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You're reading from  Conversational AI with Rasa

Product typeBook
Published inOct 2021
PublisherPackt
ISBN-139781801077057
Edition1st Edition
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Authors (2):
Xiaoquan Kong
Xiaoquan Kong
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Xiaoquan Kong

Xiaoquan is a machine learning expert specializing in NLP applications. He has extensive experience in leading teams to build NLP platforms in several Fortune Global 500 companies. He is a Google developer expert in Machine Learning and has been actively involved in contributions to TensorFlow for many years. He also has actively contributed to the development of the Rasa framework since the early stage and became a Rasa Superhero in 2018. He manages the Rasa Chinese community and has also participated in the Chinese localization of TensorFlow documents as a technical reviewer.
Read more about Xiaoquan Kong

Guan Wang
Guan Wang
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Guan Wang

Guan is currently working on Al applications and research for the insurance industry. Prior to that, he was a machine learning researcher at several industry Al labs. He was raised and educated in Mainland China, lived in Hong Kong for 10 years before relocating to Singapore in 2020. Guan holds BSc degrees in Physics and Computer Science from Peking University, and an MPhil degree in Physics from HKUST. Guan is an active tech blogger and community contributor to open source projects including Rasa, receiving more than10,000 stars for his own projects on Github.
Read more about Guan Wang

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How do you use knowledge base actions?

To tackle the challenges that we introduced in the previous section, Rasa can be integrated with a knowledge base via a knowledge base action. A knowledge base action is a special action that has been developed to handle referential resolution and queries on objects and their properties.

In general, to use knowledge base actions, you need to do the following:

  • Create a knowledge base from where the bot can retrieve information that will be used to answer the questions that have been asked.
  • Create a knowledge base action using Rasa SDK, which will query the knowledge base according to the user's inputs and reply with relevant answers.
  • Define some Natural Language Understanding (NLU) data so that users can trigger the knowledge base action via the inputs.
  • Modify your knowledge base actions to make the responses more human-like.

Let's start by defining a knowledge base.

Creating a knowledge base

A knowledge...

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Conversational AI with Rasa
Published in: Oct 2021Publisher: PacktISBN-13: 9781801077057

Authors (2)

author image
Xiaoquan Kong

Xiaoquan is a machine learning expert specializing in NLP applications. He has extensive experience in leading teams to build NLP platforms in several Fortune Global 500 companies. He is a Google developer expert in Machine Learning and has been actively involved in contributions to TensorFlow for many years. He also has actively contributed to the development of the Rasa framework since the early stage and became a Rasa Superhero in 2018. He manages the Rasa Chinese community and has also participated in the Chinese localization of TensorFlow documents as a technical reviewer.
Read more about Xiaoquan Kong

author image
Guan Wang

Guan is currently working on Al applications and research for the insurance industry. Prior to that, he was a machine learning researcher at several industry Al labs. He was raised and educated in Mainland China, lived in Hong Kong for 10 years before relocating to Singapore in 2020. Guan holds BSc degrees in Physics and Computer Science from Peking University, and an MPhil degree in Physics from HKUST. Guan is an active tech blogger and community contributor to open source projects including Rasa, receiving more than10,000 stars for his own projects on Github.
Read more about Guan Wang