Datasets:

ysjung77
/

CEG

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
text: string
hard: list<item: string>
  child 0, item: string
to
{'hard': List(Value('string'))}
because column names don't match
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 489, 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
              text: string
              hard: list<item: string>
                child 0, item: string
              to
              {'hard': List(Value('string'))}
              because column names don't match

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CEG — AppWorld Hidden-API Discovery Benchmark

Benchmark specification for the hidden-API discovery setting used in the CEG project (Observation-Verified Partial-Skill Memory for Training-Free LLM Agents).

A set of advanced-feature APIs is removed from the agent's documentation (their existence, signature, and docs are redacted) while they remain executable, forcing a frozen agent to (i) discover each capability from its own observations and (ii) use it reliably to complete multi-requirement AppWorld tasks.

This repo ships the selection spec, not raw task content. The actual AppWorld tasks come from the appworld Python package (pip install appworld); these files tell you which tasks to run and which APIs to hide.

appworld_hidden_api/
  config_13api/        # main paper set — 48 tasks, 13 hidden APIs
    hidden_apis.json   #   {"hard": [ 13 fully-qualified API names to redact ]}
    task_ids.json      #   [ 48 AppWorld task ids ]  (16 templates × 3 variations)
    task_meta.json     #   task_id -> {"split": ..., "gold_hidden": [APIs the gold solution calls]}
  config_30api/        # larger variant — 75 tasks, 30 hidden APIs (same schema)

How the sets were built (reward-free, no hardcoding)

Pool AppWorld tasks across train+dev splits.
Keep a task only if its ground-truth solution genuinely calls one of the hidden APIs (recorded per task in task_meta.json["gold_hidden"]) — so discovery is required, not optional.
The hidden APIs are non-basic "new-feature" actions (e.g. spotify.follow_artist, spotify.add_to_queue, venmo.remind_payment_request, file_system.compress_directory); each app's authentication, reads (show_/list_/search_), and primary create/send/play actions stay visible.

Usage

import json
hidden = json.load(open("appworld_hidden_api/config_13api/hidden_apis.json"))["hard"]
task_ids = json.load(open("appworld_hidden_api/config_13api/task_ids.json"))
# Run each task_id in AppWorld while redacting `hidden` from the API catalog
# (show_api_descriptions / show_api_doc / search_api_docs) but keeping them CALLABLE.

The 13-API config is the headline benchmark; official Task Goal Completion (TGC) is the metric.

Citation

CEG — Observation-Verified Partial-Skill Memory for Training-Free LLM Agents (in progress).

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Total file size:

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CEG — AppWorld Hidden-API Discovery Benchmark

Contents

How the sets were built (reward-free, no hardcoding)

Usage

Citation