Metadata-Version: 2.0
Name: ChatterBot
Version: 0.1.1
Summary: An open-source chat bot program written in Python.
Home-page: https://github.com/gunthercox/ChatterBot
Author: Gunther Cox
Author-email: gunthercx@gmail.com
License: BSD
Keywords: ChatterBot,chatbot,chat,bot
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Environment :: Console
Classifier: Environment :: Web Environment
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Requires-Dist: fuzzywuzzy (==0.5.0)
Requires-Dist: requests (==2.5.1)
Requires-Dist: requests-oauthlib (==0.4.2)
Requires-Dist: jsondatabase (==0.0.2)
Requires-Dist: stemming (==1.0.1)

.. 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.

|Package Version| |PyPi| |Requirements Status| |Build Status| |Coverage
Status|

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 recieves 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

Create a new chat bot
~~~~~~~~~~~~~~~~~~~~~

**Note:** *The ``ChatBot`` object takes an optional parameter for the
bot's name. The default name is 'bot'.*

::

    from chatterbot import ChatBot
    chatbot = ChatBot("Ron Obvious")

Training
~~~~~~~~

After creating a new chatterbot instance it is also possible to train
the bot. Training is a good way to ensure that the bot starts off with
knowledge about specific responses. The current training method takes a
list of statements that represent a conversation.

**Note:** Training is not required but it is recommended.

::

    conversation = [
        "Hello",
        "Hi there!",
        "How are you doing?",
        "I'm doing great.",
        "That is good to hear",
        "Thank you.",
        "Your welcome."
    ]

    chatbot.train(conversation)

Get a response
~~~~~~~~~~~~~~

::

    response = chatbot.get_response("Good morning!")
    print(response)

Change the default log file
~~~~~~~~~~~~~~~~~~~~~~~~~~~

**Note:** The default log file is ``database.db``.

::

    chatbot.database.path = "path/to/file.db"

Other bot types
---------------

ChatterBot comes with a selection of useful chat bots built in.

Terminal ChatterBot
^^^^^^^^^^^^^^^^^^^

This is a simple chatterbot that runs in the console. It responds to any
user input that is entered.

::

    from chatterbot import Terminal
    terminal = Terminal()
    terminal.begin()

Social ChatterBot
~~~~~~~~~~~~~~~~~

This bot type integrates with various social networking sites to
communicate.

::

    from chatterbot import SocialBot

    TWITTER = {
        "CONSUMER_KEY": "<consumer_key>",
        "CONSUMER_SECRET": "<consumer_secret>"
    }

    chatbot = SocialBot(twitter=TWITTER)

You will need to generate your own keys for using any API. To use this
feature with twitter's api you will need to register your application at
`Twitter's developer website <https://dev.twitter.com/apps>`__ to get
the token and secret keys.

Talk with CleverBot
~~~~~~~~~~~~~~~~~~~

Want to see what two bots have to say to each other? This allows your
ChatterBot to talk to `CleverBot <http://www.cleverbot.com/>`__.

::

    from chatterbot import TalkWithCleverbot
    talk = TalkWithCleverbot()
    talk.begin()

Use Cases
---------

**Using ChatterBot in your app? Let us know!** - `Salvius (humanoid
robot) <https://github.com/gunthercox/salvius>`__

History
-------

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

.. |Package Version| image:: https://badge.fury.io/py/ChatterBot.png
   :target: http://badge.fury.io/py/ChatterBot
.. |PyPi| image:: https://pypip.in/download/ChatterBot/badge.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
.. |Coverage Status| image:: https://img.shields.io/coveralls/gunthercox/ChatterBot.svg
   :target: https://coveralls.io/r/gunthercox/ChatterBot


