DESIGNING LLM SYSTEMS: RAG, Tool Use, Guardrails, and Evals—Step-by-Step Walkthroughs + an Actively Maintained GitHub Repo to Design, Test, and Ship Reliable LLM Features
by Ethan Vector
This book offers step-by-step walkthroughs on designing LLM systems, focusing on RAG, tool use, guardrails, and evaluations. It includes an actively maintained GitHub repo to help you design, test, and ship reliable LLM features. Ideal for developers building AI applications.
About This Book
Designing LLM Systems provides a comprehensive guide to creating reliable large language model applications. It covers key components such as Retrieval-Augmented Generation (RAG), tool integration, safety guardrails, and evaluation methods through detailed, hands-on walkthroughs.
The book emphasizes practical implementation, helping readers design and test LLM features effectively. An accompanying GitHub repository is actively maintained, offering resources to support the development process from concept to deployment.
Whether you're a developer or engineer working with AI, this resource equips you with the knowledge to build production-ready LLM systems that are both efficient and secure.
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