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artifacia

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    artifacia

A javascript client to integrate visual recommendation feature from Artifacia API


Version published
Weekly downloads
4
decreased by-63.64%
Maintainers
1
Install size
3.72 MB
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Artifacia javascript Client

This javascript client is a simple wrapper around our powerful Visual Discovery API.

The wrapper allows you to create your own index of images on which you would like to enhance the product discovery experiences. It also allows you to get various types of recommendations which are listed below.

  • Visual Recommendation
  • Cross Product Recommendation
  • Personalized Recommendation

Installation

To install the package you can follow the steps:-

[sudo] npm install artifacia --save

Getting Started

The API is really easy and simple to use. First you need to visit this page and request for username and password. Using that credentials you can create your constructor and get stated.

"use strict";
var client = require("artifacia");
var api_key = <api_key>;
client.artifacia(api_key);

Creating your index

The first step is to create a index of the items that you would like to store in our databases to perform search against. If you don't have data ready right now you can quickly get started with our sample data. Once the data is stored and indexed we will inform you shortly.

var sample_data = require("./sample_data.json");
client.upload_item_data(sample_data,function(result){console.log(result)});

Performing Visual Recommendation

Once you receive a notification from us about the status of the indexed data, you are ready to search. You can search for a product ID indexed in the sample data you inserted/uploaded. And also you can specify the number to results to be returned as well as you can set attribute if you want to prioritize the result on the basis of tags like color, material, pattern etc as given below.

var sample_prod_id = 2709;
var num = 4;
var filters = {'color':1, 'pattern':1};
client.get_visual_recommendation(sample_prod_id,num,filters,function(result){console.log(result)});

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Last updated on 10 Nov 2016

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