1. Go to this page and download the library: Download recombee/php-api-client library. Choose the download type require.
2. Extract the ZIP file and open the index.php.
3. Add this code to the index.php.
<?php
require_once('vendor/autoload.php');
/* Start to develop here. Best regards https://php-download.com/ */
recombee / php-api-client example snippets
use Recombee\RecommApi\Client;
use Recombee\RecommApi\Requests as Reqs;
use Recombee\RecommApi\Exceptions as Ex;
$client = new Client('--my-database-id--', '--db-private-token--', ['region' => 'us-west']);
const NUM = 100;
const PROBABILITY_PURCHASED = 0.1;
try
{
// Generate some random purchases of items by users
$purchase_requests = array();
for($i=0; $i < NUM; $i++) {
for($j=0; $j < NUM; $j++) {
if(mt_rand() / mt_getrandmax() < PROBABILITY_PURCHASED) {
$request = new Reqs\AddPurchase("user-{$i}", "item-{$j}",
['cascadeCreate' => true] // Use cascadeCreate to create the
// yet non-existing users and items
);
array_push($purchase_requests, $request);
}
}
}
echo "Send purchases\n";
$res = $client->send(new Reqs\Batch($purchase_requests)); //Use Batch for faster processing of larger data
// Get 5 recommendations for user 'user-25'
$response = $client->send(new Reqs\RecommendItemsToUser('user-25', 5));
echo 'Recommended items: ' . json_encode($response, JSON_PRETTY_PRINT) . "\n";
// User scrolled down - get next 3 recommended items
$response = $client->send(new Reqs\RecommendNextItems($response['recommId'], 3));
echo 'Next recommended items: ' . json_encode($response, JSON_PRETTY_PRINT) . "\n";
}
catch(Ex\ApiException $e)
{
//use fallback
}
use Recombee\RecommApi\Client;
use Recombee\RecommApi\Requests as Reqs;
use Recombee\RecommApi\Exceptions as Ex;
const NUM = 100;
const PROBABILITY_PURCHASED = 0.1;
$client = new Client('--my-database-id--', '--db-private-token--', ['region' => 'ap-se']);
$client->send(new Reqs\ResetDatabase()); // Clear everything from the database
/*
We will use computers as items in this example
Computers have five properties
- price (floating point number)
- number of processor cores (integer number)
- description (string)
- date from which it is in stock (timestamp)
- image (url of computer's photo)
*/
// Add properties of items
$client->send(new Reqs\AddItemProperty('price', 'double'));
$client->send(new Reqs\AddItemProperty('num-cores', 'int'));
$client->send(new Reqs\AddItemProperty('description', 'string'));
$client->send(new Reqs\AddItemProperty('in_stock_from', 'timestamp'));
$client->send(new Reqs\AddItemProperty('image', 'image'));
# Prepare requests for setting a catalog of computers
$requests = array();
for($i=0; $i<NUM; $i++)
{
$itemId = "computer-{$i}";
$r = new Reqs\SetItemValues(
$itemId,
//values:
[
'price' => rand(15000, 25000),
'num-cores' => rand(1, 8),
'description' => 'Great computer',
'in_stock_from' => new DateTime('NOW'),
'image' => "http://examplesite.com/products/{$itemId}.jpg"
],
//optional parameters:
['cascadeCreate' => true] // Use cascadeCreate for creating item
// with given itemId, if it doesn't exist]
);
array_push($requests, $r);
}
// Send catalog to the recommender system
$result = $client->send(new Reqs\Batch($requests));
var_dump($result);
// Generate some random purchases of items by users
$requests = array();
for($i=0; $i<NUM; $i++)
for($j=0; $j<NUM; $j++)
if(mt_rand() / mt_getrandmax() < PROBABILITY_PURCHASED)
{
$r = new Reqs\AddPurchase("user-{$i}", "computer-{$j}", ['cascadeCreate' => true]);
array_push($requests, $r);
}
// Send purchases to the recommender system
$client->send(new Reqs\Batch($requests));
// Get 5 items related to item computer-6. Personalize them for user-42, who is currently viewing that item.
// Recommend only computers that have at least 3 cores
$recommended = $client->send(
new Reqs\RecommendItemsToItem('computer-6', 'user-42', 5, ['filter' => "'num-cores'>=3"])
);
echo 'Recommended items with at least 3 processor cores: ' . json_encode($recommended, JSON_PRETTY_PRINT) . "\n";
// Recommend only items that are more expensive then currently viewed item computer-6 (up-sell)
$recommended = $client->send(
new Reqs\RecommendItemsToItem('computer-6', 'user-42', 5,
['filter' => "'price' > context_item[\"price\"]"])
);
echo 'Recommended up-sell items: ' . json_encode($recommended, JSON_PRETTY_PRINT) . "\n";
// Filters, boosters and other settings can be set also in the Admin UI (admin.recombee.com)
// when scenario is specified
$recommended = $client->send(
new Reqs\RecommendItemsToItem('computer-6', 'user-42', 5, ['scenario' => 'product_detail'])
);
// Perform personalized full-text search with a user's search query (e.g. 'computers')
$matches = $client->send(
new Reqs\SearchItems('user-42', 'computers', 5, ['scenario' => 'search_top'])
);
echo 'Matched items: ' . json_encode($matches, JSON_PRETTY_PRINT) . "\n";
use Recombee\RecommApi\Client;
use Recombee\RecommApi\Requests as Reqs;
use Recombee\RecommApi\Exceptions as Ex;
try
{
$recommended = $client->send(
new Reqs\RecommendItemsToItem('computer-6', 'user-42', 5,
['filter' => "'price' > context_item[\"price\"]"])
);
}
catch(Ex\ApiTimeoutException $e)
{
//Handle timeout => use fallback
}
catch(Ex\ResponseException $e)
{
//Handle errorneous request => use fallback
}
catch(Ex\ApiException $e)
{
//ApiException is parent of both ResponseException and ApiTimeoutException
}
composer
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