**LangChain and Generative AI with LangGraph** is a practical guide to building modern AI applications using Large Language Models (LLMs), Generative AI, LangChain, and LangGraph.

This book takes you from the fundamentals of Generative AI and LLMs to advanced concepts such as Prompt Engineering, embeddings, vector databases, Retrieval-Augmented Generation (RAG), tool calling, AI agents, memory, workflows, and multi-step agentic applications.

You will learn how LangChain can be used to connect LLMs with tools, documents, databases, APIs, and external services. You will also explore LangGraph for creating stateful, reliable, and controllable AI agent workflows.

The book covers:

• Generative AI and Large Language Models (LLMs)
• Prompt Engineering and effective prompting techniques
• LangChain fundamentals and LLM integration
• Chat models, prompts, chains, tools, and structured outputs
• Embeddings and vector databases
• Retrieval-Augmented Generation (RAG) applications
• Document loading, splitting, indexing, and retrieval
• Tool calling and external API integration
• AI Agents and Agentic AI
• LangGraph architecture and state-based workflows
• Human-in-the-loop AI applications
• Memory and persistent agent workflows
• Multi-step and multi-agent systems
• Practical Generative AI and AI Agent projects

With practical examples and project-oriented learning, this book is designed for students, developers, software engineers, trainers, and AI enthusiasts who want to move beyond basic chatbot development and build real-world LLM-powered applications.

Whether you are starting with Generative AI or looking to advance your skills in LangChain and LangGraph, this book provides a structured path toward developing modern, intelligent, and agentic AI applications.