Ai Agents In Langgraphh Demystified
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Ai Agents In Langgraphh Demystified
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Author : Robert M Tolbert
language : en
Publisher: Independently Published
Release Date : 2025-03-16
Ai Agents In Langgraphh Demystified written by Robert M Tolbert and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-16 with Computers categories.
AI Agents in LangGraph Demystified: Building Smarter, Connected Systems Are you ready to build AI agents that think, reason, and collaborate seamlessly? Artificial intelligence is evolving rapidly, and AI agents are at the forefront of this transformation. From chatbots and virtual assistants to autonomous systems and decision-making networks, AI agents are revolutionizing industries. But how do you build intelligent, scalable, and efficient agents that interact seamlessly? This book provides the answers. What This Book Covers AI Agents in LangGraph Demystified is your hands-on guide to understanding, designing, and deploying AI agents using LangGraph-a powerful framework for constructing graph-based, multi-agent systems. You'll explore core principles, architectures, real-world applications, and cutting-edge innovations that will help you build smarter, more connected AI solutions. What Makes This Book Different? Comprehensive yet Practical - Covers both the theory and real-world implementation of AI agents, with extensive hands-on examples. Code-Driven Learning - Provides step-by-step code snippets to build, test, and deploy AI agents efficiently. Scalability and Optimization - Learn how to handle complex workflows, scale multi-agent systems, and optimize for performance. Security and Ethics - Understand the challenges of AI governance, bias mitigation, and secure agent interactions. Future-Proof Strategies - Explore emerging trends such as AI agent collaboration, edge deployment, and real-time decision-making. Who Should Read This Book? AI developers and data scientists looking to implement multi-agent AI systems. Engineers and architects building scalable and secure AI workflows. Entrepreneurs and innovators eager to explore real-world AI agent applications. Researchers and students interested in the future of AI-driven automation. If you're looking to master AI agent development and stay ahead of the curve, this book is for you. Start building smarter, autonomous systems today!
Generative Ai With Langchain
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Author : Ben Auffarth
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-05-23
Generative Ai With Langchain written by Ben Auffarth 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 2025-05-23 with Computers categories.
Go beyond foundational LangChain documentation with detailed coverage of LangGraph interfaces, design patterns for building AI agents, and scalable architectures used in production—ideal for Python developers building GenAI applications Key Features Bridge the gap between prototype and production with robust LangGraph agent architectures Apply enterprise-grade practices for testing, observability, and monitoring Build specialized agents for software development and data analysis Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThis second edition tackles the biggest challenge facing companies in AI today: moving from prototypes to production. Fully updated to reflect the latest developments in the LangChain ecosystem, it captures how modern AI systems are developed, deployed, and scaled in enterprise environments. This edition places a strong focus on multi-agent architectures, robust LangGraph workflows, and advanced retrieval-augmented generation (RAG) pipelines. You'll explore design patterns for building agentic systems, with practical implementations of multi-agent setups for complex tasks. The book guides you through reasoning techniques such as Tree-of -Thoughts, structured generation, and agent handoffs—complete with error handling examples. Expanded chapters on testing, evaluation, and deployment address the demands of modern LLM applications, showing you how to design secure, compliant AI systems with built-in safeguards and responsible development principles. This edition also expands RAG coverage with guidance on hybrid search, re-ranking, and fact-checking pipelines to enhance output accuracy. Whether you're extending existing workflows or architecting multi-agent systems from scratch, this book provides the technical depth and practical instruction needed to design LLM applications ready for success in production environments.What you will learn Design and implement multi-agent systems using LangGraph Implement testing strategies that identify issues before deployment Deploy observability and monitoring solutions for production environments Build agentic RAG systems with re-ranking capabilities Architect scalable, production-ready AI agents using LangGraph and MCP Work with the latest LLMs and providers like Google Gemini, Anthropic, Mistral, DeepSeek, and OpenAI's o3-mini Design secure, compliant AI systems aligned with modern ethical practices Who this book is for This book is for developers, researchers, and anyone looking to learn more about LangChain and LangGraph. With a strong emphasis on enterprise deployment patterns, it’s especially valuable for teams implementing LLM solutions at scale. While the first edition focused on individual developers, this updated edition expands its reach to support engineering teams and decision-makers working on enterprise-scale LLM strategies. A basic understanding of Python is required, and familiarity with machine learning will help you get the most out of this book.
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.
Impacts Of Sensetech On Society
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Author : Moutinho, Luiz
language : en
Publisher: IGI Global
Release Date : 2025-04-08
Impacts Of Sensetech On Society written by Moutinho, Luiz and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-08 with Social Science categories.
Emerging stages of the internet are now built on a plethora of different technologies working in an interoperable ecosystem. Many of these technologies converge, creating unexpected, innovative value for society and organizations. For society, disruptive technologies alter the way people interact and lead their lives both personally and professionally. These changes have immediate and long-term consequences, whose effects are subtle and need to be further identified and discussed. Impacts of Sensetech on Society explores emerging technologies that amplify social and economic change. It examines various fields where the impact would otherwise be lower, namely by leveraging the convergence effect. Covering topics such as information technologies, user preferences, and immersive journalism, this book is an excellent resource for computer engineers, sociologists, economists, policymakers, researchers, academicians, and more.
Langgraph
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Author : MORGAN. DEVLINE
language : en
Publisher:
Release Date : 2024
Langgraph written by MORGAN. DEVLINE and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with categories.
The Langgraph Langchain Handbook
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Author : William Deckman
language : en
Publisher: Independently Published
Release Date : 2025
The Langgraph Langchain Handbook written by William Deckman 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 with Computers categories.
Unlock the full potential of Natural Language Processing (NLP) with "The LangGraph LangChain Handbook: A Developer's Guide to Tackling NLP Challenges to Create Powerful and Cutting-Edge AI Solutions." This comprehensive guide empowers developers, data scientists, and AI enthusiasts to harness the combined strengths of LangGraph and LangChain frameworks, enabling the creation of sophisticated and intelligent AI applications. Dive into the essentials of LangChain for Retrieval-Augmented Generation (RAG) beginners and advance to mastering Large Language Model (LLM) application development. This handbook provides step-by-step instructions on building autonomous AI agents, managing multi-agent systems, and designing advanced AI workflows. Learn how to develop generative AI solutions on Google Cloud with LangChain, integrating seamlessly with modern cloud infrastructures to deliver scalable and efficient applications. Featuring detailed project blueprints and a dedicated projects lab section, "The LangGraph LangChain Handbook" bridges the gap between theory and practice. Engage with real-world projects such as building intelligent AI agents with LangGraph, utilizing LangChain for robust LLM applications, and integrating CrewAI for enhanced AI development. Explore hands-on examples like LangGraph RAG in JavaScript and delve into the intricacies of architecture-based design for multi-agent systems. Whether you are a beginner embarking on your first AI project or an experienced developer seeking to expand your expertise, this handbook offers valuable insights and practical tools to overcome complex NLP challenges. From understanding the fundamentals of multi-agent reinforcement learning to implementing advanced AI agent systems, you will gain the knowledge and skills needed to create powerful and cutting-edge AI solutions. Embrace the future of AI development with "The LangGraph LangChain Handbook" and transform your approach to building intelligent, scalable, and innovative NLP applications. Equip yourself with the expertise to lead in the rapidly evolving landscape of artificial intelligence and make a significant impact in your projects and career. Get your copy today and start building the next generation of AI solutions!
Langgraph 2nd Edition
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Author : MORGAN. DEVLINE
language : en
Publisher:
Release Date : 2025
Langgraph 2nd Edition written by MORGAN. DEVLINE and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with categories.
Learning Langchain
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Author : Mayo Oshin
language : en
Publisher: O'Reilly Media
Release Date : 2025-04-30
Learning Langchain written by Mayo Oshin and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-30 with Business & Economics categories.
If you're looking to build a production-ready AI application that enables users to "chat" with your company's private data, then you'll need to master LangChain--a premier AI development framework used by global corporations and startups like Zapier, Replit, Databricks, and more. This guide is an indispensable resource for developers who understand Python or JavaScript but are beginners eager to harness the power of AI. Authors Mayo Oshin and Nuno Campos demystify the use of LangChain through practical insights and in-depth tutorials. Starting with basic concepts, this book will show you step-by-step how to build a production-ready AI chatbot trained on your own data. After reading this book, you'll be equipped to: Understand and use the core components of LangChain in your development projects Harness the power of retrieval-augmented generation (RAG) to enhance the accuracy of LLMs using external, up-to-date data Develop and deploy AI chatbots that interact intelligently and contextually with users Utilize LangChain Expression Language to create custom, efficient AI operational chains Integrate and manage third-party APIs and tools to extend the functionality of your AI applications Learn the foundations of LLM app development and how they can be used with LangChain
Mcp Agent
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Author : Trent K Zussman
language : en
Publisher: Independently Published
Release Date : 2025-05-26
Mcp Agent written by Trent K Zussman and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-26 with Computers categories.
Moving from theory to practice, MCP Agent delves into advanced techniques that every experienced developer will appreciate. You'll explore Graph RAG (Graph-based Retrieval Augmented Generation) workflows to enrich your agents' knowledge using connected knowledge graphs alongside vector databases. You'll also master LangGraph - LangChain's powerful new framework for graph-driven agent orchestration - to create complex LLM workflows with fine-grained control. Learn how to structure your AI agents as deterministic graphs or state machines, enabling transparent decision flows, tool use, retries, and conditional logic for even the most challenging tasks. Throughout the book, Zussman emphasizes a hands-on, modular design approach. Each chapter is packed with code snippets, step-by-step tutorials, and real-world examples that bring concepts to life. You'll build agents that connect to popular tools and data sources (like databases, document repositories, web services, and dev ops tools) via MCP, equipping your AI with relevant context on the fly. Discover how to implement robust agent memory and state management techniques so your agents remember important information across interactions. You'll also learn best practices for evaluating an agent's reasoning and responses, with guidance on testing and debugging to refine your agents' performance before deployment. Inside this practical guide, you'll learn to: Master MCP Fundamentals: Understand the Model Context Protocol architecture and how to use this open standard to give your AI secure access to databases, knowledge bases, and APIs for rich context integration. Integrate Tools and Data Sources: Connect your agents to the outside world through tool integration and API calling, so they can retrieve up-to-the-minute information (files, code, queries) and interact with services in real time. Build with LangGraph Workflows: Leverage the LangGraph framework to orchestrate complex agent behaviors. Design graph-based workflows that chain LLM prompts, tool uses, and decisions with full control over loops, branching, and error handling. Implement Memory & Context Management: Incorporate long-term memory stores and context summarization to maintain conversational history and user preferences. Use Retrieval Augmented Generation (RAG) and Graph RAG techniques to inject relevant knowledge graph data into your agent's responses for greater accuracy. Evaluate and Refine Agents: Employ proven strategies to test your AI agents, from unit-testing tool functions to benchmarking output quality. Learn how to debug reasoning steps, handle edge cases, and iteratively improve your agents' decision-making. Deploy Scalable Intelligent Agents: Get best practices for deploying your AI agents in production. Containerize and integrate agents into applications, monitor their performance, and scale up securely - whether you're building an internal enterprise assistant or a customer-facing AI service. Written for software engineers and AI professionals, MCP Agent balances deep technical insights with a practical, engineering-focused tone. You'll gain the know-how to build scalable, intelligent agents that are grounded in real-world context and robust design principles. Whether you're architecting a new enterprise AI assistant or enhancing an existing LLM application, this book provides the patterns and tools to succeed. Take your AI agent development to the next level with MCP Agent - and create the context-aware, tool-using, autonomous agents that are defining the future of intelligent software.
Learning Langchain
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Author : Mayo Oshin
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-02-13
Learning Langchain written by Mayo Oshin 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 2025-02-13 with Business & Economics categories.
If you're looking to build production-ready AI applications that can reason and retrieve external data for context-awareness, you'll need to master LangChain—a popular development framework and platform for building, running, and managing agentic applications. LangChain is used by several leading companies, including Zapier, Replit, Databricks, and many more. This guide is an indispensable resource for developers who understand Python or JavaScript but are beginners eager to harness the power of AI. Authors Mayo Oshin and Nuno Campos demystify the use of LangChain through practical insights and in-depth tutorials. Starting with basic concepts, this book shows you step-by-step how to build a production-ready AI agent that uses your data. Harness the power of retrieval-augmented generation (RAG) to enhance the accuracy of LLMs using external up-to-date data Develop and deploy AI applications that interact intelligently and contextually with users Make use of the powerful agent architecture with LangGraph Integrate and manage third-party APIs and tools to extend the functionality of your AI applications Monitor, test, and evaluate your AI applications to improve performance Understand the foundations of LLM app development and how they can be used with LangChain