Master LangGraph Building Dynamic AI Workflows and Agents with LangChain: A Comprehensive Guide to Designing, Developing, and Deploying Intelligent Multi-Agent Systems - Softcover
Inhaltsangabe
Unlock the power of intelligent AI systems with LangGraph.
Dive into the world of advanced AI development with Mastering LangGraph: Building Production-Grade AI Workflows, the definitive guide for creating robust, scalable, and intelligent AI systems using LangGraph, LangChain, and Python-based tools. Written by a seasoned AI engineer with over a decade of experience, this book is designed for technically proficient developers and advanced learners seeking to master the art of building dynamic, multi-agent AI workflows that thrive in real-world applications.
This comprehensive guide takes you through the entire process of designing, implementing, and deploying production-grade AI systems. Starting with the fundamentals of dynamic workflows, you will progress to orchestrating autonomous agents and multi-agent systems, mastering advanced techniques for multi-step reasoning, dynamic input handling, and performance optimization. The book concludes with strategies for testing, debugging, and ensuring reliability, preparing your applications for the demands of production environments. The appendix includes an in-depth reference guide with insights into LangGraph architecture, state management, tool integration, and common design patterns.
Key Features
In-depth theory and practical implementation. Each chapter combines rigorous conceptual explanations with production-ready Python examples, helping you understand both the why and the how of AI workflow design.
Real-world examples. Learn through practical applications such as customer support automation, content summarization, and collaborative multi-agent systems.
Comprehensive testing and debugging. Discover best practices for unit, integration, and stress testing, along with practical debugging strategies for AI pipelines.
Advanced techniques. Explore multi-step reasoning, performance optimization, dynamic adaptability, and distributed execution, with detailed discussions on state management and system reliability.
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Master LangGraph Building Dynamic AI Workflows and Agents with LangChain (Paperback)
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Paperback. Zustand: new. Paperback. Unlock the power of intelligent AI systems with LangGraph. Dive into the world of advanced AI development with Mastering LangGraph: Building Production-Grade AI Workflows, the definitive guide for creating robust, scalable, and intelligent AI systems using LangGraph, LangChain, and Python-based tools. Written by a seasoned AI engineer with over a decade of experience, this book is designed for technically proficient developers and advanced learners seeking to master the art of building dynamic, multi-agent AI workflows that thrive in real-world applications. This comprehensive guide takes you through the entire process of designing, implementing, and deploying production-grade AI systems. Starting with the fundamentals of dynamic workflows, you will progress to orchestrating autonomous agents and multi-agent systems, mastering advanced techniques for multi-step reasoning, dynamic input handling, and performance optimization. The book concludes with strategies for testing, debugging, and ensuring reliability, preparing your applications for the demands of production environments. The appendix includes an in-depth reference guide with insights into LangGraph architecture, state management, tool integration, and common design patterns. Key Features In-depth theory and practical implementation. Each chapter combines rigorous conceptual explanations with production-ready Python examples, helping you understand both the why and the how of AI workflow design. Real-world examples. Learn through practical applications such as customer support automation, content summarization, and collaborative multi-agent systems. Comprehensive testing and debugging. Discover best practices for unit, integration, and stress testing, along with practical debugging strategies for AI pipelines. Advanced techniques. Explore multi-step reasoning, performance optimization, dynamic adaptability, and distributed execution, with detailed discussions on state management and system reliability. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9798271118784
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Master LangGraph Building Dynamic AI Workflows and Agents with LangChain: A Comprehensive Guide to Designing, Developing, and Deploying Intelligent Multi-Agent Systems
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Master LangGraph Building Dynamic AI Workflows and Agents with LangChain (Paperback)
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Paperback. Zustand: new. Paperback. Unlock the power of intelligent AI systems with LangGraph. Dive into the world of advanced AI development with Mastering LangGraph: Building Production-Grade AI Workflows, the definitive guide for creating robust, scalable, and intelligent AI systems using LangGraph, LangChain, and Python-based tools. Written by a seasoned AI engineer with over a decade of experience, this book is designed for technically proficient developers and advanced learners seeking to master the art of building dynamic, multi-agent AI workflows that thrive in real-world applications. This comprehensive guide takes you through the entire process of designing, implementing, and deploying production-grade AI systems. Starting with the fundamentals of dynamic workflows, you will progress to orchestrating autonomous agents and multi-agent systems, mastering advanced techniques for multi-step reasoning, dynamic input handling, and performance optimization. The book concludes with strategies for testing, debugging, and ensuring reliability, preparing your applications for the demands of production environments. The appendix includes an in-depth reference guide with insights into LangGraph architecture, state management, tool integration, and common design patterns. Key Features In-depth theory and practical implementation. Each chapter combines rigorous conceptual explanations with production-ready Python examples, helping you understand both the why and the how of AI workflow design. Real-world examples. Learn through practical applications such as customer support automation, content summarization, and collaborative multi-agent systems. Comprehensive testing and debugging. Discover best practices for unit, integration, and stress testing, along with practical debugging strategies for AI pipelines. Advanced techniques. Explore multi-step reasoning, performance optimization, dynamic adaptability, and distributed execution, with detailed discussions on state management and system reliability. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9798271118784
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