cv65kr/sylius-personalized-products

Personalized products, choices by machine learning (Prediction IO) for Sylius.

dev-master / 1.3.x-dev 2018-07-14 21:45 UTC

Requires

• php: ^7.2
• predictionio/predictionio: ^0.9.1
• sylius/sylius: ^1.1|^1.2|~1.3.0@dev
• symfony/symfony: ^3.4|^4.1

Requires (Dev)

• behat/behat: ^3.4
• behat/mink: ^1.7@dev
• behat/mink-browserkit-driver: ^1.3
• behat/mink-extension: ^2.2
• behat/mink-selenium2-driver: ^1.3
• friends-of-behat/context-service-extension: ^1.2
• friends-of-behat/cross-container-extension: ^1.1
• friends-of-behat/service-container-extension: ^1.0
• friends-of-behat/symfony-extension: ^1.2.1
• friends-of-behat/variadic-extension: ^1.1
• lakion/mink-debug-extension: ^1.2.3
• phpspec/phpspec: ^4.0
• phpstan/phpstan-doctrine: ^0.10
• phpstan/phpstan-shim: ^0.10
• phpstan/phpstan-symfony: ^0.10
• phpstan/phpstan-webmozart-assert: ^0.10
• phpunit/phpunit: ^6.5
• sylius-labs/coding-standard: ^2.0

MIT

README

Overview

I used Apache PredictionIO to create plugin, which shows personalize recommended products, based on watched products.

Installation

Sylius

composer require cv65kr/sylius-personalized-products

Add plugin dependencies to your AppKernel.php file:

public function registerBundles()
{
    return array_merge(parent::registerBundles(), [
        ...
        
        new \cv65kr\SyliusPersonalizedProducts\SyliusPersonalizedProductsPlugin(),
    ]);
}

Import required config in your app/config/config.yml file and setup parameters:

imports:
    ...
    
    - { resource: "@SyliusPersonalizedProductsPlugin/Resources/config/services.yml" }
    
parameters:
    sylius_prediction_event_host: http://machine_learning
    sylius_prediction_event_port: 7070
    sylius_prediction_engine_host: https://machine_learning
    sylius_prediction_engine_port: 8000
    sylius_prediction_key: 'a-mevXQWyArRnxmHvlFKrjHLdjuvhnpqOgYEu8XgvfpLW0RTuPl_wUUQo3ZWQa5F'

Import routing in your app/config/routing.yml file:

app_personalized_products:
    resource: "@SyliusPersonalizedProductsPlugin/Resources/config/routing.yml"

Embed in template:

{{ render(path('sylius_personalized_products_controller')) }}

Note 1: Controller render should be used only for logged customers.

Note 2: You can use limit and template parameres in route.

Apache PredictionIO

First of all, add in docker-compose.yml machine learning:

  machine_learning:
      build: ../ml
      ports:
        - "9000:9000"
        - "7070:7070"
        - "8000:8000"
      volumes:
        - /ml/engine:/CustomEngine

And go inside container:

docker exec -it machine_learning bash

Next:

cd /CustomEngine

We need, download template for 0.9 version:

pio template get apache/predictionio-template-recommender --version v0.3.2 MyRecommendation

Create API key and paste them in Sylius config parameter - sylius_prediction_key:

pio app new SyliusPersonalizedProducts

Let’s verify that our new app is there with this command:

pio app list

In Sylius run:

bin/console s:p:p

And now back into machine_learning container

cd /CustomEngine/MyRecommendation

Build, they may few minutes:

pio build --verbose

Edit engine.json:

vim engine.json

Change:

"appName": "INVALID_APP_NAME"

To:

"appName": "SyliusPersonalizedProducts"

Next train:

Create sample data for training and import them by:

pio import --appid 1 --input data-sample.json

Note: Example sample file, You need modify this file: https://gist.githubusercontent.com/vaghawan/0a5fb8ddb85e03631dd500d7c8f0677d/raw/17487437dd8269588d9dd1ac859b129a43842ba5/data-sample.json

Next run:

pio train

And deploy, hooray!

pio deploy

Contribution

Learn more about our contribution workflow on http://docs.sylius.org/en/latest/contributing/.