Practical Guide To Building Agents

Agentic AI:A Practical Guide to Build Agent-Based AI Systems That Think and Act

Build real-world AI systems that do more than just respond. They think, plan, and act with purpose. Agentic AI is a comprehensive, hands-on guide to building autonomous AI agents using Python, large language models (LLMs), LangGraph, CrewAI, FAISS, and other modern tools. Whether you are an AI developer, a machine learning engineer, or a tech enthusiast, this book will help you move beyond simple chatbots and prompt-based models into the advanced world of intelligent, agent-based systems that function independently and handle real tasks. In this step-by-step guide, you’ll learn how to build LLM-powered autonomous agents capable of reasoning, tool use, memory recall, and multi-step task execution. From integrating with real-world APIs to deploying production-ready agent workflows, you'll gain the skills to create powerful and reliable agentic AI systems using today's top frameworks and best practices. 🔍 What You Will Learn: How to build autonomous AI agents that work independently without constant human input How to create agents with long-term memory using vector databases like FAISS and Chroma How to orchestrate multi-agent systems using frameworks like LangGraph and CrewAI How to integrate AI with external tools, APIs, and web services How to use Python to script smart agent behaviors and decision-making logic How to deploy agentic systems in cloud environments or containers with live monitoring How to implement agent safety, performance testing, and real-time feedback loops 💡 Why This Book Is Different: This is not just another theoretical AI book. Agentic AI is a project-based, code-driven manual that gives you everything you need to: Build tool-using AI assistants, copilots, and multi-agent task managers Use LangChain, LangGraph, CrewAI, and LLM toolchains effectively Combine LLMs with real-time data, plugins, memory, and feedback systems Design and deploy goal-driven AI agents with full autonomy and context awareness Stay ahead in the fast-evolving field of agent-based AI and LLM integration 🧠 Tools and Technologies Covered: Python 3.x LangGraph & LangChain CrewAI & OpenAgents ChromaDB & FAISS for memory OpenAI, Claude, Gemini, HuggingFace APIs FastAPI, Docker, REST APIs, and Webhooks Autonomous task chaining, multi-agent routing, and smart tool use 📦 Who Should Read This Book? AI Engineers ready to move beyond static models Python Developers exploring LLMs and autonomous systems Tech founders building smart assistants and AI copilots Data Scientists interested in real-world AI deployment Prompt engineers ready to level up into full-stack AI workflows

Constructing Intelligent Agents Using Java

A state-of-the-art guide on how to build intelligent Web-based applications using Java Joseph and Jennifer Bigus update and significantly expand their book on building intelligent Web-based applications using Java. Geared to network programmers or Web developers who have previously programmed agents in Smalltalk or C++, this practical book explains in detail how to construct agents capable of learning and competing, including both design principles and actual code for personal agents, network or Web agents, multi-agent systems and commercial agents. New and revised coverage includes agent tools, agent uses for Web applications (including personalization, cross-selling, and e-commerce), and additional AI technologies such as fuzzy logic and genetic algorithms.

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