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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

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Product type Paperback
Published in Sep 2024
Publisher Packt
ISBN-13 9781836207252
Length 298 pages
Edition 1st Edition
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Table of Contents (18) Chapters Close

Preface 1. Chapter 1: Getting Started with Generative AI 2. Chapter 2: Building Blocks of Intelligent Applications FREE CHAPTER 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

Testing and red teaming

Testing AI systems is critical to ensure their accuracy, reliability, and overall performance. Typically, in software engineering, automated testing is used as part of the software development process. GenAI applications are no different. You’ll want to routinely and regularly test the outputs to ensure there are no radical shifts in output quality.

Testing

Just like your typical software engineering features, you’ll want to include the phases of unit testing, integration testing, performance testing, and user acceptance into your test plan. However, the specifics of how this is done vary from one use case to another.

In the context of GenAI applications, unit testing still has the same basic tenets and involves testing individual components or modules of the application to ensure they function correctly. However, in the case of GenAI applications, your unit tests will need to also include steps such as the following:

  • Input validation...
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