Practical Generative AI Engineering with LangChain and LlamaIndex: Building Production-Ready LLM Applications and RAG Systems
English | May 27, 2026 | ASIN: B0H34WVK4B | 337 pages | Epub | 306.97 KB
Tired of theoretical Generative AI discussions and grappling with the complexities of building robust, production-grade LLM applications? Are you struggling to move beyond simple prompt engineering to truly leverage the power of LangChain and LlamaIndex for RAG systems and real-world deployment? The gap between exciting LLM capabilities and practical, scalable engineering solutions can feel vast.In this book you will learn:* How to architect and implement advanced RAG systems combining LangChain and LlamaIndex for superior retrieval and generation.* Practical strategies for building, evaluating, and monitoring LLM applications at scale.* Techniques for optimizing costs, enhancing performance, and ensuring the security of your GenAI solutions.* Best practices for ethical considerations and responsible AI development in your projects.* Hands-on methods for deploying LLM workflows into production environments with confidence.* Master advanced prompt engineering, agentic systems, and output parsing with LangChain.Who this book is for: This book is meticulously crafted for mid-to-senior level Machine Learning Engineers, Data Scientists, and Software Developers eager to transition from experimental LLM projects to stable, efficient, and impactful production systems.What's inside: This guide walks you through the journey from understanding core GenAI concepts to implementing advanced solutions, following a clear Problem→Realisation→Solution→Outcome structure. Every technical concept is reinforced with practical code examples available in the companion GitHub repository.Elevate your Generative AI engineering skills. Transform your LLM concepts into production-ready reality-order your copy today!
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