Overview

Generative AI with LangChain for Beginners: Build Smart AI Agents, RAG Systems, and Real-World LLM Applications with Practical Python Tutorials Overview This book is a practical, beginner-friendly guide to building real-world generative AI applications using LangChain and Python. It introduces you to the core ideas behind large language models and shows you how to move beyond simple prompts to create intelligent systems that reason, retrieve information, use tools, and operate reliably in production. Rather than focusing on theory alone, the book emphasizes hands-on learning and clear explanations that help you understand how modern AI applications actually work. You will learn how to design AI agents, build Retrieval-Augmented Generation systems, manage memory and tools, evaluate outputs, optimize performance, and deploy scalable applications. Each concept builds naturally on the previous one, making the learning journey smooth and confidence-building, even if you are new to LangChain or generative AI. The book starts by explaining how generative AI and LangChain fit together, then gradually guides you into building increasingly capable applications. You explore prompt design, chains, tools, and memory before moving into advanced topics like agent workflows, graph-based control, observability, evaluation, and cost optimization. Later chapters focus on deployment, security, monitoring, and real-world project walkthroughs that mirror production use cases. By the end, you are able to design, build, evaluate, and deploy complete AI systems with confidence using Python. Key Features of This Book This book focuses on practical, step-by-step learning using real examples that reflect how AI is used in professional environments. It covers AI agents, RAG pipelines, vector databases, observability with LangSmith, performance tuning, and deployment strategies. The content follows a clear progression from beginner concepts to production-ready applications, with an emphasis on clean design, reliability, and scalability. All tutorials are written in Python and aligned with modern LangChain workflows. Target Audience This book is ideal for beginners who want to enter generative AI development, Python developers looking to build LLM-powered applications, data engineers and software engineers exploring AI systems, and technical professionals who want a clear and practical introduction to LangChain, AI agents, and RAG systems. No advanced AI background is required, only basic Python knowledge and curiosity. If you want to stop experimenting with isolated prompts and start building real, reliable AI applications, this book is your guide. Dive in and learn how to design, build, and deploy intelligent generative AI systems with LangChain and Python one practical step at a time.

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