curl 'https://my.orq.ai/v3/experiments/<experiment_id>/runs/<run_id>/evaluators' \
  --header 'Authorization: Bearer $ORQ_API_KEY' \
  --header 'Content-Type: application/json' \
  --data '{ "evaluator_id": "<evaluator_id>" }'

import { Orq } from '@orq-ai/node';

const client = new Orq({ apiKey: process.env.ORQ_API_KEY });

await client.experiments.createEval({
  experimentId: '<experiment_id>',
  runId: '<run_id>',
  evaluatorId: '<evaluator_id>',
});

import os
from orq_ai_sdk import Orq

client = Orq(api_key=os.environ["ORQ_API_KEY"])

column = client.experiments.create_eval(
    experiment_id="<experiment_id>",
    run_id="<run_id>",
    evaluator_id="<evaluator_id>",
)

{
  "column_id": "<string>",
  "key": "<string>",
  "display_name": "<string>",
  "position": 123,
  "active": true,
  "prompt": {
    "prompt_config": {},
    "messages_source": "MESSAGES_SOURCE_UNSPECIFIED",
    "engine": "<string>",
    "tools": [
      {}
    ],
    "knowledge_bases": [
      {}
    ],
    "metadata": {}
  },
  "agent": {
    "agent_key": "<string>",
    "messages_source": "MESSAGES_SOURCE_UNSPECIFIED",
    "messages": [
      {}
    ],
    "engine": "<string>",
    "parent_id": "<string>",
    "agent_tag": "<string>"
  },
  "openresponse": {},
  "evaluator": {
    "evaluator_id": "<string>",
    "evaluator_name": "<string>",
    "evaluator_type": "<string>",
    "evaluator_output_type": "<string>"
  },
  "review": {
    "human_eval_id": "<string>",
    "human_eval_name": "<string>",
    "human_eval_type": "<string>"
  },
  "dataset": {
    "column_type": "<string>"
  },
  "metric": {
    "metric_key": "<string>"
  },
  "job_output": {
    "job_name": "<string>"
  },
  "width": 123
}

{
  "message": "<string>",
  "code": 123,
  "details": [
    "<unknown>"
  ]
}