Ai Agent Pydanticai
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Ai Agent Pydanticai
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Author : อนุชิต ชโลธร
language : th
Publisher: สำนักพิมพ์ก๊อปวาง
Release Date :
Ai Agent Pydanticai written by อนุชิต ชโลธร and has been published by สำนักพิมพ์ก๊อปวาง this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
เปลี่ยนไอเดียในหัว...ให้กลายเป็น AI Agent ที่ใช้งานได้จริง! ในยุคที่ Generative AI และ Large Language Models (LLMs) กำลังเปลี่ยนแปลงโลก, นักพัฒนาทุกคนต่างมองหาเครื่องมือที่จะช่วยสร้างแอปพลิเคชันอัจฉริยะได้อย่างรวดเร็วและมีประสิทธิภาพ แต่ความท้าทายสำคัญคือการจัดการกับผลลัพธ์จาก LLM ที่มักจะ "ไร้ระเบียบ" และนำไปใช้งานต่อได้ยาก PydanticAI คือคำตอบสุดท้าย ที่จะเชื่อมโลกของ AI ที่ยืดหยุ่นเข้ากับโลกของซอฟต์แวร์ที่ต้องการความแม่นยำและโครงสร้างที่ชัดเจน หนังสือเล่มนี้ไม่ใช่แค่คู่มือการใช้ไลบรารี แต่เป็น "ตำราอาหาร" (Cookbook) ที่รวบรวม "สูตรสำเร็จ" สำหรับการสร้าง AI Agent ในทุกสถานการณ์ที่คุณต้องเจอ ตั้งแต่พื้นฐานจนถึงระดับโปรดักชัน สิ่งที่คุณจะได้เรียนรู้จากหนังสือเล่มนี้ - เริ่มต้นอย่างมั่นคง: ทำความเข้าใจปัญหาของ LLM และเรียนรู้ว่า PydanticAI เข้ามาแก้ปัญหาได้อย่างไร พร้อมสร้าง Agent ตัวแรกของคุณในไม่กี่นาที - เครื่องมือครบมือ: สร้าง Tools ให้ Agent ของคุณสามารถเชื่อมต่อกับ API ภายนอก, ทำงานกับฐานข้อมูล (SQL) หรือแม้กระทั่งทำงานร่วมกับ Agent อื่นๆ - สร้าง Chatbot อัจฉริยะ: เรียนรู้วิธีสร้าง Chatbot ที่จดจำบทสนทนาและมีบุคลิก (Persona) ที่น่าสนใจ- ระบบถาม-ตอบ (RAG) จากเอกสารของคุณ: สอนให้ Agent เรียนรู้และตอบคำถามจากข้อมูลเฉพาะทาง, เอกสารภายในองค์กร หรือไฟล์ PDF ของคุณเอง - สถาปัตยกรรมขั้นสูง (Multi-agent & Graphs): ออกแบบระบบที่ซับซ้อนให้ Agent หลายตัวทำงานร่วมกันอย่างเป็นระบบผ่าน Workflow และ Graph - เชื่อมต่อกับโลกภายนอก (A2A & AG-UI Protocols): เรียนรู้มาตรฐานเปิดอย่าง Agent2Agent (A2A) และ Agent-User Interaction (AG-UI) เพื่อให้ Agent ของคุณสามารถสื่อสารกับ Agent อื่นๆ และเชื่อมต่อกับแอปพลิเคชัน Frontend ได้อย่างเป็นระบบ - ทดสอบและประเมินผล: วัดประสิทธิภาพของ Agent อย่างเป็นวิทยาศาสตร์ด้วย pydantic-evals เพื่อให้มั่นใจในคุณภาพก่อนนำไปใช้งานจริง - Monitoring และ Debug: ติดตามการทำงานของ Agent ทุกฝีก้าวด้วย Logfire และ OpenTelemetry เพื่อหาจุดบกพร่องได้อย่างรวดเร็ว - นำไปใช้งานจริง (Deployment): เรียนรู้วิธีการ Deploy Agent ของคุณในรูปแบบต่างๆ ทั้ง API ด้วย FastAPI, เว็บแอปด้วย Streamlit และ CLI ไม่ว่าคุณจะเป็นนักพัฒนาที่เพิ่งก้าวเข้าสู่โลกของ AI หรือวิศวกรที่ต้องการยกระดับการสร้าง AI Application ให้เป็นระบบและพร้อมสำหรับสเกลใหญ่ หนังสือเล่มนี้คือเข็มทิศที่จะนำทางคุณไปสู่การเป็นมืออาชีพด้านการสร้าง AI Agent ได้อย่างแน่นอน พร้อมหรือยังที่จะเปลี่ยน "Prompt" ให้กลายเป็น "Product"? หยิบหนังสือเล่มนี้แล้วเริ่มสร้างสรรค์ผลงานที่น่าทึ่งไปพร้อมกัน!
Hands On Apis For Ai And Data Science
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Author : Ryan Day
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-03-04
Hands On Apis For Ai And Data Science written by Ryan Day and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-04 with Computers categories.
To succeed in AI and data science, you must first master APIs. API skills are essential for AI and data science success. With this practical book, data scientists and software developers will gain hands-on experience developing and using APIs with the Python programming language and popular frameworks like FastAPI and StreamLit. Part 1 takes you step-by-step through coding projects to build APIs using Python and FastAPI and deploy them in the cloud. Part 2 teaches you to consume APIs in a data science project using industry-standard tools. And in Part 3, you'll use ChatGPT, the LangChain framework, and other tools to access your APIs with generative AI and large language models (LLMs). As you complete the chapters in the book, you'll be creating a professional online portfolio demonstrating your new skill with APIs, AI, and data science. You'll learn how to: Design APIs that data scientists and AIs love Develop APIs using Python and FastAPI Deploy APIs using multiple cloud providers Create data science projects such as visualizations and models using APIs as a data source Access APIs using generative AI and LLMs Author Ryan Day is a data scientist in the financial services industry and an open source developer.
Case Based Reasoning Research And Development
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Author : Isabelle Bichindaritz
language : en
Publisher: Springer Nature
Release Date : 2025-06-29
Case Based Reasoning Research And Development written by Isabelle Bichindaritz and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-29 with Computers categories.
This book constitutes the refereed proceedings of the 33rd International Conference on Case-Based Reasoning Research and Development, ICCBR 2025, held in Biarritz, France, during June 30–July 3, 2025. The 30 full papers presented in this volume were carefully reviewed and selected from 81 submissions. The book also contains one invited talk in full-paper lenght. The papers are grouped into the following topical sections: Invited Talk; CBR and Generative AI Synergies; Theoretical or Methodological CBR Research; and Applied CBR Research.
Ai Agents In Action
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Author : Micheal Lanham
language : en
Publisher: Simon and Schuster
Release Date : 2025-03-25
Ai Agents In Action written by Micheal Lanham and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-25 with Computers categories.
In AI Agents in Action, you'll learn how to build production-ready assistants, multi-agent systems, and behavioral agents. You'll master the essential parts of an agent, including retrieval-augmented knowledge and memory, while you create multi-agent applications that can use software tools, plan tasks autonomously, and learn from experience. As you explore the many interesting examples, you'll work with state-of-the-art tools like OpenAI Assistants API, GPT Nexus, LangChain, Prompt Flow, AutoGen, and CrewAI.
Intro Guide To Concept Of Ai Agent
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Author : Barron Wilson
language : en
Publisher: Estalontech
Release Date : 2025-06-06
Intro Guide To Concept Of Ai Agent written by Barron Wilson and has been published by Estalontech this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-06 with Computers categories.
So you want to know what AI agents are all about? Great! Think of this as your friendly, easy-to-digest intro to one of the most exciting trends in tech today — no jargon, no complicated theories, just simple ideas and real-world examples. An AI Agent isn’t just a chatbot or a bot that follows strict rules. It’s more like a smart assistant that can understand your goals, make plans, use tools, and even adapt when things don’t go as expected. Imagine telling an AI: “Find me the best flight to London next week,” and it actually figures out how to do that using different websites, compares prices, checks for availability, and books it — all on its own. That’s the power of an AI agent. This guide breaks everything down into bite-sized pieces so anyone can understand. You’ll learn: What makes an AI agent different from regular bots How they work behind the scenes — think of them having a brain (powered by large language models), a toolkit (like APIs, apps, databases), memory, and a rulebook (your instructions). Real-life examples , like AI assistants handling customer service or helping coders debug software. How to start experimenting with automation using visual tools like n8n, Zapier, or Make — no coding required! Important safety tips — because building smart systems also means thinking about ethics, privacy, and responsibility. One of the coolest parts is seeing how multiple AI agents can work together like a team. Just like humans divide up tasks, AI agents can split up complex problems, help each other out, and get things done faster and smarter. The guide also gives you a peek into the future — where you can start building your own AI agents using development kits from big companies like Google. But here’s the key advice: start simple . Don’t jump into complex systems unless you really need to. Often, a clear instruction or a basic workflow is all you need. And if you're inspired and want to go further, the book recommends diving into "AI Agents Made Easy" — a hands-on guide to building your own digital helpers using no-code tools. In short, this pocket guide is perfect for beginners who want to understand AI agents, see how they can change the way we work, and take the first step toward building their own. Whether you're a business owner, student, or just plain curious, this is your doorway into the future of AI — and it's already here.
Ai Agents In Practice
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Author : Valentina Alto
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-08-28
Ai Agents In Practice written by Valentina Alto and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-28 with Computers categories.
Master the art of building AI agents with this hands-on guide to orchestration, multi-agent systems, real-world case studies, and ethical insights to drive immediate business impact Key Features Build production-ready AI agents with hands-on tutorials for diverse industry applications Explore multi-agent system architectures with practical frameworks for orchestrator comparison Future-proof your AI development with ethical implementation strategies and security patterns Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAs AI agents evolve to take on complex tasks and operate autonomously, you need to learn how to build these next-generation systems. Author Valentina Alto brings practical, industry-grounded expertise in AI Agents in Practice to help you go beyond simple chatbots and create AI agents that plan, reason, collaborate, and solve real-world problems using large language models (LLMs) and the latest open-source frameworks. In this book, you'll get a comparative tour of leading AI agent frameworks such as LangChain and LangGraph, covering each tool's strengths, ideal use cases, and how to apply them in real-world projects. Through step-by-step examples, you’ll learn how to construct single-agent and multi-agent architectures using proven design patterns to orchestrate AI agents working together. Case studies across industries will show you how AI agents drive value in real-world scenarios, while guidance on responsible AI will help you implement ethical guardrails from day one. The chapters also set the stage with a brief history of AI agents, from early rule-based systems to today's LLM-driven autonomous agents, so you understand how we got here and where the field is headed. By the end of this book, you'll have the practical skills, design insights, and ethical foresight to build and deploy AI agents that truly make an impact.What you will learn Build core agent components such as LLMs, memory systems, tool integration, and context management Develop production-ready AI agents using frameworks such as LangChain with code Create effective multi-agent systems using orchestration patterns for problem-solving Implement industry-specific agents for e-commerce, customer support, and more Design robust memory architectures for agents with short- and long-term recall Apply responsible AI practices with monitoring, guardrails, and human oversight Optimize AI agent performance and cost for production environments Who this book is for This book is ideal for AI engineers and data scientists looking to move beyond basic LLM implementations to build sophisticated autonomous agents. Software developers and system architects will find practical guidelines for integrating agents into existing tech stacks. Product managers and technical entrepreneurs will gain strategic insights into how AI agents can solve business problems across industries. A basic understanding of machine learning concepts and working knowledge of Python are required to make the most of this book and implement production-ready AI agent systems.
Building Agentic Ai Systems
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Author : Anjanava Biswas
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-04-21
Building Agentic Ai Systems written by Anjanava Biswas and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-21 with Computers categories.
Master the art of building AI agents with large language models using the coordinator, worker, and delegator approach for orchestrating complex AI systems Key Features Understand the foundations and advanced techniques of building intelligent, autonomous AI agents Learn advanced techniques for reflection, introspection, tool use, planning, and collaboration in agentic systems Explore crucial aspects of trust, safety, and ethics in AI agent development and applications Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGain unparalleled insights into the future of AI autonomy with this comprehensive guide to designing and deploying autonomous AI agents that leverage generative AI (GenAI) to plan, reason, and act. Written by industry-leading AI architects and recognized experts shaping global AI standards and building real-world enterprise AI solutions, it explores the fundamentals of agentic systems, detailing how AI agents operate independently, make decisions, and leverage tools to accomplish complex tasks. Starting with the foundations of GenAI and agentic architectures, you’ll explore decision-making frameworks, self-improvement mechanisms, and adaptability. The book covers advanced design techniques, such as multi-step planning, tool integration, and the coordinator, worker, and delegator approach for scalable AI agents. Beyond design, it addresses critical aspects of trust, safety, and ethics, ensuring AI systems align with human values and operate transparently. Real-world applications illustrate how agentic AI transforms industries such as automation, finance, and healthcare. With deep insights into AI frameworks, prompt engineering, and multi-agent collaboration, this book equips you to build next-generation adaptive, scalable AI agents that go beyond simple task execution and act with minimal human intervention.What you will learn Master the core principles of GenAI and agentic systems Understand how AI agents operate, reason, and adapt in dynamic environments Enable AI agents to analyze their own actions and improvise Implement systems where AI agents can leverage external tools and plan complex tasks Apply methods to enhance transparency, accountability, and reliability in AI Explore real-world implementations of AI agents across industries Who this book is for This book is ideal for AI developers, machine learning engineers, and software architects who want to advance their skills in building intelligent, autonomous agents. It's perfect for professionals with a strong foundation in machine learning and programming, particularly those familiar with Python and large language models. While prior experience with generative AI is beneficial, the book covers foundational concepts for those new to agentic systems.
Agentic Ai A Practical Guide To Build Agent Based Ai Systems That Think And Act
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Author : Tejas Patthi
language : en
Publisher: Tejas Patthi
Release Date : 2025-06-30
Agentic Ai A Practical Guide To Build Agent Based Ai Systems That Think And Act written by Tejas Patthi and has been published by Tejas Patthi this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-30 with Computers categories.
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
Introduction To Ai Agents
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Author : Kaelix Draven
language : en
Publisher: Independently Published
Release Date : 2025-04-29
Introduction To Ai Agents written by Kaelix Draven and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-29 with Computers categories.
What exactly is an AI agent? Why do some of them feel smarter than your coworkers, and others can't even figure out how to turn off your living room lights? Welcome to Introduction to AI Agents: Concepts, Types, and Applications-your friendly, slightly sarcastic, surprisingly deep dive into the wild world of intelligent systems that see, think, act, and (sometimes) get confused by the word "weather." This isn't just another dry tech manual. Think of this book as the orientation packet for anyone who wants to truly understand the minds behind machines-told in a way that doesn't make your brain want to stage a walkout. We're breaking down everything from reflex agents and goal-based thinkers to belief systems, decision-making, and how agents survive in environments that are about as predictable as a toddler on espresso. Inside, you'll learn: What makes an agent "intelligent" (and when it's just pretending) How agents interact with their environment-and why they sometimes fail hilariously The difference between simple rule-followers and full-blown learning systems What makes a good architecture for an agent (spoiler: not duct tape) The ethical rabbit holes we tumble into when AI starts making decisions Real-world applications that go beyond "Hey Siri" and into industries like healthcare, robotics, finance, and more Whether you're an AI beginner, a developer ready to dive into agent design, or just someone who wants to sound smart at parties, this book is designed for you. It's the first stop in the Mastering AI Agents: From Theory to Deployment series-a guided journey from foundational theory to full-fledged deployment of AI-powered systems. And trust me, you'll want to stick around. Here's where the path leads next: Building AI Agents with Python: A Hands-on Guide - Code your own digital brain without losing your mind Reinforcement Learning for AI Agents: Training Intelligent Systems - Teach your agents the art of learning from glorious failure Multi-Agent Systems: Coordination, Communication, and Collaboration - What happens when you throw a bunch of agents into a room and tell them to get along AI Agents in the Real World - From smart homes to city-wide systems, this is where the action is And yes, we go niche: AI Agents for Automation, Robotics, Finance, Cybersecurity, and Healthcare-because agents are everywhere now If you've ever wanted to peek inside the mind of an intelligent system, build your own, or just understand what's really going on behind the algorithm, this book will get you there-with clarity, humor, and enough real-world relevance to keep you hooked. So whether you're building the future or just trying to outsmart your smart toaster, consider this your invitation into the world of AI agents. Let's make it smart, make it ethical, and-most importantly-make it fun.
Building Ai Agents With Llms Rag And Knowledge Graphs
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Author : Salvatore Raieli
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-07-11
Building Ai Agents With Llms Rag And Knowledge Graphs written by Salvatore Raieli and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-11 with Computers categories.
Master LLM fundamentals to advanced techniques like RAG, reinforcement learning, and knowledge graphs to build, deploy, and scale intelligent AI agents that reason, retrieve, and act autonomously Key Features Implement RAG and knowledge graphs for advanced problem-solving Leverage innovative approaches like LangChain to create real-world intelligent systems Integrate large language models, graph databases, and tool use for next-gen AI solutions Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThis AI agents book addresses the challenge of building AI that not only generates text but also grounds its responses in real data and takes action. Authored by AI specialists with deep expertise in drug discovery and systems optimization, this guide empowers you to leverage retrieval-augmented generation (RAG), knowledge graphs, and agent-based architectures to engineer truly intelligent behavior. By combining large language models (LLMs) with up-to-date information retrieval and structured knowledge, you'll create AI agents capable of deeper reasoning and more reliable problem-solving. Inside, you'll find a practical roadmap from concept to implementation. You’ll discover how to connect language models with external data via RAG pipelines for increasing factual accuracy and incorporate knowledge graphs for context-rich reasoning. The chapters will help you build and orchestrate autonomous agents that combine planning, tool use, and knowledge retrieval to achieve complex goals. Concrete Python examples built on popular libraries, along with real-world case studies, reinforce each concept and show you how these techniques come together. By the end of this book, you’ll be well-equipped to build intelligent AI agents that reason, retrieve, and interact dynamically, empowering you to deploy powerful AI solutions across industries.What you will learn Learn how LLMs work, their structure, uses, and limits, and design RAG pipelines to link them to external data Build and query knowledge graphs for structured context and factual grounding Develop AI agents that plan, reason, and use tools to complete tasks Integrate LLMs with external APIs and databases to incorporate live data Apply techniques to minimize hallucinations and ensure accurate outputs Orchestrate multiple agents to solve complex, multi-step problems Optimize prompts, memory, and context handling for long-running tasks Deploy and monitor AI agents in production environments Who this book is for If you are a data scientist or researcher who wants to learn how to create and deploy an AI agent to solve limitless tasks, this book is for you. To get the most out of this book, you should have basic knowledge of Python and Gen AI. This book is also excellent for experienced data scientists who want to explore state-of-the-art developments in LLM and LLM-based applications.