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Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      JSON parse error: Invalid value. in row 0
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 324, in _generate_tables
                  df = pandas_read_json(f)
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
                  return pd.read_json(path_or_buf, **kwargs)
                         ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 815, in read_json
                  return json_reader.read()
                         ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1014, in read
                  obj = self._get_object_parser(self.data)
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
                  obj = FrameParser(json, **kwargs).parse()
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1176, in parse
                  self._parse()
                  ~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1392, in _parse
                  ujson_loads(json, precise_float=self.precise_float), dtype=None
                  ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
              ValueError: Expected object or value
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4408, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2679, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2861, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2395, in _iter_arrow
                  yield from 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 327, in _generate_tables
                  raise e
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
                  pa_table = paj.read_json(
                      io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
                  )
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0

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Blender-to-MiniMax-H3 motion-reference lab record

This dataset is the public reproducibility package for an Agentic Film Lab production experiment testing whether deliberately designed Blender animation can guide motion, camera behavior, event timing, and spatial relationships in MiniMax H3 reference-video generation.

Headline result

The first output looked related to the Blender animatic but drifted in timing, so it could not by itself distinguish reference use from prompt-following. A mirrored-reference control then reversed corresponding camera and spatial relationships while prompt, seed, model, and generation settings remained fixed, providing evidence that H3 materially read the video reference.

That fidelity also transferred an unwanted foot shuffle. In three preserved first-roll mitigation tests, F1 still visibly shuffled while F2 and F3 did not. This is a bounded observation from one scene and one first roll per treatment, not a universal ranking.

Included evidence

  • editable Blender source scenes and reproducible builder scripts
  • original and mirrored Blender references
  • complete first-proof and mirrored-control H3 outputs
  • F1, F2, and F3 references and complete H3 first rolls
  • exact prompts, seeds, ComfyUI API workflows, checkpoints, and manifests
  • comparison media, observation ledger, QC, costs, failures, and trial chronology
  • SHA-256 manifest and English episode captions

The downloadable evidence ZIP preserves the directory structure and omits private voice-reference audio, narration stems, the final narrated episode master, model weights, and redundant PNG render sequences.

Test conditions

  • MiniMax H3 Base Ref2VA through the official ComfyUI workflow
  • RunPod Secure Cloud RTX PRO 6000 Blackwell Server Edition
  • 1344×768, 24 fps, 241 requested frames, 20 steps
  • res_multistep sampler, simple scheduler
  • zero aesthetic rerolls
  • approximately USD 7.70 conservative combined lifecycle estimate

License and reuse boundary

No model weights are redistributed. Blender assets were created for this project. Generated outputs and workflows remain subject to applicable upstream model and service terms. The repository uses the other license marker because the package contains mixed production assets and generated media; consult source-assets-v001.json inside the evidence archive before reuse.

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