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
Build Your Own AI ChatBOT: Create Private, Powerful RAG Applications with PostgreSQL, pgvector, Python, and FastAPI

Build Your Own AI ChatBOT: Create Private, Powerful RAG Applications with PostgreSQL, pgvector, Python, and FastAPI

Lightcap, Richard

Paperback

General ReferenceProgramming

ISBN10: 1972154222
ISBN13: 9781972154229
Publisher: Veritasio Press
Published: Jul 18 2026
Pages: 230
Weight: 0.69
Height: 0.48 Width: 6.00 Depth: 9.00
Language: English
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. Designed 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

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