Datasets:

---

space1637

/

iapyx-finetune-report

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
ranking: list<item: struct<name: string, kind: string, slug: string, display: string, risk_macro_f1: double,  (... 107 chars omitted)
  child 0, item: struct<name: string, kind: string, slug: string, display: string, risk_macro_f1: double, n: int64, s (... 95 chars omitted)
      child 0, name: string
      child 1, kind: string
      child 2, slug: string
      child 3, display: string
      child 4, risk_macro_f1: double
      child 5, n: int64
      child 6, schema: double
      child 7, tool_acc: double
      child 8, overcall_supp: double
      child 9, latency: double
      child 10, created: timestamp[s]
tiebreak: string
label: string
risk: struct<total: int64, json_validity: double, schema_conformance: double, risk_level_accuracy: double, (... 96 chars omitted)
  child 0, total: int64
  child 1, json_validity: double
  child 2, schema_conformance: double
  child 3, risk_level_accuracy: double
  child 4, latency_s_mean: double
  child 5, preds: list<item: struct<id: string, raw: string, risk_level: string>>
      child 0, item: struct<id: string, raw: string, risk_level: string>
          child 0, id: string
          child 1, raw: string
          child 2, risk_level: string
model: string
backend: string
fc: struct<total: int64, matched_predictions: int64, tool_selection_correct: int64, tool_selection_accur (... 299 chars omitted)
  child 0, total: int64
  child 1, matched_predictions: int64
  child 2, tool_selection_correct: int64
  child 3, tool_selection_accuracy: double
  child 4, argument_format_correct: int64
  child 5, argument_format_accuracy: double
  child 6, negative_total: int64
  child 7, no_call_suppressed: int64
  child 8, overcall_suppression_rate: double
  child 9, overcall_count: int64
  child 10, missing_prediction_count: int64
  child 11, invalid_prediction_count: int64
  child 12, json_validity: double
  child 13, latency_s_mean: double
to
{'label': Value('string'), 'backend': Value('string'), 'model': Value('string'), 'risk': {'total': Value('int64'), 'json_validity': Value('float64'), 'schema_conformance': Value('float64'), 'risk_level_accuracy': Value('float64'), 'latency_s_mean': Value('float64'), 'preds': List({'id': Value('string'), 'raw': Value('string'), 'risk_level': Value('string')})}, 'fc': {'total': Value('int64'), 'matched_predictions': Value('int64'), 'tool_selection_correct': Value('int64'), 'tool_selection_accuracy': Value('float64'), 'argument_format_correct': Value('int64'), 'argument_format_accuracy': Value('float64'), 'negative_total': Value('int64'), 'no_call_suppressed': Value('int64'), 'overcall_suppression_rate': Value('float64'), 'overcall_count': Value('int64'), 'missing_prediction_count': Value('int64'), 'invalid_prediction_count': Value('int64'), 'json_validity': Value('float64'), 'latency_s_mean': Value('float64')}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              ranking: list<item: struct<name: string, kind: string, slug: string, display: string, risk_macro_f1: double,  (... 107 chars omitted)
                child 0, item: struct<name: string, kind: string, slug: string, display: string, risk_macro_f1: double, n: int64, s (... 95 chars omitted)
                    child 0, name: string
                    child 1, kind: string
                    child 2, slug: string
                    child 3, display: string
                    child 4, risk_macro_f1: double
                    child 5, n: int64
                    child 6, schema: double
                    child 7, tool_acc: double
                    child 8, overcall_supp: double
                    child 9, latency: double
                    child 10, created: timestamp[s]
              tiebreak: string
              label: string
              risk: struct<total: int64, json_validity: double, schema_conformance: double, risk_level_accuracy: double, (... 96 chars omitted)
                child 0, total: int64
                child 1, json_validity: double
                child 2, schema_conformance: double
                child 3, risk_level_accuracy: double
                child 4, latency_s_mean: double
                child 5, preds: list<item: struct<id: string, raw: string, risk_level: string>>
                    child 0, item: struct<id: string, raw: string, risk_level: string>
                        child 0, id: string
                        child 1, raw: string
                        child 2, risk_level: string
              model: string
              backend: string
              fc: struct<total: int64, matched_predictions: int64, tool_selection_correct: int64, tool_selection_accur (... 299 chars omitted)
                child 0, total: int64
                child 1, matched_predictions: int64
                child 2, tool_selection_correct: int64
                child 3, tool_selection_accuracy: double
                child 4, argument_format_correct: int64
                child 5, argument_format_accuracy: double
                child 6, negative_total: int64
                child 7, no_call_suppressed: int64
                child 8, overcall_suppression_rate: double
                child 9, overcall_count: int64
                child 10, missing_prediction_count: int64
                child 11, invalid_prediction_count: int64
                child 12, json_validity: double
                child 13, latency_s_mean: double
              to
              {'label': Value('string'), 'backend': Value('string'), 'model': Value('string'), 'risk': {'total': Value('int64'), 'json_validity': Value('float64'), 'schema_conformance': Value('float64'), 'risk_level_accuracy': Value('float64'), 'latency_s_mean': Value('float64'), 'preds': List({'id': Value('string'), 'raw': Value('string'), 'risk_level': Value('string')})}, 'fc': {'total': Value('int64'), 'matched_predictions': Value('int64'), 'tool_selection_correct': Value('int64'), 'tool_selection_accuracy': Value('float64'), 'argument_format_correct': Value('int64'), 'argument_format_accuracy': Value('float64'), 'negative_total': Value('int64'), 'no_call_suppressed': Value('int64'), 'overcall_suppression_rate': Value('float64'), 'overcall_count': Value('int64'), 'missing_prediction_count': Value('int64'), 'invalid_prediction_count': Value('int64'), 'json_validity': Value('float64'), 'latency_s_mean': Value('float64')}}
              because column names don't match