The AIML Chatbot kernel wraps the pyAIML Python library to create a conversational bot within a notebook. The bot behaviour is defined by loading AIML categories. A "category" in AIML is akin to a rule, and defines a pattern-template pair
Input cells are messages for the bot, which get interpreted and the bot output is the result of the cell execution. Additionally, a few magics for both control (cells starting with apercent sign) are available; these are not passed to the bot as user messages, but executed to change the bot behaviour in some way.
On an empty bot there is nothing to do (the bot does not produce any output, since it does not have rules to work with). So when creating an (empty) AIML notebook, any input cell will just return the general help message
This same help message can also be obtained at any time by using the
%help magic command
%lsmagics command lists all available magics with their meaning
The most important of these magics is
%learn, which loads an AIML database into the bot.
There are three versions for that:
%learn standard. AIML categories defined in the DB will be automatically loaded.
%learn <directory>where directory is a directory containing a set of AIML files to learn, plus an
startup.xmlfile referencing them. A
load <name>command is needed afterwards to load the learned rules into the bot
See 02-chatbot-alice.ipynb for an example of the first type.
An additional way of creating rules is by writing them directly in notebook cells, using the
%aiml magic. Such rules are immediately added to the bot when the cell is executed. You can: