Datasets:

---

Mithilss

/

outputs-v5

like 0

Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
custom_id: string
central_claim: string
claim_evidence: string
paper_kind: string
mre_config: string
verified_links: struct<paper_or_project: list<item: string>, code: list<item: string>, dataset: list<item: string>,  (... 28 chars omitted)
  child 0, paper_or_project: list<item: string>
      child 0, item: string
  child 1, code: list<item: string>
      child 0, item: string
  child 2, dataset: list<item: string>
      child 0, item: string
  child 3, weights: list<item: string>
      child 0, item: string
signals: struct<code_available: struct<value: bool, verification: string, evidence: string>, dataset_availabl (... 225 chars omitted)
  child 0, code_available: struct<value: bool, verification: string, evidence: string>
      child 0, value: bool
      child 1, verification: string
      child 2, evidence: string
  child 1, dataset_available: struct<value: bool, verification: string, evidence: string>
      child 0, value: bool
      child 1, verification: string
      child 2, evidence: string
  child 2, weights_available: struct<value: bool, verification: string, evidence: string>
      child 0, value: bool
      child 1, verification: string
      child 2, evidence: string
  child 3, dataset_is_standard: struct<value: bool, verification: string, evidence: string>
      child 0, value: bool
      child 1, verification: string
      child 2, evidence: string
agent_task: string
h100_estimate: struct<hours: double, basis_kind: string, gpu_count: int64, gpu_type: string, 
...

                  child 6, tool_calls: list<item: null>
                      child 0, item: null
                  child 7, reasoning: string
              child 2, logprobs: null
              child 3, finish_reason: string
              child 4, stop_reason: null
              child 5, token_ids: null
              child 6, routed_experts: null
      child 5, service_tier: null
      child 6, system_fingerprint: string
      child 7, usage: struct<prompt_tokens: int64, total_tokens: int64, completion_tokens: int64, prompt_tokens_details: n (... 4 chars omitted)
          child 0, prompt_tokens: int64
          child 1, total_tokens: int64
          child 2, completion_tokens: int64
          child 3, prompt_tokens_details: null
      child 8, prompt_logprobs: null
      child 9, prompt_token_ids: null
      child 10, prompt_text: null
      child 11, kv_transfer_params: null
tool_loop: struct<tool_rounds_used: int64, max_tool_rounds: int64, hit_tool_round_limit: bool, exit_reason: str (... 142 chars omitted)
  child 0, tool_rounds_used: int64
  child 1, max_tool_rounds: int64
  child 2, hit_tool_round_limit: bool
  child 3, exit_reason: string
  child 4, telemetry: struct<tool_calls: int64, tool_errors: int64, conversation_chars: int64, estimated_input_tokens: int (... 25 chars omitted)
      child 0, tool_calls: int64
      child 1, tool_errors: int64
      child 2, conversation_chars: int64
      child 3, estimated_input_tokens: int64
      child 4, input_overflow: bool
to
{'custom_id': Value('string'), 'response': {'status_code': Value('int64'), 'body': {'id': Value('string'), 'object': Value('string'), 'created': Value('int64'), 'model': Value('string'), 'choices': List({'index': Value('int64'), 'message': {'role': Value('string'), 'content': Value('string'), 'refusal': Value('null'), 'annotations': Value('null'), 'audio': Value('null'), 'function_call': Value('null'), 'tool_calls': List(Value('null')), 'reasoning': Value('string')}, 'logprobs': Value('null'), 'finish_reason': Value('string'), 'stop_reason': Value('null'), 'token_ids': Value('null'), 'routed_experts': Value('null')}), 'service_tier': Value('null'), 'system_fingerprint': Value('string'), 'usage': {'prompt_tokens': Value('int64'), 'total_tokens': Value('int64'), 'completion_tokens': Value('int64'), 'prompt_tokens_details': Value('null')}, 'prompt_logprobs': Value('null'), 'prompt_token_ids': Value('null'), 'prompt_text': Value('null'), 'kv_transfer_params': Value('null')}}, 'tool_loop': {'tool_rounds_used': Value('int64'), 'max_tool_rounds': Value('int64'), 'hit_tool_round_limit': Value('bool'), 'exit_reason': Value('string'), 'telemetry': {'tool_calls': Value('int64'), 'tool_errors': Value('int64'), 'conversation_chars': Value('int64'), 'estimated_input_tokens': Value('int64'), 'input_overflow': Value('bool')}}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1816, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 611, in wrapped
                  for item in generator(*args, **kwargs):
                              ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 310, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 130, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              custom_id: string
              central_claim: string
              claim_evidence: string
              paper_kind: string
              mre_config: string
              verified_links: struct<paper_or_project: list<item: string>, code: list<item: string>, dataset: list<item: string>,  (... 28 chars omitted)
                child 0, paper_or_project: list<item: string>
                    child 0, item: string
                child 1, code: list<item: string>
                    child 0, item: string
                child 2, dataset: list<item: string>
                    child 0, item: string
                child 3, weights: list<item: string>
                    child 0, item: string
              signals: struct<code_available: struct<value: bool, verification: string, evidence: string>, dataset_availabl (... 225 chars omitted)
                child 0, code_available: struct<value: bool, verification: string, evidence: string>
                    child 0, value: bool
                    child 1, verification: string
                    child 2, evidence: string
                child 1, dataset_available: struct<value: bool, verification: string, evidence: string>
                    child 0, value: bool
                    child 1, verification: string
                    child 2, evidence: string
                child 2, weights_available: struct<value: bool, verification: string, evidence: string>
                    child 0, value: bool
                    child 1, verification: string
                    child 2, evidence: string
                child 3, dataset_is_standard: struct<value: bool, verification: string, evidence: string>
                    child 0, value: bool
                    child 1, verification: string
                    child 2, evidence: string
              agent_task: string
              h100_estimate: struct<hours: double, basis_kind: string, gpu_count: int64, gpu_type: string, 
              ...
              
                                child 6, tool_calls: list<item: null>
                                    child 0, item: null
                                child 7, reasoning: string
                            child 2, logprobs: null
                            child 3, finish_reason: string
                            child 4, stop_reason: null
                            child 5, token_ids: null
                            child 6, routed_experts: null
                    child 5, service_tier: null
                    child 6, system_fingerprint: string
                    child 7, usage: struct<prompt_tokens: int64, total_tokens: int64, completion_tokens: int64, prompt_tokens_details: n (... 4 chars omitted)
                        child 0, prompt_tokens: int64
                        child 1, total_tokens: int64
                        child 2, completion_tokens: int64
                        child 3, prompt_tokens_details: null
                    child 8, prompt_logprobs: null
                    child 9, prompt_token_ids: null
                    child 10, prompt_text: null
                    child 11, kv_transfer_params: null
              tool_loop: struct<tool_rounds_used: int64, max_tool_rounds: int64, hit_tool_round_limit: bool, exit_reason: str (... 142 chars omitted)
                child 0, tool_rounds_used: int64
                child 1, max_tool_rounds: int64
                child 2, hit_tool_round_limit: bool
                child 3, exit_reason: string
                child 4, telemetry: struct<tool_calls: int64, tool_errors: int64, conversation_chars: int64, estimated_input_tokens: int (... 25 chars omitted)
                    child 0, tool_calls: int64
                    child 1, tool_errors: int64
                    child 2, conversation_chars: int64
                    child 3, estimated_input_tokens: int64
                    child 4, input_overflow: bool
              to
              {'custom_id': Value('string'), 'response': {'status_code': Value('int64'), 'body': {'id': Value('string'), 'object': Value('string'), 'created': Value('int64'), 'model': Value('string'), 'choices': List({'index': Value('int64'), 'message': {'role': Value('string'), 'content': Value('string'), 'refusal': Value('null'), 'annotations': Value('null'), 'audio': Value('null'), 'function_call': Value('null'), 'tool_calls': List(Value('null')), 'reasoning': Value('string')}, 'logprobs': Value('null'), 'finish_reason': Value('string'), 'stop_reason': Value('null'), 'token_ids': Value('null'), 'routed_experts': Value('null')}), 'service_tier': Value('null'), 'system_fingerprint': Value('string'), 'usage': {'prompt_tokens': Value('int64'), 'total_tokens': Value('int64'), 'completion_tokens': Value('int64'), 'prompt_tokens_details': Value('null')}, 'prompt_logprobs': Value('null'), 'prompt_token_ids': Value('null'), 'prompt_text': Value('null'), 'kv_transfer_params': Value('null')}}, 'tool_loop': {'tool_rounds_used': Value('int64'), 'max_tool_rounds': Value('int64'), 'hit_tool_round_limit': Value('bool'), 'exit_reason': Value('string'), 'telemetry': {'tool_calls': Value('int64'), 'tool_errors': Value('int64'), 'conversation_chars': Value('int64'), 'estimated_input_tokens': Value('int64'), 'input_overflow': Value('bool')}}}
              because column names don't match
              
              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 1361, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 940, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1683, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1869, 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