The dataset viewer is not available for this split.
Error code: InfoError
Exception: ConnectionError
Message: Couldn't reach 'fredk8/fred_core_document_corpus_v1' on the Hub (LocalEntryNotFoundError)
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 208, in compute_first_rows_from_streaming_response
info = get_dataset_config_info(path=dataset, config_name=config, token=hf_token)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 268, in get_dataset_config_info
builder = load_dataset_builder(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1132, in load_dataset_builder
dataset_module = dataset_module_factory(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1031, in dataset_module_factory
raise e1 from None
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 953, in dataset_module_factory
raise ConnectionError(f"Couldn't reach '{path}' on the Hub ({e.__class__.__name__})") from e
ConnectionError: Couldn't reach 'fredk8/fred_core_document_corpus_v1' on the Hub (LocalEntryNotFoundError)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.
Fred Test Corpus
Purpose: Benchmark and regression testing for the Fred open-source agentic AI platform (https://fredk8.dev).
Overview
This dataset contains a heterogeneous corpus of PDF documents used to validate and benchmark the ingestion, vectorization, and retrieval (RAG) components of the Fred platform.
It includes real-world documents from three distinct domains:
| Folder | Source | Description |
|---|---|---|
ECB/ |
European Central Bank | Recent ECB Working Papers (economic research). |
OCDE/ |
Organisation for Economic Co-operation and Development | French-language policy and analysis papers. |
ARXIV-AI/ |
arXiv.org (Artificial Intelligence category) | AI-related scientific preprints from September 2025. |
Each folder contains between 8 and 15 representative PDF files, with typical file sizes between 300 KB and 2 MB.
⚙️ Intended Use
The corpus is designed for functional and performance testing of Fred’s document ingestion and retrieval subsystems, including:
- Document ingestion pipeline: testing metadata extraction, text conversion, and storage backends (e.g. MinIO, OpenSearch, DuckDB).
- Embedding & vectorization: validating chunking, embedding quality, and retrieval accuracy.
- RAG agents: verifying contextual retrieval within Fred’s DocumentsExpert and Knowledge Flow agents.
- Library selection & tagging: evaluating how agents choose contextually relevant sources from mixed-domain libraries.
This corpus is not a production dataset; it is meant for open-source experimentation, demos, and reproducibility of Fred agent behavior.
Folder Structure
fred-test-corpus/
├── ECB/
│ ├── ecb.wp3098~f8a4989211.en.pdf
│ ├── ecb.wp3099~d0ab147fbf.en.pdf
│ └── ...
├── OCDE/
│ ├── 04b537a4-fr.pdf
│ ├── 299d5974-fr.pdf
│ └── ...
└── ARXIV-AI/
├── 2509.03768v1.pdf
├── 2509.03827v1.pdf
└── ...
⚖️ Licensing and Sources
All included PDFs are publicly available documents from:
They are redistributed for non-commercial research and testing purposes only, under fair-use / open-access terms of their respective publishers.
Fred and its contributors make no claim of ownership over the contents of these documents.
This corpus is distributed solely for reproducibility and testing of open-source AI workflows.
🧾 Citation
If you use this corpus in your work, please cite:
Fred Open Source Project (2025).
"Fred Test Corpus for Document Ingestion and RAG Evaluation."
https://huggingface.co/fredk8/fred-test-corpus
🧱 Related Projects
- Fred Agentic FRamework](https://github.com/ThalesGroup/fred)
- Official Site
Maintainer: ThalesGroup / Fred Open Source
License: Apache 2.0 (for scripts & metadata)
Data License: As per original publishers (non-commercial research use)
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