Artificial Intelligence Knowledge Information Framework
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README.md

AIKIF

Artificial Intelligence Knowledge Information Framework (Alpha)

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This is an information classification framework that maps structured or freeform data to a standard knowledge store.

Manages a dataset of your applications, the source data, parameters, runs and results and then uses your business rules to convert and store the information in a machine usable format.

Your AI software can link to AIKIF by setting up logging watch-points to define success / failure along with the range of input parameters. Goals and plans are defined by breaking them down to smaller tasks until the task can be run by a tool in the Toolbox.

A tool is any python wrapped function or application and is easily extensible.

Overview of AIKIF

Quick Start

This github repository https://github.com/acutesoftware/AIKIF contains the latest code, but the current public release is available via

pip install aikif

To start the API server use aikif/api_main.py and run the tests/test_api.py

 * Running on http://127.0.0.1:5000/
 * Restarting with reloader
127.0.0.1 - - [28/May/2015 19:22:49] "GET /facts HTTP/1.1" 200 -
127.0.0.1 - - [28/May/2015 19:22:49] "GET /help HTTP/1.1" 200 -
127.0.0.1 - - [28/May/2015 19:22:49] "GET /users/1 HTTP/1.1" 200 -

To start the web interface use aikif/web_app/web_aikif.py or the batch file aikif\go_web_aikif

screenshot of web interface

Simple Usage

In its simplest form AIKIF can be used to manage your projects and tasks, by updating information from scripts and tracking via the web application

my_biz = project.Project(name='Acute Software', type='business', desc='Custom Software')
my_biz.add_detail('website', 'http://www.acutesoftware.com.au')
my_biz.add_detail('email', 'djmurray@acutesoftware.com.au')

Logging data

You can use AIKIF as a database to manage adhoc data logging tasks

proj2 = project.Project(name='Sales Log', desc='Record list of sales')
proj2.add_detail('Note', 'List of sales taken from manual entries in test program')

tbl_exp = cls_datatable.DataTable('expenses.csv', col_names=['date', 'amount', 'details'])
proj2.record(tbl_exp, 'Expense', ['2015-02-13', 49.94, 'restaurant'])
proj2.record(tbl_exp, 'Expense', ['2015-02-15', 29.00, 'petrol'])
proj2.record(tbl_exp, 'Expense', ['2015-02-17', 89.95, 'fringe tickets'])

Data Collection Usage

p = aikif.project.Project('update Country reference', type='Auto')
p.add_task(1, 'download file', aikif.toolbox.web_download)
p.add_task(2, 'extract zip', aikif.toolbox.zip_util)  # not implemented
p.add_task(3, 'overwrite TXT to database staging', aikif.toolbox.data_load)

p.add_param(task=1, url='http://www.')
p.add_param(task=1, dest_zip = 'T:\data\download\country')
p.add_param(task=3, tbl='S_REF_COUNTRY')
p.execute()

This will execute the methods for each task using the specified parameters to update the table from the web

Map information

Define how columns in raw data should be mapped

m = aikif.mapper('custom mapper for countries', tbl = 'S_REF_COUNTRY')
m.add_col('code', data_type='STR', map_to_col='COUNTRY_CODE')
m.add_col('Name', data_type='STR', map_to_col='COUNTRY_NAME')
m.add_col('Continent', data_type='STR', map_to_col='CONTINENT')
m.add_col('Population', data_type='NUMBER', map_to_col='POPULATION')

Define your own Toolbox methods

Say you have a program 'my_average.py' which calculates averages that you want to include in the toolbox methods

t = aikif.toolbox.Toolbox()
t.add_tool(1, 'Calc Average', src=T:\dev\src\python\my_tools\my_average.py')

p2 = aikif.project.Project('Aggregate Country by Continent')
p2.add_task(1, 'Fetch source data', aikif.toolbox.data_view)
p2.add_task(2, 'Aggregate Population', t['Calc Average'])

p2.add_param(task=1, tbl = 'S_REF_COUNTRY' )
p2.add_param(task=2, group_by_col = 'CONTINENT', measure_col='POPULATION' )

p2.execute()  # with no parameters, data outputs to console

More Information

Requirements Documentation
Design Notes
Overview Diagram