Personalizer Client v1.1-preview.3
Personalizer Service is an Azure Cognitive Service that makes it easy to target content and experiences without complex pre-analysis or cleanup of past data. Given a context and featurized content, the Personalizer Service returns which content item to show to users in rewardActionId. As rewards are sent in response to the use of rewardActionId, the reinforcement learning algorithm will improve the model and improve performance of future rank calls.
Update Service Configuration.
Update the Personalizer service configuration.
Select the testing console in the region where you created your resource:
Open API testing consoleRequest URL
Request headers
string
Media type of the body sent to the API.
string
Subscription key which provides access to this API. Found in your Cognitive Services accounts.
Request body
The personalizer service configuration.
{
"rewardWaitTime": "PT10M",
"defaultReward": 0,
"rewardAggregation": "earliest",
"explorationPercentage": 0.2,
"modelExportFrequency": "PT5M",
"logMirrorEnabled": true,
"logMirrorSasUri": "https://testblob.blob.core.windows.net/container?se=2020-08-13T00%3A00Z&sp=rwl&spr=https&sv=2018-11-09&sr=c&sig=signature",
"logRetentionDays": 7,
"learningMode": "Online",
"isAutoOptimizationEnabled": true,
"autoOptimizationFrequency": "P7D",
"autoOptimizationStartDate": "2019-01-19T00:00:00Z"
}{
"description": "The configuration of the service.",
"required": [
"defaultReward",
"explorationPercentage",
"logRetentionDays",
"modelExportFrequency",
"rewardAggregation",
"rewardWaitTime"
],
"type": "object",
"properties": {
"rewardWaitTime": {
"format": "duration",
"description": "The time span waited until a request is marked with the default reward\r\nand should be between 5 seconds and 2 days.\r\nFor example, PT5M (5 mins). For information about the time format,\r\nsee http://en.wikipedia.org/wiki/ISO_8601#Durations",
"type": "string"
},
"defaultReward": {
"format": "float",
"description": "The reward given if a reward is not received within the specified wait time.",
"maximum": 1,
"minimum": -1,
"type": "number"
},
"rewardAggregation": {
"description": "The function used to process rewards, if multiple reward scores are received before rewardWaitTime is over.",
"maxLength": 256,
"type": "string"
},
"explorationPercentage": {
"format": "float",
"description": "The percentage of rank responses that will use exploration.",
"maximum": 1,
"minimum": 0,
"type": "number"
},
"modelExportFrequency": {
"format": "duration",
"description": "Personalizer will start using the most updated trained model for online ranks automatically every specified time period.\r\nFor example, PT5M (5 mins). For information about the time format,\r\nsee http://en.wikipedia.org/wiki/ISO_8601#Durations",
"type": "string"
},
"logMirrorEnabled": {
"description": "Flag indicates whether log mirroring is enabled.",
"type": "boolean"
},
"logMirrorSasUri": {
"description": "Azure storage account container SAS URI for log mirroring.",
"type": "string"
},
"logRetentionDays": {
"format": "int32",
"description": "Number of days historical logs are to be maintained. -1 implies the logs will never be deleted.",
"maximum": 2147483647,
"minimum": -1,
"type": "integer"
},
"lastConfigurationEditDate": {
"format": "date-time",
"description": "Last time model training configuration was updated",
"type": "string"
},
"learningMode": {
"description": "Learning Modes for Personalizer",
"enum": [
"Online",
"Apprentice",
"LoggingOnly"
],
"type": "string",
"x-ms-enum": {
"name": "LearningMode",
"modelAsString": true
}
},
"latestApprenticeModeMetrics": {
"required": [
"lastProcessedEventTime",
"numberOfEvents",
"numberOfImitatedEvents",
"startTime",
"sumOfImitatedRewards",
"sumOfRewards"
],
"type": "object",
"properties": {
"startTime": {
"format": "date-time",
"type": "string"
},
"lastProcessedEventTime": {
"format": "date-time",
"type": "string"
},
"lastBatchMetrics": {
"required": [
"numberOfEvents",
"numberOfImitatedEvents",
"sumOfImitatedRewards",
"sumOfRewards"
],
"type": "object",
"properties": {
"numberOfEvents": {
"format": "int64",
"type": "integer"
},
"sumOfRewards": {
"format": "float",
"type": "number"
},
"numberOfImitatedEvents": {
"format": "int64",
"type": "integer"
},
"sumOfImitatedRewards": {
"format": "float",
"type": "number"
}
}
},
"numberOfEvents": {
"format": "int64",
"type": "integer"
},
"sumOfRewards": {
"format": "float",
"type": "number"
},
"numberOfImitatedEvents": {
"format": "int64",
"type": "integer"
},
"sumOfImitatedRewards": {
"format": "float",
"type": "number"
}
}
},
"isAutoOptimizationEnabled": {
"description": "Flag indicating whether Personalizer will automatically optimize Learning Settings by running Offline Evaluations periodically.",
"type": "boolean"
},
"autoOptimizationFrequency": {
"format": "duration",
"description": "Frequency of automatic optimization. Only relevant if IsAutoOptimizationEnabled is true.\r\nFor example, PT5M (5 mins). For information about the time format,\r\n\\r\\nsee http://en.wikipedia.org/wiki/ISO_8601#Durations",
"type": "string"
},
"autoOptimizationStartDate": {
"format": "date-time",
"description": "Date when the first automatic optimization evaluation must be performed. Only relevant if IsAutoOptimizationEnabled is true.",
"type": "string"
}
},
"example": {
"rewardWaitTime": "PT10M",
"defaultReward": 0,
"rewardAggregation": "earliest",
"explorationPercentage": 0.2,
"modelExportFrequency": "PT5M",
"logMirrorEnabled": true,
"logMirrorSasUri": "https://testblob.blob.core.windows.net/container?se=2020-08-13T00%3A00Z&sp=rwl&spr=https&sv=2018-11-09&sr=c&sig=signature",
"logRetentionDays": 7,
"learningMode": "Online",
"isAutoOptimizationEnabled": true,
"autoOptimizationFrequency": "P7D",
"autoOptimizationStartDate": "2019-01-19T00:00:00Z"
}
}Response 200
Success
{
"rewardWaitTime": "PT10M",
"defaultReward": 0,
"rewardAggregation": "earliest",
"explorationPercentage": 0.2,
"modelExportFrequency": "PT5M",
"logMirrorEnabled": true,
"logMirrorSasUri": "https://testblob.blob.core.windows.net/container?se=2020-08-13T00%3A00Z&sp=rwl&spr=https&sv=2018-11-09&sr=c&sig=signature",
"logRetentionDays": 7,
"lastConfigurationEditDate": "2019-01-19T00:00:00Z",
"learningMode": "Online",
"isAutoOptimizationEnabled": true,
"autoOptimizationFrequency": "P7D",
"autoOptimizationStartDate": "2019-01-19T00:00:00Z"
}{
"description": "The configuration of the service.",
"required": [
"defaultReward",
"explorationPercentage",
"logRetentionDays",
"modelExportFrequency",
"rewardAggregation",
"rewardWaitTime"
],
"type": "object",
"properties": {
"rewardWaitTime": {
"format": "duration",
"description": "The time span waited until a request is marked with the default reward\r\nand should be between 5 seconds and 2 days.\r\nFor example, PT5M (5 mins). For information about the time format,\r\nsee http://en.wikipedia.org/wiki/ISO_8601#Durations",
"type": "string"
},
"defaultReward": {
"format": "float",
"description": "The reward given if a reward is not received within the specified wait time.",
"maximum": 1,
"minimum": -1,
"type": "number"
},
"rewardAggregation": {
"description": "The function used to process rewards, if multiple reward scores are received before rewardWaitTime is over.",
"maxLength": 256,
"type": "string"
},
"explorationPercentage": {
"format": "float",
"description": "The percentage of rank responses that will use exploration.",
"maximum": 1,
"minimum": 0,
"type": "number"
},
"modelExportFrequency": {
"format": "duration",
"description": "Personalizer will start using the most updated trained model for online ranks automatically every specified time period.\r\nFor example, PT5M (5 mins). For information about the time format,\r\nsee http://en.wikipedia.org/wiki/ISO_8601#Durations",
"type": "string"
},
"logMirrorEnabled": {
"description": "Flag indicates whether log mirroring is enabled.",
"type": "boolean"
},
"logMirrorSasUri": {
"description": "Azure storage account container SAS URI for log mirroring.",
"type": "string"
},
"logRetentionDays": {
"format": "int32",
"description": "Number of days historical logs are to be maintained. -1 implies the logs will never be deleted.",
"maximum": 2147483647,
"minimum": -1,
"type": "integer"
},
"lastConfigurationEditDate": {
"format": "date-time",
"description": "Last time model training configuration was updated",
"type": "string"
},
"learningMode": {
"description": "Learning Modes for Personalizer",
"enum": [
"Online",
"Apprentice",
"LoggingOnly"
],
"type": "string",
"x-ms-enum": {
"name": "LearningMode",
"modelAsString": true
}
},
"latestApprenticeModeMetrics": {
"required": [
"lastProcessedEventTime",
"numberOfEvents",
"numberOfImitatedEvents",
"startTime",
"sumOfImitatedRewards",
"sumOfRewards"
],
"type": "object",
"properties": {
"startTime": {
"format": "date-time",
"type": "string"
},
"lastProcessedEventTime": {
"format": "date-time",
"type": "string"
},
"lastBatchMetrics": {
"required": [
"numberOfEvents",
"numberOfImitatedEvents",
"sumOfImitatedRewards",
"sumOfRewards"
],
"type": "object",
"properties": {
"numberOfEvents": {
"format": "int64",
"type": "integer"
},
"sumOfRewards": {
"format": "float",
"type": "number"
},
"numberOfImitatedEvents": {
"format": "int64",
"type": "integer"
},
"sumOfImitatedRewards": {
"format": "float",
"type": "number"
}
}
},
"numberOfEvents": {
"format": "int64",
"type": "integer"
},
"sumOfRewards": {
"format": "float",
"type": "number"
},
"numberOfImitatedEvents": {
"format": "int64",
"type": "integer"
},
"sumOfImitatedRewards": {
"format": "float",
"type": "number"
}
}
},
"isAutoOptimizationEnabled": {
"description": "Flag indicating whether Personalizer will automatically optimize Learning Settings by running Offline Evaluations periodically.",
"type": "boolean"
},
"autoOptimizationFrequency": {
"format": "duration",
"description": "Frequency of automatic optimization. Only relevant if IsAutoOptimizationEnabled is true.\r\nFor example, PT5M (5 mins). For information about the time format,\r\n\\r\\nsee http://en.wikipedia.org/wiki/ISO_8601#Durations",
"type": "string"
},
"autoOptimizationStartDate": {
"format": "date-time",
"description": "Date when the first automatic optimization evaluation must be performed. Only relevant if IsAutoOptimizationEnabled is true.",
"type": "string"
}
},
"example": {
"rewardWaitTime": "PT10M",
"defaultReward": 0,
"rewardAggregation": "earliest",
"explorationPercentage": 0.2,
"modelExportFrequency": "PT5M",
"logMirrorEnabled": true,
"logMirrorSasUri": "https://testblob.blob.core.windows.net/container?se=2020-08-13T00%3A00Z&sp=rwl&spr=https&sv=2018-11-09&sr=c&sig=signature",
"logRetentionDays": 7,
"learningMode": "Online",
"isAutoOptimizationEnabled": true,
"autoOptimizationFrequency": "P7D",
"autoOptimizationStartDate": "2019-01-19T00:00:00Z"
}
}Response 400
Updating defaultReward, rewardWaitTime and rewardAggregation when changing learning mode from Online to Apprentice mode and vice versa is not allowed. Make the mode change and then change the additional settings with an additional API call.
Code samples
@ECHO OFF
curl -v -X PUT "https://*.cognitiveservices.azure.us/personalizer/v1.1-preview.3/configurations/service"
-H "Content-Type: application/json"
-H "Ocp-Apim-Subscription-Key: {subscription key}"
--data-ascii "{body}"
using System;
using System.Net.Http.Headers;
using System.Text;
using System.Net.Http;
using System.Web;
namespace CSHttpClientSample
{
static class Program
{
static void Main()
{
MakeRequest();
Console.WriteLine("Hit ENTER to exit...");
Console.ReadLine();
}
static async void MakeRequest()
{
var client = new HttpClient();
var queryString = HttpUtility.ParseQueryString(string.Empty);
// Request headers
client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", "{subscription key}");
var uri = "https://*.cognitiveservices.azure.us/personalizer/v1.1-preview.3/configurations/service?" + queryString;
HttpResponseMessage response;
// Request body
byte[] byteData = Encoding.UTF8.GetBytes("{body}");
using (var content = new ByteArrayContent(byteData))
{
content.Headers.ContentType = new MediaTypeHeaderValue("< your content type, i.e. application/json >");
response = await client.PutAsync(uri, content);
}
}
}
} // // This sample uses the Apache HTTP client from HTTP Components (http://hc.apache.org/httpcomponents-client-ga/)
import java.net.URI;
import org.apache.http.HttpEntity;
import org.apache.http.HttpResponse;
import org.apache.http.client.HttpClient;
import org.apache.http.client.methods.HttpGet;
import org.apache.http.client.utils.URIBuilder;
import org.apache.http.impl.client.HttpClients;
import org.apache.http.util.EntityUtils;
public class JavaSample
{
public static void main(String[] args)
{
HttpClient httpclient = HttpClients.createDefault();
try
{
URIBuilder builder = new URIBuilder("https://*.cognitiveservices.azure.us/personalizer/v1.1-preview.3/configurations/service");
URI uri = builder.build();
HttpPut request = new HttpPut(uri);
request.setHeader("Content-Type", "application/json");
request.setHeader("Ocp-Apim-Subscription-Key", "{subscription key}");
// Request body
StringEntity reqEntity = new StringEntity("{body}");
request.setEntity(reqEntity);
HttpResponse response = httpclient.execute(request);
HttpEntity entity = response.getEntity();
if (entity != null)
{
System.out.println(EntityUtils.toString(entity));
}
}
catch (Exception e)
{
System.out.println(e.getMessage());
}
}
}
<!DOCTYPE html>
<html>
<head>
<title>JSSample</title>
<script src="http://ajax.googleapis.com/ajax/libs/jquery/1.9.0/jquery.min.js"></script>
</head>
<body>
<script type="text/javascript">
$(function() {
var params = {
// Request parameters
};
$.ajax({
url: "https://*.cognitiveservices.azure.us/personalizer/v1.1-preview.3/configurations/service?" + $.param(params),
beforeSend: function(xhrObj){
// Request headers
xhrObj.setRequestHeader("Content-Type","application/json");
xhrObj.setRequestHeader("Ocp-Apim-Subscription-Key","{subscription key}");
},
type: "PUT",
// Request body
data: "{body}",
})
.done(function(data) {
alert("success");
})
.fail(function() {
alert("error");
});
});
</script>
</body>
</html>
#import <Foundation/Foundation.h>
int main(int argc, const char * argv[])
{
NSAutoreleasePool * pool = [[NSAutoreleasePool alloc] init];
NSString* path = @"https://*.cognitiveservices.azure.us/personalizer/v1.1-preview.3/configurations/service";
NSArray* array = @[
// Request parameters
@"entities=true",
];
NSString* string = [array componentsJoinedByString:@"&"];
path = [path stringByAppendingFormat:@"?%@", string];
NSLog(@"%@", path);
NSMutableURLRequest* _request = [NSMutableURLRequest requestWithURL:[NSURL URLWithString:path]];
[_request setHTTPMethod:@"PUT"];
// Request headers
[_request setValue:@"application/json" forHTTPHeaderField:@"Content-Type"];
[_request setValue:@"{subscription key}" forHTTPHeaderField:@"Ocp-Apim-Subscription-Key"];
// Request body
[_request setHTTPBody:[@"{body}" dataUsingEncoding:NSUTF8StringEncoding]];
NSURLResponse *response = nil;
NSError *error = nil;
NSData* _connectionData = [NSURLConnection sendSynchronousRequest:_request returningResponse:&response error:&error];
if (nil != error)
{
NSLog(@"Error: %@", error);
}
else
{
NSError* error = nil;
NSMutableDictionary* json = nil;
NSString* dataString = [[NSString alloc] initWithData:_connectionData encoding:NSUTF8StringEncoding];
NSLog(@"%@", dataString);
if (nil != _connectionData)
{
json = [NSJSONSerialization JSONObjectWithData:_connectionData options:NSJSONReadingMutableContainers error:&error];
}
if (error || !json)
{
NSLog(@"Could not parse loaded json with error:%@", error);
}
NSLog(@"%@", json);
_connectionData = nil;
}
[pool drain];
return 0;
}
<?php
// This sample uses the Apache HTTP client from HTTP Components (http://hc.apache.org/httpcomponents-client-ga/)
require_once 'HTTP/Request2.php';
$request = new Http_Request2('https://*.cognitiveservices.azure.us/personalizer/v1.1-preview.3/configurations/service');
$url = $request->getUrl();
$headers = array(
// Request headers
'Content-Type' => 'application/json',
'Ocp-Apim-Subscription-Key' => '{subscription key}',
);
$request->setHeader($headers);
$parameters = array(
// Request parameters
);
$url->setQueryVariables($parameters);
$request->setMethod(HTTP_Request2::METHOD_PUT);
// Request body
$request->setBody("{body}");
try
{
$response = $request->send();
echo $response->getBody();
}
catch (HttpException $ex)
{
echo $ex;
}
?>########### Python 2.7 #############
import httplib, urllib, base64
headers = {
# Request headers
'Content-Type': 'application/json',
'Ocp-Apim-Subscription-Key': '{subscription key}',
}
params = urllib.urlencode({
})
try:
conn = httplib.HTTPSConnection('*.cognitiveservices.azure.us')
conn.request("PUT", "/personalizer/v1.1-preview.3/configurations/service?%s" % params, "{body}", headers)
response = conn.getresponse()
data = response.read()
print(data)
conn.close()
except Exception as e:
print("[Errno {0}] {1}".format(e.errno, e.strerror))
####################################
########### Python 3.2 #############
import http.client, urllib.request, urllib.parse, urllib.error, base64
headers = {
# Request headers
'Content-Type': 'application/json',
'Ocp-Apim-Subscription-Key': '{subscription key}',
}
params = urllib.parse.urlencode({
})
try:
conn = http.client.HTTPSConnection('*.cognitiveservices.azure.us')
conn.request("PUT", "/personalizer/v1.1-preview.3/configurations/service?%s" % params, "{body}", headers)
response = conn.getresponse()
data = response.read()
print(data)
conn.close()
except Exception as e:
print("[Errno {0}] {1}".format(e.errno, e.strerror))
####################################require 'net/http'
uri = URI('https://*.cognitiveservices.azure.us/personalizer/v1.1-preview.3/configurations/service')
uri.query = URI.encode_www_form({
})
request = Net::HTTP::Put.new(uri.request_uri)
# Request headers
request['Content-Type'] = 'application/json'
# Request headers
request['Ocp-Apim-Subscription-Key'] = '{subscription key}'
# Request body
request.body = "{body}"
response = Net::HTTP.start(uri.host, uri.port, :use_ssl => uri.scheme == 'https') do |http|
http.request(request)
end
puts response.body