https://github.com/jay-johnson/antinex-client
AntiNex python client for training and using pre-trained deep neural networks with JWT authentication
https://github.com/jay-johnson/antinex-client
ai ai-security anti-nex artificial-intelligence deep-neural-networks jwt keras python rest-client tensorflow
Last synced: 3 months ago
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AntiNex python client for training and using pre-trained deep neural networks with JWT authentication
- Host: GitHub
- URL: https://github.com/jay-johnson/antinex-client
- Owner: jay-johnson
- License: apache-2.0
- Created: 2018-03-24T07:50:22.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2020-09-04T19:49:18.000Z (over 4 years ago)
- Last Synced: 2025-01-31T02:36:53.589Z (3 months ago)
- Topics: ai, ai-security, anti-nex, artificial-intelligence, deep-neural-networks, jwt, keras, python, rest-client, tensorflow
- Language: Python
- Homepage: http://antinex.readthedocs.io/en/latest/
- Size: 92.8 KB
- Stars: 5
- Watchers: 4
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.rst
- License: LICENSE
Awesome Lists containing this project
README
AntiNex Python Client
=====================
Python API Client for training deep neural networks with the REST API running
https://github.com/jay-johnson/train-ai-with-django-swagger-jwt
.. image:: https://travis-ci.org/jay-johnson/antinex-client.svg?branch=master
:target: https://travis-ci.org/jay-johnson/antinex-client
.. image:: https://readthedocs.org/projects/antinex-client/badge/?version=latest
:target: http://antinex-client.readthedocs.io/en/latest/?badge=latest
Install
-------
pip install antinex-client
AntiNex Stack Status
--------------------
AntiNex client is part of the AntiNex stack:
.. list-table::
:header-rows: 1
* - Component
- Build
- Docs Link
- Docs Build
* - `REST API `__
- .. image:: https://travis-ci.org/jay-johnson/train-ai-with-django-swagger-jwt.svg?branch=master
:alt: Travis Tests
:target: https://travis-ci.org/jay-johnson/train-ai-with-django-swagger-jwt.svg
- `Docs `__
- .. image:: https://readthedocs.org/projects/antinex/badge/?version=latest
:alt: Read the Docs REST API Tests
:target: https://readthedocs.org/projects/antinex/badge/?version=latest
* - `Core Worker `__
- .. image:: https://travis-ci.org/jay-johnson/antinex-core.svg?branch=master
:alt: Travis AntiNex Core Tests
:target: https://travis-ci.org/jay-johnson/antinex-core.svg
- `Docs `__
- .. image:: https://readthedocs.org/projects/antinex-core-worker/badge/?version=latest
:alt: Read the Docs AntiNex Core Tests
:target: http://antinex-core-worker.readthedocs.io/en/latest/?badge=latest
* - `Network Pipeline `__
- .. image:: https://travis-ci.org/jay-johnson/network-pipeline.svg?branch=master
:alt: Travis AntiNex Network Pipeline Tests
:target: https://travis-ci.org/jay-johnson/network-pipeline.svg
- `Docs `__
- .. image:: https://readthedocs.org/projects/antinex-network-pipeline/badge/?version=latest
:alt: Read the Docs AntiNex Network Pipeline Tests
:target: https://readthedocs.org/projects/antinex-network-pipeline/badge/?version=latest
* - `AI Utils `__
- .. image:: https://travis-ci.org/jay-johnson/antinex-utils.svg?branch=master
:alt: Travis AntiNex AI Utils Tests
:target: https://travis-ci.org/jay-johnson/antinex-utils.svg
- `Docs `__
- .. image:: https://readthedocs.org/projects/antinex-ai-utilities/badge/?version=latest
:alt: Read the Docs AntiNex AI Utils Tests
:target: http://antinex-ai-utilities.readthedocs.io/en/latest/?badge=latest
* - `Client `__
- .. image:: https://travis-ci.org/jay-johnson/antinex-client.svg?branch=master
:alt: Travis AntiNex Client Tests
:target: https://travis-ci.org/jay-johnson/antinex-client.svg
- `Docs `__
- .. image:: https://readthedocs.org/projects/antinex-client/badge/?version=latest
:alt: Read the Docs AntiNex Client Tests
:target: https://readthedocs.org/projects/antinex-client/badge/?version=latest
Run Predictions
===============
These examples use the default user ``root`` with password ``123321``. It is advised to change this to your own user in the future.
Train a Deep Neural Network with a JSON List of Records
-------------------------------------------------------
::
ai -u root -p 123321 -f examples/predict-rows-scaler-django-simple.json
Train a Deep Neural Network to Predict Attacks with the AntiNex Datasets
------------------------------------------------------------------------
Please make sure the datasets are available to the REST API, Celery worker, and AntiNex Core worker. The datasets are already included in the docker container ``ai-core`` provided in the default ``compose.yml`` file:
https://github.com/jay-johnson/train-ai-with-django-swagger-jwt/blob/51f731860daf134ea2bd3b68468927c614c83ee5/compose.yml#L53-L104
If you're running outside docker make sure to clone the repo with:
::
git clone https://github.com/jay-johnson/antinex-datasets.git /opt/antinex/antinex-datasets
Train the Django Defensive Deep Neural Network
----------------------------------------------
Please wait as this will take a few minutes to return and convert the predictions to a pandas DataFrame.
::
ai -u root -p 123321 -f examples/scaler-full-django-antinex-simple.json
...
[30200 rows x 72 columns]
Using Pre-trained Neural Networks to make Predictions
-----------------------------------------------------
The `AntiNex Core`_ manages pre-trained deep neural networks in memory. These can be used with the REST API by adding the ``"publish_to_core": true`` to a request while running with the `REST API compose.yml`_ docker containers running.
Run:
::
ai -u root -p 123321 -f examples/publish-to-core-scaler-full-django.json
Here is the diff between requests that will run using a pre-trained model and one that will train a new neural network:
::
antinex-client$ diff examples/publish-to-core-scaler-full-django.json examples/scaler-full-django-antinex-simple.json
5d4
< "publish_to_core": true,
antinex-client$
.. _AntiNex Core: https://github.com/jay-johnson/antinex-core
.. _REST API compose.yml: https://github.com/jay-johnson/train-ai-with-django-swagger-jwt/blob/master/compose.yml
Prepare a Dataset
-----------------
::
ai_prepare_dataset.py -u root -p 123321 -f examples/prepare-new-dataset.json
Get Job Record for a Deep Neural Network
----------------------------------------
Get a user's MLJob record by setting: ``-i ``
This include the model json or model description for the Keras DNN.
::
ai_get_job.py -u root -p 123321 -i 4
Get Predictions Results for a Deep Neural Network
-------------------------------------------------
Get a user's MLJobResult record by setting: ``-i ``
This includes predictions from the training or prediction job.
::
ai_get_results.py -u root -p 123321 -i 4
Get a Prepared Dataset
----------------------
Get a user's MLPrepare record by setting: ``-i ``
::
ai_get_prepared_dataset.py -u root -p 123321 -i 15
Using a Client Built from Environment Variables
-----------------------------------------------
This is how the `Network Pipeline`_ streams data to the `AntiNex Core`_ to make predictions with pre-trained models.
Export the example environment file:
::
source examples/example-prediction.env
Run the client prediction stream script
::
ai_env_predict.py -f examples/predict-rows-scaler-full-django.json
.. _Network Pipeline: https://github.com/jay-johnson/network-pipeline
.. _AntiNex Core: https://github.com/jay-johnson/antinex-core
Development
-----------
::
virtualenv -p python3 ~/.venvs/antinexclient && source ~/.venvs/antinexclient/bin/activate && pip install -e .
Testing
-------
Run all
::
python setup.py test
Linting
-------
flake8 .
pycodestyle .
License
-------
Apache 2.0 - Please refer to the LICENSE_ for more details
.. _License: https://github.com/jay-johnson/antinex-client/blob/master/LICENSE