An open-source chat bot program written in Python.
Project description
.. figure:: http://i.imgur.com/b3SCmGT.png
:alt: Chatterbot: Machine learning in Python
Chatterbot: Machine learning in Python
ChatterBot
==========
ChatterBot is a machine-learning based conversational dialog engine
build in Python which makes it possible to generate responses based on
collections of known conversations. The language independent design of
ChatterBot allows it to be trained to speak any language.
*`Read in English <readme.md>`__* *`Leia em Português <readme.pt.md>`__*
*`Leer en español <readme.es.md>`__*
|Package Version| |Requirements Status| |Build Status| |Documentation
Status| |Coverage Status| |Code Climate| |Join the chat at
https://gitter.im/chatter\_bot/Lobby|
An example of typical input would be something like this:
| **user:** Good morning! How are you doing?
| **bot:** I am doing very well, thank you for asking.
| **user:** You're welcome.
| **bot:** Do you like hats?
How it 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 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 returns the most likely response to that
statement based on how frequently each response is issued by the people
the bot communicates with.
Installation
------------
This package can be installed from
`PyPi <https://pypi.python.org/pypi/ChatterBot>`__ by running:
::
pip install chatterbot
Basic Usage
-----------
::
from chatterbot import ChatBot
chatbot = ChatBot(
'Ron Obvious',
trainer='chatterbot.trainers.ChatterBotCorpusTrainer'
)
# Train based on the english corpus
chatbot.train("chatterbot.corpus.english")
# Get a response to an input statement
chatbot.get_response("Hello, how are you today?")
Training data
=============
Chatterbot comes with a data utility module that can be used to train
chat bots. At the moment there is three languages, English, Spanish and
Portuguese training data in this module. Contributions of additional
training data or training data in other languages would be greatly
appreciated. Take a look at the data files in the
`chatterbot/corpus <https://github.com/gunthercox/ChatterBot/tree/master/chatterbot/corpus>`__
directory if you are interested in contributing.
::
# Train based on the english corpus
chatbot.train("chatterbot.corpus.english")
# Train based on english greetings corpus
chatbot.train("chatterbot.corpus.english.greetings")
# Train based on the english conversations corpus
chatbot.train("chatterbot.corpus.english.conversations")
**Corpus contributions are welcome! Please make a pull request.**
`Documentation <http://chatterbot.readthedocs.io/>`__
=====================================================
View the `documentation <http://chatterbot.readthedocs.io/>`__ for
ChatterBot on Read the Docs.
To build the documentation yourself using
`Sphinx <http://www.sphinx-doc.org/>`__, run:
::
sphinx-build -b html docs/ build/
Examples
========
For examples, see the
`examples <https://github.com/gunthercox/ChatterBot/tree/master/examples>`__
directory in this project's git repository.
There is also an example `Django project using
ChatterBot <https://github.com/gunthercox/django_chatterbot>`__, as well
as an example `Flask project using
ChatterBot <https://github.com/chamkank/flask-chatterbot>`__.
History
=======
See release notes for changes
https://github.com/gunthercox/ChatterBot/releases
.. |Package Version| image:: https://img.shields.io/pypi/v/chatterbot.svg
:target: https://pypi.python.org/pypi/chatterbot/
.. |Requirements Status| image:: https://requires.io/github/gunthercox/ChatterBot/requirements.svg?branch=master
:target: https://requires.io/github/gunthercox/ChatterBot/requirements/?branch=master
.. |Build Status| image:: https://travis-ci.org/gunthercox/ChatterBot.svg?branch=master
:target: https://travis-ci.org/gunthercox/ChatterBot
.. |Documentation Status| image:: https://readthedocs.org/projects/chatterbot/badge/?version=stable
:target: http://chatterbot.readthedocs.io/en/stable/?badge=stable
.. |Coverage Status| image:: https://img.shields.io/coveralls/gunthercox/ChatterBot.svg
:target: https://coveralls.io/r/gunthercox/ChatterBot
.. |Code Climate| image:: https://codeclimate.com/github/gunthercox/ChatterBot/badges/gpa.svg
:target: https://codeclimate.com/github/gunthercox/ChatterBot
.. |Join the chat at https://gitter.im/chatter\_bot/Lobby| image:: https://badges.gitter.im/chatter_bot/Lobby.svg
:target: https://gitter.im/chatter_bot/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge
:alt: Chatterbot: Machine learning in Python
Chatterbot: Machine learning in Python
ChatterBot
==========
ChatterBot is a machine-learning based conversational dialog engine
build in Python which makes it possible to generate responses based on
collections of known conversations. The language independent design of
ChatterBot allows it to be trained to speak any language.
*`Read in English <readme.md>`__* *`Leia em Português <readme.pt.md>`__*
*`Leer en español <readme.es.md>`__*
|Package Version| |Requirements Status| |Build Status| |Documentation
Status| |Coverage Status| |Code Climate| |Join the chat at
https://gitter.im/chatter\_bot/Lobby|
An example of typical input would be something like this:
| **user:** Good morning! How are you doing?
| **bot:** I am doing very well, thank you for asking.
| **user:** You're welcome.
| **bot:** Do you like hats?
How it 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 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 returns the most likely response to that
statement based on how frequently each response is issued by the people
the bot communicates with.
Installation
------------
This package can be installed from
`PyPi <https://pypi.python.org/pypi/ChatterBot>`__ by running:
::
pip install chatterbot
Basic Usage
-----------
::
from chatterbot import ChatBot
chatbot = ChatBot(
'Ron Obvious',
trainer='chatterbot.trainers.ChatterBotCorpusTrainer'
)
# Train based on the english corpus
chatbot.train("chatterbot.corpus.english")
# Get a response to an input statement
chatbot.get_response("Hello, how are you today?")
Training data
=============
Chatterbot comes with a data utility module that can be used to train
chat bots. At the moment there is three languages, English, Spanish and
Portuguese training data in this module. Contributions of additional
training data or training data in other languages would be greatly
appreciated. Take a look at the data files in the
`chatterbot/corpus <https://github.com/gunthercox/ChatterBot/tree/master/chatterbot/corpus>`__
directory if you are interested in contributing.
::
# Train based on the english corpus
chatbot.train("chatterbot.corpus.english")
# Train based on english greetings corpus
chatbot.train("chatterbot.corpus.english.greetings")
# Train based on the english conversations corpus
chatbot.train("chatterbot.corpus.english.conversations")
**Corpus contributions are welcome! Please make a pull request.**
`Documentation <http://chatterbot.readthedocs.io/>`__
=====================================================
View the `documentation <http://chatterbot.readthedocs.io/>`__ for
ChatterBot on Read the Docs.
To build the documentation yourself using
`Sphinx <http://www.sphinx-doc.org/>`__, run:
::
sphinx-build -b html docs/ build/
Examples
========
For examples, see the
`examples <https://github.com/gunthercox/ChatterBot/tree/master/examples>`__
directory in this project's git repository.
There is also an example `Django project using
ChatterBot <https://github.com/gunthercox/django_chatterbot>`__, as well
as an example `Flask project using
ChatterBot <https://github.com/chamkank/flask-chatterbot>`__.
History
=======
See release notes for changes
https://github.com/gunthercox/ChatterBot/releases
.. |Package Version| image:: https://img.shields.io/pypi/v/chatterbot.svg
:target: https://pypi.python.org/pypi/chatterbot/
.. |Requirements Status| image:: https://requires.io/github/gunthercox/ChatterBot/requirements.svg?branch=master
:target: https://requires.io/github/gunthercox/ChatterBot/requirements/?branch=master
.. |Build Status| image:: https://travis-ci.org/gunthercox/ChatterBot.svg?branch=master
:target: https://travis-ci.org/gunthercox/ChatterBot
.. |Documentation Status| image:: https://readthedocs.org/projects/chatterbot/badge/?version=stable
:target: http://chatterbot.readthedocs.io/en/stable/?badge=stable
.. |Coverage Status| image:: https://img.shields.io/coveralls/gunthercox/ChatterBot.svg
:target: https://coveralls.io/r/gunthercox/ChatterBot
.. |Code Climate| image:: https://codeclimate.com/github/gunthercox/ChatterBot/badges/gpa.svg
:target: https://codeclimate.com/github/gunthercox/ChatterBot
.. |Join the chat at https://gitter.im/chatter\_bot/Lobby| image:: https://badges.gitter.im/chatter_bot/Lobby.svg
:target: https://gitter.im/chatter_bot/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge
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