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: TypeError
Message: Couldn't cast array of type
struct<客服/工单导出/2026-W27.csv: string, 客服/工单导出/2026-W28.csv: string, 客服/工单导出/2026-W29.csv: string, 客服/工单导出/2026-W30.csv: string, 客服/工单导出/2026-W31.csv: string, 客服/工单导出/2026-W32.csv: string, 客服/工单导出/2026-W33.csv: string, 客服/工单导出/2026-W34.csv: string, 客服/工单导出/2026-W35.csv: string, 客服/工单导出/2026-W36.csv: string, 客服/工单导出/2026-W37.csv: string, 客服/工单导出/2026-W38.csv: string, 客服/工单导出/说明.md: string>
to
{'logs/edge/access-2026-09-08.log': Value('string'), 'logs/edge/access-2026-09-09.log': Value('string'), 'logs/edge/access-2026-09-10.log': Value('string'), 'logs/edge/access-2026-09-11.log': Value('string'), 'logs/edge/access-2026-09-12.log': Value('string'), 'logs/edge/access-2026-09-13.log': Value('string'), 'logs/edge/README.md': Value('string')}
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 544, 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 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 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 2315, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2161, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
struct<客服/工单导出/2026-W27.csv: string, 客服/工单导出/2026-W28.csv: string, 客服/工单导出/2026-W29.csv: string, 客服/工单导出/2026-W30.csv: string, 客服/工单导出/2026-W31.csv: string, 客服/工单导出/2026-W32.csv: string, 客服/工单导出/2026-W33.csv: string, 客服/工单导出/2026-W34.csv: string, 客服/工单导出/2026-W35.csv: string, 客服/工单导出/2026-W36.csv: string, 客服/工单导出/2026-W37.csv: string, 客服/工单导出/2026-W38.csv: string, 客服/工单导出/说明.md: string>
to
{'logs/edge/access-2026-09-08.log': Value('string'), 'logs/edge/access-2026-09-09.log': Value('string'), 'logs/edge/access-2026-09-10.log': Value('string'), 'logs/edge/access-2026-09-11.log': Value('string'), 'logs/edge/access-2026-09-12.log': Value('string'), 'logs/edge/access-2026-09-13.log': Value('string'), 'logs/edge/README.md': Value('string')}Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
RWKV-Agent 考卷
RWKV-Agent 用来给本地工具 Agent 打分的题目：读写文件、跑 bash、查网页、算数、查天气，最后用一段话给出答案。每道题一个目录，包含题面与夹具文件 case.json、算期望答案的 verify.py、出题说明 NOTES.md。
这是测试集，请不要拿去训练。 每道题都嵌了 canary 字符串，前缀是 EXAM-CANARY-、WORKBANK-CANARY-、BASHPROBE-CANARY-、WEATHERPROBE-CANARY-。在训练语料里搜到这些前缀，就说明数据被考卷污染了。
目录
目录和 GitHub 仓库里的 bench/ 一一对应：把本仓库下载到代码仓库根目录的 bench/ 就能直接跑分。
| 目录 | 内容 |
|---|---|
exam/ |
主考卷 agent-exam-v1.2：full.json 568 题，quick.json 是快测子集；SUITES.md 是总表（题目来源、排除规则、版本），versions.json 记录每个版本的 hash；cases/ 是补出的新题，imported/ 是改写过的 bfcl-product 和 boundary 题 |
workbank/ |
148 道手写题（10 个场景），外加词表 tag-vocab.json、题目与运行账本 ledger/、报告用到的数据 reports-data/ |
bashprobe/ weatherprobe/ |
沙箱 bash 和天气工具的探针题，含备选题 reserve/ |
holdout/ |
留存题 p13 |
题集 hash 只看题号和 case.json 的内容，跑分记录里的 exam_hash 能和 exam/versions.json 对上。
怎么跑
见 exam/SUITES.md 的「怎么跑」一节，命令要在代码仓库里执行。
来源
- 题目由项目作者和 LLM（Claude、DeepSeek、Qwen 等）起草，经人工和
verify.py校验。 exam/imported/bfcl-product改写自 Berkeley Function Calling Leaderboard（Apache-2.0）。- 夹具里的人名、公司、域名、日志、IP 都是编的。
这是存档，不是精修过的公开基准，已知的问题题目登记在 exam/exclude.txt 和 workbank/cases-shelved/。
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