Mastering Retrieval Augmented Generation
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Mastering Retrieval-Augmented Generation
Author: Prashanth Josyula
language: en
Publisher: BPB Publications
Release Date: 2025-03-21
DESCRIPTION Large language models (LLMs) like GPT, BERT, and T5 are revolutionizing how we interact with technology — powering virtual assistants, content generation, and data analysis. As their influence grows, understanding their architecture, capabilities, and ethical considerations is more important than ever. This book breaks down the essentials of LLMs and explores retrieval-augmented generation (RAG), a powerful approach that combines retrieval systems with generative AI for smarter, faster, and more reliable results. It provides a step-by-step approach to building advanced intelligent systems that utilize an innovative technique known as the RAG thus making them factually correct, context-aware, and sustainable. You will start with foundational knowledge — understanding architectures, training processes, and ethical considerations — before diving into the mechanics of RAG, learning how retrievers and generators collaborate to improve performance. The book introduces essential frameworks like LangChain and LlamaIndex, walking you through practical implementations, troubleshooting, and optimization techniques. It explores advanced optimization techniques, and offers hands-on coding exercises to ensure practical understanding. Real-world case studies and industry applications help bridge the gap between theory and implementation. By the final chapter, you will have the skills to design, build, and optimize RAG-powered applications — integrating LLMs with retrieval systems, creating custom pipelines, and scaling for performance. Whether you are an experienced AI professional or an aspiring developer, this book equips you with the knowledge and tools to stay ahead in the ever-evolving world of AI. WHAT YOU WILL LEARN ● Understand the fundamentals of LLMs. ● Explore RAG and its key components. ● Build GenAI applications using LangChain and LlamaIndex frameworks. ● Optimize retrieval strategies for accurate and grounded AI responses. ● Deploy scalable, production-ready RAG pipelines with best practices. ● Troubleshoot and fine-tune RAG pipelines for optimal performance. WHO THIS BOOK IS FOR This book is for AI practitioners, data scientists, students, and developers looking to implement RAG using LangChain and LlamaIndex. Readers having basic knowledge of Python, ML concepts, and NLP fundamentals would be able to leverage the knowledge gained to accelerate their careers. TABLE OF CONTENTS 1. Introduction to Large Language Models 2. Introduction to Retrieval-augmented Generation 3. Getting Started with LangChain 4. Fundamentals of Retrieval-augmented Generation 5. Integrating RAG with LangChain 6. Comprehensive Guide to LangChain 7. Introduction to LlamaIndex 8. Building and Optimizing RAG Pipelines with LlamaIndex 9. Advanced Techniques with LlamaIndex 10. Deploying RAG Models in Production 11. Future Trends and Innovations in RAG
Mastering Spring AI
Dive into the future of programming with this comprehensive guide for Java developers to integrate large language models (LLMs) and Generative AI using the Spring Framework. This book comes at a revolutionary time when AI technology is transforming how we implement solutions in various fields, including natural language processing, content generation, and predictive analytics. With its widespread use in the Java community, the Spring Framework is a logical choice for this integration. By focusing on integrating LLMs and GenAI with Spring, this book bridges a significant gap between cutting-edge AI technologies and traditional Java development practices. The author uses a hands-on approach, guiding you through practical implementation to effectively show how to apply theory in real-world situations. Basic introductions of topics—Spring AI, Spring Framework, and other related AI technologies—evolve into advanced integrations to ensure that you find valuable insights regardless of your starting level. Additionally, this book dedicates sections to security and ethical considerations, addressing the pressing issues associated with AI. With a look at emerging trends and future developments, this book prepares you for what's next, ensuring that you are not just catching up with the current state of technology but are also ready for future advancements. What You Will Learn • Master the integration of LLMs and GenAI with the Spring Framework • Develop practical skills in developing AI-driven applications using Java • Gain insights into handling data, security, and ethical considerations in AI applications • Apply strategies for optimizing performance and scalability in AI-enabled applications • Prepare for future AI trends and technologies Who This Book Is For Intermediate to advanced Java developers who are familiar with the Spring Framework, including concepts such as dependency injection, Spring Boot, and building RESTful services. This foundational knowledge will help developers grasp the more advanced topics of integrating AI technologies with Spring. Prior knowledge of basic AI concepts and machine learning is helpful but not essential as the book covers these topics from the ground up.
Mastering OpenAI for Enterprise
Author: Sriram Subramanian
language: en
Publisher: Orange Education Pvt Ltd
Release Date: 2025-03-11
TAGLINE Master OpenAI and Unlock the Future of AI-Powered Innovation KEY FEATURES ● In-depth exploration of OpenAI tools, models, and enterprise use cases ● Hands-on projects with extensive code samples for practical learning ● Real-world case studies with ethical AI insights and best practices DESCRIPTION OpenAI is transforming industries with cutting-edge AI models, redefining how businesses operate, innovate, and compete. Mastering OpenAI for Enterprise is your definitive guide to harnessing the power of OpenAI’s groundbreaking technologies, including GPT models, DALL·E, and more. Designed for AI engineers, developers, and business leaders, this book offers an in-depth understanding of OpenAI’s tools and their real-world applications in enterprise settings. This hands-on guide provides a structured learning path, featuring practical code samples, step-by-step implementations, and industry case studies that bridge theory with practice. Whether you're building intelligent chatbots, leveraging AI for automation, or exploring generative AI for creative solutions, this book equips you with the knowledge and skills to seamlessly integrate OpenAI into your workflows. Ethical AI development and responsible implementation are also key themes, ensuring that innovation is balanced with accountability. As AI continues to evolve at an unprecedented pace, mastering OpenAI is no longer optional—it’s essential. The future belongs to those who can effectively leverage these technologies. Don’t get left behind—equip yourself with the expertise needed to stay ahead in the AI revolution. WHAT WILL YOU LEARN ● Gain expertise in OpenAI’s models, APIs, and enterprise applications ● Build intelligent chatbots and virtual assistants using ChatGPT ● Implement ethical AI practices for responsible and fair deployment ● Optimize and deploy OpenAI models for scalable business solutions ● Analyze real-world case studies to drive AI-powered innovation ● Leverage generative AI to automate, enhance, and transform workflows WHO IS THIS BOOK FOR? This book is tailored for both beginners and experienced professionals looking to harness the power of OpenAI. Ideal for application architects, developers, AI engineers, CTOs, and technology leaders, it provides the essential knowledge and hands-on skills needed to integrate OpenAI solutions into enterprise applications effectively. TABLE OF CONTENTS 1. OpenAI Primer 2. Deep Learning, Transformers, and OpenAI Tools 3. Natural Language Processing with GPTs 4. Computer Vision with DALL-E and CLIP 5. Building Chatbots with ChatGPT 6. AI Ethics and Responsible AI 7. Deploying OpenAI Models 8. Case Studies and Best Practices Appendix. Retrieval-Augmented Generation (RAG) Index