Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Rag in Action: Foundations, Architecture, and Agentic Implementation

Rag in Action: Foundations, Architecture, and Agentic Implementation

Thummarakoti, Sairohith
Pendyala, Jothsna Praveena

Hardcover

General Computers

PREORDER - Expected ship date April 29, 2027

ISBN10: 1041284543
ISBN13: 9781041284543
Publisher: Auerbach Publications
Published: Apr 29 2027
Pages: 482
Language: English

Retrieval-Augmented Generation (RAG) has become a fundamental architectural pattern in generative AI systems and addresses critical limitations of large language models (LLMs). While LLMs excel at language comprehension and content generation, they are constrained by static training data and parametric memory, raising concerns about factual accuracy, transparency, and controllability. RAG overcomes these challenges by integrating structured information retrieval into the generative process. Instead of relying solely on memorized representations, RAG systems dynamically access external knowledge sources during inference to enhance factual grounding, contextuality, and access to domain-specific or continuously updated information.

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