Practical Generative AI Engineering with LangChain and LlamaIndex: Building Production-Ready LLM Applications RAG Systems

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. >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!