Overview

This book is a project-focused guide for developers who want to move beyond toy examples and create working AI systems. Inside you will find step by step projects to build AI chatbots with LangChain, retrieval augmented generation pipelines, customer support bots, research assistants, and more. Across fifteen complete builds you will learn how to design LangChain agents projects that combine tools, memory, and vector stores. Each project is written in clear Python, with fully explained code examples that show exactly how to connect LangChain applications with Python to real data sources. You will see how to integrate LangChain and vector databases to create production ready retrieval systems, how to apply prompt engineering Python LangChain techniques for reliable outputs, and how to design autonomous AI applications LangChain that can coordinate tasks and work across multiple services. This handbook is structured to help you learn by doing. Early chapters cover beginner friendly projects showing LangChain agents in action, while later builds introduce more advanced workflows such as multi-agent collaboration, financial data analysis, and deployment with FastAPI and Docker. Every project is designed to be runnable out of the box and adaptable to your own needs. Whether your goal is to understand retrieval augmented generation RAG LangChain techniques, build AI agents with LangChain for production environments, or simply add real AI applications to your developer portfolio, this book provides the practical tutorials for developers working with LangChain agents that you need. By the end you will have not only learned LangChain but also built a complete set of AI applications that demonstrate your skills

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