curl --request GET \
  --url https://training-suite.app.simplismart.ai/job/get/ \
  --header 'Authorization: Bearer <token>'

import requests

url = "https://training-suite.app.simplismart.ai/job/get/"

headers = {"Authorization": "Bearer <token>"}

response = requests.get(url, headers=headers)

print(response.text)

const options = {method: 'GET', headers: {Authorization: 'Bearer <token>'}};

fetch('https://training-suite.app.simplismart.ai/job/get/', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://training-suite.app.simplismart.ai/job/get/",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "GET",
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>"
  ],
]);

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

curl_close($curl);

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

package main

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

func main() {

	url := "https://training-suite.app.simplismart.ai/job/get/"

	req, _ := http.NewRequest("GET", url, nil)

	req.Header.Add("Authorization", "Bearer <token>")

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

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

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.get("https://training-suite.app.simplismart.ai/job/get/")
  .header("Authorization", "Bearer <token>")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://training-suite.app.simplismart.ai/job/get/")

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

request = Net::HTTP::Get.new(url)
request["Authorization"] = 'Bearer <token>'

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

{
  "request_id": "<string>",
  "experiment_name": "<string>",
  "created_at": "2023-11-07T05:31:56Z",
  "updated_at": "2023-11-07T05:31:56Z",
  "started_at": "2023-11-07T05:31:56Z",
  "completed_at": "2023-11-07T05:31:56Z",
  "progress": 123,
  "dataset_config": {
    "preprocessing": {
      "lazy_tokenize": true,
      "streaming": true,
      "prompt": {
        "system": "<string>",
        "max_length": 123,
        "template": "<string>"
      }
    },
    "split": {
      "ratios": [
        123
      ]
    }
  },
  "model_details": {
    "base_model": "<string>",
    "quantization": {}
  },
  "train_config": {
    "tuner_backend": "<string>",
    "hyperparameters": {
      "num_epochs": 123,
      "per_device_train_batch_size": 123,
      "per_device_eval_batch_size": 123,
      "gradient_checkpointing": true,
      "save_steps": 123,
      "save_total_limit": 123,
      "eval_steps": 123,
      "logging_steps": 123,
      "learning_rate": 123,
      "dataloader_num_workers": 123
    },
    "adapter_config": {
      "r": 123,
      "alpha": 123,
      "dropout": 123,
      "targets": [
        "<string>"
      ]
    },
    "distributed": {}
  },
  "dataset_details": {
    "dataset_name": "<string>",
    "dataset_path": "<string>",
    "dataset_description": "<string>",
    "secret_id": "<string>",
    "region": "<string>"
  },
  "infra_config": {
    "gpu_count": 2,
    "infra_type": "<string>",
    "node_count": 2
  },
  "output_model_path": "<string>",
  "error_message": "<string>"
}