sunishsheth2009 / chatterbot

Uses Python, Flask, Natural Language processing, SQLAlchemy, NLTK and beautiful soup for web scrapping.

ChatterBot

Uses Python, Flask, Natural Language processing, SQLAlchemy, NLTK and beautiful soup for web scrapping. ChatterBot is a Python library that makes it easy to generate automated responses to a user’s input. ChatterBot uses a selection of machine learning algorithms to produce different types of responses. This makes it easy for developers to create chat bots and automate conversations with users. Language Independence The language independent design of ChatterBot allows it to be trained to speak any language. Additionally, the machine-learning nature of ChatterBot allows an agent instance to improve it’s own knowledge of possible responses as it interacts with humans and other sources of informative data.

How ChatterBot Works ChatterBot is a Python library designed to make it easy to create software that can engage in conversation.

An untrained instance of ChatterBot starts off with no knowledge of how to communicate. Each time a user enters a statement, the library saves the text that they entered and the text that the statement was in response to. As ChatterBot receives more input the number of responses that it can reply and the accuracy of each response in relation to the input statement increase.

The program selects the closest matching response by searching for the closest matching known statement that matches the input, it then chooses a response from the selection of known responses to that statement.