9781972154229 - build your own ai chatbot: create private, powerful rag applications with postgresql, pgvector, python, and fastapi de lightcap, richard (7 resultados)
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Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de AmericaBargainBookStores
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Paperback or Softback. Condición: New. Build Your Own AI ChatBOT: Create Private, Powerful RAG Applications with PostgreSQL, pgvector, Python, and FastAPI. Book.
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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Paperback. Condición: new. Paperback. Build a private, production-ready AI chatbot from the ground up-without surrendering control of your data. *Build Your Own AI Chatbot* is a practical, implementation-focused guide to creating retrieval-augmented generation (RAG) applications with PostgreSQL, pgvector, Python, and FastAPI. De…signed for developers, technology professionals, students, and educators, the book moves beyond basic chatbot demonstrations to explain how reliable RAG systems are architected, secured, tested, evaluated, and deployed. Readers begin by building a working local chatbot and then progressively strengthen every layer of the system. The book covers document ingestion, source tracking, semantic chunking, embedding generation, vector indexing, similarity search, hybrid retrieval, reranking, evidence selection, prompt assembly, citation validation, and grounded response generation. It also addresses the challenges that frequently separate experimental projects from dependable applications, including hallucinations, insufficient evidence, prompt injection, tenant isolation, data retention, observability, performance, and recovery. The hands-on examples use Python and FastAPI for application services, PostgreSQL and pgvector for durable vector storage, and a provider-neutral model interface that supports local, private deployment. Practical code snippets throughout the chapters demonstrate how the individual components fit together while preserving clear security and authorization boundaries. This expanded textbook edition includes: * 12 detailed chapters covering the complete RAG lifecycle* A working chatbot quickstart* 24 cumulative, hands-on implementation labs* Complete lab solutions collected in the back of the book* 120 end-of-chapter questions with a comprehensive answer key* Troubleshooting guidance, a technical glossary, and real-world RAG recipes* Deployment, evaluation, security, and operational checklists Whether you are creating an internal knowledge assistant, a secure enterprise chatbot, an educational project, or your first AI-powered application, *Build Your Own AI Chatbot* provides the technical foundation and practical direction needed to transform a promising prototype into a private, powerful, and trustworthy RAG system. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
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EUR 22,86
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Paperback. Condición: new. Paperback. Build a private, production-ready AI chatbot from the ground up-without surrendering control of your data. *Build Your Own AI Chatbot* is a practical, implementation-focused guide to creating retrieval-augmented generation (RAG) applications with PostgreSQL, pgvector, Python, and FastAPI. De…signed for developers, technology professionals, students, and educators, the book moves beyond basic chatbot demonstrations to explain how reliable RAG systems are architected, secured, tested, evaluated, and deployed. Readers begin by building a working local chatbot and then progressively strengthen every layer of the system. The book covers document ingestion, source tracking, semantic chunking, embedding generation, vector indexing, similarity search, hybrid retrieval, reranking, evidence selection, prompt assembly, citation validation, and grounded response generation. It also addresses the challenges that frequently separate experimental projects from dependable applications, including hallucinations, insufficient evidence, prompt injection, tenant isolation, data retention, observability, performance, and recovery. The hands-on examples use Python and FastAPI for application services, PostgreSQL and pgvector for durable vector storage, and a provider-neutral model interface that supports local, private deployment. Practical code snippets throughout the chapters demonstrate how the individual components fit together while preserving clear security and authorization boundaries. This expanded textbook edition includes: * 12 detailed chapters covering the complete RAG lifecycle* A working chatbot quickstart* 24 cumulative, hands-on implementation labs* Complete lab solutions collected in the back of the book* 120 end-of-chapter questions with a comprehensive answer key* Troubleshooting guidance, a technical glossary, and real-world RAG recipes* Deployment, evaluation, security, and operational checklists Whether you are creating an internal knowledge assistant, a secure enterprise chatbot, an educational project, or your first AI-powered application, *Build Your Own AI Chatbot* provides the technical foundation and practical direction needed to transform a promising prototype into a private, powerful, and trustworthy RAG system. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
