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Building AI Intensive Python Applications

You're reading from Building AI Intensive Python Applications Create intelligent apps with LLMs and vector databases

Product type Paperback

Published in Sep 2024

Publisher Packt

ISBN-13 9781836207252

Length 298 pages

Edition 1st Edition

Languages

Python

Tools

MongoDB

Concepts

Artificial Intelligence

Table of Contents (18) Chapters

Preface

1. Chapter 1: Getting Started with Generative AI FREE CHAPTER

2. Chapter 2: Building Blocks of Intelligent Applications

3. Part 1: Foundations of AI: LLMs, Embedding Models, Vector Databases, and Application Design

4. Chapter 3: Large Language Models

5. Chapter 4: Embedding Models

6. Chapter 5: Vector Databases

7. Chapter 6: AI/ML Application Design

8. Part 2: Building Your Python Application: Frameworks, Libraries, APIs, and Vector Search

9. Chapter 7: Useful Frameworks, Libraries, and APIs

10. Chapter 8: Implementing Vector Search in AI Applications

11. Part 3: Optimizing AI Applications: Scaling, Fine-Tuning, Troubleshooting, Monitoring, and Analytics

12. Chapter 9: LLM Output Evaluation

13. Chapter 10: Refining the Semantic Data Model to Improve Accuracy

14. Chapter 11: Common Failures of Generative AI

15. Chapter 12: Correcting and Optimizing Your Generative AI Application

16. Other Books You May Enjoy

Appendix: Further Reading: Index

Why subscribe?

Technical requirements

The following are the prerequisites to follow along with the code in this chapter:

A MongoDB Atlas cluster M0 tier (free) should be sufficient
An OpenAI account and API key with access to the text-embedding-3-large model
A Python 3 working environment
Installed Python libraries for MongoDB, LangChain, and OpenAI
Atlas Search indexes and Vector Search indexes created on the MongoDB Atlas cluster

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