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 Bard. It also 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 โ 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
โข Understand LLMs, their strengths and limitations
โข Grasp generative AI fundamentals and industry trends
โข Create LLM apps with LangChain like question-answering systems and chatbots
โข Understand transformer models and attention mechanisms
โข Automate data analysis and visualization using pandas and Python
โข Grasp prompt engineering to improve performance
โข Fine-tune LLMs and get to know the tools to unleash their power
โข Deploy LLMs as a service with LangChain and apply evaluation strategies
โข 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 LLMs. Basic knowledge of Python is a prerequisite, while