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

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

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2024 Edition – Get to grips with the LangChain framework to develop production-ready applications, including agents and personal assistants. The 2024 edition features updated code examples and an improved GitHub repository.

Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free

Key Features

  • Learn how to leverage LangChain to work around LLMs’ inherent weaknesses
  • Delve into LLMs with LangChain and explore their fundamentals, ethical dimensions, and application challenges
  • Get better at using ChatGPT and GPT models, from heuristics and training to scalable deployment, empowering you to transform ideas into reality

Book Description

ChatGPT and the GPT models by OpenAI have brought about a revolution not only in how we write and research but also in how we can process information. This book discusses the functioning, capabilities, and limitations of LLMs underlying chat systems, including ChatGPT and Gemini. It demonstrates, in a series of practical examples, how to use the LangChain framework to build production-ready and responsive LLM applications for tasks ranging from customer support to software development assistance and data analysis – illustrating the expansive utility of LLMs in real-world applications.

Unlock the full potential of LLMs within your projects as you navigate through guidance on fine-tuning, prompt engineering, and best practices for deployment and monitoring in production environments. Whether you're building creative writing tools, developing sophisticated chatbots, or crafting cutting-edge software development aids, this book will be your roadmap to mastering the transformative power of generative AI with confidence and creativity.

What you will learn

  • Create LLM apps with LangChain, like question-answering systems and chatbots
  • Understand transformer models and attention mechanisms
  • Automate data analysis and visualization using pandas and Python
  • Grasp prompt engineering to improve performance
  • Fine-tune LLMs and get to know the tools to unleash their power
  • Deploy LLMs as a service with LangChain and apply evaluation strategies
  • Privately interact with documents using open-source LLMs to prevent data leaks

Who this book is for

The book is for developers, researchers, and anyone interested in learning more about LangChain. Whether you are a beginner or an experienced developer, this book will serve as a valuable resource if you want to get the most out of LLMs using LangChain.

Basic knowledge of Python is a prerequisite, while prior exposure to machine learning will help you follow along more easily.

Table of Contents

  1. What Is Generative AI?
  2. LangChain for LLM Apps
  3. Getting Started with LangChain
  4. Building Capable Assistants
  5. Building a Chatbot like ChatGPT
  6. Developing Software with Generative AI
  7. LLMs for Data Science
  8. Customizing LLMs and Their Output
  9. Generative AI in Production
  10. The Future of Generative Models

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Customer Reviews
4.1 out of 5 stars 95
4.2 out of 5 stars 46
4.1 out of 5 stars 82
Who Is This Book For? Developers, researchers, and anyone interested in staying ahead of the curve with LLMs and LangChain Software engineers, data scientists, and researchers who want hands-on guidance to build LLM apps Data scientists and NLP, CV, and ML engineers looking to advance their LLM and GenAI skills
Goals and Learning Outcomes Get guidance on the LangChain framework and learn to deploy LLM apps in production environments Gain foundational knowledge and learn how to use LLMs in an ethical and responsible way Learn how to use NLP, CV, and GenAI, focusing on transformers and their applications across domains
Tools Used LangChain, ChatGPT, Llama 2, StarCoder, Streamlit GPT 3.5, GPT 4, LangChain, Llama 2, Falcon LLM, StarCoder, Streamlit Hugging Face, ChatGPT, GPT-4V, DALL-E 2, DALL-E 3, Google Trax, Gemini, BERT, RoBERTa

Editorial Reviews

About the Author

Ben Auffarth is a full-stack data scientist with more than 15 years of work experience. With a background and Ph.D. in computational and cognitive neuroscience, he has designed and conducted wet lab experiments on cell cultures, analyzed experiments with terabytes of data, run brain models on IBM supercomputers with up to 64k cores, built production systems processing hundreds and thousands of transactions per day, and trained language models on a large corpus of text documents. He co-founded and is the former president of Data Science Speakers, London.

Product details

  • Publisher ‏ : ‎ Packt Publishing
  • Publication date ‏ : ‎ December 22, 2023
  • Language ‏ : ‎ English
  • Print length ‏ : ‎ 360 pages
  • ISBN-10 ‏ : ‎ 1835083463
  • ISBN-13 ‏ : ‎ 978-1835083468
  • Item Weight ‏ : ‎ 1.42 pounds
  • Dimensions ‏ : ‎ 7.5 x 0.85 x 9.25 inches
  • Best Sellers Rank: #1,213,938 in Books (See Top 100 in Books)
  • Customer Reviews:
    4.1 out of 5 stars (95)

About the author

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Ben Auffarth
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Ben Auffarth, PhD, is a bestselling author and AI implementation expert with over 15 years of experience bridging advanced technology with measurable business outcomes. As founder of Chelsea AI Ventures, he specializes in helping small and medium enterprises implement enterprise-grade AI solutions that deliver tangible ROI. His systems have prevented millions in fraud losses and process transactions at sub-300ms latency. With a background in computational neuroscience, Ben brings rare depth to practical AI applications—from supercomputing brain models to production systems that combine technical excellence with business strategy. His books are practical "cookbooks" that explain complex AI concepts in accessible, hands-on ways, while his consulting work focuses on delivering concrete, measurable outcomes for businesses. Based in London, Ben balances his technical expertise with family time and participation in the Data Science Speakers community.