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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
timestamp: string
ordinal: int64
type: string
payload: struct<type: string, thread_id: string, turn_id: string, item: struct<type: string, id: string, tool (... 5622 chars omitted)
  child 0, type: string
  child 1, thread_id: string
  child 2, turn_id: string
  child 3, item: struct<type: string, id: string, tool: string, arguments: struct<position: list<item: double>, quate (... 382 chars omitted)
      child 0, type: string
      child 1, id: string
      child 2, tool: string
      child 3, arguments: struct<position: list<item: double>, quaternion: list<item: double>, gripper: int64, steps: int64>
          child 0, position: list<item: double>
              child 0, item: double
          child 1, quaternion: list<item: double>
              child 0, item: double
          child 2, gripper: int64
          child 3, steps: int64
      child 4, status: string
      child 5, content_items: list<item: struct<type: string, text: string, imageUrl: string>>
          child 0, item: struct<type: string, text: string, imageUrl: string>
              child 0, type: string
              child 1, text: string
              child 2, imageUrl: string
      child 6, success: bool
      child 7, duration: struct<secs: int64, nanos: int64>
          child 0, secs: int64
          child 1, nanos: int64
      child 8, content: list<item: struct<type: string, text: string, text_elements: list<item: null>>>
          child 0, item: struct<type: string, text: string, text_elements: list<item
...
    child 2, cache_write_input_tokens: int64
          child 3, output_tokens: int64
          child 4, reasoning_output_tokens: int64
          child 5, total_tokens: int64
      child 2, model_context_window: int64
  child 60, rate_limits: struct<limit_id: string, limit_name: null, primary: null, secondary: null, credits: null, individual (... 90 chars omitted)
      child 0, limit_id: string
      child 1, limit_name: null
      child 2, primary: null
      child 3, secondary: null
      child 4, credits: null
      child 5, individual_limit: null
      child 6, spend_control_reached: null
      child 7, plan_type: null
      child 8, rate_limit_reached_type: null
  child 61, encrypted_content: string
  child 62, arguments: string
event: null
metadata: struct<client_authored: bool, mcp_attribution: struct<status: string>, retained_source: struct<id: s (... 155 chars omitted)
  child 0, client_authored: bool
  child 1, mcp_attribution: struct<status: string>
      child 0, status: string
  child 2, retained_source: struct<id: struct<message_id: string, turn_id: string, role: string>, revision: string, complete: bo (... 3 chars omitted)
      child 0, id: struct<message_id: string, turn_id: string, role: string>
          child 0, message_id: string
          child 1, turn_id: string
          child 2, role: string
      child 1, revision: string
      child 2, complete: bool
  child 3, user_input_order: int64
  child 4, fallback_token_limit_override: int64
direction: string
to
{'direction': Value('string'), 'event': Json(decode=True)}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                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 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              timestamp: string
              ordinal: int64
              type: string
              payload: struct<type: string, thread_id: string, turn_id: string, item: struct<type: string, id: string, tool (... 5622 chars omitted)
                child 0, type: string
                child 1, thread_id: string
                child 2, turn_id: string
                child 3, item: struct<type: string, id: string, tool: string, arguments: struct<position: list<item: double>, quate (... 382 chars omitted)
                    child 0, type: string
                    child 1, id: string
                    child 2, tool: string
                    child 3, arguments: struct<position: list<item: double>, quaternion: list<item: double>, gripper: int64, steps: int64>
                        child 0, position: list<item: double>
                            child 0, item: double
                        child 1, quaternion: list<item: double>
                            child 0, item: double
                        child 2, gripper: int64
                        child 3, steps: int64
                    child 4, status: string
                    child 5, content_items: list<item: struct<type: string, text: string, imageUrl: string>>
                        child 0, item: struct<type: string, text: string, imageUrl: string>
                            child 0, type: string
                            child 1, text: string
                            child 2, imageUrl: string
                    child 6, success: bool
                    child 7, duration: struct<secs: int64, nanos: int64>
                        child 0, secs: int64
                        child 1, nanos: int64
                    child 8, content: list<item: struct<type: string, text: string, text_elements: list<item: null>>>
                        child 0, item: struct<type: string, text: string, text_elements: list<item
              ...
                  child 2, cache_write_input_tokens: int64
                        child 3, output_tokens: int64
                        child 4, reasoning_output_tokens: int64
                        child 5, total_tokens: int64
                    child 2, model_context_window: int64
                child 60, rate_limits: struct<limit_id: string, limit_name: null, primary: null, secondary: null, credits: null, individual (... 90 chars omitted)
                    child 0, limit_id: string
                    child 1, limit_name: null
                    child 2, primary: null
                    child 3, secondary: null
                    child 4, credits: null
                    child 5, individual_limit: null
                    child 6, spend_control_reached: null
                    child 7, plan_type: null
                    child 8, rate_limit_reached_type: null
                child 61, encrypted_content: string
                child 62, arguments: string
              event: null
              metadata: struct<client_authored: bool, mcp_attribution: struct<status: string>, retained_source: struct<id: s (... 155 chars omitted)
                child 0, client_authored: bool
                child 1, mcp_attribution: struct<status: string>
                    child 0, status: string
                child 2, retained_source: struct<id: struct<message_id: string, turn_id: string, role: string>, revision: string, complete: bo (... 3 chars omitted)
                    child 0, id: struct<message_id: string, turn_id: string, role: string>
                        child 0, message_id: string
                        child 1, turn_id: string
                        child 2, role: string
                    child 1, revision: string
                    child 2, complete: bool
                child 3, user_input_order: int64
                child 4, fallback_token_limit_override: int64
              direction: string
              to
              {'direction': Value('string'), 'event': Json(decode=True)}
              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 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1879, 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

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direction
string
event
unknown
send
{ "id": 1, "method": "initialize", "params": { "clientInfo": { "name": "robot_harness", "version": "2" }, "capabilities": { "experimentalApi": true } } }
receive
{ "id": 1, "result": { "userAgent": "robot_harness/0.159.2 (Ubuntu 22.4.0; x86_64) screen (robot_harness; 2)", "codexHome": "/home/myx/codebase/outputs/harness/20261001T054755.827592Z_eval/episode-0001/runtime_5ailebky/codex", "platformFamily": "unix", "platformOs": "linux" } }
send
{ "method": "initialized", "params": {} }
send
{ "id": 2, "method": "thread/start", "params": { "model": "gpt-6-astra", "modelProvider": "robot_harness", "cwd": "/home/myx/codebase/outputs/harness/20261001T054755.827592Z_eval/episode-0001/runtime_5ailebky/workspace", "ephemeral": false, "approvalPolicy": "never", "permissions": "robot_...
receive
{ "method": "remoteControl/status/changed", "params": { "status": "disabled", "serverName": "xmu15", "installationId": "c6072d4d-1a16-4ea8-ad11-b5f7c1f62fdd", "environmentId": null }, "emittedAtMs": 1790833928337 }
receive
{ "id": 2, "result": { "thread": { "id": "01a0f605-289e-7883-8f1b-3147ca921a0f", "environments": [ { "environmentId": "local", "cwd": "/home/myx/codebase/outputs/harness/20261001T054755.827592Z_eval/episode-0001/runtime_5ailebky/workspace", "runtimeWorkspaceRoot...
send
{ "id": 3, "method": "thread/goal/set", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "status": "active", "objective": "Execute this robot episode toward the supplied task until observe/act returns done=true. Then stop acting and complete the goal. Task: Pack canned foods into the bi...
receive
{ "method": "thread/started", "params": { "thread": { "id": "01a0f605-289e-7883-8f1b-3147ca921a0f", "environments": [ { "environmentId": "local", "cwd": "/home/myx/codebase/outputs/harness/20261001T054755.827592Z_eval/episode-0001/runtime_5ailebky/workspace", "r...
receive
{ "method": "warning", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "message": "Under-development features enabled: skip_host_skill_discovery. Under-development features are incomplete and may behave unpredictably. To suppress this warning, set `suppress_unstable_features_warning = true` ...
receive
{ "id": 3, "result": { "goal": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "objective": "Execute this robot episode toward the supplied task until observe/act returns done=true. Then stop acting and complete the goal. Task: Pack canned foods into the bin", "status": "active", "...
send
{ "id": 4, "method": "turn/start", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "input": [ { "type": "text", "text": "Execute the current episode autonomously. Start with observe().\nTask instruction: Pack canned foods into the bin\nControl period: 0.06666666666666...
receive
{ "method": "thread/goal/updated", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": null, "goal": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "objective": "Execute this robot episode toward the supplied task until observe/act returns done=true. Then stop ac...
receive
{ "method": "thread/status/changed", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "status": { "type": "active", "activeFlags": [] } }, "emittedAtMs": 1790833928632 }
receive
{ "method": "turn/started", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turn": { "id": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "items": [], "itemsView": "notLoaded", "status": "inProgress", "error": null, "startedAt": 1790833928, "completedAt": ...
receive
{ "id": 4, "result": { "turn": { "id": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "items": [], "itemsView": "notLoaded", "status": "inProgress", "error": null, "startedAt": null, "completedAt": null, "durationMs": null } } }
receive
{ "method": "item/started", "params": { "item": { "type": "agentMessage", "id": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "text": "", "phase": "commentary", "memoryCitation": null, "delivery": null, "questions": null }, "threadId": "01a0f605-289e...
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": "I" }, "emittedAtMs": 1790833932711 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": "’ll" }, "emittedAtMs": 1790833932714 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": " inspect" }, "emittedAtMs": 1790833932717 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": " the" }, "emittedAtMs": 1790833932718 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": " scene" }, "emittedAtMs": 1790833932718 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": "," }, "emittedAtMs": 1790833932803 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": " then" }, "emittedAtMs": 1790833932809 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": " move" }, "emittedAtMs": 1790833932809 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": " the" }, "emittedAtMs": 1790833932813 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": " canned" }, "emittedAtMs": 1790833932818 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": " foods" }, "emittedAtMs": 1790833932820 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": " into" }, "emittedAtMs": 1790833932823 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": " the" }, "emittedAtMs": 1790833932823 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": " bin" }, "emittedAtMs": 1790833932921 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": " and" }, "emittedAtMs": 1790833932922 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": " continue" }, "emittedAtMs": 1790833932925 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": " until" }, "emittedAtMs": 1790833932928 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": " the" }, "emittedAtMs": 1790833932930 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": " episode" }, "emittedAtMs": 1790833932930 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": " ends" }, "emittedAtMs": 1790833933009 }
receive
{ "method": "item/agentMessage/delta", "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "itemId": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "delta": ".\n" }, "emittedAtMs": 1790833933009 }
receive
{ "method": "item/completed", "params": { "item": { "type": "agentMessage", "id": "msg_0d1c183efb1d539e016abdf50c93bc87d0a657f61e7ddbefe7", "text": "I’ll inspect the scene, then move the canned foods into the bin and continue until the episode ends.\n", "phase": "commentary", "memo...
receive
{ "method": "item/started", "params": { "item": { "type": "dynamicToolCall", "id": "exec-3f47c4fd-392f-473d-8ce5-d67f97133e7a", "namespace": null, "tool": "observe", "arguments": {}, "status": "inProgress", "contentItems": null, "success": null, "durationMs"...
receive
{ "method": "item/tool/call", "id": 0, "params": { "threadId": "01a0f605-289e-7883-8f1b-3147ca921a0f", "turnId": "01a0f605-29af-7820-9cd8-6ca64eedf57a", "callId": "exec-3f47c4fd-392f-473d-8ce5-d67f97133e7a", "namespace": null, "tool": "observe", "arguments": {} } }
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