Agentic Graph RAG (Early Release)
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- Дата: 25-06-2025, 12:48
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Автор: Anthony Alcaraz
Издательство: O’Reilly Media, Inc.
Год: 2025-06-24
Страниц: 160
Язык: английский
Формат: epub
Размер: 10.1 MB
What if your AI systems could retrieve information, reason over complex knowledge, plan actions, and continuously learn—all while maintaining enterprise-grade security and compliance? Agentic Graph RAG guides technical leaders, engineers, and architects through the next evolution of Generative AI. Combining retrieval-augmented generation (RAG) with graph-based reasoning and agentic capabilities, this guide provides a practical blueprint for building scalable, auditable, and intelligent AI systems.
Written by Anthony Alcaraz, this book demystifies knowledge graphs, graph memory, neural-symbolic reasoning, and agent orchestration through real-world case studies, hands-on design patterns, and production-ready architectures. Readers will learn how to construct graph-native retrieval systems, integrate advanced reasoning into agent workflows, and address enterprise challenges around governance, scalability, and transparency.
Design graph-augmented architectures that surpass traditional RAG
Implement agents with dynamic memory, planning, and decision-making capabilities
Integrate knowledge graphs with large language models for robust, explainable AI
Deploy scalable, governable multiagent systems ready for production environments
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