Datasets:

---

benchflow

/

frontierphysics-pr596-evidence

like 0

Follow

BenchFlow 14

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
task_name: string
rollout_name: string
rewards: null
agent: string
agent_name: string
model: string
skill_mode: string
skill_source: string
requested_skills_dir: null
effective_skills_dir: null
skills_sandbox_dir: null
include_task_skills: bool
n_tool_calls: int64
n_skill_invocations: int64
n_prompts: int64
agent_result: struct<n_tool_calls: int64, n_skill_invocations: int64, n_prompts: int64, n_input_tokens: int64, n_o (... 159 chars omitted)
  child 0, n_tool_calls: int64
  child 1, n_skill_invocations: int64
  child 2, n_prompts: int64
  child 3, n_input_tokens: int64
  child 4, n_output_tokens: int64
  child 5, n_cache_read_tokens: int64
  child 6, n_cache_creation_tokens: int64
  child 7, total_tokens: int64
  child 8, cost_usd: null
  child 9, usage_source: string
  child 10, price_source: null
final_metrics: struct<total_prompt_tokens: int64, total_completion_tokens: int64, total_cached_tokens: int64, total (... 16 chars omitted)
  child 0, total_prompt_tokens: int64
  child 1, total_completion_tokens: int64
  child 2, total_cached_tokens: int64
  child 3, total_cost_usd: null
trajectory_summary: struct<steps: int64, tool_call_steps: int64, user_message_steps: int64, agent_message_steps: int64,  (... 162 chars omitted)
  child 0, steps: int64
  child 1, tool_call_steps: int64
  child 2, user_message_steps: int64
  child 3, agent_message_steps: int64
  child 4, agent_thought_steps: int64
  child 5, other_steps: int64
  child 6, event_type_counts: struct<>
  child 7, too
...
  child 2, iterations_run: int64
  child 3, stop_reason: string
  child 4, reward_trajectory: list<item: null>
      child 0, item: null
  child 5, tokens_trajectory: list<item: null>
      child 0, item: null
  child 6, first_pass_iteration: null
  child 7, tokens_to_pass: null
task_digest: string
sandbox_id: null
completion: null
tool_defs: list<item: null>
  child 0, item: null
reward: double
is_truncated: bool
info: struct<task_id: string, task_name: string, rollout_name: string, environment: string, agent: string, (... 125 chars omitted)
  child 0, task_id: string
  child 1, task_name: string
  child 2, rollout_name: string
  child 3, environment: string
  child 4, agent: string
  child 5, agent_name: string
  child 6, model: string
  child 7, source: string
  child 8, rollout_dir: string
  child 9, training_ready: bool
  child 10, training_ready_reason: string
metrics: struct<n_tool_calls: int64, n_prompts: int64>
  child 0, n_tool_calls: int64
  child 1, n_prompts: int64
total_tool_calls: double
score: double
token_usage: struct<input_tokens: double, output_tokens: double, final_input_tokens: double, final_output_tokens: (... 30 chars omitted)
  child 0, input_tokens: double
  child 1, output_tokens: double
  child 2, final_input_tokens: double
  child 3, final_output_tokens: double
  child 4, total_tokens: double
trajectory: list<item: null>
  child 0, item: null
stop_condition: string
is_completed: bool
example_id: int64
prompt: list<item: null>
  child 0, item: null
to
{'example_id': Value('int64'), 'prompt': List(Value('null')), 'completion': Value('null'), 'info': {'task_id': Value('string'), 'task_name': Value('string'), 'rollout_name': Value('string'), 'environment': Value('string'), 'agent': Value('string'), 'agent_name': Value('string'), 'model': Value('string'), 'source': Value('string'), 'rollout_dir': Value('string'), 'training_ready': Value('bool'), 'training_ready_reason': Value('string')}, 'reward': Value('float64'), 'error': {'error': Value('string'), 'error_chain_str': Value('string'), 'error_chain_repr': Value('string')}, 'timing': {'total': Value('float64')}, 'is_completed': Value('bool'), 'is_truncated': Value('bool'), 'stop_condition': Value('string'), 'metrics': {'n_tool_calls': Value('int64'), 'n_prompts': Value('int64')}, 'tool_defs': List(Value('null')), 'token_usage': {'input_tokens': Value('float64'), 'output_tokens': Value('float64'), 'final_input_tokens': Value('float64'), 'final_output_tokens': Value('float64'), 'total_tokens': Value('float64')}, 'score': Value('float64'), 'total_tool_calls': Value('float64'), 'trajectory': List(Value('null'))}
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
              task_name: string
              rollout_name: string
              rewards: null
              agent: string
              agent_name: string
              model: string
              skill_mode: string
              skill_source: string
              requested_skills_dir: null
              effective_skills_dir: null
              skills_sandbox_dir: null
              include_task_skills: bool
              n_tool_calls: int64
              n_skill_invocations: int64
              n_prompts: int64
              agent_result: struct<n_tool_calls: int64, n_skill_invocations: int64, n_prompts: int64, n_input_tokens: int64, n_o (... 159 chars omitted)
                child 0, n_tool_calls: int64
                child 1, n_skill_invocations: int64
                child 2, n_prompts: int64
                child 3, n_input_tokens: int64
                child 4, n_output_tokens: int64
                child 5, n_cache_read_tokens: int64
                child 6, n_cache_creation_tokens: int64
                child 7, total_tokens: int64
                child 8, cost_usd: null
                child 9, usage_source: string
                child 10, price_source: null
              final_metrics: struct<total_prompt_tokens: int64, total_completion_tokens: int64, total_cached_tokens: int64, total (... 16 chars omitted)
                child 0, total_prompt_tokens: int64
                child 1, total_completion_tokens: int64
                child 2, total_cached_tokens: int64
                child 3, total_cost_usd: null
              trajectory_summary: struct<steps: int64, tool_call_steps: int64, user_message_steps: int64, agent_message_steps: int64,  (... 162 chars omitted)
                child 0, steps: int64
                child 1, tool_call_steps: int64
                child 2, user_message_steps: int64
                child 3, agent_message_steps: int64
                child 4, agent_thought_steps: int64
                child 5, other_steps: int64
                child 6, event_type_counts: struct<>
                child 7, too
              ...
                child 2, iterations_run: int64
                child 3, stop_reason: string
                child 4, reward_trajectory: list<item: null>
                    child 0, item: null
                child 5, tokens_trajectory: list<item: null>
                    child 0, item: null
                child 6, first_pass_iteration: null
                child 7, tokens_to_pass: null
              task_digest: string
              sandbox_id: null
              completion: null
              tool_defs: list<item: null>
                child 0, item: null
              reward: double
              is_truncated: bool
              info: struct<task_id: string, task_name: string, rollout_name: string, environment: string, agent: string, (... 125 chars omitted)
                child 0, task_id: string
                child 1, task_name: string
                child 2, rollout_name: string
                child 3, environment: string
                child 4, agent: string
                child 5, agent_name: string
                child 6, model: string
                child 7, source: string
                child 8, rollout_dir: string
                child 9, training_ready: bool
                child 10, training_ready_reason: string
              metrics: struct<n_tool_calls: int64, n_prompts: int64>
                child 0, n_tool_calls: int64
                child 1, n_prompts: int64
              total_tool_calls: double
              score: double
              token_usage: struct<input_tokens: double, output_tokens: double, final_input_tokens: double, final_output_tokens: (... 30 chars omitted)
                child 0, input_tokens: double
                child 1, output_tokens: double
                child 2, final_input_tokens: double
                child 3, final_output_tokens: double
                child 4, total_tokens: double
              trajectory: list<item: null>
                child 0, item: null
              stop_condition: string
              is_completed: bool
              example_id: int64
              prompt: list<item: null>
                child 0, item: null
              to
              {'example_id': Value('int64'), 'prompt': List(Value('null')), 'completion': Value('null'), 'info': {'task_id': Value('string'), 'task_name': Value('string'), 'rollout_name': Value('string'), 'environment': Value('string'), 'agent': Value('string'), 'agent_name': Value('string'), 'model': Value('string'), 'source': Value('string'), 'rollout_dir': Value('string'), 'training_ready': Value('bool'), 'training_ready_reason': Value('string')}, 'reward': Value('float64'), 'error': {'error': Value('string'), 'error_chain_str': Value('string'), 'error_chain_repr': Value('string')}, 'timing': {'total': Value('float64')}, 'is_completed': Value('bool'), 'is_truncated': Value('bool'), 'stop_condition': Value('string'), 'metrics': {'n_tool_calls': Value('int64'), 'n_prompts': Value('int64')}, 'tool_defs': List(Value('null')), 'token_usage': {'input_tokens': Value('float64'), 'output_tokens': Value('float64'), 'final_input_tokens': Value('float64'), 'final_output_tokens': Value('float64'), 'total_tokens': Value('float64')}, 'score': Value('float64'), 'total_tool_calls': Value('float64'), 'trajectory': List(Value('null'))}
              because column names don't match