[Obsoleto] Criar um job de fine-tuning

curl --request POST \
  --url https://apigw.mka1.com/api/v1/llm/fine_tuning/jobs \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "meetkai:functionary-medium",
  "training_file": "file_abc123",
  "suffix": "my-model",
  "method": {
    "type": "supervised",
    "supervised": {
      "hyperparameters": {
        "n_epochs": 3
      }
    }
  }
}
'

import requests

url = "https://apigw.mka1.com/api/v1/llm/fine_tuning/jobs"

payload = {
    "model": "meetkai:functionary-medium",
    "training_file": "file_abc123",
    "suffix": "my-model",
    "method": {
        "type": "supervised",
        "supervised": { "hyperparameters": { "n_epochs": 3 } }
    }
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    model: 'meetkai:functionary-medium',
    training_file: 'file_abc123',
    suffix: 'my-model',
    method: {type: 'supervised', supervised: {hyperparameters: {n_epochs: 3}}}
  })
};

fetch('https://apigw.mka1.com/api/v1/llm/fine_tuning/jobs', 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://apigw.mka1.com/api/v1/llm/fine_tuning/jobs",
  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([
    'model' => 'meetkai:functionary-medium',
    'training_file' => 'file_abc123',
    'suffix' => 'my-model',
    'method' => [
        'type' => 'supervised',
        'supervised' => [
                'hyperparameters' => [
                                'n_epochs' => 3
                ]
        ]
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

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

curl_close($curl);

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

package main

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

func main() {

	url := "https://apigw.mka1.com/api/v1/llm/fine_tuning/jobs"

	payload := strings.NewReader("{\n  \"model\": \"meetkai:functionary-medium\",\n  \"training_file\": \"file_abc123\",\n  \"suffix\": \"my-model\",\n  \"method\": {\n    \"type\": \"supervised\",\n    \"supervised\": {\n      \"hyperparameters\": {\n        \"n_epochs\": 3\n      }\n    }\n  }\n}")

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

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

}

HttpResponse<String> response = Unirest.post("https://apigw.mka1.com/api/v1/llm/fine_tuning/jobs")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"model\": \"meetkai:functionary-medium\",\n  \"training_file\": \"file_abc123\",\n  \"suffix\": \"my-model\",\n  \"method\": {\n    \"type\": \"supervised\",\n    \"supervised\": {\n      \"hyperparameters\": {\n        \"n_epochs\": 3\n      }\n    }\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://apigw.mka1.com/api/v1/llm/fine_tuning/jobs")

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

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"model\": \"meetkai:functionary-medium\",\n  \"training_file\": \"file_abc123\",\n  \"suffix\": \"my-model\",\n  \"method\": {\n    \"type\": \"supervised\",\n    \"supervised\": {\n      \"hyperparameters\": {\n        \"n_epochs\": 3\n      }\n    }\n  }\n}"

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

{
  "id": "ftjob_aa87e2b1112a455b8deabed784372198",
  "object": "fine_tuning.job",
  "created_at": 1704067200,
  "model": "meetkai:functionary-medium",
  "training_file": "file_abc123",
  "validation_file": null,
  "fine_tuned_model": null,
  "organization_id": "org-123",
  "status": "running",
  "result_files": [],
  "seed": 42,
  "hyperparameters": {
    "n_epochs": 3,
    "batch_size": "auto",
    "learning_rate_multiplier": "auto"
  },
  "method": {
    "type": "supervised",
    "supervised": {
      "hyperparameters": {
        "n_epochs": 3
      }
    }
  },
  "finished_at": null,
  "estimated_finish": null,
  "trained_tokens": null,
  "error": null,
  "integrations": null,
  "metadata": {
    "experiment": "v1"
  },
  "suffix": "my-model"
}