This very simple rule based chatbot will work by searching for specific keywords in inputs given by a user.
Python includes support for regular expression through the re package. They are widely used for text searching and matching in UNIX. Regular Expression (RegEx) in PythonĪ regular expression is a special sequence of characters that helps you search for and find patterns of words/sentences/sequence of letters in sets of strings, using a specialized syntax. It provides easy-to-use interfaces to many language-based resources such as the Open Multilingual Wordnet, as well as access to a variety of text-processing libraries. Natural Language Toolkit is a Python library that makes it easy to process human language data.
Now that we’re familiar with how chatbots work, we’ll be looking at the libraries that will be used to build our simple Rule-based Chatbot. Unlike their rule-based kin, AI based chatbots are based on complex machine learning models that enable them to self-learn. Using artificial intelligence, it has become possible to create extremely intuitive and precise chatbots tailored to specific purposes. With the rise in the use of machine learning in recent years, a new approach to building chatbots has emerged. These bots are extremely limited and can only respond to queries if they are an exact match with the inputs defined in their database. The simplest form of Rule-based Chatbots have one-to-one tables of inputs and their responses. They cannot generate their own answers but with an extensive database of answers and smartly designed rules, they can be very productive and useful. They are provided with a database of responses and are given a set of rules that help them match out an appropriate response from the provided database. Rule-based chatbots are pretty straight forward. Types of ChatbotsĬhatbots can be classified into two different types, based on how they are built: Rule-Based Chatbots
Before we start with the tutorial, we need to understand the different types of chatbots and how they work.
PYTHON CHATBOT HOW TO
In this second part of the series, we’ll be taking you through how to build a simple Rule-based chatbot in Python. We also saw how the technology has evolved over the past 50 years. In the first part of A Beginners Guide to Chatbots, we discussed what chatbots were, their rise to popularity and their use-cases in the industry. They have become so critical in the support industry, for example, that almost 25% of all customer service operations are expected to use them by 2020. They have found a strong foothold in almost every task that requires text-based public dealing. Chatbots have become extremely popular in recent years and their use in the industry has skyrocketed.
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