Xiaoquan Kong - Conversational AI with Rasa: Build, test, and deploy AI-powered, enterprise-grade virtual assistants and chatbots

Build, test, and deploy AI-powered, enterprise-grade virtual assistants and chatbots

Xiaoquan Kong

Guan Wang

BIRMINGHAMMUMBAI

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To my parents, for their unwavering devotion. To my wife, for her support behind the scenes. In addition, thanks to Google for providing the Google Cloud credits to support this work.

Xiaoquan Kong

To my mom and dad. To my wife and kids. Thank you!

Guan Wang

Conversational AI combines ideas from linguistics, human-computer interaction, artificial intelligence, and machine learning to develop voice and chat assistants for a near-infinite set of use cases. Since 2016 there has been a surge in interest in this field, driven by the widespread adoption of mobile chat applications. The coronavirus pandemic accelerated this trend, with almost all one-on-one interactions becoming digital.

2016 was also the year Rasa was first released and we saw the first community contributions come in on GitHub. Open source communities live and die by their users and contributors, and this is doubly true for Rasa, where our global community builds assistants in hundreds of human languages. Xiaoquan Kong and Guan Wang have been leading members of our community for years and I am grateful for their many contributions. Not least Xiaoquan's efforts to ensure Rasa has robust support for building assistants in Mandarin. I've been eagerly awaiting the publication of this book.

Conversational AI with Rasa covers precisely the topics required to become proficient at building real-world applications with Rasa. Aside from covering the fundamentals of natural language understanding and dialogue management, the book emphasizes the real-world context of building great products. In the first chapter, you are challenged to think whether a conversational experience is even the right one to build. The book also covers the essential process of Conversation-Driven Development, without which many assistants get built but fail to serve their intended users. Additionally, readers are taught practical skills like debugging an assistant, writing tests, and deploying an assistant to production.

This book will be of great use for anyone starting out as a Rasa developer, and I'm sure many existing Rasa developers will discover things they didn't know.

Alan Nichol

Co-founder and CTO, Rasa

Xiaoquan Kong is a machine learning expert specializing in NLP applications. He has extensive experience of leading teams to build NLP platforms for several Fortune Global 500 companies. He is a Google Developer Expert in machine learning and has been actively involved in contributing to TensorFlow for many years. He also has actively contributed to the development of the Rasa framework since the early stages 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.Guan Wang is currently working on Al applications and research for the insurance industry. Prior to that, he worked as a machine learning researcher for several industry Al labs. He was raised and educated in mainland China and 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 than 10,000 stars for his own projects on GitHub.

Harin Joshi's journey in chabot development started with an internship at ImpactGuru, India's fourth largest crowdfunding platform. There he developed two chatbots and a machine learning module. He was awarded Intern of the Month for this. Thereafter, he associated with the Co-learning Lounge AI community and developed a chatbot as educational content. Currently, he is working for the QuickGHY start-up as a chatbot developer.

I would like to thank my parents for always being there no matter what. Moreover, I am very grateful to have friends, who stood strong when I needed them at different stages of my life. And lastly, I would thank all the readers of this book: you are definitely going to learn a lot about Rasa and its functionalities.

Pratik Kotian is an conversational AI engineer with 5 years of experience in building conversational AI agents and designing products related to conversational design. He is working as a machine learning engineer (specializing in conversational AI) at Quantiphi, which is an AI company and recognized Google Partner. He has also worked with Packt on reviewing The Tensorflow Workshop.

I would like to thank my family and friends, who are always supportive and have always believed in me and my talents. It's because of them that I am doing well in my career and helping others to build great conversational bots.