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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
episode_index: int64
tasks: list<item: string>
  child 0, item: string
length: int64
task_index: int64
frame_index: int64
action: list<item: double>
  child 0, item: double
index: int64
observation.state: list<item: double>
  child 0, item: double
timestamp: double
to
{'observation.state': List(Value('float64')), 'action': List(Value('float64')), 'timestamp': Value('float64'), 'frame_index': Value('int64'), 'episode_index': Value('int64'), 'index': Value('int64'), 'task_index': Value('int64')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/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 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 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
              episode_index: int64
              tasks: list<item: string>
                child 0, item: string
              length: int64
              task_index: int64
              frame_index: int64
              action: list<item: double>
                child 0, item: double
              index: int64
              observation.state: list<item: double>
                child 0, item: double
              timestamp: double
              to
              {'observation.state': List(Value('float64')), 'action': List(Value('float64')), 'timestamp': Value('float64'), 'frame_index': Value('int64'), 'episode_index': Value('int64'), 'index': Value('int64'), 'task_index': Value('int64')}
              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 1683, 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 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

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observation.state
list
action
list
timestamp
float64
frame_index
int64
episode_index
int64
index
int64
task_index
int64
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End of preview.

physicalai-bmi/forge-arm-reach

An open robot-trajectory dataset generated fully in the browser, on-device with Institute for Physical AI · Forge (in-browser MuJoCo, on-device).

  • Robot: forge_arm
  • Task: Reach the target with the end effector
  • Episodes: 11 · Frames: 3777 · Control rate: 60 Hz
  • observation.state: 7 dims · action: 3 dims

Format

LeRobot v2.1-compatible. meta/ holds info.json, episodes.jsonl, tasks.jsonl, and stats.json.

Per-episode frames are provided both ways under data/chunk-000/:

  • episode_*.parquet — canonical LeRobot parquet (what info.json's data_path points at). Ready to load.
  • episode_*.jsonl — the exact source produced client-side by the in-browser exporter, kept for provenance.

to_parquet.py is the (already-applied) converter, included so anyone can reproduce the parquet from the JSONL.

Load

from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
ds = LeRobotDataset("physicalai-bmi/forge-arm-reach")
print(ds[0]["observation.state"], ds[0]["action"])

How it was made

Recorded in a real browser against the live Forge: the "Reach Trials" arm preset, auto-expert demonstrations, exported on-device. No hardware, no cloud, no install. Reproduce it yourself in about a minute.

See DATASHEET.md for provenance, composition, and intended uses. Licensed CC-BY-4.0.

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