curl --request GET \
  --url https://api.orq.ai/v2/evaluators/{id} \
  --header 'Authorization: Bearer <token>'

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

fetch('https://api.orq.ai/v2/evaluators/{id}', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

import requests

url = "https://api.orq.ai/v2/evaluators/{id}"

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

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

print(response.text)

{
  "metadata": {
    "required_model_with_tools_support": true,
    "required_retrieval_context": true,
    "required_expected_output": true,
    "supported_on_input_type": true,
    "supported_on_output_type": true,
    "support_use_as_guardrail": true
  },
  "_id": "<string>",
  "display_name": "<string>",
  "description": "<string>",
  "owner": "<string>",
  "domain_id": "<string>",
  "type": "llm_eval",
  "prompt": "<string>",
  "enabled": true,
  "created": "2026-08-04T15:14:03.981Z",
  "updated": "2026-08-04T15:14:03.981Z",
  "created_by_id": "<string>",
  "updated_by_id": "<string>",
  "guardrail_config": {
    "type": "boolean",
    "value": true,
    "enabled": true,
    "alert_on_failure": false
  },
  "repetitions": 2,
  "model": {
    "id": "<string>",
    "integration_id": "<string>",
    "model_parameters": {
      "temperature": 123,
      "max_tokens": 123,
      "top_k": 123,
      "top_p": 123,
      "frequency_penalty": 123,
      "presence_penalty": 123,
      "reasoning_effort": "<string>",
      "budget_tokens": 123
    }
  },
  "jury": {
    "judges": [
      {
        "model": {
          "id": "<string>",
          "integration_id": "<string>",
          "model_parameters": {
            "temperature": 123,
            "max_tokens": 123,
            "top_k": 123,
            "top_p": 123,
            "frequency_penalty": 123,
            "presence_penalty": 123,
            "reasoning_effort": "<string>",
            "budget_tokens": 123
          }
        },
        "retry": {
          "count": 2,
          "on_codes": [
            429,
            500,
            502,
            503,
            504
          ]
        },
        "fallbacks": []
      }
    ],
    "replacement_judges": [],
    "min_successful_judges": 2,
    "tie_value": "Tie"
  },
  "categories": [
    "<string>"
  ],
  "categorical_labels": [
    {
      "value": "<string>",
      "description": "<string>"
    }
  ],
  "dataset_id": "<string>"
}

{
  "message": "Evaluator not found"
}