about this book
Building LLM Applications with DSPy was written to help you develop prompt-based tasks in an efficient way using the DSPy framework. We start by explaining the basic machinery of DSPy, such as signatures, using basic prompt examples. Then we showcase the three-stage methodology of development: build a baseline classifier and evaluate and optimize on four different projects, the first of which is intent classification of an airline customer service.
Who should read this book
Building LLM Applications with DSPy is for AI engineers and data scientists who want to ship large language model (LLM)–based features faster and in a more reliable way. Even if a coding agent is generating the code, it’s crucial to work methodologically; otherwise, it is too easy to automate slop rather than something valuable. DSPy will help you get the extra mile by letting you evaluate your features.
How this book is organized: A road map
The book is divided into nine chapters: