Product guide

Building AI Intensive Python Applications: LLMs and Vector Databases

Building AI Intensive Python Applications is a developer-focused guide to creating generative AI applications with Python, LLMs, and vector databases. Its stated topics include retrieval-augmented generation (RAG), vector search, model evaluation, and optimization. Basic Python knowledge is required, so it is not a Python-from-zero text.

At a glance

Covers the generative AI stack, including LLMs, embedding models, vector databases, and Python frameworks.
Includes RAG strategies and vector search, with MongoDB Atlas specifically named in the listing.
Topics include preparing data, selecting and fine-tuning models, evaluating LLM output, and addressing common generative AI failures.
Listing says print or Kindle purchases include a free PDF eBook.

Price

$49.49Save 34%

Reference price: ~~$74.99~~

Price checked: Nov 14, 2026

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Pros and cons

Pros

The scope spans application architecture, vector search, RAG, evaluation, and performance tuning rather than focusing only on prompt writing.
A basic Python background is the stated entry requirement, making it suitable for developers who know Python but are new to generative AI application design.

Cons

Readers looking for a Python fundamentals course will need other material because basic Python understanding is required.

Technical specifications

8 specifications

Publication details
Publisher	Packt Publishing
Publication date	September 6, 2024
Language	English
Print length	298 pages
ISBN-10	1836207255
ISBN-13	978-1836207252

Dimensions and installation
Weight listed	1.57 pounds
Dimensions	7.5 x 0.7 x 9.25 inches

Who is it for?

A good fit for

Software engineers and developers who want to build intelligent applications with generative AI and already understand basic Python.
Readers interested in connecting LLMs with vector databases, implementing RAG, and evaluating application outputs.

Less suited to

People seeking a beginner Python programming course or a guide limited to theory without application-development topics.

Customer reviews on Amazon

5 / 5 · 5 ratings

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The available aggregate rating is uniformly five-star, but it represents only a small number of ratings and comes without written feedback. It therefore offers little detail about which topics readers valued or where the book may fall short. Judge fit by the listed scope and note that basic Python knowledge is required.

Frequently asked questions

Does this book teach Python from the beginning?

The listing says basic Python understanding is required. It is aimed at developers applying Python to generative AI, not at readers learning Python from scratch.

What AI application topics does it cover?

The stated topics include LLMs, embedding models, vector databases, Python frameworks, vector search, RAG, model evaluation, fine-tuning, and application optimization.

Does it cover MongoDB Atlas?

Yes. The listing specifically describes implementing RAG strategies with MongoDB Atlas.

Is a PDF eBook included?

The listing says purchase of the print or Kindle book includes a free PDF eBook.