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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
kind: string
schema_version: int64
clock: string
coverage: string
sequence: int64
event: null
id: int64
start_ns: int64
reason: string
end_ns: int64
last_response_ns: int64
outcome: string
error_kind: string
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 1835, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 621, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 361, 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 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              kind: string
              schema_version: int64
              clock: string
              coverage: string
              sequence: int64
              event: null
              id: int64
              start_ns: int64
              reason: string
              end_ns: int64
              last_response_ns: int64
              outcome: string
              error_kind: string
              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 1379, 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 956, 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 1702, 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 1887, 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
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{ "id": 1, "method": "initialize", "params": { "clientInfo": { "name": "robot_harness", "version": "2" }, "capabilities": { "experimentalApi": true } } }
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{ "id": 1, "result": { "userAgent": "robot_harness/0.0.0 (Ubuntu 22.4.0; x86_64) screen (robot_harness; 2)", "codexHome": "/data/NTU_slab/draven/proj/codebase/outputs/robolab_exploration/embo_astra/gpu_0/harness/20261030T160311.809061Z_eval/episode-0001/runtime_iato5xbg/codex", "platformFamily": "unix",...
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{ "method": "initialized", "params": {} }
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{ "id": 2, "method": "thread/start", "params": { "model": "gpt-6-astra", "modelProvider": "robot_harness", "cwd": "/data/NTU_slab/draven/proj/codebase/outputs/robolab_exploration/embo_astra/gpu_0/harness/20261030T160311.809061Z_eval/episode-0001/runtime_iato5xbg/workspace", "ephemeral": false, ...
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{ "method": "remoteControl/status/changed", "params": { "status": "disabled", "serverName": "pt-65339c1fff804251bd32398d4e3b6c24-worker-0", "installationId": "9e03e29c-74ab-472a-847f-7a7d4962b6ce", "environmentId": null }, "emittedAtMs": 1793376302740 }
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{ "id": 2, "result": { "thread": { "id": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "environments": [ { "environmentId": "local", "cwd": "/data/NTU_slab/draven/proj/codebase/outputs/robolab_exploration/embo_astra/gpu_0/harness/20261030T160311.809061Z_eval/episode-0001/runtim...
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{ "id": 3, "method": "thread/settings/update", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "collaborationMode": { "mode": "default", "settings": { "model": "gpt-6-astra", "reasoning_effort": "medium", "developer_instructions": "Control DROID autonomo...
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{ "method": "thread/started", "params": { "thread": { "id": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "environments": [ { "environmentId": "local", "cwd": "/data/NTU_slab/draven/proj/codebase/outputs/robolab_exploration/embo_astra/gpu_0/harness/20261030T160311.809061Z_eval/...
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{ "method": "warning", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "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` ...
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{ "id": 3, "result": {} }
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{ "id": 4, "method": "thread/goal/set", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "status": "active", "objective": "Execute this robot episode toward the supplied task until a robot tool returns done=true. Then stop acting and complete the goal. Task: Put all the small plastic bo...
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{ "method": "thread/settings/updated", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "threadSettings": { "disabledPluginIds": [], "cwd": "/data/NTU_slab/draven/proj/codebase/outputs/robolab_exploration/embo_astra/gpu_0/harness/20261030T160311.809061Z_eval/episode-0001/runtime_i...
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{ "id": 4, "result": { "goal": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "objective": "Execute this robot episode toward the supplied task until a robot tool returns done=true. Then stop acting and complete the goal. Task: Put all the small plastic bottles in the square pail", "sta...
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{ "id": 5, "method": "turn/start", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "input": [ { "type": "text", "text": "Execute the current episode autonomously. Start with observe().\nTask instruction: Put all the small plastic bottles in the square pail\nControl pe...
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{ "method": "thread/goal/updated", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": null, "goal": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "objective": "Execute this robot episode toward the supplied task until a robot tool returns done=true. Then stop a...
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{ "method": "thread/status/changed", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "status": { "type": "active", "activeFlags": [] } }, "emittedAtMs": 1793376303795 }
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{ "method": "turn/started", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turn": { "id": "01a18d8e-ba69-7691-b64c-ee4045941713", "rootTurnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "items": [], "itemsView": "notLoaded", "status": "inProgress", "error"...
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{ "id": 5, "result": { "turn": { "id": "01a18d8e-ba69-7691-b64c-ee4045941713", "rootTurnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "items": [], "itemsView": "notLoaded", "status": "inProgress", "error": null, "startedAt": null, "completedAt": null, "durati...
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{ "method": "item/started", "params": { "item": { "type": "userMessage", "id": "01a18d8e-bb01-7581-9b76-67a7dd4a0b01", "clientId": null, "content": [ { "type": "text", "text": "Execute the current episode autonomously. Start with observe().\nTask instruction: ...
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{ "method": "item/completed", "params": { "item": { "type": "userMessage", "id": "01a18d8e-bb01-7581-9b76-67a7dd4a0b01", "clientId": null, "content": [ { "type": "text", "text": "Execute the current episode autonomously. Start with observe().\nTask instruction...
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{ "method": "item/started", "params": { "item": { "type": "agentMessage", "id": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "text": "", "phase": "commentary", "memoryCitation": null, "delivery": null, "questions": null }, "threadId": "01a18d8e-b725...
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{ "method": "item/agentMessage/delta", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "itemId": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "delta": "I" }, "emittedAtMs": 1793376330171 }
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{ "method": "item/agentMessage/delta", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "itemId": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "delta": "’ll" }, "emittedAtMs": 1793376330171 }
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{ "method": "item/agentMessage/delta", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "itemId": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "delta": " inspect" }, "emittedAtMs": 1793376330171 }
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{ "method": "item/agentMessage/delta", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "itemId": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "delta": " the" }, "emittedAtMs": 1793376330171 }
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{ "method": "item/agentMessage/delta", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "itemId": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "delta": " scene" }, "emittedAtMs": 1793376330171 }
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{ "method": "item/agentMessage/delta", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "itemId": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "delta": "," }, "emittedAtMs": 1793376330171 }
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{ "method": "item/agentMessage/delta", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "itemId": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "delta": " then" }, "emittedAtMs": 1793376330172 }
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{ "method": "item/agentMessage/delta", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "itemId": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "delta": " move" }, "emittedAtMs": 1793376330172 }
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{ "method": "item/agentMessage/delta", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "itemId": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "delta": " the" }, "emittedAtMs": 1793376330172 }
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{ "method": "item/agentMessage/delta", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "itemId": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "delta": " small" }, "emittedAtMs": 1793376330172 }
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{ "method": "item/agentMessage/delta", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "itemId": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "delta": " plastic" }, "emittedAtMs": 1793376330182 }
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{ "method": "item/agentMessage/delta", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "itemId": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "delta": " bottles" }, "emittedAtMs": 1793376330183 }
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{ "method": "item/agentMessage/delta", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "itemId": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "delta": " into" }, "emittedAtMs": 1793376330183 }
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{ "method": "item/agentMessage/delta", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "itemId": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "delta": " the" }, "emittedAtMs": 1793376330183 }
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{ "method": "item/agentMessage/delta", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "itemId": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "delta": " square" }, "emittedAtMs": 1793376330183 }
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{ "method": "item/agentMessage/delta", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "itemId": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "delta": " p" }, "emittedAtMs": 1793376330183 }
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{ "method": "item/agentMessage/delta", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "itemId": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "delta": "ail" }, "emittedAtMs": 1793376330183 }
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{ "method": "item/agentMessage/delta", "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "itemId": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "delta": "." }, "emittedAtMs": 1793376330183 }
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{ "method": "item/completed", "params": { "item": { "type": "agentMessage", "id": "msg_03997b6a5cc25e0e016ae4c0491fd487d08ee1ca008b7a2dd6", "text": "I’ll inspect the scene, then move the small plastic bottles into the square pail.", "phase": "commentary", "memoryCitation": null, ...
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{ "method": "item/started", "params": { "item": { "type": "dynamicToolCall", "id": "exec-1a9848f9-cae3-40d9-a6b8-5d1be873a63f", "namespace": null, "tool": "observe", "arguments": {}, "status": "inProgress", "contentItems": null, "success": null, "durationMs"...
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{ "method": "item/tool/call", "id": 0, "params": { "threadId": "01a18d8e-b725-7c33-ba16-3cab9d2ee0db", "turnId": "01a18d8e-ba69-7691-b64c-ee4045941713", "callId": "exec-1a9848f9-cae3-40d9-a6b8-5d1be873a63f", "namespace": null, "tool": "observe", "arguments": {} } }
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{ "id": 0, "result": { "contentItems": [ { "type": "inputText", "text": "{\"robot_state\": {\"position\": [0.3597031235694885, 3.300374373793602e-08, 0.47176671028137207], \"quaternion\": [0.7071064533609271, 1.1920928656665167e-07, 0.7071071090120032, -5.9604643283325836e-08], \"joint_pos...
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