Error code:   ConfigNamesError
Exception:    AttributeError
Message:      'str' object has no attribute 'items'
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 67, in compute_config_names_response
                  config_names = get_dataset_config_names(
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                                   ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1217, in dataset_module_factory
                  raise e1 from None
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1192, in dataset_module_factory
                  ).get_module()
                    ^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 700, in get_module
                  config_name: DatasetInfo.from_dict(dataset_info_dict)
                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/info.py", line 284, in from_dict
                  return cls(**{k: v for k, v in dataset_info_dict.items() if k in field_names})
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "<string>", line 20, in __init__
                File "/usr/local/lib/python3.12/site-packages/datasets/info.py", line 170, in __post_init__
                  self.features = Features.from_dict(self.features)
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1993, in from_dict
                  obj = generate_from_dict(dic)
                        ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1574, in generate_from_dict
                  return {key: generate_from_dict(value) for key, value in obj.items()}
                               ^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1574, in generate_from_dict
                  return {key: generate_from_dict(value) for key, value in obj.items()}
                               ^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1574, in generate_from_dict
                  return {key: generate_from_dict(value) for key, value in obj.items()}
                                                                           ^^^^^^^^^
              AttributeError: 'str' object has no attribute 'items'

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.

DeepLumen AI Search Visibility Benchmarks

Clean, source-linked benchmark data derived from public DeepLumen case study pages. The dataset is intended as a publish-ready starter package for GitHub and Hugging Face, with each metric tied back to an editorially relevant canonical source.

Dataset Files

data/ai_search_visibility_benchmarks.json and .csv: one row per public case study.
data/metric_observations.json and .csv: one row per measured benchmark observation.
data/timeline_events.json and .csv: implementation and outcome milestones.
data/sources.csv: source URLs and provenance notes.
docs/schema.md: field definitions and release notes.

Intended Use

This dataset can support public benchmarking, AI search visibility analysis, retrieval demos, and examples for evaluating agentic search performance across ecommerce categories.

Source Links

The dataset uses public DeepLumen pages as source material. Key canonical references include:

Data Sensitivity

All rows are derived from public pages on www.deeplumen.com. Brand names are retained only where already publicly published by DeepLumen. The brand_public_alias field can be replaced with anonymous IDs such as brand_001 before release if a more conservative publication mode is preferred.

Citation

If you use this dataset, cite DeepLumen and link to the corresponding source URL in each row.

License

This dataset is released under CC-BY-4.0.

Downloads last month: 340

Total file size:

49.7 kB