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.
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: Your welcome.
bot: Do you like hats?
This package can be installed using
pip install chatterbot
Create a new chat bot
Note: This object takes an optional parameter for the bot's name.
from chatterbot import ChatBot
chatbot = ChatBot("Ron Obvious")
Getting a response to input text
response = chatbot.get_response("Good morning!")
print(response)
Specify a default location for conversation log files
Note: The default log directory is conversation_engrams/.
chatbot.log_directory = "path/to/directory/"
Terminal mode (User and chat bot)
from chatterbot import Terminal
terminal = Terminal()
terminal.begin()
Have the chat bot talk with CleverBot
from chatterbot import TalkWithCleverbot
talk = TalkWithCleverbot()
talk.begin()
Social mode (Have the bot respond to users on social media sites)
from chatterbot import SocialBot
log_dir = "path/to/conversation_engrams/"
TWITTER = {
"CONSUMER_KEY": "<consumer_key>",
"CONSUMER_SECRET": "<consumer_secret>",
"ACCESS_KEY": "<access_key>",
"ACCESS_SECRET": "<access_secret>"
}
chatbot = SocialBot(log_directory=log_dir, twitter=TWITTER)
You will need to generate your own keys for using any API. To use this feature you will need to register your application at Twitter's developer website to get the token and secret keys.
Sample conversations for training the chat bot can be downloaded from https://gist.github.com/gunthercox/6bde8279615b9b638f71