Book Image

Conversational AI with Rasa

By : Xiaoquan Kong, Guan Wang
Book Image

Conversational AI with Rasa

By: Xiaoquan Kong, Guan Wang

Overview of this book

The Rasa framework enables developers to create industrial-strength chatbots using state-of-the-art natural language processing (NLP) and machine learning technologies quickly, all in open source. Conversational AI with Rasa starts by showing you how the two main components at the heart of Rasa work – Rasa NLU (natural language understanding) and Rasa Core. You'll then learn how to build, configure, train, and serve different types of chatbots from scratch by using the Rasa ecosystem. As you advance, you'll use form-based dialogue management, work with the response selector for chitchat and FAQ-like dialogs, make use of knowledge base actions to answer questions for dynamic queries, and much more. Furthermore, you'll understand how to customize the Rasa framework, use conversation-driven development patterns and tools to develop chatbots, explore what your bot can do, and easily fix any mistakes it makes by using interactive learning. Finally, you'll get to grips with deploying the Rasa system to a production environment with high performance and high scalability and cover best practices for building an efficient and robust chat system. By the end of this book, you'll be able to build and deploy your own chatbots using Rasa, addressing the common pain points encountered in the chatbot life cycle.
Table of Contents (16 chapters)
1
Section 1: The Rasa Framework
5
Section 2: Rasa in Action
11
Section 3: Best Practices

Using channels to communicate with instant messaging software

In most cases, users will be using all kinds of instant messaging (IM) apps to interact with chatbots.

Rasa is one of the best platforms for seamlessly integrating with different IMs. Rasa supports most of the mainstream IMs on the market that support OpenAPI. Currently, it includes Facebook Messenger, Slack, Telegram, Twilio, Microsoft Bot Framework, Cisco Webex Teams, RocketChat, Mattermost, and Google Hangouts Chat.

Community developers have also developed many open source IMs for Rasa, and those open source IMs are often used by start-ups and developers for product demonstration purposes. Rasa Webchat (https://github.com/botfront/rasa-webchat) and Chatroom (https://github.com/scalableminds/chatroom) have the most mature functionalities.

In Rasa, the connector is responsible for connecting a Rasa system to an IM. The Connect feature handles the communication protocol. Since different IMs may share the same communication...