How to Make a Rule-based Chatbot in Python Using Flask by Khushal Jethava Python in Plain English

door | jul 20, 2023

Rule-based Chatbot vs AI Chatbot: Which One to Choose

rule based chatbot python

In conclusion, we recommend an AI-based chatbot if you expect a wide range of varied user inputs, or if personalization and ensuring a great user experience are your highest priority. Before delving into AI chatbot development, make sure you have sufficient resources to not only train your model but also to support and maintain it after deployment. The significance of Python AI chatbots is paramount, especially in today’s digital age. They are changing the dynamics of customer interaction by being available around the clock, handling multiple customer queries simultaneously, and providing instant responses.

rule based chatbot python

The first chatbot named ELIZA was designed and developed by Joseph Weizenbaum in 1966 that could imitate the language of a psychotherapist in only 200 lines of code. But as the technology gets more advance, we have come a long way from scripted chatbots to chatbots in Python today. Conversational AI chatbots for eCommerce have several features that create a 20% to 40% lift in revenue when customers converse with Ochatbot. Now we have everything set up that we need to generate a response to the user queries related to tennis.

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In today’s fast-paced digital economy, businesses constantly seek creative solutions to enhance customer engagement and streamline processes. Chatbots have evolved into flexible technologies that offer benefits like improved customer service and cost reductions. In this comprehensive tutorial, TECHVIFY will explore their various forms, how to build a chatbot, and how to develop a chatbot using Chat GPT. In addition, we’ll discuss best practices so you may maximize your potential in today’s competitive business environment. Your cleaning functions have already been taken care of, so this step will take little of your time or energy.

  • AI chatbots offer businesses a competitive edge by providing highly personalized interactions and valuable data insights.
  • By comparing the new input to historic data, the chatbot can select a response that is linked to the closest possible known input.
  • Some people visit e-commerce websites to shop for a specific product, but there are always a few shoppers that just visit a site and realize they need the product or service!
  • In this second part of the series, we’ll be taking you through how to build a simple Rule-based chatbot in Python.
  • Line 8 creates a While Loop that will loop until one of the conditions from Line 7 is met, and Line 13 finally calls.get_response() giving all input collected earlier from Line 9.

Classes are code templates used for creating objects, and we’re going to use them to build our chatbot. Now that we’re armed with some background knowledge, it’s time to build our own chatbot. Chatbots can help you perform many tasks and increase your productivity. First, let make a very basic chatbot using basic Python skills like input/output and basic condition statements, which will take basic information from the user and print it accordingly.

Advantages of a rule-based chatbot

The punctuation_removal list removes the punctuation from the passed text. Finally, the get_processed_text method takes a sentence as input, tokenizes it, lemmatizes it, and then removes the punctuation from the sentence. Congratulations, we have successfully built a chatbot using python and flask. You guys can refer to chatterbot official documents for more information, or you can see the GitHub code of it. Also, you can see the below chatbot flowchart to understand better how chatterbot works.

In simple words, Rule based chatbot python project are computer programs that follow a set of predetermined rules to reply to users. These programs are designed to simulate a conversation with a human being. They can be programmed by anyone who has the knowledge of programming languages such as Python, Java, and all other programming languages.

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This is where tokenizing supports text data – it converts the large text dataset into smaller, readable chunks (such as words). Once this process is complete, we can go for lemmatization to transform a word into its lemma form. This article assumes you are familiar with the basics of neural networks.

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What are the disadvantages of rule-based approach?

The main disadvantage is that rule-based methods are usually not the best performers in terms of prediction quality. Other methods (forests, SVM, deep nets) tends to be better. Also, rule-based methods are better for data with categorical features.