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Building LLM Powered  Applications

You're reading from   Building LLM Powered Applications Create intelligent apps and agents with large language models

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781835462317
Length 342 pages
Edition 1st Edition
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Author (1):
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Valentina Alto Valentina Alto
Author Profile Icon Valentina Alto
Valentina Alto
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Table of Contents (16) Chapters Close

Preface 1. Introduction to Large Language Models FREE CHAPTER 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

Principles of prompt engineering

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Clear Instructions

The principle of giving clear instructions is to provide the model with enough information and guidance to perform the task correctly and efficiently. Clear instructions should include the following elements:

  • The goal or objective of the task, such as “write a poem” or “summarize an article”.
  • The format or structure of the expected output, such as “use four lines with rhyming words” or “use bullet points with no more than 10 words each”.
  • The constraints or limitations of the task, such as “do not use any profanity” or “do not copy any text from the source”.
  • The context or background of the task, such as “the poem is about autumn” or “the article is from a scientific journal”.

Let’s say, for example, that we want our model to fetch any kind of instructions from text and return to us a tutorial in a bullet list....

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