How To Install Chatterbot In Windows

ChatterBot

ChatterBot is a automobile-learning based conversational dialog engine build in Python which makes information technology possible to generate responses based on collections of known conversations. The language independent design of ChatterBot allows it to exist trained to speak any language.

An example of typical input would be something like this:

user: Good morning! How are you doing?
bot: I am doing very well, thanks for request.
user: You're welcome.
bot: Exercise you similar hats?

How information technology works

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 than input the number of responses that it can answer and the accuracy of each response in relation to the input argument increase. The program selects the closest matching response by searching for the closest matching known argument that matches the input, it then returns the nearly likely response to that statement based on how often each response is issued by the people the bot communicates with.

Installation

This packet can be installed from PyPi by running:

          pip install chatterbot                  

Basic Usage

          from chatterbot import ChatBot from chatterbot.trainers import ChatterBotCorpusTrainer  chatbot = ChatBot('Ron Obvious')  # Create a new trainer for the chatbot trainer = ChatterBotCorpusTrainer(chatbot)  # Train the chatbot based on the english corpus trainer.train("chatterbot.corpus.english language")  # Get a response to an input statement chatbot.get_response("Hello, how are you today?")                  

Preparation data

ChatterBot comes with a data utility module that tin be used to railroad train conversation bots. At the moment there is training data for over a dozen languages in this module. Contributions of additional training data or preparation data in other languages would be profoundly appreciated. Have a look at the data files in the chatterbot-corpus package if yous are interested in contributing.

          from chatterbot.trainers import ChatterBotCorpusTrainer  # Create a new trainer for the chatbot trainer = ChatterBotCorpusTrainer(chatbot)  # Railroad train based on the english language corpus trainer.railroad train("chatterbot.corpus.english")  # Train based on english greetings corpus trainer.railroad train("chatterbot.corpus.english.greetings")  # Railroad train based on the english language conversations corpus trainer.train("chatterbot.corpus.english.conversations")                  

Corpus contributions are welcome! Please make a pull asking.

Documentation

View the documentation for ChatterBot on Read the Docs.

To build the documentation yourself using Sphinx, run:

          sphinx-build -b html docs/ build/                  

Examples

For examples, see the examples directory in this project's git repository.

There is as well an example Django projection using ChatterBot, as well every bit an case Flask project using ChatterBot.

History

See release notes for changes https://github.com/gunthercox/ChatterBot/releases

Development blueprint for contributors

1. Create a fork of the main ChatterBot repository on GitHub.
2. Make your changes in a branch named something unlike from main, e.m. create a new branch my-pull-request.
3. Create a pull request.
4. Please follow the Python fashion guide for PEP-8.
5. Apply the projects built-in automated testing. to help make certain that your contribution is gratuitous from errors.

License

ChatterBot is licensed nether the BSD iii-clause license.

Source: https://pypi.org/project/ChatterBot/

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