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Mastering GitHub Actions

You're reading from  Mastering GitHub Actions

Product type Book
Published in Mar 2024
Publisher Packt
ISBN-13 9781805128625
Pages 490 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Eric Chapman Eric Chapman
Profile icon Eric Chapman

Table of Contents (22) Chapters

Preface 1. Part 1:Centralized Workflows to Assist with Governance
2. Chapter 1: An Overview of GitHub and GitHub Actions 3. Chapter 2: Exploring Workflows 4. Chapter 3: Deep Dive into Reusable Workflows and Composite Actions 5. Chapter 4: Workflow Personalization Using GitHub Apps 6. Chapter 5: Utilizing Starter Workflows in Your Team 7. Part 2: Implementing Advanced Patterns within Actions
8. Chapter 6: Using HashiCorp Vault in GitHub 9. Chapter 7: Deploying to Azure Using OpenID Connect 10. Chapter 8: Working with Checks 11. Chapter 9: Annotating Code with Actions 12. Chapter 10: Advancing with Event-Driven Workflows 13. Chapter 11: Setting Up Self-Hosted Runners 14. Part 3: Best Practices, Patterns, Tricks, and Tips Toolkit
15. Chapter 12: The Crawler Pattern 16. Chapter 13: The Configuration Centralization Pattern 17. Chapter 14: Using Remote Workflows to Kickstart Your Products 18. Chapter 15: Housekeeping Tips for Your Organization 19. Chapter 16: Handy Workflows for Managing Your Software 20. Index 21. Other Books You May Enjoy

Designing a chatbot using ChatGPT

In this section, we delve into crafting a basic chatbot utilizing GitHub issues, building on the knowledge we’ve accumulated throughout this book. While I wouldn’t argue that this is the most effective chatbot design—given the current AI landscape and considering similar endeavors by platforms such as GitHub—it does offer an enjoyable experience and a closer look at the Issues API.

To kick things off, we’ll initiate a new workflow named event-comment-ai.yml. Our primary goal is to subscribe to comment-made events within issues. Unlike traditional chatbots that respond to every statement, our design aims for a more flexible conversation flow. The bot will only engage when triggered by specific keywords and use past interactions to provide context in its responses. This ensures that it picks up the conversation from the right context when prompted again. To achieve this, we’ll search for all comments made...

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