Datasets:

Ailiance-fr
/

kicad9plus-copyleft

license: gpl-3.0
language:
  - en
  - fr
pretty_name: Ailiance — KiCad 9+ Schematic Corpus (Copyleft)
task_categories:
  - text-generation
tags:
  - kicad
  - eda
  - schematic
  - s-expression
  - electronics
  - hardware
  - copyleft
  - ailiance
size_categories:
  - n<1K

Ailiance — KiCad 9+ Schematic Corpus (Copyleft)

🇫🇷 Ailiance — curated by Ailiance for production deployment ; co-published with the upstream electron-rare/kicad9plus-copyleft. 🇪🇺 Compatible EU AI Act (Template AI Office, July 2025).

Corpus de 209 schémas KiCad 9+ (.kicad_sch, format S-expression, version ≥ 20240722) collectés sous licences copyleft / réciproques fortes (GPL-3.0, CERN-OHL-S-2.0, EUPL-1.2). Compatible GPL-3.0-or-later au niveau aggregé. Pensé pour l'entraînement de modèles open-source soumis aux mêmes obligations de réciprocité.

Statistics

Métrique	Valeur
Total samples	209
Size	~2.1 MB JSONL (raw `.kicad_sch` ≈ 38 MB before chat-format wrapping)
Format	JSONL chat format (`messages` array, user/assistant)
Languages	French + English
Aggregate license	GPL-3.0-or-later

Composition

Copyleft / strong reciprocal licenses only: GPL-3.0 (169), CERN-OHL-S-2.0 (36), EUPL-1.2 (4).

Copyleft split of the original electron-rare/kicad9plus-sch-corpus (now deprecated). L'aggregé est re-licencié sous GPL-3.0-or-later, le plus restrictif des inputs (CERN-OHL-S-2.0 et EUPL-1.2 sont explicitement compatibles avec GPL-3.0+ via FSF / EUPL appendix interoperability).

Pour les samples permissifs (Apache-2.0, MIT, CC0-1.0, CERN-OHL-P-2.0) : voir Ailiance-fr/kicad9plus-permissive.

EU AI Act compliance (Template AI Office, July 2025)

General information

Name: kicad9plus-sch-corpus (copyleft subset)
Modality: text (KiCad S-expression source)
Languages: English (technical), French (some title-block descriptions)
Intended use: entraînement / fine-tuning de modèles de génération de schémas KiCad 9 / KiCad 10. Les modèles entraînés sur ce dataset doivent respecter les obligations GPL-3.0-or-later (disclosure des poids, des données dérivées d'entraînement, et du code d'inférence si redistribué).

Data sources

Publicly available datasets: None.

Web scraping: Yes — public GitHub repositories.

Discovery method: gh search code "(kicad_sch (version 202X)" extension:kicad_sch
Filtering: SPDX license detection of GPL-3.0, CERN-OHL-S-2.0, EUPL-1.2
Per-sample provenance: see metadata.source_url, metadata.commit_sha, metadata.repo

Licensed data: None (no commercial / proprietary licenses).

Data processing

Sparse-clone with gh repo clone --depth 1
Per-file .meta.json sidecar with source_url, commit_sha, license_spdx, kicad_version
Deduplication via SHA-256 of file contents
Truncation at 8 KB to fit training context (marked in metadata when applicable)
Validation via kicad-cli sch erc --format json --severity-all (99.6% pass rate on tested subset)
All processing scripts available at https://github.com/ailiance/ailiance-bench/tree/main/scripts

Data characteristics

Size: 209 samples, ~2.1 MB JSONL (raw .kicad_sch totals ~38 MB before chat-format wrapping)
License mix (input):
- GPL-3.0: 169 samples (80.9%)
- CERN-OHL-S-2.0: 36 (17.2%)
- EUPL-1.2: 4 (1.9%)
KiCad version mix: 20240819 / 20240910 / 20241004 / 20241209 (KiCad 9 dev), 20250114 (KiCad 9 stable), 20250227 / 20250318 / 20250610 / 20250829 / 20250901 / 20250922 / 20251012 / 20251028 (later 9.x), 20260101 / 20260306 (KiCad 10)
Source repos: 9 distinct upstream projects (full list in LICENSE_INVENTORY.md); largest contributors are jaguilar/kicad (133) and flaviens/kicad (34) — both KiCad demo / fork repositories under GPL-3.0.

Sample format

Each line is a chat-format JSON object:

{
  "messages": [
    {"role": "user", "content": "Generate a KiCad 9 schematic (titled '...', by ..., N components, libraries: ...). Use the standard S-expression format starting with `(kicad_sch ...)`."},
    {"role": "assistant", "content": "(kicad_sch\n\t(version 20250114)\n\t..."}
  ],
  "metadata": {
    "repo": "owner/name",
    "rel_path": "path/to/file.kicad_sch",
    "source_url": "https://github.com/owner/name/blob/<sha>/path/to/file.kicad_sch",
    "commit_sha": "<git sha>",
    "license_spdx": "GPL-3.0",
    "kicad_version": "20250114",
    "file_sha256": "<content sha>",
    "file_size_bytes": 12345,
    "downloaded_at": "2026-05-11T...",
    "compliance_notes": "...",
    "ia_act_status": "requires_review"
  }
}

Licenses applied

This dataset (the aggregated work) is released under GPL-3.0-or-later.

Per-sample original licenses are preserved in metadata.license_spdx and listed in LICENSE_INVENTORY.md. Downstream users MUST preserve attribution per sample and comply with the strongest applicable copyleft term (GPL-3.0-or-later for the aggregate).

Compatibility notes:

CERN-OHL-S-2.0 -> GPL-3.0+: explicitly compatible (CERN-OHL-S §7 allows redistribution under GPL when combining with GPL works).
EUPL-1.2 -> GPL-3.0+: compatible via the EUPL §5 / Appendix list (GPL-3.0 is a listed compatible licence).
GPL-3.0 -> GPL-3.0+: trivially compatible.

Copyright considerations

All sources are public GitHub repositories under copyleft licenses.
The .kicad_sch files are treated as software source under their original licenses.
Opt-out mechanism: contact c.saillant@gmail.com (Ailiance) to remove specific samples; nous respectons l'Article 4(3) de la directive DSM (TDM reservations).
Reservations of rights: nous honorons robots.txt, les meta tags HTML noai / noimageai, et le protocole TDM Reservation Protocol (TDMRep) quand discoverable sur les repos sources.

Pipeline reproducibility

See https://github.com/ailiance/ailiance-bench/tree/main/scripts:

kicad9plus_pipeline.sh, build_kicad9plus_dataset.py
Original audit: https://github.com/ailiance/ailiance-bench/blob/main/docs/audit_kicad9plus.md

Provenance & upstream attribution

This dataset is co-published with electron-rare/kicad9plus-copyleft under the same GPL-3.0-or-later license. Original collection, curation, and pipeline tooling: electron-rare (upstream contributor). Production maintenance, EU AI Act packaging, and downstream support: Ailiance (this org).

Audit log (legal attribution, EU AI Act July 2025 template alignment): see docs/audit_kicad9plus.md and the companion docs/audit_mascarade_se_attribution.md on GitHub.

About Ailiance

🇫🇷 Ailiance is a French AI organisation building EU-compliant resources for embedded systems and electronics design. Ailiance curates open datasets and fine-tuned models targeting:

🇪🇺 EU AI Act compliance (aligned with the GPAI Code of Practice signatories: Anthropic, Mistral, Google)
⚡ Electronics, embedded systems, hardware design
🔬 SPICE simulation, KiCad PCB / schematic, EDA workflows
🇫🇷 French + English technical content

Maintainer contact: c.saillant@gmail.com — see also the public bench/audit repo: electron-bench.

License & EU AI Act

GPL-3.0-or-later. Données collectées et curées dans le cadre du projet electron-rare, packagées et maintenues par Ailiance pour déploiement production aligné EU AI Act.

Compatible EU AI Act : voir les signataires du GPAI Code of Practice (Anthropic, Mistral, Google) et la documentation transparence : electron-bench.

Audit log: docs/audit_kicad9plus.md.

Citation

@dataset{ailiance_kicad9plus_copyleft_2026,
  author       = {Ailiance},
  title        = {{Ailiance — KiCad 9+ Schematic Corpus (Copyleft)}},
  year         = {2026},
  publisher    = {Hugging Face},
  license      = {GPL-3.0-or-later},
  url          = {https://huggingface.co/datasets/Ailiance-fr/kicad9plus-copyleft},
  note         = {Co-published with upstream electron-rare/kicad9plus-copyleft}
}

@dataset{electron_rare_kicad9plus_copyleft_2026,
  author       = {electron-rare},
  title        = {{Upstream: kicad9plus-copyleft}},
  year         = {2026},
  publisher    = {Hugging Face},
  url          = {https://huggingface.co/datasets/Ailiance-fr/kicad9plus-copyleft}
}

Related datasets

Ailiance dataset family (co-published with electron-rare/*):

Ailiance-fr/kicad9plus-permissive — KiCad 9+ schematics, permissive subset
Ailiance-fr/kicad9plus-copyleft — KiCad 9+ schematics, copyleft subset
Ailiance-fr/kill-life-embedded-qa — Kill_LIFE embedded knowledge base
Ailiance-fr/mascarade-stm32-dataset — STM32 & ARM Cortex-M Q&A
Ailiance-fr/mascarade-spice-dataset — SPICE & analog simulation Q&A
Ailiance-fr/mascarade-iot-dataset — IoT & connected devices Q&A
Ailiance-fr/mascarade-embedded-dataset — embedded systems generic Q&A

Used to train models evaluated in `ailiance/ailiance-bench` v0.2

This dataset contributes to training data for hardware-domain LoRA adapters benchmarked in the Ailiance bench suite.

Phase 6 scoreboard verdicts (7-task KiCad/SPICE evaluation):

🥇 eu-kiki: champion 4/7 tasks (DSL/PCB/SPICE/extract)
🥇 mascarade-embedded: champion P3 extraction (+48 pts)
⚠️ mascarade-kicad: catastrophic forgetting on SPICE/P2/P3

See full scoreboard: ailiance-bench README#scoreboard-lora-phase-6.

Note: this corpus is GPL-3.0 (upstream KiCad library symbols). Use of derived models trained exclusively on this dataset must comply with GPL distribution requirements.