Name: Hands-On Rag for Production: Design, Develop, and Deploy Production-Ready Rag Applications (en Inglés)
SKU: 66147664
Price: 70.87 USD
Availability: InStock
Author: Mendelevitch, Ofer; Bao, Forrest

portada Hands-On Rag for Production: Design, Develop, and Deploy Production-Ready Rag Applications (en Inglés)

Hands-On Rag for Production: Design, Develop, and Deploy Production-Ready Rag Applications (en Inglés)

Formato

Libro Físico

Editorial

O'Reilly Media

Autor

Mendelevitch, Ofer; Bao, Forrest

Año

2026

Idioma

Inglés

N° páginas

356

Encuadernación

Tapa Blanda

Dimensiones

23x17 cm

ISBN13

9798341621718

Hands-On Rag for Production: Design, Develop, and Deploy Production-Ready Rag Applications (en Inglés)

Mendelevitch, Ofer; Bao, Forrest (Autor) · O'Reilly Media · Tapa Blanda

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Reseña del libro "Hands-On Rag for Production: Design, Develop, and Deploy Production-Ready Rag Applications (en Inglés)"

Retrieval-augmented generation (RAG) is the go-to strategy for integrating large language models with your organization's unique knowledge. However, the market is full of RAG pipelines and components, making it hard to choose the right solution for your enterprise's needs. This book simplifies the process, offering a comprehensive road map to building, refining, and scaling production-grade RAG applications.

Authors Ofer Mendelevitch and Forrest Bao guide you through every phase of development, from data ingestion, embeddings, and vector search to advanced techniques like agentic RAG, multimodal RAG, and GraphRAG. Engineers and architects will learn how to tackle the challenges they'll encounter when building RAG applications at enterprise scale: ensuring high accuracy with minimal hallucinations, maintaining low-latency performance, safeguarding data privacy, and providing transparent, explainable responses among them.

Determine whether to build RAG yourself or deploy a RAG-as-a-service platform
Build a basic RAG stack that maximizes performance and cost-effectiveness
Measure key metrics such as hallucinations, response quality, latency, and cost
Address challenges in enterprise deployment, such as compliance with data security and privacy requirements, explainability, and prompt design
Implement advanced techniques such as multimodal RAG, agentic RAG, and GraphRAG