This is a Jupyter kernel that deploys a chatbot, implemented using the python-aiml package. The idea was taken from the Calysto chatbot kernel.
It has been tested with Jupyter 4.x. The code works with either Python 2.7 or Python 3 (tested with Python 3.4)
The installation process requires two steps:
Install the Python package:
pip install aimlbotkernel
Install the kernel into Jupyter:
jupyter aimlbotkernel install [--user] [--logdir <dir>]
The --user
option will install the kernel in the current user's personal
config, while the generic command will install it as a global kernel (but
needs write permissions in the system directories).
The --logdir
specifies the default place into which the logfile will be
written (unless overriden at runtime by the LOGDIR
environment variable).
If no directory is specified, the (platform-specific) default temporal
directory will be used. The logging filename is aimlbotkernel-<uid>.log
where <uid> is the user id of the user running the notebook server.
Note that the Jupyter kernel installation also installs some custom CSS; its purpose is to improve the layout of the kernel results as they are presented in the notebook (but it also means that the rendered notebook will look slightly different in a Jupyter deployment in which the kernel has not been installed, or within an online viewer).
To uninstall, perform the inverse operations (in reverse order), to uninstall the kernel from Jupyter and to remove the Python package:
jupyter aimlbotkernel remove pip uninstall aimlbotkernel
Once installed, an AIML Chatbot kernel will be available in the Notebook
New menu. Starting one such kernel will create a chatbot. The chatbot is
initially empty but can be loaded with a couple of predefined DBs (use the
%help
magic for initial instructions).
Notebook input is of two kinds:
- Regular text cells are considered human input and are sent to the chatbot, which produces its corresponding output
- Cells starting with
%
contain "magic" commands that affect the operation of the kernel (load AIML databases, inspecting/modifying bot state, saving/loading state to/from disk, etc). Use the%help
magic for some instructions, and%lsmagics
to show the current list of defined magics (magics have autocompletion and contextual help).
The examples directory contains a few notebooks showing some of the provided functionality. They can also be seen with online Notebook viewer (note that, as said above, they will look slightly different than in a running kernel).
AIML is an XML-based specification to design conversational agents. Its most famous application is ALICE, a chatbot (the DB for the free version of ALICE is included in this kernel, as it is included in python-aiml)
The chatbot can load an AIML database (which is basically a bunch of XML
files). It can also define AIML rules on the fly, by using the %aiml
magic
in a cell.