Datasets:

---

SitongGong

/

paper_final_results

Like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
index: int64
question: string
answer: string
question_type: string
pred: struct<answer: string, reasoning: string, tools_used: list<item: string>>
  child 0, answer: string
  child 1, reasoning: string
  child 2, tools_used: list<item: string>
      child 0, item: string
gpt_score: int64
gpt_raw: string
aggregated: struct<per_main_type: struct<Instant: struct<precision: double, recall: double, f1: double, num_pred (... 3737 chars omitted)
  child 0, per_main_type: struct<Instant: struct<precision: double, recall: double, f1: double, num_pred: int64, num_gt: int64 (... 376 chars omitted)
      child 0, Instant: struct<precision: double, recall: double, f1: double, num_pred: int64, num_gt: int64, num_matched: i (... 5 chars omitted)
          child 0, precision: double
          child 1, recall: double
          child 2, f1: double
          child 3, num_pred: int64
          child 4, num_gt: int64
          child 5, num_matched: int64
      child 1, Short-Term: struct<precision: double, recall: double, f1: double, num_pred: int64, num_gt: int64, num_matched: i (... 5 chars omitted)
          child 0, precision: double
          child 1, recall: double
          child 2, f1: double
          child 3, num_pred: int64
          child 4, num_gt: int64
          child 5, num_matched: int64
      child 2, Long-Term: struct<precision: double, recall: double, f1: double, num_pred: int64, num_gt: int64, num_matched: i (... 5 chars omitted)
          child 0, precision: double
         
...
e, num_pred: int64, num_gt: int64, num_matched: i (... 5 chars omitted)
              child 0, precision: double
              child 1, recall: double
              child 2, f1: double
              child 3, num_pred: int64
              child 4, num_gt: int64
              child 5, num_matched: int64
          child 9, task_reminder: struct<precision: double, recall: double, f1: double, num_pred: int64, num_gt: int64, num_matched: i (... 5 chars omitted)
              child 0, precision: double
              child 1, recall: double
              child 2, f1: double
              child 3, num_pred: int64
              child 4, num_gt: int64
              child 5, num_matched: int64
      child 2, overall: struct<precision: double, recall: double, f1: double, num_pred: int64, num_gt: int64, num_matched: i (... 5 chars omitted)
          child 0, precision: double
          child 1, recall: double
          child 2, f1: double
          child 3, num_pred: int64
          child 4, num_gt: int64
          child 5, num_matched: int64
config: struct<matching_strategy: string, persons: list<item: string>, days: list<item: string>, tolerance:  (... 94 chars omitted)
  child 0, matching_strategy: string
  child 1, persons: list<item: string>
      child 0, item: string
  child 2, days: list<item: string>
      child 0, item: string
  child 3, tolerance: double
  child 4, caption_model: string
  child 5, llm_model: string
  child 6, response_name: string
  child 7, no_llm_scoring: bool
to
{'config': {'matching_strategy': Value('string'), 'persons': List(Value('string')), 'days': List(Value('string')), 'tolerance': Value('float64'), 'caption_model': Value('string'), 'llm_model': Value('string'), 'response_name': Value('string'), 'no_llm_scoring': Value('bool')}, 'aggregated': {'per_main_type': {'Instant': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'Short-Term': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'Long-Term': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'Episodic': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}}, 'per_sub_type': {'safety': {'main_type': Value('string'), 'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'tool_use': {'main_type': Value('string'), 'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'next_step_guidance
...
y': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'resource_reminder': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'habit_coaching': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'memory_link_contextual': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'routine_optimization': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'memory_recall': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'task_reminder': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}}, 'overall': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}}}}
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 544, 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 3052, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 361, 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 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              index: int64
              question: string
              answer: string
              question_type: string
              pred: struct<answer: string, reasoning: string, tools_used: list<item: string>>
                child 0, answer: string
                child 1, reasoning: string
                child 2, tools_used: list<item: string>
                    child 0, item: string
              gpt_score: int64
              gpt_raw: string
              aggregated: struct<per_main_type: struct<Instant: struct<precision: double, recall: double, f1: double, num_pred (... 3737 chars omitted)
                child 0, per_main_type: struct<Instant: struct<precision: double, recall: double, f1: double, num_pred: int64, num_gt: int64 (... 376 chars omitted)
                    child 0, Instant: struct<precision: double, recall: double, f1: double, num_pred: int64, num_gt: int64, num_matched: i (... 5 chars omitted)
                        child 0, precision: double
                        child 1, recall: double
                        child 2, f1: double
                        child 3, num_pred: int64
                        child 4, num_gt: int64
                        child 5, num_matched: int64
                    child 1, Short-Term: struct<precision: double, recall: double, f1: double, num_pred: int64, num_gt: int64, num_matched: i (... 5 chars omitted)
                        child 0, precision: double
                        child 1, recall: double
                        child 2, f1: double
                        child 3, num_pred: int64
                        child 4, num_gt: int64
                        child 5, num_matched: int64
                    child 2, Long-Term: struct<precision: double, recall: double, f1: double, num_pred: int64, num_gt: int64, num_matched: i (... 5 chars omitted)
                        child 0, precision: double
                       
              ...
              e, num_pred: int64, num_gt: int64, num_matched: i (... 5 chars omitted)
                            child 0, precision: double
                            child 1, recall: double
                            child 2, f1: double
                            child 3, num_pred: int64
                            child 4, num_gt: int64
                            child 5, num_matched: int64
                        child 9, task_reminder: struct<precision: double, recall: double, f1: double, num_pred: int64, num_gt: int64, num_matched: i (... 5 chars omitted)
                            child 0, precision: double
                            child 1, recall: double
                            child 2, f1: double
                            child 3, num_pred: int64
                            child 4, num_gt: int64
                            child 5, num_matched: int64
                    child 2, overall: struct<precision: double, recall: double, f1: double, num_pred: int64, num_gt: int64, num_matched: i (... 5 chars omitted)
                        child 0, precision: double
                        child 1, recall: double
                        child 2, f1: double
                        child 3, num_pred: int64
                        child 4, num_gt: int64
                        child 5, num_matched: int64
              config: struct<matching_strategy: string, persons: list<item: string>, days: list<item: string>, tolerance:  (... 94 chars omitted)
                child 0, matching_strategy: string
                child 1, persons: list<item: string>
                    child 0, item: string
                child 2, days: list<item: string>
                    child 0, item: string
                child 3, tolerance: double
                child 4, caption_model: string
                child 5, llm_model: string
                child 6, response_name: string
                child 7, no_llm_scoring: bool
              to
              {'config': {'matching_strategy': Value('string'), 'persons': List(Value('string')), 'days': List(Value('string')), 'tolerance': Value('float64'), 'caption_model': Value('string'), 'llm_model': Value('string'), 'response_name': Value('string'), 'no_llm_scoring': Value('bool')}, 'aggregated': {'per_main_type': {'Instant': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'Short-Term': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'Long-Term': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'Episodic': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}}, 'per_sub_type': {'safety': {'main_type': Value('string'), 'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'tool_use': {'main_type': Value('string'), 'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'next_step_guidance
              ...
              y': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'resource_reminder': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'habit_coaching': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'memory_link_contextual': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'routine_optimization': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'memory_recall': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}, 'task_reminder': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}}, 'overall': {'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_pred': Value('int64'), 'num_gt': Value('int64'), 'num_matched': Value('int64')}}}}
              because column names don't match