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The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
question_id: string
prompt: string
valid: bool
runs_without_an_answer: int64
truncated_turns: int64
on_path: string
off_path: string
on_grounding: double
off_grounding: double
delta: double
on_claims: string
off_claims: string
off_fabricated_tool_result: string
echoed_facts_not_scored: string
on_says_unknown: bool
off_says_unknown: bool
on_answer: string
off_answer: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2503
to
{'question': Value('string'), 'tool': Value('string'), 'condition': Value('string'), 'path_used': Value('string'), 'grounding': Value('float64'), 'facts_hit': Value('int64'), 'n_facts': Value('int64'), 'says_unknown': Value('bool'), 'fabricated_tool_result': Value('bool'), 'confident_claims': Value('int64'), 'calls': Value('int64'), 'seconds': Value('float64'), 'prompt_tokens': Value('int64'), 'completion_tokens': Value('int64'), 'cost_usd': Value('float64'), 'answer': Value('string'), 'valid': Value('bool'), 'truncated_turns': Value('int64')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 783, in write_table
self.write_rows_on_file() # in case there are buffered rows to write first
~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 663, in write_rows_on_file
self._write_table(table)
~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 795, in _write_table
pa_table = table_cast(pa_table, self._schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
question_id: string
prompt: string
valid: bool
runs_without_an_answer: int64
truncated_turns: int64
on_path: string
off_path: string
on_grounding: double
off_grounding: double
delta: double
on_claims: string
off_claims: string
off_fabricated_tool_result: string
echoed_facts_not_scored: string
on_says_unknown: bool
off_says_unknown: bool
on_answer: string
off_answer: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2503
to
{'question': Value('string'), 'tool': Value('string'), 'condition': Value('string'), 'path_used': Value('string'), 'grounding': Value('float64'), 'facts_hit': Value('int64'), 'n_facts': Value('int64'), 'says_unknown': Value('bool'), 'fabricated_tool_result': Value('bool'), 'confident_claims': Value('int64'), 'calls': Value('int64'), 'seconds': Value('float64'), 'prompt_tokens': Value('int64'), 'completion_tokens': Value('int64'), 'cost_usd': Value('float64'), 'answer': Value('string'), 'valid': Value('bool'), 'truncated_turns': Value('int64')}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1850, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
...<4 lines>...
)
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 16 new columns ({'on_claims', 'prompt', 'off_says_unknown', 'off_fabricated_tool_result', 'off_claims', 'off_path', 'on_says_unknown', 'question_id', 'runs_without_an_answer', 'off_answer', 'echoed_facts_not_scored', 'on_answer', 'on_grounding', 'delta', 'off_grounding', 'on_path'}) and 16 missing columns ({'cost_usd', 'grounding', 'n_facts', 'confident_claims', 'answer', 'question', 'path_used', 'condition', 'completion_tokens', 'tool', 'seconds', 'facts_hit', 'calls', 'fabricated_tool_result', 'prompt_tokens', 'says_unknown'}).
This happened while the csv dataset builder was generating data using
hf://datasets/coinhead/lab06-tool-calling/per_turn_tokens.csv (at revision 5fe405f2c56bd91806992f01e05be61e831f199b), ['hf://datasets/coinhead/lab06-tool-calling@5fe405f2c56bd91806992f01e05be61e831f199b/grounding_sweep.csv', 'hf://datasets/coinhead/lab06-tool-calling@5fe405f2c56bd91806992f01e05be61e831f199b/headline_contrast.csv', 'hf://datasets/coinhead/lab06-tool-calling@5fe405f2c56bd91806992f01e05be61e831f199b/per_turn_tokens.csv', 'hf://datasets/coinhead/lab06-tool-calling@5fe405f2c56bd91806992f01e05be61e831f199b/tools_registry.csv', 'hf://datasets/coinhead/lab06-tool-calling@5fe405f2c56bd91806992f01e05be61e831f199b/trace_stages.csv', 'hf://datasets/coinhead/lab06-tool-calling@5fe405f2c56bd91806992f01e05be61e831f199b/traces.csv']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1868, in _prepare_split_single
num_examples, num_bytes = writer.finalize()
~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 803, in finalize
self.write_rows_on_file()
~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 663, in write_rows_on_file
self._write_table(table)
~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 795, in _write_table
pa_table = table_cast(pa_table, self._schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
question_id: string
prompt: string
valid: bool
runs_without_an_answer: int64
truncated_turns: int64
on_path: string
off_path: string
on_grounding: double
off_grounding: double
delta: double
on_claims: string
off_claims: string
off_fabricated_tool_result: string
echoed_facts_not_scored: string
on_says_unknown: bool
off_says_unknown: bool
on_answer: string
off_answer: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2503
to
{'question': Value('string'), 'tool': Value('string'), 'condition': Value('string'), 'path_used': Value('string'), 'grounding': Value('float64'), 'facts_hit': Value('int64'), 'n_facts': Value('int64'), 'says_unknown': Value('bool'), 'fabricated_tool_result': Value('bool'), 'confident_claims': Value('int64'), 'calls': Value('int64'), 'seconds': Value('float64'), 'prompt_tokens': Value('int64'), 'completion_tokens': Value('int64'), 'cost_usd': Value('float64'), 'answer': Value('string'), 'valid': Value('bool'), 'truncated_turns': Value('int64')}
because column names don't match
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1879, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
question string | tool string | condition string | path_used string | grounding float64 | facts_hit int64 | n_facts int64 | says_unknown bool | fabricated_tool_result bool | confident_claims int64 | calls int64 | seconds float64 | prompt_tokens int64 | completion_tokens int64 | cost_usd float64 | answer string | valid bool | truncated_turns int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
drug_tier | get_drug_info | tools on | native | 0.5 | 1 | 2 | false | false | 1 | 2 | 2.59 | 1,154 | 189 | 0 | Based on the MIS 752 Lab 6 synthetic formulary data, zephadril is assigned to **formulary tier 3** and **requires prior authorisation**. This information comes from the drug record retrieved via the `get_drug_info` tool. | true | 0 |
drug_tier | get_drug_info | tools off | tools-disabled | 0 | 0 | 2 | false | false | 0 | 1 | 3.35 | 481 | 219 | 0 | User Safety: safe | true | 0 |
drug_flags | get_drug_info | tools on | native | 0.75 | 3 | 4 | false | false | 2 | 3 | 7.7 | 2,279 | 348 | 0 | Renavex is flagged against **zephadril** and **neurvolan**, and it carries the monitoring label **stub-monitor-2 (invented label)** (source: MIS 752 Lab 6 invented formulary v1). | true | 0 |
drug_absent | get_drug_info | tools on | native | 0.429 | 3 | 7 | true | false | 0 | 2 | 1.7 | 1,379 | 159 | 0 | There is no record for xyloprane in the MIS 752 Lab 6 formulary — the lookup returned "found: false." I cannot assign a tier because the drug is not in the formulary. (I am relying on the `get_drug_info` tool result, which explicitly states xyloprane is not in the invented formulary v1.) | true | 0 |
drug_absent | get_drug_info | tools off | tools-disabled | 0 | 0 | 7 | false | false | 0 | 1 | 1.13 | 165 | 61 | 0 | <tool_call>search_formulary
<arg_key>drug_name</arg_key>
<arg_value>xyloprane</arg_value>
</tool_call> | true | 0 |
ed_surge | forecast_ed_arrivals | tools on | native | 0.667 | 2 | 3 | false | false | 0 | 2 | 4.69 | 1,143 | 360 | 0 | The peak day is 2026-10-10 (Saturday) with 243 predicted arrivals. There are 3 days flagged as a surge: 2026-10-05, 2026-10-09, and 2026-10-10. This information comes from the forecast_ed_arrivals tool result. | true | 0 |
ed_surge | forecast_ed_arrivals | tools off | tools-disabled | 0 | 0 | 3 | false | false | 0 | 1 | 6.18 | 173 | 609 | 0 | <|tool_call_start|>[tool_call(name='get_forecast', arguments={'start_date': '2026-10-05', 'days': 7})]<|tool_call_end|> | true | 0 |
null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | true | 0 |
drug_tier | null | null | null | null | null | null | null | null | null | null | 0.91 | 562 | 57 | null | null | null | null |
drug_tier | null | null | null | null | null | null | null | null | null | null | 1.68 | 592 | 132 | null | null | null | null |
drug_tier-forced | null | null | null | null | null | null | null | null | null | null | 0.91 | 562 | 57 | null | null | null | null |
drug_tier-forced | null | null | null | null | null | null | null | null | null | null | 1.68 | 592 | 132 | null | null | null | null |
ed_surge | null | null | null | null | null | null | null | null | null | null | 2.98 | 481 | 164 | null | null | null | null |
ed_surge | null | null | null | null | null | null | null | null | null | null | 1.71 | 662 | 196 | null | null | null | null |
drug_flags | null | null | null | null | null | null | null | null | null | null | 0.95 | 597 | 93 | null | null | null | null |
drug_flags | null | null | null | null | null | null | null | null | null | null | 4.83 | 838 | 203 | null | null | null | null |
drug_flags | null | null | null | null | null | null | null | null | null | null | 1.92 | 844 | 52 | null | null | null | null |
drug_absent | null | null | null | null | null | null | null | null | null | null | 0.57 | 605 | 48 | null | null | null | null |
drug_absent | null | null | null | null | null | null | null | null | null | null | 1.13 | 774 | 111 | null | null | null | null |
null | get_drug_info | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
null | forecast_ed_arrivals | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 0.91 | 562 | 57 | null | null | null | null |
null | get_drug_info | null | native | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | get_drug_info | null | native | null | null | null | null | null | null | null | 0.000061 | 0 | 0 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 1.68 | 592 | 132 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | null | null | tools-disabled | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | null | null | tools-disabled | null | null | null | null | null | null | null | 3.35 | 481 | 219 | null | null | null | null |
null | null | null | tools-disabled | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 0.91 | 562 | 57 | null | null | null | null |
null | get_drug_info | null | native | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | get_drug_info | null | native | null | null | null | null | null | null | null | 0.000055 | 0 | 0 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 1.68 | 592 | 132 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 2.98 | 481 | 164 | null | null | null | null |
null | forecast_ed_arrivals | null | native | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | forecast_ed_arrivals | null | native | null | null | null | null | null | null | null | 0.000393 | 0 | 0 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 1.71 | 662 | 196 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 0.95 | 597 | 93 | null | null | null | null |
null | get_drug_info | null | native | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | get_drug_info | null | native | null | null | null | null | null | null | null | 0.000041 | 0 | 0 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 4.83 | 838 | 203 | null | null | null | null |
null | get_drug_info | null | native | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | get_drug_info | null | native | null | null | null | null | null | null | null | 0.000062 | 0 | 0 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 1.92 | 844 | 52 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | null | null | tools-disabled | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | null | null | tools-disabled | null | null | null | null | null | null | null | 8.31 | 156 | 2,000 | null | null | null | null |
null | null | null | tools-disabled | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 0.57 | 605 | 48 | null | null | null | null |
null | get_drug_info | null | native | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | get_drug_info | null | native | null | null | null | null | null | null | null | 0.000054 | 0 | 0 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 1.13 | 774 | 111 | null | null | null | null |
null | null | null | native | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | null | null | tools-disabled | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | null | null | tools-disabled | null | null | null | null | null | null | null | 1.13 | 165 | 61 | null | null | null | null |
null | null | null | tools-disabled | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | null | null | tools-disabled | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
null | null | null | tools-disabled | null | null | null | null | null | null | null | 6.18 | 173 | 609 | null | null | null | null |
null | null | null | tools-disabled | null | null | null | null | null | null | null | 0 | 0 | 0 | null | null | null | null |
What is the formulary tier for zephadril, and does it require prior authorisation? | null | null | native | null | null | null | null | null | null | 2 | 2.59 | 1,154 | 189 | 0 | null | true | 0 |
What is the formulary tier for zephadril, and does it require prior authorisation? | null | null | tools-disabled | null | null | null | null | null | null | 1 | 3.35 | 481 | 219 | 0 | null | true | 0 |
What is the formulary tier for zephadril, and does it require prior authorisation? | null | null | native | null | null | null | null | null | null | 2 | 2.59 | 1,154 | 189 | 0 | null | true | 0 |
Starting 2026-10-05, forecast ED arrivals for the next 7 days. Which day is the peak and how many days are flagged as a surge? | null | null | native | null | null | null | null | null | null | 2 | 4.69 | 1,143 | 360 | 0 | null | true | 0 |
Which other formulary drugs is renavex flagged against, and what monitoring label does it carry? | null | null | native | null | null | null | null | null | null | 3 | 7.7 | 2,279 | 348 | 0 | null | true | 0 |
Which other formulary drugs is renavex flagged against, and what monitoring label does it carry? | null | null | tools-disabled | null | null | null | null | null | null | 1 | 8.31 | 156 | 2,000 | 0 | null | false | 1 |
What is the formulary tier for xyloprane? If you cannot find it, say so plainly. | null | null | native | null | null | null | null | null | null | 2 | 1.7 | 1,379 | 159 | 0 | null | true | 0 |
What is the formulary tier for xyloprane? If you cannot find it, say so plainly. | null | null | tools-disabled | null | null | null | null | null | null | 1 | 1.13 | 165 | 61 | 0 | null | true | 0 |
Starting 2026-10-05, forecast ED arrivals for the next 7 days. Which day is the peak and how many days are flagged as a surge? | null | null | tools-disabled | null | null | null | null | null | null | 1 | 6.18 | 173 | 609 | 0 | null | true | 0 |
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