curl 'https://my.orq.ai/v3/experiments/<experiment_id>/runs' \
  --header 'Authorization: Bearer $ORQ_API_KEY'

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

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

const page = await client.experiments.listRuns({ experimentId: '<experiment_id>' });

for (const run of page.data) {
  console.log(run.runId, run.status, run.cellStatusCounts);
}

import os
from orq_ai_sdk import Orq

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

page = client.experiments.list_runs(experiment_id="<experiment_id>")

for run in page.data:
    print(run.run_id, run.status, run.cell_status_counts)

{
  "data": [
    {
      "run_id": "<string>",
      "experiment_id": "<string>",
      "key": "<string>",
      "status": "RUN_STATUS_UNSPECIFIED",
      "dataset_id": "<string>",
      "row_count": 123,
      "cell_status_counts": {
        "not_run": 123,
        "queued": 123,
        "running": 123,
        "completed": 123,
        "failed": 123,
        "canceled": 123
      },
      "columns": [
        {
          "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
        }
      ],
      "settings": {
        "concurrency": 123,
        "timeout": "<string>",
        "max_turns": 123,
        "hidden_column_ids": [
          "<string>"
        ]
      },
      "started_at": "2023-11-07T05:31:56Z",
      "completed_at": "2023-11-07T05:31:56Z",
      "created_at": "2023-11-07T05:31:56Z",
      "updated_at": "2023-11-07T05:31:56Z",
      "metrics": {},
      "stats": {
        "total_cost": 123,
        "total_errors": 123,
        "total_done": 123
      },
      "created_by_id": "<string>"
    }
  ],
  "has_more": true
}

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