Datasets:
Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
id: int64
text: string
hero: string
creature: string
realm: string
magic: string
scaffold: string
moral_source: string
moral: string
moral_source_counts: struct<curated: int64, synthetic: int64>
child 0, curated: int64
child 1, synthetic: int64
seed: int64
max_words: int64
combination_space_lower_bound: int64
scaffold_counts: struct<betrayal: int64, meeting: int64, discovery: int64, transformation: int64, quest: int64>
child 0, betrayal: int64
child 1, meeting: int64
child 2, discovery: int64
child 3, transformation: int64
child 4, quest: int64
avg_words_per_story: double
total_words: int64
num_stories: int64
min_words: int64
pools: struct<archetypes: int64, creatures: int64, realms: int64, magic_systems: int64, scaffolds: int64, m (... 13 chars omitted)
child 0, archetypes: int64
child 1, creatures: int64
child 2, realms: int64
child 3, magic_systems: int64
child 4, scaffolds: int64
child 5, morals: int64
to
{'num_stories': Value('int64'), 'total_words': Value('int64'), 'avg_words_per_story': Value('float64'), 'min_words': Value('int64'), 'max_words': Value('int64'), 'combination_space_lower_bound': Value('int64'), 'pools': {'archetypes': Value('int64'), 'creatures': Value('int64'), 'realms': Value('int64'), 'magic_systems': Value('int64'), 'scaffolds': Value('int64'), 'morals': Value('int64')}, 'scaffold_counts': {'betrayal': Value('int64'), 'meeting': Value('int64'), 'discovery': Value('int64'), 'transformation': Value('int64'), 'quest': Value('int64')}, 'moral_source_counts': {'curated': Value('int64'), 'synthetic': Value('int64')}, 'seed': Value('int64')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
for key, pa_table in 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 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
id: int64
text: string
hero: string
creature: string
realm: string
magic: string
scaffold: string
moral_source: string
moral: string
moral_source_counts: struct<curated: int64, synthetic: int64>
child 0, curated: int64
child 1, synthetic: int64
seed: int64
max_words: int64
combination_space_lower_bound: int64
scaffold_counts: struct<betrayal: int64, meeting: int64, discovery: int64, transformation: int64, quest: int64>
child 0, betrayal: int64
child 1, meeting: int64
child 2, discovery: int64
child 3, transformation: int64
child 4, quest: int64
avg_words_per_story: double
total_words: int64
num_stories: int64
min_words: int64
pools: struct<archetypes: int64, creatures: int64, realms: int64, magic_systems: int64, scaffolds: int64, m (... 13 chars omitted)
child 0, archetypes: int64
child 1, creatures: int64
child 2, realms: int64
child 3, magic_systems: int64
child 4, scaffolds: int64
child 5, morals: int64
to
{'num_stories': Value('int64'), 'total_words': Value('int64'), 'avg_words_per_story': Value('float64'), 'min_words': Value('int64'), 'max_words': Value('int64'), 'combination_space_lower_bound': Value('int64'), 'pools': {'archetypes': Value('int64'), 'creatures': Value('int64'), 'realms': Value('int64'), 'magic_systems': Value('int64'), 'scaffolds': Value('int64'), 'morals': Value('int64')}, 'scaffold_counts': {'betrayal': Value('int64'), 'meeting': Value('int64'), 'discovery': Value('int64'), 'transformation': Value('int64'), 'quest': Value('int64')}, 'moral_source_counts': {'curated': Value('int64'), 'synthetic': Value('int64')}, 'seed': Value('int64')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
AetherStory Dataset
A procedurally generated corpus of unique fantasy fables, purpose-built to train the AetherStory storyteller model. Every story is synthesised on the fly from a combinatorial space of realms, creatures, character archetypes, magic systems, and plot scaffolds.
Why this dataset is unique
It is not scraped from the web. Each fable is constructed by code from hand-written ingredients, so:
- there is no copyright risk — every word is original or drawn from public-domain-style aphorisms,
- the dataset is fully reproducible from a single seed,
- the combination space is astronomically larger than the corpus itself, so duplicates are effectively impossible.
See stats.json for the exact size and ingredient counts of this release.
Structure
Each line of stories.jsonl is a JSON object:
{
"id": 0,
"text": "In the Glasslands there lived a wind-listener. ...",
"hero": "a wind-listener",
"creature": "a hollow crow",
"realm": "the Glasslands",
"magic": "freezing moments in glass",
"scaffold": "betrayal",
"moral_source": "synthetic",
"moral": "In the end, an unspoken name outlasts the cleverest lie."
}
Regeneration
python scripts/build_dataset.py --num-stories 50000
License
MIT — the dataset, the generator code, and the curated morals are all released under MIT. Do whatever you like; attribution appreciated.
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