curl --request POST \
  --url https://api.galileo.ai/v2/scorers/{scorer_id}/version/luna3 \
  --header 'Content-Type: application/json' \
  --header 'Splunk-AO-API-Key: <api-key>' \
  --data '
{
  "instruction": "<string>",
  "adapter_path": "<string>",
  "class_name_to_vocab_ix": {},
  "threshold": 123
}
'

import requests

url = "https://api.galileo.ai/v2/scorers/{scorer_id}/version/luna3"

payload = {
    "instruction": "<string>",
    "adapter_path": "<string>",
    "class_name_to_vocab_ix": {},
    "threshold": 123
}
headers = {
    "Splunk-AO-API-Key": "<api-key>",
    "Content-Type": "application/json"
}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {'Splunk-AO-API-Key': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    instruction: '<string>',
    adapter_path: '<string>',
    class_name_to_vocab_ix: {},
    threshold: 123
  })
};

fetch('https://api.galileo.ai/v2/scorers/{scorer_id}/version/luna3', 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://api.galileo.ai/v2/scorers/{scorer_id}/version/luna3",
  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([
    'instruction' => '<string>',
    'adapter_path' => '<string>',
    'class_name_to_vocab_ix' => [
        
    ],
    'threshold' => 123
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "Splunk-AO-API-Key: <api-key>"
  ],
]);

$response = curl_exec($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://api.galileo.ai/v2/scorers/{scorer_id}/version/luna3"

	payload := strings.NewReader("{\n  \"instruction\": \"<string>\",\n  \"adapter_path\": \"<string>\",\n  \"class_name_to_vocab_ix\": {},\n  \"threshold\": 123\n}")

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

	req.Header.Add("Splunk-AO-API-Key", "<api-key>")
	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://api.galileo.ai/v2/scorers/{scorer_id}/version/luna3")
  .header("Splunk-AO-API-Key", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"instruction\": \"<string>\",\n  \"adapter_path\": \"<string>\",\n  \"class_name_to_vocab_ix\": {},\n  \"threshold\": 123\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.galileo.ai/v2/scorers/{scorer_id}/version/luna3")

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

request = Net::HTTP::Post.new(url)
request["Splunk-AO-API-Key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"instruction\": \"<string>\",\n  \"adapter_path\": \"<string>\",\n  \"class_name_to_vocab_ix\": {},\n  \"threshold\": 123\n}"

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

{
  "id": "<string>",
  "version": 123,
  "scorer_id": "<string>",
  "created_at": "2023-11-07T05:31:56Z",
  "updated_at": "2023-11-07T05:31:56Z",
  "generated_scorer": {
    "id": "<string>",
    "name": "<string>",
    "chain_poll_template": {
      "template": "<string>",
      "metric_system_prompt": "<string>",
      "metric_description": "<string>",
      "value_field_name": "rating",
      "explanation_field_name": "explanation",
      "metric_few_shot_examples": [
        {
          "generation_prompt_and_response": "<string>",
          "evaluating_response": "<string>"
        }
      ],
      "response_schema": {}
    },
    "created_by": "<string>",
    "created_at": "2023-11-07T05:31:56Z",
    "updated_at": "2023-11-07T05:31:56Z",
    "scoreable_node_types": [
      "chain"
    ],
    "scorer_configuration": {
      "model_alias": "gpt-4.1-mini",
      "num_judges": 3,
      "output_type": "boolean",
      "scoreable_node_types": [
        "<string>"
      ],
      "cot_enabled": false,
      "ground_truth": false,
      "multimodal_capabilities": [
        "vision"
      ]
    },
    "instructions": "<string>",
    "user_prompt": "<string>"
  },
  "registered_scorer": {
    "id": "<string>",
    "name": "<string>",
    "score_type": "<string>",
    "created_at": "2023-11-07T05:31:56Z",
    "updated_at": "2023-11-07T05:31:56Z",
    "created_by": "<string>",
    "data_type": "unknown",
    "scoreable_node_types": [
      "<string>"
    ]
  },
  "finetuned_scorer": {
    "id": "<string>",
    "name": "<string>",
    "lora_task_id": 123,
    "prompt": "<string>",
    "created_at": "2023-11-07T05:31:56Z",
    "updated_at": "2023-11-07T05:31:56Z",
    "created_by": "<string>",
    "lora_weights_path": "<string>",
    "luna_input_type": "span",
    "luna_output_type": "float",
    "class_name_to_vocab_ix": {},
    "executor": "action_completion_luna"
  },
  "luna3_scorer": {
    "instruction": "<string>",
    "adapter_path": "<string>",
    "class_name_to_vocab_ix": {},
    "id": "<string>",
    "organization_id": "<string>",
    "created_at": "2023-11-07T05:31:56Z",
    "updated_at": "2023-11-07T05:31:56Z",
    "threshold": 123,
    "created_by": "<string>"
  },
  "decision_scorer": {
    "id": "<string>",
    "organization_id": "<string>",
    "question": "<string>",
    "created_at": "2023-11-07T05:31:56Z",
    "created_by": "<string>",
    "answer_options": [
      "<string>"
    ]
  },
  "model_name": "<string>",
  "num_judges": 123,
  "cot_enabled": true,
  "runtime": "<string>",
  "code_sha256": "<string>",
  "chain_poll_template": {
    "template": "<string>",
    "metric_system_prompt": "<string>",
    "metric_description": "<string>",
    "value_field_name": "rating",
    "explanation_field_name": "explanation",
    "metric_few_shot_examples": [
      {
        "generation_prompt_and_response": "<string>",
        "evaluating_response": "<string>"
      }
    ],
    "response_schema": {}
  },
  "scoreable_node_types": [
    "<string>"
  ],
  "output_type": "boolean",
  "allowed_model": true,
  "created_by": "<string>",
  "validation_task_id": "<string>",
  "request_id": "<string>"
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>",
      "input": "<unknown>",
      "ctx": {}
    }
  ]
}