**Generative AI and LangGraph with Agentic AI** is a practical guide to building modern AI applications using Large Language Models (LLMs), Generative AI, LangChain, LangGraph, Retrieval-Augmented Generation (RAG), and AI Agents.

This book takes you from the fundamentals of Generative AI and LLMs to the development of intelligent, tool-using, and workflow-driven AI agents. You will learn how to connect LLMs with external tools, manage multi-step workflows, build stateful agent systems, implement RAG pipelines, and create applications capable of reasoning and taking actions.

The book covers important concepts including prompt engineering, LLM application development, embeddings, vector databases, document processing, RAG, tool calling, structured outputs, memory, agent workflows, LangChain, LangGraph, human-in-the-loop systems, persistence, and multi-agent architectures.

Through practical examples and projects, you will learn how to design and develop Agentic AI applications that can automate tasks, interact with external tools, process information, and make decisions based on defined workflows.

**Key Topics Covered:**

• Generative AI and Large Language Models (LLMs)
• Prompt Engineering and LLM Application Development
• LangChain Fundamentals
• LangGraph Architecture and Workflows
• AI Agents and Agentic AI
• Tool Calling and Function Calling
• Retrieval-Augmented Generation (RAG)
• Embeddings and Vector Databases
• Document-Based Question Answering
• Memory and Stateful AI Applications
• Human-in-the-Loop AI Systems
• Persistence and Checkpointing
• Multi-Agent Systems and Agent Workflows
• Autonomous AI Task Automation
• Practical Generative AI and Agentic AI Projects

Whether you are a student, developer, software professional, AI enthusiast, or educator, this book provides a practical foundation for understanding and developing next-generation AI applications using Generative AI, LangGraph, and Agentic AI technologies.