Practical Generative AI Engineering with LangChain and LlamaIndex: Building Production-Ready LLM Applications and RAG Systems (The AI Architect Series)

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!