import requests

url = "https://application_id.applications.lucidworks.com/ai/tokenization/{MODEL_ID}"

payload = {
    "batch": [{ "text": "Mr. and Mrs. Dursley and O'\''Malley, of number four, Privet Drive, were proud to say that they were perfectly normal, thank you very much" }],
    "useCaseConfig": { "dataType": "passage" },
    "modelConfig": {
        "vectorQuantizationMethod": "max-scale",
        "dimReductionSize": 256
    }
}
headers = {"Content-Type": "application/json"}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

HttpResponse<String> response = Unirest.post("https://application_id.applications.lucidworks.com/ai/tokenization/{MODEL_ID}")
  .header("Content-Type", "application/json")
  .body("{\n  \"batch\": [\n    {\n      \"text\": \"Mr. and Mrs. Dursley and O'\\\\''Malley, of number four, Privet Drive, were proud to say that they were perfectly normal, thank you very much\"\n    }\n  ],\n  \"useCaseConfig\": {\n    \"dataType\": \"passage\"\n  },\n  \"modelConfig\": {\n    \"vectorQuantizationMethod\": \"max-scale\",\n    \"dimReductionSize\": 256\n  }\n}")
  .asString();

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({
    batch: [
      {
        text: 'Mr. and Mrs. Dursley and O\'\'\'Malley, of number four, Privet Drive, were proud to say that they were perfectly normal, thank you very much'
      }
    ],
    useCaseConfig: {dataType: 'passage'},
    modelConfig: {vectorQuantizationMethod: 'max-scale', dimReductionSize: 256}
  })
};

fetch('https://application_id.applications.lucidworks.com/ai/tokenization/{MODEL_ID}', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

require 'uri'
require 'net/http'

url = URI("https://application_id.applications.lucidworks.com/ai/tokenization/{MODEL_ID}")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Content-Type"] = 'application/json'
request.body = "{\n  \"batch\": [\n    {\n      \"text\": \"Mr. and Mrs. Dursley and O'\\\\''Malley, of number four, Privet Drive, were proud to say that they were perfectly normal, thank you very much\"\n    }\n  ],\n  \"useCaseConfig\": {\n    \"dataType\": \"passage\"\n  },\n  \"modelConfig\": {\n    \"vectorQuantizationMethod\": \"max-scale\",\n    \"dimReductionSize\": 256\n  }\n}"

response = http.request(request)
puts response.read_body

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://application_id.applications.lucidworks.com/ai/tokenization/{MODEL_ID}"

	payload := strings.NewReader("{\n  \"batch\": [\n    {\n      \"text\": \"Mr. and Mrs. Dursley and O'\\\\''Malley, of number four, Privet Drive, were proud to say that they were perfectly normal, thank you very much\"\n    }\n  ],\n  \"useCaseConfig\": {\n    \"dataType\": \"passage\"\n  },\n  \"modelConfig\": {\n    \"vectorQuantizationMethod\": \"max-scale\",\n    \"dimReductionSize\": 256\n  }\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://application_id.applications.lucidworks.com/ai/tokenization/{MODEL_ID}",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'batch' => [
        [
                'text' => 'Mr. and Mrs. Dursley and O\'\\\'\'Malley, of number four, Privet Drive, were proud to say that they were perfectly normal, thank you very much'
        ]
    ],
    'useCaseConfig' => [
        'dataType' => 'passage'
    ],
    'modelConfig' => [
        'vectorQuantizationMethod' => 'max-scale',
        'dimReductionSize' => 256
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

curl --request POST \
  --url https://application_id.applications.lucidworks.com/ai/tokenization/{MODEL_ID} \
  --header 'Content-Type: application/json' \
  --data @- <<EOF
{
  "batch": [
    {
      "text": "Mr. and Mrs. Dursley and O'\\''Malley, of number four, Privet Drive, were proud to say that they were perfectly normal, thank you very much"
    }
  ],
  "useCaseConfig": {
    "dataType": "passage"
  },
  "modelConfig": {
    "vectorQuantizationMethod": "max-scale",
    "dimReductionSize": 256
  }
}
EOF

{
  "generatedTokens": [
    {
      "tokens": [
        "\"[CLS]\",                 \"query\",                 \":\",                 \"mr\",                 \".\",                 \"and\",                 \"mrs\",                 \".\",                 \"du\",                 \"##rs\",                 \"##ley\",                 \"and\",                 \"o\",                 \"'\",                 \"malley\",                 \",\",                 \"of\",                 \"number\",                 \"four\",                 \",\",                 \"pri\",                 \"##vet\",                 \"drive\",                 \",\",                 \"were\",                 \"proud\",                 \"to\",                 \"say\",                 \"that\",                 \"they\",                 \"were\",                 \"perfectly\",                 \"normal\",                 \",\",                 \"thank\",                 \"you\",                 \"very\",                 \"much\",                 \".\",                 \"[SEP]\""
      ]
    }
  ],
  "tokensUsed": {
    "inputTokens": 40,
    "promptTokens": 148,
    "completionTokens": 0,
    "totalTokens": 175
  }
}