Datasets:

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benchflow

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frontierphysics-pr560-evidence

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BenchFlow 14

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
job_name: string
agent: string
model: string
environment: string
concurrency: int64
agent_idle_timeout_sec: null
usage_tracking: struct<requested: string>
  child 0, requested: string
loop: struct<strategy: string, params: struct<k: int64>>
  child 0, strategy: string
  child 1, params: struct<k: int64>
      child 0, k: int64
total: int64
passed: int64
failed: int64
errored: int64
pass: int64
fail: int64
error: int64
verifier_errored: int64
idle_timeout: int64
error_categories: struct<other: int64>
  child 0, other: int64
verifier_error_categories: null
score: string
score_ratio: double
score_excl_errors: string
score_excl_errors_ratio: double
elapsed_sec: double
memory_score: null
memory_score_coverage: double
memory: struct<scored: int64, avg_score: null, score: null>
  child 0, scored: int64
  child 1, avg_score: null
  child 2, score: null
memory_scores: struct<>
total_skill_invocations: int64
avg_skill_invocations: double
total_input_tokens: int64
total_output_tokens: int64
total_cache_read_tokens: int64
total_cache_creation_tokens: int64
total_tokens: int64
total_cost_usd: int64
avg_cost_per_trial_usd: null
telemetry_coverage: double
total_tool_calls: int64
avg_tool_calls_per_task: double
max_tool_calls_per_task: int64
total_trajectory_steps: int64
avg_trajectory_steps_per_task: double
max_trajectory_steps_per_task: int64
total_trajectory_tool_call_steps: int64
avg_trajectory_tool_call_steps_per_task: double
max_trajectory_tool_call_steps_per_task: int64
trajectory_sum
...
c: null
max_agent_setup_time_sec: null
agent_execution_time_sec: double
avg_agent_execution_time_sec: null
max_agent_execution_time_sec: null
verifier_time_sec: double
avg_verifier_time_sec: null
max_verifier_time_sec: null
total_time_sec: double
avg_total_time_sec: double
max_total_time_sec: double
reward: double
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
completion: null
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
is_completed: bool
prompt: list<item: null>
  child 0, item: null
stop_condition: string
trajectory: list<item: null>
  child 0, item: null
example_id: int64
timing: struct<total: double>
  child 0, total: double
metrics: struct<n_tool_calls: int64, n_prompts: int64>
  child 0, n_tool_calls: int64
  child 1, n_prompts: int64
tool_defs: list<item: null>
  child 0, item: null
is_truncated: bool
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
              job_name: string
              agent: string
              model: string
              environment: string
              concurrency: int64
              agent_idle_timeout_sec: null
              usage_tracking: struct<requested: string>
                child 0, requested: string
              loop: struct<strategy: string, params: struct<k: int64>>
                child 0, strategy: string
                child 1, params: struct<k: int64>
                    child 0, k: int64
              total: int64
              passed: int64
              failed: int64
              errored: int64
              pass: int64
              fail: int64
              error: int64
              verifier_errored: int64
              idle_timeout: int64
              error_categories: struct<other: int64>
                child 0, other: int64
              verifier_error_categories: null
              score: string
              score_ratio: double
              score_excl_errors: string
              score_excl_errors_ratio: double
              elapsed_sec: double
              memory_score: null
              memory_score_coverage: double
              memory: struct<scored: int64, avg_score: null, score: null>
                child 0, scored: int64
                child 1, avg_score: null
                child 2, score: null
              memory_scores: struct<>
              total_skill_invocations: int64
              avg_skill_invocations: double
              total_input_tokens: int64
              total_output_tokens: int64
              total_cache_read_tokens: int64
              total_cache_creation_tokens: int64
              total_tokens: int64
              total_cost_usd: int64
              avg_cost_per_trial_usd: null
              telemetry_coverage: double
              total_tool_calls: int64
              avg_tool_calls_per_task: double
              max_tool_calls_per_task: int64
              total_trajectory_steps: int64
              avg_trajectory_steps_per_task: double
              max_trajectory_steps_per_task: int64
              total_trajectory_tool_call_steps: int64
              avg_trajectory_tool_call_steps_per_task: double
              max_trajectory_tool_call_steps_per_task: int64
              trajectory_sum
              ...
              c: null
              max_agent_setup_time_sec: null
              agent_execution_time_sec: double
              avg_agent_execution_time_sec: null
              max_agent_execution_time_sec: null
              verifier_time_sec: double
              avg_verifier_time_sec: null
              max_verifier_time_sec: null
              total_time_sec: double
              avg_total_time_sec: double
              max_total_time_sec: double
              reward: double
              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
              completion: null
              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
              is_completed: bool
              prompt: list<item: null>
                child 0, item: null
              stop_condition: string
              trajectory: list<item: null>
                child 0, item: null
              example_id: int64
              timing: struct<total: double>
                child 0, total: double
              metrics: struct<n_tool_calls: int64, n_prompts: int64>
                child 0, n_tool_calls: int64
                child 1, n_prompts: int64
              tool_defs: list<item: null>
                child 0, item: null
              is_truncated: bool
              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