Datasets:

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BaiLing

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intellisu-agentsuite

Like 0

Error code:   DatasetGenerationError
Exception:    TypeError
Message:      Couldn't cast array of type
struct<id: string, task_name: string, ground_truth: string, tools: list<item: struct<type: string, function: struct<name: string, description: string, parameters: struct<type: string, properties: string, required: list<item: string>>, returns: struct<type: string, description: string, items: struct<type: string>>>>>, prompt_0: string, query_0: string, response_0: string, executed_0: string, result_0: string, prompt_1: string, query_1: string, response_1: string, executed_1: string, result_1: string, prompt_2: string, query_2: string, response_2: string, executed_2: string, result_2: string, prompt_3: string, query_3: string, response_3: string, executed_3: string, result_3: string, prompt_4: string, query_4: string, response_4: string, executed_4: string, result_4: string, prompt_5: string, query_5: string, response_5: string, executed_5: string, result_5: string, prompt_6: string, query_6: string, response_6: string, executed_6: string, result_6: string, prompt_7: string, query_7: string, response_7: string, executed_7: string, result_7: string, prompt_8: string, query_8: string, response_8: string, executed_8: string, result_8: string, prompt_9: string, query_9: string, response_9: string, executed_9: string, result_9: string, prompt_10: string, query_10: string, response_10: string, executed_10: string, result_10: string, prompt_11: string, query_11: string, response_11: string, executed_11: string, result_11: string, Max Turns Hit: string, Invalid Plan: string, Depth: string, Breadth: string, is_correct: bool, Num Functions: string, prompt_12: string, query_12: string, response_12: string, executed_12: string, result_12: string, prompt_13: string, query_13: string, response_13: string, executed_13: string, result_13: string, prompt_14: string, query_14: string, response_14: string, executed_14: string, result_14: string, prompt_15: string, query_15: string, response_15: string, executed_15: string, result_15: string, prompt_16: string, query_16: string, response_16: string, executed_16: string, result_16: string, prompt_17: string, query_17: string, response_17: string, executed_17: string, result_17: string, prompt_18: string, query_18: string, response_18: string, executed_18: string, result_18: string>
to
{'id': Value('string'), 'task_name': Value('string'), 'ground_truth': Value('string'), 'tools': List({'type': Value('string'), 'function': {'name': Value('string'), 'description': Value('string'), 'parameters': {'type': Value('string'), 'properties': Json(decode=True), 'required': List(Value('string'))}}}), 'prompt_0': Value('string'), 'query_0': Value('string'), 'response_0': Value('string'), 'executed_0': Value('string'), 'result_0': Value('string'), 'is_correct': Value('bool')}
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                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 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2312, in cast_table_to_schema
                  cast_array_to_feature(
                  ~~~~~~~~~~~~~~~~~~~~~^
                      table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                      feature,
                      ^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ~~~~^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2158, in cast_array_to_feature
                  raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
              TypeError: Couldn't cast array of type
              struct<id: string, task_name: string, ground_truth: string, tools: list<item: struct<type: string, function: struct<name: string, description: string, parameters: struct<type: string, properties: string, required: list<item: string>>, returns: struct<type: string, description: string, items: struct<type: string>>>>>, prompt_0: string, query_0: string, response_0: string, executed_0: string, result_0: string, prompt_1: string, query_1: string, response_1: string, executed_1: string, result_1: string, prompt_2: string, query_2: string, response_2: string, executed_2: string, result_2: string, prompt_3: string, query_3: string, response_3: string, executed_3: string, result_3: string, prompt_4: string, query_4: string, response_4: string, executed_4: string, result_4: string, prompt_5: string, query_5: string, response_5: string, executed_5: string, result_5: string, prompt_6: string, query_6: string, response_6: string, executed_6: string, result_6: string, prompt_7: string, query_7: string, response_7: string, executed_7: string, result_7: string, prompt_8: string, query_8: string, response_8: string, executed_8: string, result_8: string, prompt_9: string, query_9: string, response_9: string, executed_9: string, result_9: string, prompt_10: string, query_10: string, response_10: string, executed_10: string, result_10: string, prompt_11: string, query_11: string, response_11: string, executed_11: string, result_11: string, Max Turns Hit: string, Invalid Plan: string, Depth: string, Breadth: string, is_correct: bool, Num Functions: string, prompt_12: string, query_12: string, response_12: string, executed_12: string, result_12: string, prompt_13: string, query_13: string, response_13: string, executed_13: string, result_13: string, prompt_14: string, query_14: string, response_14: string, executed_14: string, result_14: string, prompt_15: string, query_15: string, response_15: string, executed_15: string, result_15: string, prompt_16: string, query_16: string, response_16: string, executed_16: string, result_16: string, prompt_17: string, query_17: string, response_17: string, executed_17: string, result_17: string, prompt_18: string, query_18: string, response_18: string, executed_18: string, result_18: string>
              to
              {'id': Value('string'), 'task_name': Value('string'), 'ground_truth': Value('string'), 'tools': List({'type': Value('string'), 'function': {'name': Value('string'), 'description': Value('string'), 'parameters': {'type': Value('string'), 'properties': Json(decode=True), 'required': List(Value('string'))}}}), 'prompt_0': Value('string'), 'query_0': Value('string'), 'response_0': Value('string'), 'executed_0': Value('string'), 'result_0': Value('string'), 'is_correct': Value('bool')}
              
              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 dataset