Building Agentic Ai With Python And Langgraph
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Building Agentic Ai With Python And Langgraph
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Author : Yuan Zhu
language : en
Publisher: Independently Published
Release Date : 2025-07-07
Building Agentic Ai With Python And Langgraph written by Yuan Zhu and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-07 with Computers categories.
Unlock the power of agentic AI with this definitive, hands-on guide to architecting production-ready intelligent systems using Python, LangGraph, Model Context Protocol (MCP), and RAG 2.0. Unlike traditional AI pipelines, agentic systems leverage stateful reasoning, context-aware memory, tool-driven execution, and dynamic retrieval to deliver autonomous, scalable solutions for real-world applications. Written by Yuan Zhu, this book provides fully executable code, architectural patterns, and best practices to transform you into a master of next-generation AI development. Dive into building modular agents capable of orchestrating complex tasks, from research assistants and customer support agents to compliance tools and autonomous workflows. You'll learn to design LangGraph-based reasoning pipelines with stateful control flows, integrate secure tools with validated I/O and retries, and implement advanced RAG 2.0 retrieval with metadata filtering, hybrid ranking, and source traceability. Explore multi-agent collaboration with role-based systems, shared memory, and message-passing, while embedding safety critics and constitutional reasoning for reliable, ethical outputs. This isn't just theory it's a practical engineering blueprint packed with complete Python code, FastAPI deployment scripts, Docker containerization, CI/CD pipelines, and real-time observability. From modular MCP context injectors for dynamic memory routing to scalable agent architectures, every chapter equips you with the tools to build production-ready AI systems that excel in performance, safety, and scalability. What You'll Master: Architect LangGraph workflows for dynamic reasoning and task orchestration Build secure tool integrations with robust error handling and fallback logic Implement MCP for context-aware memory and user profiling Create RAG 2.0 pipelines with metadata-driven retrieval and low-latency ranking Design multi-agent systems with role separation and shared memory coordination Embed safety guardrails and constitutional reasoning for auditable outputs Deploy production-grade agents with FastAPI, Docker, and real-time metrics Whether you're a developer, data scientist, or AI engineer, this book delivers step-by-step implementations to take your agentic AI projects from prototype to production. Build intelligent systems that reason, adapt, and scale-your blueprint for mastering agentic AI starts here.
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 Free with your book: PDF Copy, AI Assistant, and Next-Gen Reader 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 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 With Langchain Langgraph
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Author : Elliot R Stroud
language : en
Publisher: Independently Published
Release Date : 2025-11-18
Agentic Ai With Langchain Langgraph written by Elliot R Stroud and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-18 with Computers categories.
Unlock the power of agentic AI and start building systems that think, reason, and collaborate. This practical guide shows you exactly how to design intelligent, reliable, and scalable multi-agent applications using LangChain, LangGraph, and Python. Whether you are a developer, data engineer, researcher, or AI enthusiast, this book gives you the tools and patterns needed to build production-grade LLM systems that deliver real results. You will learn how to create autonomous agents that can plan, retrieve information, call tools, work together, and execute complex tasks with minimal human intervention. Each concept is explained clearly and supported with step-by-step examples you can use immediately. From designing your first agent to deploying advanced RAG architectures and fault-tolerant workflows, this guide removes the guesswork and puts modern agentic AI in your hands. Inside this book, you will discover: 1. How agentic AI works and why it is transforming automation, AI engineering, and product development 2. The exact process for building intelligent agents with LangChain, LangGraph, and Python 3. Proven multi-agent patterns, collaboration strategies, and workflow designs that scale in real applications 4. Essential RAG techniques for grounding your agents in reliable, up-to-date information 5. Error handling, memory design, state management, tool calling, routing, and workflow orchestration 6. Architectures that prevent hallucination, reduce failure, and keep agents aligned with your goals 7. Hands-on projects you can build and deploy, including research copilots, AI workflows, knowledge assistants, and autonomous task agents 8. Optimization, monitoring, debugging, and performance best practices for production-ready systems Whether you want to streamline workflows, automate complex tasks, build intelligent assistants, or engineer the next generation of AI-powered products, this book gives you the clarity, confidence, and practical skills to make it happen. If you are ready to move beyond simple chatbots and into real agentic engineering, this is the guide that will take you there.
A Beginner S Adventure Into Generative Ai
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Author : Kranti Kumar Appari
language : en
Publisher: JEC PUBLICATION
Release Date :
A Beginner S Adventure Into Generative Ai written by Kranti Kumar Appari and has been published by JEC PUBLICATION this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
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Mastering Agentic Ai
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Author : Rowan J Ashford
language : en
Publisher: Independently Published
Release Date : 2025-10-05
Mastering Agentic Ai written by Rowan J Ashford and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-05 with Computers categories.
Unlock the future of intelligent automation with Mastering Agentic AI, your comprehensive guide to designing, developing, and deploying autonomous AI agents that reason, adapt, and execute with unparalleled efficiency. This practical engineering manual dives deep into Python-powered agentic workflows using LangGraph for stateful reasoning, RAG 2.0 for dynamic retrieval-augmented generation, and Modular Context Protocols (MCP) for seamless memory management. Whether you're crafting research assistants, compliance auditors, customer support bots, or enterprise-grade autonomous pipelines, this book equips you with executable code, architectural blueprints, and battle-tested best practices to transition from prototypes to production-ready intelligent systems. Explore the core of agentic AI: from foundational LangGraph graphs for task orchestration and cyclic reasoning loops to advanced RAG 2.0 implementations featuring metadata filtering, hybrid semantic ranking, and traceable source attribution. Master secure tool integrations with Python automation scripts, robust error handling, retry mechanisms, and fallback strategies for real-world reliability. Delve into multi-agent collaboration frameworks with role-based hierarchies, shared memory pools, message-passing protocols, and constitutional AI guardrails to ensure ethical, auditable outputs. You'll build scalable architectures incorporating MCP for context-aware user profiling, dynamic memory injection, and low-latency inference, all while embedding safety critics for bias detection and compliance enforcement. This isn't abstract theory-it's a deployable toolkit loaded with complete Python codebases, FastAPI microservices, Docker containerization recipes, CI/CD automation pipelines, and real-time observability dashboards using Prometheus and Grafana. From single-agent prototypes to distributed multi-agent swarms, every chapter delivers step-by-step tutorials on optimizing performance, enhancing scalability, and mitigating risks in agentic ecosystems. Ideal for Python developers, AI engineers, data scientists, and DevOps specialists, Mastering Agentic AI transforms complex concepts into actionable intelligence. Harness the power of autonomous agents to automate workflows, amplify decision-making, and drive innovation-your journey to agentic mastery begins now.
Build Ai Agents With Python
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Author : Eidan Crest
language : en
Publisher: Independently Published
Release Date : 2025-11-17
Build Ai Agents With Python written by Eidan Crest and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-17 with Computers categories.
AI has changed-but tutorials haven't. Most guides stop at simple chatbots and ignore what developers really need today: agentic AI Python skills-how to design, build, and ship intelligent systems that plan, act, call tools, and integrate with real-world workflows. If you're a developer trying to build AI agents that go beyond text replies and actually perform tasks, you've probably felt the gap: fragmented resources, partial examples, and no clear path from prototype to production. This book closes that gap. It is your complete, end-to-end AI agent orchestration and engineering playbook-focused on real-world Python automation AI and modern frameworks. If you want to become the developer who can design, implement, and ship serious AI systems, this is the guide you've been looking for. With this book, you will: Master the core patterns of agent engineering - reasoning loops, planning, memory, tools, safety, and governance, all implemented in clean, production-ready agentic AI Python code. Build practical, real-world projects - from single agents to complex multi agent systems Python architectures that collaborate, debate, and delegate work. Learn LangGraph the right way - with a hands-on, step-by-step LangGraph tutorial that shows you how to model nodes, edges, and state for research, coding, and document workflows. Use Autogen in real scenarios - not just basic demos, but a full Autogen Python guide that walks you through interdependent agents, conversational loops, human-in-the-loop approvals, and safe execution. Turn your data into intelligence with LlamaIndex - build robust LlamaIndex RAG agents that index documents, perform retrieval-augmented generation, and plug cleanly into your wider agent ecosystem. Engineer powerful Python tool-calling agents - design and implement Python tool calling agents that interact with APIs, databases, files, browsers, and OS-level tools using structured, validated functions. Automate real workflows, not just prompts - build full AI workflow automation systems that handle research, reporting, coding, web tasks, and business operations from end to end. Deploy with confidence - apply best practices for testing, evaluation, monitoring, and AI agent orchestration using FastAPI, Docker, serverless platforms, and observability tooling. Whether you're a software engineer, data scientist, ML engineer, indie hacker, or technical founder, this book gives you the skills and patterns to move beyond simple scripts and into robust, scalable Python automation AI systems that deliver real value.
Mastering Langchain And Agentic Ai Systems
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Author : Finn Cordex
language : en
Publisher: Independently Published
Release Date : 2025-11-05
Mastering Langchain And Agentic Ai Systems written by Finn Cordex and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-05 with Computers categories.
Step into the future of artificial intelligence - where LLMs think, plan, and act autonomously. In Mastering LangChain and Agentic AI Systems (2025 Edition), Finn Cordex takes you beyond prompts and chatbots to teach you how to design, build, and deploy intelligent agent systems that learn, retrieve, and reason on their own. This hands-on developer's guide demystifies the new AI stack - from LangChain and LangGraph to OpenAI, RAG pipelines, and autonomous workflows - showing you how to connect these tools into cohesive, production-ready applications.
Llm Design Patterns
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Author : Ken Huang
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-05-30
Llm Design Patterns written by Ken Huang 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 2025-05-30 with Computers categories.
Explore reusable design patterns, including data-centric approaches, model development, model fine-tuning, and RAG for LLM application development and advanced prompting techniques Free with your book: PDF Copy, AI Assistant, and Next-Gen Reader Key Features Learn comprehensive LLM development, including data prep, training pipelines, and optimization Explore advanced prompting techniques, such as chain-of-thought, tree-of-thought, RAG, and AI agents Implement evaluation metrics, interpretability, and bias detection for fair, reliable models Book DescriptionThis practical guide for AI professionals enables you to build on the power of design patterns to develop robust, scalable, and efficient large language models (LLMs). Written by a global AI expert and popular author driving standards and innovation in Generative AI, security, and strategy, this book covers the end-to-end lifecycle of LLM development and introduces reusable architectural and engineering solutions to common challenges in data handling, model training, evaluation, and deployment. You’ll learn to clean, augment, and annotate large-scale datasets, architect modular training pipelines, and optimize models using hyperparameter tuning, pruning, and quantization. The chapters help you explore regularization, checkpointing, fine-tuning, and advanced prompting methods, such as reason-and-act, as well as implement reflection, multi-step reasoning, and tool use for intelligent task completion. The book also highlights Retrieval-Augmented Generation (RAG), graph-based retrieval, interpretability, fairness, and RLHF, culminating in the creation of agentic LLM systems. By the end of this book, you’ll be equipped with the knowledge and tools to build next-generation LLMs that are adaptable, efficient, safe, and aligned with human values. What you will learn Implement efficient data prep techniques, including cleaning and augmentation Design scalable training pipelines with tuning, regularization, and checkpointing Optimize LLMs via pruning, quantization, and fine-tuning Evaluate models with metrics, cross-validation, and interpretability Understand fairness and detect bias in outputs Develop RLHF strategies to build secure, agentic AI systems Who this book is for This book is essential for AI engineers, architects, data scientists, and software engineers responsible for developing and deploying AI systems powered by large language models. A basic understanding of machine learning concepts and experience in Python programming is a must.
Langgraph Engineering With Python
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Author : Zhao Colton
language : en
Publisher: Independently Published
Release Date : 2025-11-24
Langgraph Engineering With Python written by Zhao Colton and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-24 with Computers categories.
LangGraph Engineering with Python is a comprehensive, technical deep dive into modern agentic AI engineering. Written for developers, AI practitioners, and automation architects, this book demystifies LangGraph the groundbreaking framework for building deterministic, controllable, and high-performance AI agent workflows. This book guides you through a complete mastery path: from foundational graph-based reasoning patterns to advanced multi-agent coordination, persistent memory systems, event-driven tasks, and production-grade orchestration. You will learn to construct fully autonomous agents using Python, integrate structured state machines, optimize tool-calling reliability, and design scalable pipelines suitable for enterprise environments. This book goes far beyond "how LangGraph works" and instead teaches how to engineer real AI systems systems with predictable behavior, safe execution boundaries, robust error handling, and modular graph architectures. Whether you're building retrieval-augmented agents, workflow-aware copilots, multimodal systems, or operational AI automation engines, this guide gives you the practical patterns, best practices, and engineering blueprints necessary to deploy at scale. This is the definitive technical handbook for anyone serious about mastering LangGraph in a Python-driven ecosystem.
Ai Revolution Research Ethics And Society
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Author : Hamid R. Arabnia
language : en
Publisher: Springer Nature
Release Date : 2026-01-01
Ai Revolution Research Ethics And Society written by Hamid R. Arabnia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-01 with Computers categories.
This book constitutes the proceedings of the International conference on AI Revolution: Research, Ethics and Society, AIR-RES 2025, held in Las Vegas, Navada, USA, during April 14–16, 2025. The AIR-RES Conference received 620 submissions, of which 131 papers were accepted, resulting in a paper acceptance rate of 21%.