from mka1 import SDK


with SDK(
    bearer_auth="<YOUR_BEARER_TOKEN_HERE>",
) as sdk:

    res = sdk.llm.evals.cancel_run(run_id="eval_run_aa87e2b1112a455b8deabed784372198")

    # Handle response
    print(res)

{
  "id": "<string>",
  "object": "<unknown>",
  "suite_id": "<string>",
  "suite_version": 0,
  "suite_version_id": "<string>",
  "models": [
    "<string>"
  ],
  "task_ids": [
    "<string>"
  ],
  "judge_model": "<string>",
  "embedding_model": "<string>",
  "generation": {
    "instructions": "<string>",
    "temperature": 1,
    "top_p": 0.5,
    "max_output_tokens": 4503599627370496,
    "max_gen_toks": 4503599627370496,
    "stop": "<string>",
    "until": [
      "<string>"
    ],
    "max_tool_calls": 4503599627370496,
    "reasoning": "<unknown>",
    "text": "<unknown>",
    "tools": [
      null
    ],
    "tool_choice": "<unknown>",
    "parallel_tool_calls": true,
    "presence_penalty": 0,
    "frequency_penalty": 0,
    "top_k": 4503599627370495,
    "min_p": 0.5,
    "repetition_penalty": 1,
    "do_sample": true,
    "extra_body": {},
    "chat_template_kwargs": {},
    "prefill_think": true,
    "use_cache": true,
    "timeout_seconds": 1800,
    "max_retries": 5,
    "max_empty_retries": 5
  },
  "request_counts": {
    "total": 0,
    "completed": 0,
    "failed": 0
  },
  "metrics": {},
  "error": {},
  "artifact_file_ids": [
    "<string>"
  ],
  "metadata": {},
  "created_at": 0,
  "started_at": 0,
  "completed_at": 0,
  "cancelled_at": 0,
  "failed_at": 0
}