The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
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
return check_status(status)
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Column(/trace_summary/top_span_names/[]/[]) changed from string to number in row 0
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 101, in _split_generators
pa_table = next(iter(self._generate_tables(**splits[0].gen_kwargs, allow_full_read=False)))[1]
~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 304, in _generate_tables
batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
examples = [ujson_loads(line) for line in original_batch.splitlines()]
~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
return pd.io.json.ujson_loads(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
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/split_names.py", line 66, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.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.
AgentBake Trace Library
Execution-trace corpus for the AgentBake benchmark (A Personalization Layer and Benchmark for Heterogeneous Agents). 100 heterogeneous agents spanning seven frameworks (AutoGen, CrewAI, LangChain, LangGraph, LlamaIndex, PydanticAI, Strands), each contributing ~10 recorded multi-turn scenarios.
Contents
good_by_framework/
autogen/<agent>/scenario_XXX/
*__trace_sequence.json # per-step activations: input text, output, tools, timing
*__topology.json # agent graph: nodes, roles, declared capabilities
*__prebuilt_eval.json # LLM-judge scores (coherence, goal success, ...)
selection_metadata.json
crewai/ ... langchain/ ... langgraph/ ... llamaindex/ ... pydanticai/ ... strands/
~4,900 files, ~6.2 GB. 16/14/15/30/5/10/10 agents per framework.
Provenance
Traces were generated by executing rebuilt open-source agents (149-agent
adapter library, pinned upstream repos + commit SHAs in the companion code
repo) on synthetic task scenarios, with Qwen3-32B (qwen.qwen3-32b-v1:0,
via Amazon Bedrock) as the agent backend LLM and as the prebuilt evaluator
judge. The trace content (inputs, outputs, topologies, judge scores) is
generated data; upstream agent code is not included here — see the code
repository for the adapter library and per-repo licenses.
Usage
from huggingface_hub import snapshot_download
snapshot_download("zzh237/agentbake-traces", repo_type="dataset",
local_dir="data/multiagent_traces")
Then run the AgentBake benchmark from the code repo: https://github.com/zzh237/AgentBake
Intended use
Research on agent personalization, orchestration-policy learning, and benchmark evaluation. Scenarios are synthetic; no real user data.
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