Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
type: string
text: string
tool_call_id: string
kind: string
title: string
status: string
content: list<item: struct<type: string, content: struct<type: string, text: string>>>
child 0, item: struct<type: string, content: struct<type: string, text: string>>
child 0, type: string
child 1, content: struct<type: string, text: string>
child 0, type: string
child 1, text: string
final_metrics: struct<total_prompt_tokens: int64, total_completion_tokens: int64, total_cached_tokens: int64, total (... 18 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: double
finished_at: string
sandbox_id: string
export_error: null
include_task_skills: bool
transport_error_info: null
loop: struct<strategy: string>
child 0, strategy: string
partial_trajectory: bool
api_error_info: null
agent_result: struct<n_tool_calls: int64, n_skill_invocations: int64, n_prompts: int64, n_input_tokens: int64, n_o (... 163 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: double
child 9, usage_source: string
child 10, price_source: string
trajectory_source: string
trajectory_summary: struct<steps: int64, tool_call
...
me: string
rollout_name: string
skills_sandbox_dir: null
suspected_api_error_info: null
sandbox_startup_info: null
started_at: string
n_skill_invocations: int64
skill_mode: string
verifier_error: null
model: string
verifier_error_category: null
scenes: list<item: struct<name: string, skills_dir: null, roles: list<item: struct<name: string, agent: stri (... 213 chars omitted)
child 0, item: struct<name: string, skills_dir: null, roles: list<item: struct<name: string, agent: string, model: (... 201 chars omitted)
child 0, name: string
child 1, skills_dir: null
child 2, roles: list<item: struct<name: string, agent: string, model: string, reasoning_effort: null, timeout_sec: n (... 95 chars omitted)
child 0, item: struct<name: string, agent: string, model: string, reasoning_effort: null, timeout_sec: null, idle_t (... 83 chars omitted)
child 0, name: string
child 1, agent: string
child 2, model: string
child 3, reasoning_effort: null
child 4, timeout_sec: null
child 5, idle_timeout_sec: null
child 6, skills_dir: null
child 7, capabilities: null
child 8, env_keys: list<item: null>
child 0, item: null
child 3, turns: list<item: struct<role: string, has_prompt: bool>>
child 0, item: struct<role: string, has_prompt: bool>
child 0, role: string
child 1, has_prompt: bool
to
{'task_name': Value('string'), 'rollout_name': Value('string'), 'rewards': {'reward': Value('float64')}, 'agent': Value('string'), 'agent_name': Value('string'), 'model': Value('string'), 'skill_mode': Value('string'), 'skill_source': Value('string'), 'requested_skills_dir': Value('null'), 'effective_skills_dir': Value('null'), 'skills_sandbox_dir': Value('null'), 'include_task_skills': Value('bool'), 'n_tool_calls': Value('int64'), 'n_skill_invocations': Value('int64'), 'n_prompts': Value('int64'), 'agent_result': {'n_tool_calls': Value('int64'), 'n_skill_invocations': Value('int64'), 'n_prompts': Value('int64'), 'n_input_tokens': Value('int64'), 'n_output_tokens': Value('int64'), 'n_cache_read_tokens': Value('int64'), 'n_cache_creation_tokens': Value('int64'), 'total_tokens': Value('int64'), 'cost_usd': Value('float64'), 'usage_source': Value('string'), 'price_source': Value('string')}, 'final_metrics': {'total_prompt_tokens': Value('int64'), 'total_completion_tokens': Value('int64'), 'total_cached_tokens': Value('int64'), 'total_cost_usd': Value('float64')}, 'trajectory_summary': {'steps': Value('int64'), 'tool_call_steps': Value('int64'), 'user_message_steps': Value('int64'), 'agent_message_steps': Value('int64'), 'agent_thought_steps': Value('int64'), 'other_steps': Value('int64'), 'event_type_counts': {'user_message': Value('int64'), 'tool_call': Value('int64'), 'agent_message': Value('int64')}, 'tool_call_status_counts': {'completed': Value('int64')}, 'partial_trajecto
...
Value('float64'), 'agent_setup': Value('float64'), 'agent_execution': Value('float64'), 'verifier': Value('float64'), 'total': Value('float64')}, 'scenes': List({'name': Value('string'), 'skills_dir': Value('null'), 'roles': List({'name': Value('string'), 'agent': Value('string'), 'model': Value('string'), 'reasoning_effort': Value('null'), 'timeout_sec': Value('null'), 'idle_timeout_sec': Value('null'), 'skills_dir': Value('null'), 'capabilities': Value('null'), 'env_keys': List(Value('null'))}), 'turns': List({'role': Value('string'), 'has_prompt': Value('bool')})}), 'loop': {'strategy': Value('string')}, 'source': {'type': Value('string'), 'repo': Value('string'), 'requested_ref': Value('string'), 'resolved_sha': Value('string'), 'path': Value('string'), 'dirty': Value('bool'), 'file_hashes': {'environment/Dockerfile': Value('string'), 'environment/instance.json': Value('string'), 'environment/skills/vanishing-viscosity-cole-hopf/SKILL.md': Value('string'), 'environment/skills/vanishing-viscosity-cole-hopf/references/method.md': Value('string'), 'environment/skills/vanishing-viscosity-cole-hopf/scripts/cole_hopf_lib.py': Value('string'), 'oracle/provenance/manifest.json': Value('string'), 'oracle/solve.py': Value('string'), 'oracle/solve.sh': Value('string'), 'oracle/solve_config.py': Value('string'), 'task.md': Value('string'), 'verifier/test.sh': Value('string'), 'verifier/test_outputs.py': Value('string')}}, 'task_digest': Value('string'), 'sandbox_id': Value('string')}
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
type: string
text: string
tool_call_id: string
kind: string
title: string
status: string
content: list<item: struct<type: string, content: struct<type: string, text: string>>>
child 0, item: struct<type: string, content: struct<type: string, text: string>>
child 0, type: string
child 1, content: struct<type: string, text: string>
child 0, type: string
child 1, text: string
final_metrics: struct<total_prompt_tokens: int64, total_completion_tokens: int64, total_cached_tokens: int64, total (... 18 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: double
finished_at: string
sandbox_id: string
export_error: null
include_task_skills: bool
transport_error_info: null
loop: struct<strategy: string>
child 0, strategy: string
partial_trajectory: bool
api_error_info: null
agent_result: struct<n_tool_calls: int64, n_skill_invocations: int64, n_prompts: int64, n_input_tokens: int64, n_o (... 163 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: double
child 9, usage_source: string
child 10, price_source: string
trajectory_source: string
trajectory_summary: struct<steps: int64, tool_call
...
me: string
rollout_name: string
skills_sandbox_dir: null
suspected_api_error_info: null
sandbox_startup_info: null
started_at: string
n_skill_invocations: int64
skill_mode: string
verifier_error: null
model: string
verifier_error_category: null
scenes: list<item: struct<name: string, skills_dir: null, roles: list<item: struct<name: string, agent: stri (... 213 chars omitted)
child 0, item: struct<name: string, skills_dir: null, roles: list<item: struct<name: string, agent: string, model: (... 201 chars omitted)
child 0, name: string
child 1, skills_dir: null
child 2, roles: list<item: struct<name: string, agent: string, model: string, reasoning_effort: null, timeout_sec: n (... 95 chars omitted)
child 0, item: struct<name: string, agent: string, model: string, reasoning_effort: null, timeout_sec: null, idle_t (... 83 chars omitted)
child 0, name: string
child 1, agent: string
child 2, model: string
child 3, reasoning_effort: null
child 4, timeout_sec: null
child 5, idle_timeout_sec: null
child 6, skills_dir: null
child 7, capabilities: null
child 8, env_keys: list<item: null>
child 0, item: null
child 3, turns: list<item: struct<role: string, has_prompt: bool>>
child 0, item: struct<role: string, has_prompt: bool>
child 0, role: string
child 1, has_prompt: bool
to
{'task_name': Value('string'), 'rollout_name': Value('string'), 'rewards': {'reward': Value('float64')}, 'agent': Value('string'), 'agent_name': Value('string'), 'model': Value('string'), 'skill_mode': Value('string'), 'skill_source': Value('string'), 'requested_skills_dir': Value('null'), 'effective_skills_dir': Value('null'), 'skills_sandbox_dir': Value('null'), 'include_task_skills': Value('bool'), 'n_tool_calls': Value('int64'), 'n_skill_invocations': Value('int64'), 'n_prompts': Value('int64'), 'agent_result': {'n_tool_calls': Value('int64'), 'n_skill_invocations': Value('int64'), 'n_prompts': Value('int64'), 'n_input_tokens': Value('int64'), 'n_output_tokens': Value('int64'), 'n_cache_read_tokens': Value('int64'), 'n_cache_creation_tokens': Value('int64'), 'total_tokens': Value('int64'), 'cost_usd': Value('float64'), 'usage_source': Value('string'), 'price_source': Value('string')}, 'final_metrics': {'total_prompt_tokens': Value('int64'), 'total_completion_tokens': Value('int64'), 'total_cached_tokens': Value('int64'), 'total_cost_usd': Value('float64')}, 'trajectory_summary': {'steps': Value('int64'), 'tool_call_steps': Value('int64'), 'user_message_steps': Value('int64'), 'agent_message_steps': Value('int64'), 'agent_thought_steps': Value('int64'), 'other_steps': Value('int64'), 'event_type_counts': {'user_message': Value('int64'), 'tool_call': Value('int64'), 'agent_message': Value('int64')}, 'tool_call_status_counts': {'completed': Value('int64')}, 'partial_trajecto
...
Value('float64'), 'agent_setup': Value('float64'), 'agent_execution': Value('float64'), 'verifier': Value('float64'), 'total': Value('float64')}, 'scenes': List({'name': Value('string'), 'skills_dir': Value('null'), 'roles': List({'name': Value('string'), 'agent': Value('string'), 'model': Value('string'), 'reasoning_effort': Value('null'), 'timeout_sec': Value('null'), 'idle_timeout_sec': Value('null'), 'skills_dir': Value('null'), 'capabilities': Value('null'), 'env_keys': List(Value('null'))}), 'turns': List({'role': Value('string'), 'has_prompt': Value('bool')})}), 'loop': {'strategy': Value('string')}, 'source': {'type': Value('string'), 'repo': Value('string'), 'requested_ref': Value('string'), 'resolved_sha': Value('string'), 'path': Value('string'), 'dirty': Value('bool'), 'file_hashes': {'environment/Dockerfile': Value('string'), 'environment/instance.json': Value('string'), 'environment/skills/vanishing-viscosity-cole-hopf/SKILL.md': Value('string'), 'environment/skills/vanishing-viscosity-cole-hopf/references/method.md': Value('string'), 'environment/skills/vanishing-viscosity-cole-hopf/scripts/cole_hopf_lib.py': Value('string'), 'oracle/provenance/manifest.json': Value('string'), 'oracle/solve.py': Value('string'), 'oracle/solve.sh': Value('string'), 'oracle/solve_config.py': Value('string'), 'task.md': Value('string'), 'verifier/test.sh': Value('string'), 'verifier/test_outputs.py': Value('string')}}, 'task_digest': Value('string'), 'sandbox_id': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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