{ "item_title" : "The GraphRAG Playbook", "item_author" : [" Calvert Barclay "], "item_description" : "Build Intelligent AI Applications with Knowledge Graphs, LLMs, RAG, and Semantic SearchTraditional retrieval-augmented generation can provide useful context to large language models, but many complex questions require more than retrieving isolated passages. GraphRAG combines the power of knowledge graphs with retrieval and language models to help AI systems work with connected information, relationships, and broader context. The GraphRAG Playbook provides a practical guide to understanding and building GraphRAG-powered AI applications. It builds on the concepts behind knowledge graphs and explores how graph-based retrieval can enhance modern RAG and LLM workflows. You will learn how GraphRAG works, how information can be represented and retrieved through connected structures, and how graph-based context can support more capable AI applications.Inside, you will explore: GraphRAG concepts, architectures, and workflowsKnowledge graphs as a foundation for GraphRAGGraph-based retrieval and contextual searchCombining graph retrieval with traditional RAGLLM integration and prompt-driven retrieval workflowsEntity, relationship, and multi-hop retrievalSemantic search and graph-aware information discoveryBuilding practical GraphRAG pipelinesDesigning GraphRAG applications for real-world use casesEvaluating, improving, and extending GraphRAG systems Whether you are new to GraphRAG or already familiar with RAG and knowledge graphs, this playbook provides a structured path toward building knowledge graph-powered AI applications with LLMs, retrieval-augmented generation, semantic search, and connected data.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/9/79/819/262/9798192629321_b.jpg", "price_data" : { "retail_price" : "19.99", "online_price" : "19.99", "our_price" : "19.99", "club_price" : "19.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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