Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT and other LLMs (Paperback) (使用 LangChain 的生成式 AI：用 Python、ChatGPT 和其他大型語言模型 (LLM) 建立應用程式)

Get to grips with the LangChain framework to develop production-ready applications, including agents and personal assistants, integrating with web searches and code execution.

Purchase of the print or Kindle book includes a free PDF eBook

Key Features:

• GitHub repository updated regularly to stay abreast of LangChain developments
• Delve into the realm of LLMs with LangChain and go on an in-depth exploration of 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:

The ChatGPT and the GPT models by OpenAI have brought about a revolution in the way we think about the world - and not only in how we write and research, but in how we can process information.

This book discusses the functioning, capabilities, and limitations of LLMs including ChatGPT and Bard. It also demonstrates how to use the LangChain framework to implement production-ready applications based on these models, such as agents and personal assistants, and integrate with other tools such as web searches and code execution.

As you progress through the chapters, you'll use transformer models and diverse attention mechanisms, refining the intricate process of training and fine-tuning. You'll get to grips with data-driven decision-making with automated analysis and visualization using pandas and Python. You'll also take a closer look at the heuristics of how to use these models, prompting, training and fine-tuning, and deploying at scale.

By the time you've finished this book, you'll have a deep understanding of what makes LLMs tick and how to make the most of them.

What You Will Learn:

• Gain an understanding of LLMs and their legal implications
• Understand transformer models and different attention mechanisms
• Train and fine-tune LLMs and get to know the tools for using them
• Build applications with LangChain like question-answering systems and chatbots
• Implement automated data analysis and visualization with pandas and Python
• Grasp prompt engineering to improve prompts and evaluation strategies
• Deploy LLMs as a service with LangChain
• Interact privately with your documents without data leaks using ChatGPT

Who this book is for:

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

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