Datasets:

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benchflow

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frontierphysics-pr709-evidence

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BenchFlow 14

Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
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_output_tokens: int64, n_cache_read_tokens: int64, n_cache_creation_tokens: int64, total_tokens: int64, cost_usd: null, usage_source: string, price_source: null>
final_metrics: struct<total_prompt_tokens: int64, total_completion_tokens: int64, total_cached_tokens: int64, total_cost_usd: null>
trajectory_summary: struct<steps: int64, tool_call_steps: int64, user_message_steps: int64, agent_message_steps: int64, agent_thought_steps: int64, other_steps: int64, event_type_counts: struct<>, tool_call_status_counts: struct<>, partial_trajectory: bool, trajectory_source: null>
usage_tracking: struct<requested: string, status: string, environment: string, endpoint_kind: string, usage_source: string>
error: string
error_category: string
verifier_error: null
verifier_error_category: null
export_error: null
idle_timeout_info: null
agent_timeout_info: null
sandbox_startup_info: null
transport_error_info: null
verifier_timeout_info: null
api_error_info: null
suspected_api_error_info: null
partial_trajectory: bool
trajectory_source: null
started_at: string
finished_at: string
timing: struct<total: double>
scenes: list<item: struct<name: string, skills_dir: null, roles: list<item: struct<name: string, agent: string, model: string, reasoning_effort: null, timeout_sec: null, idle_timeout_sec: null, skills_dir: null, capabilities: null, env_keys: list<item: null>>>, turns: list<item: struct<role: string, has_prompt: bool>>>>
loop: struct<strategy: string, params: struct<k: int64>, iterations_run: int64, stop_reason: string, reward_trajectory: list<item: null>, tokens_trajectory: list<item: null>, first_pass_iteration: null, tokens_to_pass: null>
task_digest: string
sandbox_id: null
vs
example_id: int64
prompt: list<item: null>
completion: null
info: struct<task_id: string, task_name: string, rollout_name: string, environment: string, agent: string, agent_name: string, model: string, source: string, rollout_dir: string, training_ready: bool, training_ready_reason: string>
reward: double
error: struct<error: string, error_chain_str: string, error_chain_repr: string>
timing: struct<total: double>
is_completed: bool
is_truncated: bool
stop_condition: string
metrics: struct<n_tool_calls: int64, n_prompts: int64>
tool_defs: list<item: null>
token_usage: struct<input_tokens: double, output_tokens: double, final_input_tokens: double, final_output_tokens: double, total_tokens: double>
score: double
total_tool_calls: double
trajectory: list<item: null>
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 249, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4379, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2661, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2839, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 564, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                                 ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^
                File "pyarrow/table.pxi", line 5039, in pyarrow.lib.Table.from_batches
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              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_output_tokens: int64, n_cache_read_tokens: int64, n_cache_creation_tokens: int64, total_tokens: int64, cost_usd: null, usage_source: string, price_source: null>
              final_metrics: struct<total_prompt_tokens: int64, total_completion_tokens: int64, total_cached_tokens: int64, total_cost_usd: null>
              trajectory_summary: struct<steps: int64, tool_call_steps: int64, user_message_steps: int64, agent_message_steps: int64, agent_thought_steps: int64, other_steps: int64, event_type_counts: struct<>, tool_call_status_counts: struct<>, partial_trajectory: bool, trajectory_source: null>
              usage_tracking: struct<requested: string, status: string, environment: string, endpoint_kind: string, usage_source: string>
              error: string
              error_category: string
              verifier_error: null
              verifier_error_category: null
              export_error: null
              idle_timeout_info: null
              agent_timeout_info: null
              sandbox_startup_info: null
              transport_error_info: null
              verifier_timeout_info: null
              api_error_info: null
              suspected_api_error_info: null
              partial_trajectory: bool
              trajectory_source: null
              started_at: string
              finished_at: string
              timing: struct<total: double>
              scenes: list<item: struct<name: string, skills_dir: null, roles: list<item: struct<name: string, agent: string, model: string, reasoning_effort: null, timeout_sec: null, idle_timeout_sec: null, skills_dir: null, capabilities: null, env_keys: list<item: null>>>, turns: list<item: struct<role: string, has_prompt: bool>>>>
              loop: struct<strategy: string, params: struct<k: int64>, iterations_run: int64, stop_reason: string, reward_trajectory: list<item: null>, tokens_trajectory: list<item: null>, first_pass_iteration: null, tokens_to_pass: null>
              task_digest: string
              sandbox_id: null
              vs
              example_id: int64
              prompt: list<item: null>
              completion: null
              info: struct<task_id: string, task_name: string, rollout_name: string, environment: string, agent: string, agent_name: string, model: string, source: string, rollout_dir: string, training_ready: bool, training_ready_reason: string>
              reward: double
              error: struct<error: string, error_chain_str: string, error_chain_repr: string>
              timing: struct<total: double>
              is_completed: bool
              is_truncated: bool
              stop_condition: string
              metrics: struct<n_tool_calls: int64, n_prompts: int64>
              tool_defs: list<item: null>
              token_usage: struct<input_tokens: double, output_tokens: double, final_input_tokens: double, final_output_tokens: double, total_tokens: double>
              score: double
              total_tool_calls: double
              trajectory: list<item: null>