to the Langchain part of the book, you have a bigger arsenal of tools to chain together to do your bidding correctly instead of poking at random things with a stick.
   
   Essentially, Langchain is a tool to create a generative AI pipeline that can connect to various AI models, load documents, and store those documents for use by the models so tailor them to your use case and the last 80% of the book covers how to do this. So if you ever wanted to create your own AI agents and chatbots that can use the features of existing models like GPT-4 but customized for your own use, this is this book for you.

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   Nostromo500

   Rated 5 out of 5

   December 28, 2023

   If you build LLM applications, this book is a MUST HAVE.

   Simply the best book I've read on LLMs in general and the LangChain eco-system. Very in-depth and clearly explained with excellent code examples.

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   F. P.

   Rated 5 out of 5

   December 22, 2023

   One-stop resource for the current landscape of LLM application development

   During my learning journey into large language model (LLM) development, I encountered several challenges:- The difficulty of providing precise instruc...More

   During my learning journey into large language model (LLM) development, I encountered several challenges:
   
   - The difficulty of providing precise instructions within specific contexts, which I found to be the most challenging and crucial aspect.
   - Switching between different LLM models with minimal programming effort.
   - Selectively saving chat history in memory.
   - Handling data efficiently, including managing input data of various modalities and making output data accessible.
   
   In overcoming these obstacles, I came across LangChain, a robust toolkit designed for LLM application development. The book "Generative AI with LangChain" by Ben Auffarth provides a comprehensive overview, covering the basics of LLM, LangChain, and its key components (chains, agents, memory, tools). The book also explores sample applications such as chatbots, customization of LLM models (conditioning, fine-tuning), and the deployment of LLM apps into production. Unlike theoretical research materials, this book serves as a practical, one-stop resource for understanding the current landscape of LLM applications.
   
   Some of the interesting points:
   - LangChain helps standardize prompts by providing prompt templates (LangChain Expression Language).
   - LangChain provides extensive integrations to other model APIs including Fake LLM, OpenAI, Hugging Face, GCP, Jina AI, Replicate, etc.
   - LangChain has "memory" which allows the model to be context-aware.
   - LangChain supports advanced data facilities such as map-reduce approach and output parser.
   
   This book has significantly saved me time, providing consolidated information without the need for extensive online searches or inquiries to ChatGPT. For those unsure about its content, I recommend checking out the free sample on Amazon – it's undoubtedly worth every penny.

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