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Building LLM Powered  Applications

You're reading from  Building LLM Powered Applications

Product type Book
Published in May 2024
Publisher Packt
ISBN-13 9781835462317
Pages 342 pages
Edition 1st Edition
Languages
Author (1):
Valentina Alto Valentina Alto
Profile icon Valentina Alto
Toc

Table of Contents (16) Chapters close

Preface 1. Introduction to Large Language Models 2. LLMs for AI-Powered Applications 3. Choosing an LLM for Your Application 4. Prompt Engineering 5. Embedding LLMs within Your Applications 6. Building Conversational Applications 7. Search and Recommendation Engines with LLMs 8. Using LLMs with Structured Data 9. Working with Code 10. Building Multimodal Applications with LLMs 11. Fine-Tuning Large Language Models 12. Responsible AI 13. Emerging Trends and Innovations 14. Other Books You May Enjoy
15. Index

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Qr code Description automatically generated

In Chapter 2, we introduced the concept of prompt engineering as the process of designing and optimizing prompts – the text inputs that guides the behaviour of a large language model - to LLMs for a wide variety of applications and research topics.Since prompts have a massive impact on LLMs performance, prompt engineering is a crucial activity while designing LLM-powered applications. In fact, there are several techniques that can be implemented to not only to refine your LLM’s responses, but also to reduce risks associated with hallucination and biases.In this chapter, we are going to cover the emerging techniques in the field of prompt engineering, starting from basic approaches up to advanced frameworks. More specifically, we will go through the following topics:

  • Introduction to prompt engineering
  • Basic principles of prompt engineering
  • Advanced techniques of prompt engineering
  • Mitigation of risks...
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