How to build a chatbot using Rasa and Python by Arya Pandey

Therefore, if we want to apply a neural network algorithm on the text, it is important that we convert it to numbers first. And one way to achieve this is using the Bag-of-words (BoW) model. It is one of the most common models used to represent text through numbers so that machine learning algorithms can be applied on it.

Moreover, the ML algorithms support the bot to improve its performance with experience. Artificial intelligence, specifically designed to improve human−computer interactions, utilises machine learning and Natural Language Processing (NLP) to create chatbots. Chatbots converse with humans in a natural, human−like manner by adapting to natural human language. ChatterBot is a Python library used to create chatbots that generate automated responses to users’ input by using machine learning algorithms.

Types of AI Chatbots

Now that we’re armed with some background knowledge, it’s time to build our own chatbot. Python is a popular choice for creating various types of bots due to its versatility and abundant libraries. Whether it’s chatbots, web crawlers, or automation bots, Python’s simplicity, extensive ecosystem, and NLP tools make it well-suited for developing effective and efficient bots. Now, notice that we haven’t considered punctuations while converting our text into numbers.

From here on you can talk to the bot, below is a gif showing a conversation with the bot, you can stop the conversation by typing /stop. You can download the following two softwares from the link provided below (if you don’t already have them on your PC, or you can continue with the article if you do). Now, if the get_weather() function successfully fetches the weather then it is communicated to the user otherwise if some error occurred a message is shown to the user. We have a function which is capable of fetching the weather conditions of any city in the world.

Advantages of Using Python for Chatbot Development

We’ll be using the ChatterBot library to create our Python chatbot, so  ensure you have access to a version of Python that works with your chosen version of ChatterBot. Moreover, the more interactions the chatbot engages in over time, the more historic data it has to work from, and the more accurate its responses will be. A chatbot built using ChatterBot works by saving the inputs and responses it deals with, using this data to generate relevant automated responses when it receives a new input.

Read more about https://www.metadialog.com/ here.