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Building AI Applications with ChatGPT APIs

You're reading from  Building AI Applications with ChatGPT APIs

Product type Book
Published in Sep 2023
Publisher Packt
ISBN-13 9781805127567
Pages 258 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Martin Yanev Martin Yanev
Profile icon Martin Yanev

Table of Contents (19) Chapters

Preface 1. Part 1:Getting Started with OpenAI APIs
2. Chapter 1: Beginning with the ChatGPT API for NLP Tasks 3. Chapter 2: Building a ChatGPT Clone 4. Part 2: Building Web Applications with the ChatGPT API
5. Chapter 3: Creating and Deploying an AI Code Bug Fixing SaaS Application Using Flask 6. Chapter 4: Integrating the Code Bug Fixer Application with a Payment Service 7. Chapter 5: Quiz Generation App with ChatGPT and Django 8. Part 3: The ChatGPT, DALL-E, and Whisper APIs for Desktop Apps Development
9. Chapter 6: Language Translation Desktop App with the ChatGPT API and Microsoft Word 10. Chapter 7: Building an Outlook Email Reply Generator 11. Chapter 8: Essay Generation Tool with PyQt and the ChatGPT API 12. Chapter 9: Integrating ChatGPT and DALL-E API: Build End-to-End PowerPoint Presentation Generator 13. Chapter 10: Speech Recognition and Text-to-Speech with the Whisper API 14. Part 4:Advanced Concepts for Powering ChatGPT Apps
15. Chapter 11: Choosing the Right ChatGPT API Model 16. Chapter 12: Fine-Tuning ChatGPT to Create Unique API Models 17. Index 18. Other Books You May Enjoy

Using Chat Completion Parameters

In this section, we will be using ChatGPT API parameters and will look at their profound impact on the quality of responses generated by models. By understanding and harnessing the power of these parameters, you will gain the ability to optimize your interactions with the ChatGPT API, unlocking its true potential. Some of the key parameters to control the API response are as follows:

  • model: Specifies the specific ChatGPT model to use for generating responses.
  • messages: Provides the conversation history as a list of message objects, including user and assistant messages.
  • temperature: Controls the randomness of the generated responses. Higher values (for example, 0.8) make the responses more random, while lower values (for example, 0.2) make them more focused and deterministic.
  • max_tokens: Sets the maximum number of tokens in the generated response. Limiting this parameter can control the length of the response.
  • stop: Allows you...
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