Datasets:

---

phzwart

/

boteval-phenixbb

like 0

Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 3 was different: 
evaluation_metadata: struct<evaluation_date: timestamp[s], total_questions: int64, evaluator: string, scoring_scale: string, description: string>
evaluation_criteria: struct<key_alignment: struct<description: string, scale: string>, strengths_added_value: struct<description: string, scale: string>, missing_info_concerns: struct<description: string, scale: string>, overall_assessment: struct<description: string, scale: string>>
evaluations: list<item: struct<question_id: string, question_text: string, scores: struct<key_alignment: int64, strengths_added_value: int64, missing_info_concerns: int64, overall_assessment: int64>, brief_note: string, key_issue: string, key_concepts_from_reference: list<item: string>, missing_concepts: list<item: string>, additional_notes: string>>
summary_stats: struct<average_scores: struct<key_alignment: double, strengths_added_value: double, missing_info_concerns: double, overall_assessment: double>, questions_below_threshold: int64, threshold_score: int64, most_common_issues: list<item: string>, evaluation_notes: string>
validation_instructions: struct<usage: string, scoring_guidelines: struct<1-3: string, 4-5: string, 6-7: string, 8-9: string, 10: string>, required_fields: list<item: string>, optional_fields: list<item: string>>
session_id: string
vs
evaluation_metadata: struct<evaluation_date: string, total_questions: int64, evaluator: string, scoring_scale: string, description: string>
evaluation_criteria: struct<key_alignment: struct<description: string, scale: string>, strengths_added_value: struct<description: string, scale: string>, missing_info_concerns: struct<description: string, scale: string>, overall_assessment: struct<description: string, scale: string>>
evaluations: list<item: struct<question_id: string, question_text: string, scores: struct<key_alignment: int64, strengths_added_value: int64, missing_info_concerns: int64, overall_assessment: int64>, brief_note: string, key_issue: string, key_concepts_from_reference: list<item: string>, missing_concepts: list<item: string>, additional_notes: string>>
?summary_stats: struct<average_scores: struct<key_alignment: double, strengths_added_value: double, missing_info_concerns: double, overall_assessment: double>, questions_below_threshold: int64, threshold_score: int64, most_common_issues: list<item: string>, evaluation_notes: string>
validation_instructions: struct<usage: string, scoring_guidelines: struct<1-3: string, 4-5: string, 6-7: string, 8-9: string, 10: string>, required_fields: list<item: string>, optional_fields: list<item: string>>
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 228, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 3357, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2111, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2315, in iter
                  for key, example in iterator:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1856, in __iter__
                  for key, pa_table in self._iter_arrow():
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1878, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                File "pyarrow/table.pxi", line 4116, in pyarrow.lib.Table.from_batches
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Schema at index 3 was different: 
              evaluation_metadata: struct<evaluation_date: timestamp[s], total_questions: int64, evaluator: string, scoring_scale: string, description: string>
              evaluation_criteria: struct<key_alignment: struct<description: string, scale: string>, strengths_added_value: struct<description: string, scale: string>, missing_info_concerns: struct<description: string, scale: string>, overall_assessment: struct<description: string, scale: string>>
              evaluations: list<item: struct<question_id: string, question_text: string, scores: struct<key_alignment: int64, strengths_added_value: int64, missing_info_concerns: int64, overall_assessment: int64>, brief_note: string, key_issue: string, key_concepts_from_reference: list<item: string>, missing_concepts: list<item: string>, additional_notes: string>>
              summary_stats: struct<average_scores: struct<key_alignment: double, strengths_added_value: double, missing_info_concerns: double, overall_assessment: double>, questions_below_threshold: int64, threshold_score: int64, most_common_issues: list<item: string>, evaluation_notes: string>
              validation_instructions: struct<usage: string, scoring_guidelines: struct<1-3: string, 4-5: string, 6-7: string, 8-9: string, 10: string>, required_fields: list<item: string>, optional_fields: list<item: string>>
              session_id: string
              vs
              evaluation_metadata: struct<evaluation_date: string, total_questions: int64, evaluator: string, scoring_scale: string, description: string>
              evaluation_criteria: struct<key_alignment: struct<description: string, scale: string>, strengths_added_value: struct<description: string, scale: string>, missing_info_concerns: struct<description: string, scale: string>, overall_assessment: struct<description: string, scale: string>>
              evaluations: list<item: struct<question_id: string, question_text: string, scores: struct<key_alignment: int64, strengths_added_value: int64, missing_info_concerns: int64, overall_assessment: int64>, brief_note: string, key_issue: string, key_concepts_from_reference: list<item: string>, missing_concepts: list<item: string>, additional_notes: string>>
              ?summary_stats: struct<average_scores: struct<key_alignment: double, strengths_added_value: double, missing_info_concerns: double, overall_assessment: double>, questions_below_threshold: int64, threshold_score: int64, most_common_issues: list<item: string>, evaluation_notes: string>
              validation_instructions: struct<usage: string, scoring_guidelines: struct<1-3: string, 4-5: string, 6-7: string, 8-9: string, 10: string>, required_fields: list<item: string>, optional_fields: list<item: string>>