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Conversational AI with Rasa

You're reading from   Conversational AI with Rasa Build, test, and deploy AI-powered, enterprise-grade virtual assistants and chatbots

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Product type Paperback
Published in Oct 2021
Publisher Packt
ISBN-13 9781801077057
Length 264 pages
Edition 1st Edition
Tools
Concepts
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Authors (2):
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Xiaoquan Kong Xiaoquan Kong
Author Profile Icon Xiaoquan Kong
Xiaoquan Kong
Guan Wang Guan Wang
Author Profile Icon Guan Wang
Guan Wang
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Toc

Table of Contents (16) Chapters Close

Preface 1. Section 1: The Rasa Framework
2. Chapter 1: Introduction to Chatbots and the Rasa Framework FREE CHAPTER 3. Chapter 2: Natural Language Understanding in Rasa 4. Chapter 3: Rasa Core 5. Section 2: Rasa in Action
6. Chapter 4: Handling Business Logic 7. Chapter 5: Working with Response Selector to Handle Chitchat and FAQs 8. Chapter 6: Knowledge Base Actions to Handle Question Answering 9. Chapter 7: Entity Roles and Groups for Complex Named Entity Recognition 10. Chapter 8: Working Principles and Customization of Rasa 11. Section 3: Best Practices
12. Chapter 9: Testing and Production Deployment 13. Chapter 10: Conversation-Driven Development and Interactive Learning 14. Chapter 11: Debugging, Optimization, and Community Ecosystem 15. Other Books You May Enjoy

Chapter 8: Working Principles and Customization of Rasa

In this chapter, we introduce the working principles behind Rasa. We will discuss exactly what happens after Rasa receives requests from its users. This is essential for you to understand how to debug a Rasa application, which we will discuss in Chapter 11, Debugging, Optimization, and the Community Ecosystem.

We will also learn how to extend and customize Rasa. Using detailed examples, you will learn to create and use custom components that allow you to use adapters or advanced features not included in Rasa. This will help you to create highly customized or complex chatbot applications.

In this chapter, we will cover the following topics:

  • Understanding Rasa's Natural Language Understanding (NLU) module
  • Understanding Rasa policies
  • Writing Rasa extensions
  • Practice: Creating your own custom English tokenizer
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