Звіт про здоров'я програмного забезпеченнясхема 0.27.0 · метрики 2.5.0 · 2026-07-27 00:43 UTC

ludwig-ai / ludwig

Low-code framework for building custom LLMs, neural networks, and other AI models

PythonApache-2.0★ 11 746 зірок⑂ 1 218 форківз груд. 2018 р.Переглянути на GitHub ↗

ludwig-ai/ludwig має індекс здоров’я 94 зі 100, що відповідає смузі «Винятковий». Найвищий показник — Engineering Quality (96/100), найнижчий — AI Readiness (52/100). Останнє оновлення — сьогодні. Більшість нещодавньої роботи виконують 3 учасники.

загалом / 100

Винятковий

Індекс здоров'я програмного забезпечення

Метрики згруповано у зважені категорії на шкалі 1–100. Загальна оцінка починається як їхнє зважене середнє, відкаліброване за розподілом публічного реєстру, тож діапазони мають перцентильний зміст; коли публічні дані активують Політику юрисдикцій високого ризику, рейтинг коригується й отримує верхню межу 34 («У зоні ризику»).

Винятковий93-100Верхній щабель реєстру (≈ топ-5%); відповідає практично всім перевіреним критеріям

Відмінний80-92Сильний за всіма напрямами; незначні прогалини

Добрий65-79Здоровий; прогалини обмежені та керовані

Помірний50-64Прийнятний, але з помітними прогалинами; рекомендовано перевірку

Слабкий35-49Суттєві недоліки в кількох сферах

У зоні ризику20-34Суттєві слабкі місця; впровадження потребує обережності

Критичний1-19Серйозні проблеми (покинутий, єдиний мейнтейнер, без базової гігієни)

Профіль оцінок

Кожна вісь — окрема категорія. Форма важить більше, ніж середнє: здоровий об'єкт заповнює всю фігуру, тоді як профіль із піками та провалами означає, що сила в одному вимірі маскує ризик в іншому.

Зважений загальний бал 81 калібровано до 94 за шкалою опублікованого індексу (калібрування реєстру 2026-08-02).

Власність

LudwigОрганізація

176 підписників6 публічних репозиторіївз трав. 2020 р.

За цим репозиторієм стоїть організація — спільна, підзвітна опіка, здатна пережити будь-якого окремого мейнтейнера.

Пакетні екосистеми

Реєстр	Пакет	Версія	Завантажень / міс	Версії	Остання публікація	Теги
PyPI	ludwig	0.17.8	3 413	77	0 днів тому	computer-vision deep-learning ludwig machine-learning natural-language-processing

Метрики за категоріями

Життєздатність

Чи живий проєкт — чи пишеться код і чи виходять релізи?

83Відмінний · 21% загального індексу

Активність розробки

72Добрий

Як обчислюється оцінка

36/36	Свіжість push — останній push 0 дн. тому
8.3/36	Ритм комітів — 12/52 тижнів із комітами
18/18	Обсяг комітів — 267 комітів за останній рік
10/10	OpenSSF Scorecard: Maintained — 30 commit(s) and 9 issue activity found in the last 90 days -- score normalized to 10

Використані вхідні дані

commits_last_year	267
human_commit_share	0,98
days_since_last_push	0
active_weeks_last_year	12

Дисципліна релізів

100Винятковий

Як обчислюється оцінка

27/27	Випускає релізи — опубліковано 73 релізів
36/36	Свіжість релізів — останній реліз 0 дн. тому
27/27	Ритм релізів — реліз кожні ~9 дн.
0/10	OpenSSF Scorecard: Signed-Releases — немає даних

Використані вхідні дані

releases_count	73
latest_release_tag	v0.17.8
releases_from_tags	ні
days_since_latest_release	0
mean_days_between_releases	9

Виключено з оцінювання (немає даних або не застосовно): OpenSSF Scorecard: Signed-Releases. Залишкові ваги перенормовано.

Спільнота та впровадження

Чи має проєкт користувачів, завантаження, увагу та влаштовані умови для контриб’юторів?

86Відмінний · 17% загального індексу

Здоров'я спільноти

92Відмінний

Як обчислюється оцінка

22.5/22.5	README
22.5/22.5	Ліцензія — визнана ліцензія (Apache-2.0)
18/18	Настанови CONTRIBUTING
13.5/13.5	Кодекс поведінки
0/7.2	Шаблон issue
6.3/6.3	Шаблон PR

Використані вхідні дані

has_readme	так
has_license	так
readme_badges	—
has_contributing	так
has_issue_template	ні
has_code_of_conduct	так
readme_badge_services	—
has_pull_request_template	так

Впровадження в екосистемі (завантаження)

59Помірний

Як обчислюється оцінка

47.1/80	Щомісячні завантаження — 3 413 завантажень/місяць у pypi
0/20	Залежні пакети в реєстрі — ця екосистема цього не повідомляє

Використані вхідні дані

packages	ludwig
dependents	—
ecosystems	pypi
total_downloads	—
monthly_downloads	3 413

Виключено з оцінювання (немає даних або не застосовно): Залежні пакети в реєстрі. Залишкові ваги перенормовано.

Сталість та врядування

Чи переживе проєкт своїх людей — бас-фактор, реактивність, хто за ним стоїть і як супроводжуються пакети?

79Добрий · 23% загального індексу

Стійкість мейнтейнерів (бас-фактор)

77Добрий

Як обчислюється оцінка

36/54	Бас-фактор — на 3 контриб’ютор(ів) припадає половина всіх комітів
17.6/22.5	Розподіл комітів — головний контриб’ютор — автор 22% комітів
13.5/13.5	Широта контриб’юторів — 98 контриб’юторів
10/10	OpenSSF Scorecard: Contributors — project has 17 contributing companies or organizations

Використані вхідні дані

bus_factor	3
contributors_sampled	98
top_contributor_share	0,219

Реактивність на issue та PR

78Добрий

Як обчислюється оцінка

42/42	Вирішення issue — закрито 100% issue
25.9/30	Прийняття PR — злито 2 588/2 999 вирішених PR
0/13	Newcomer PR acceptance — за 30 дн. не вирішено жодного PR від новачка
0/15	OpenSSF Scorecard: Code-Review — Found 0/28 approved changesets -- score normalized to 0

Використані вхідні дані

merged_prs	2 588
open_issues	1
closed_issues	1 094
prs_merged_7d	—
prs_decided_7d	—
prs_merged_30d	—
prs_decided_30d	—
issue_closed_ratio	0,999
closed_unmerged_prs	411
first_time_authors_30d	—
first_time_prs_merged_30d	—
first_time_prs_decided_30d	—

Виключено з оцінювання (немає даних або не застосовно): newcomer_pr_acceptance. Залишкові ваги перенормовано.

Власність та опіка

64Помірний

Як обчислюється оцінка

30/30	Підтримка власника — у власності організації
0/20	Верифікований домен
16.2/25	Охоплення власника — 176 підписників у ludwig-ai
18.2/25	Послужний список — 6 публічних репозиторіїв, вік облікового запису ~6 р.

Використані вхідні дані

followers	176
owner_type	Organization
is_verified	—
owner_login	ludwig-ai
public_repos	6
account_age_days	2 261

Супровід пакетів

100Винятковий

Як обчислюється оцінка

25/25	Опубліковано й доступно — 1 пакет(ів) у pypi
35/35	Свіжість публікацій — остання публікація 0 дн. тому
20/20	Історія версій — 77 опублікованих версій
20/20	Не застарілий — активний, не deprecated і не yanked

Використані вхідні дані

packages	ludwig
ecosystems	pypi
any_deprecated	ні
min_days_since_publish	0

Інженерна якість

Чи наявні базові інженерні практики та документація?

96Винятковий · 19% загального індексу

Інженерні практики

94Винятковий

Як обчислюється оцінка

24/24	Процеси CI — 6 процес(ів) CI
24/24	Наявні тести
16/16	Конфігурація лінтера — .flake8
9.6/9.6	Pre-commit-хуки
0/6.4	.editorconfig
20/20	OpenSSF Scorecard: CI-Tests — 2 out of 2 merged PRs checked by a CI test -- score normalized to 10

Використані вхідні дані

has_ci	так
has_tests	так
has_editorconfig	ні
has_linter_config	так
has_precommit_config	так

Документація

100Винятковий

Як обчислюється оцінка

30/30	README
25/25	Каталог документації
15/15	Сайт документації / домашня сторінка — http://ludwig.ai
10/10	Опис репозиторію
10/10	Теми — 20 тем
10/10	Wiki

Використані вхідні дані

topics	deep-learning, deeplearning, deep, learning, machine-learning, machinelearning, natural-language-processing, natural-language, computer-vision, data-centric, data-science, pytorch, neural-network, ml, llm, llm-training, fine-tuning, llama, mistral, llama2
has_wiki	так
homepage	http://ludwig.ai
has_readme	так
has_docs_dir	так
has_description	так

Безпека

Чи міцні видимі практики безпеки й ланцюга постачання, без непослабленої пов’язаності з юрисдикціями високого ризику?

64Помірний · 16% загального індексу

Стан безпеки

64Помірний

Як обчислюється оцінка

7.5/7.5	Binary-Artifacts — no binaries found in the repo
0/7.5	Branch-Protection — немає даних
2.5/2.5	CI-Tests — 2 out of 2 merged PRs checked by a CI test -- score normalized to 10
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5	Code-Review — Found 0/28 approved changesets -- score normalized to 0
2.5/2.5	Contributors — project has 17 contributing companies or organizations
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5	Dependency-Update-Tool — update tool detected
0/5	Fuzzing — project is not fuzzed
2.5/2.5	Ліцензія — license file detected
7.5/7.5	Maintained — 30 commit(s) and 9 issue activity found in the last 90 days -- score normalized to 10
5/5	Packaging — packaging workflow detected
0/5	Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5	SAST — SAST tool is not run on all commits -- score normalized to 0
5/5	Security-Policy — security policy file detected
0/7.5	Signed-Releases — немає даних
0/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5	Vulnerabilities — 0 existing vulnerabilities detected

Використані вхідні дані

source	openssf_scorecard
checks_evaluated	16
scorecard_version	v5.5.0
checks_inconclusive	2
scorecard_aggregate	6,4

Виключено з оцінювання (немає даних або не застосовно): branch_protection, signed_releases. Залишкові ваги перенормовано.

Готовність до ШІ

Наскільки репозиторій оснащений для розробки та супроводу за участі ШІ-агентів? Має свідомо малу вагу (4%): агентний інструментарій — реальний сигнал супроводу, але репозиторій без нього все одно може отримати 100/100.

52Помірний · 4% загального індексу

Контекст і настанови для агентів

40Слабкий

Як обчислюється оцінка

0/45	Інструкції для агентів — немає CLAUDE.md / AGENTS.md / правил редактора
0/15	Машиночитана документація (llms.txt)
40/40	Читабельна історія комітів — намір зазначено у 90 з 98 людських комітів (структурований заголовок або пояснювальний текст)

Використані вхідні дані

has_llms_txt	ні
legible_history_share	0,918
agent_instruction_files	—
agent_instruction_max_bytes	—

Цикл верифікації (збірка / тести / перевірка типів)

54Помірний

Як обчислюється оцінка

0/18	Розгортання однією командою
22/22	Автоматизовані тести
11/11	Конфігурація лінтера / форматера — .flake8
11/11	Статична перевірка типів — ludwig/py.typed
10/10	Відтворюване середовище — devcontainer, Dockerfile
0/10	Підтверджена практика роботи з агентами — серед останніх 100 комітів немає створених агентом
0/8	Автоматизоване супроводження — автоматичних оновлень залежностей не виявлено
0/10	OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0

Використані вхідні дані

has_nix	ні
has_tests	так
lockfiles	—
has_dockerfile	так
typed_language	ні
bootstrap_files	—
has_devcontainer	так
has_linter_config	так
typecheck_configs	ludwig/py.typed
agent_commit_share	0
toolchain_manifests	—
dependency_bot_commit_share	0

Читабельність коду для моделей

82Відмінний

Як обчислюється оцінка

27/45	Типізований код — Python з конфігурацією перевірки типів (ludwig/py.typed)
54.5/55	Керовані розміри файлів — 7/805 файлів вихідного коду понад 60 КБ

Використані вхідні дані

primary_language	Python
largest_source_bytes	107 706
source_files_sampled	805
oversized_source_files	7

Машиночитні інтерфейси

40Слабкий

Як обчислюється оцінка

0/40	Схема API (OpenAPI/GraphQL/proto)
0/20	Сервер MCP
40/40	Придатні до запуску приклади — examples, notebooks

Використані вхідні дані

example_dirs	examples, notebooks
has_mcp_signal	ні
api_schema_files	—

Ключові факти

11 746зірок GitHub

98контриб'юторів

267комітів за останні 12 місяців

0днів від останнього пушу

73релізів

3бас-фактор

1відкритих issue

PyPIпакетних екосистем

Попередження щодо збору даних

Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
deps.dev does not index pypi:ludwig@0.17.8; advisories assessed against the repository dependency graph instead
No resolved dependencies carried a version and a supported ecosystem

Докладніше

Історія зірок і форків 0 ★ / 1 218 ⇿

0Зірки

1 218Форки

71Релізи

Коли додано кожну зірку й форк — зібрано з GitHub і згруповано за днями. Кумулятивне зростання розміщено просто над денними додаваннями, з яких воно складається, тож їх видно одне проти одного: рівномірне органічне накопичення виглядає зовсім інакше, ніж різкий короткочасний сплеск. Там, де цю різницю можна виміряти, її подано як автентичність росту.

Показано лише найновішу історію — цей репозиторій перевищує вікно збору, тож найраніша історія не захоплена.

Мажорні 0Мінорні 8Патчі 49

Кожна точка охоплює 7 днів.

OpenSSF Scorecard 6.4 / 10

6.4сукупно

Незалежна, не прив'язана до інструментів оцінка безпеки від відкритого проєкту OpenSSF Scorecard. Кожна перевірка винагороджує практику безпеки, а не інструмент конкретного постачальника. Перевірки, які Scorecard не зміг визначити, позначено н/д і виключено з оцінки безпеки (вони ніколи не зараховуються як нуль).Scorecard v5.5.0 · 2026-07-27 00:42 UTC

10	Binary-Artifacts	no binaries found in the repo
н/д	Branch-Protection	internal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
10	CI-Tests	2 out of 2 merged PRs checked by a CI test -- score normalized to 10
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
0	Code-Review	Found 0/28 approved changesets -- score normalized to 0
10	Contributors	project has 17 contributing companies or organizations
10	Dangerous-Workflow	no dangerous workflow patterns detected
10	Dependency-Update-Tool	update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
10	Maintained	30 commit(s) and 9 issue activity found in the last 90 days -- score normalized to 10
10	Packaging	packaging workflow detected
0	Pinned-Dependencies	dependency not pinned by hash detected -- score normalized to 0
0	SAST	SAST tool is not run on all commits -- score normalized to 0
10	Security-Policy	security policy file detected
н/д	Signed-Releases	no releases found
0	Token-Permissions	detected GitHub workflow tokens with excessive permissions
10	Vulnerabilities	0 existing vulnerabilities detected

Прямі залежності 40

Реєстр	Пакет	Обмеження версії	Маніфест
PyPI	numpy	`>=1.24`	pyproject.toml
PyPI	pandas	`>=2.0`	pyproject.toml
PyPI	scipy	`>=1.10`	pyproject.toml
PyPI	tabulate	`>=0.9`	pyproject.toml
PyPI	scikit-learn	`>=1.3`	pyproject.toml
PyPI	tqdm	`>=4.60`	pyproject.toml
PyPI	torch	`>=2.11`	pyproject.toml
PyPI	torchaudio	`>=2.11`	pyproject.toml
PyPI	torchcodec	`>=0.1`	pyproject.toml
PyPI	torchvision	`>=0.26`	pyproject.toml
PyPI	transformers	`>=5.0`	pyproject.toml
PyPI	sentencepiece	`>=0.2`	pyproject.toml
PyPI	spacy	`>=2.3`	pyproject.toml
PyPI	PyYAML	`>=6.0`	pyproject.toml
PyPI	absl-py	`—`	pyproject.toml
PyPI	kaggle	`—`	pyproject.toml
PyPI	requests	`>=2.28`	pyproject.toml
PyPI	py-cpuinfo	`—`	pyproject.toml
PyPI	fsspec	`—`	pyproject.toml
PyPI	dataclasses-json	`—`	pyproject.toml
PyPI	jsonschema	`>=4.17`	pyproject.toml
PyPI	tensorboard	`—`	pyproject.toml
PyPI	torchmetrics	`>=1.0`	pyproject.toml
PyPI	torchinfo	`—`	pyproject.toml
PyPI	filelock	`—`	pyproject.toml
PyPI	psutil	`—`	pyproject.toml
PyPI	protobuf	`>=4.0`	pyproject.toml
PyPI	gpustat	`—`	pyproject.toml
PyPI	rich	`>=12.4.4`	pyproject.toml
PyPI	packaging	`—`	pyproject.toml
PyPI	retry	`—`	pyproject.toml
PyPI	sacremoses	`—`	pyproject.toml
PyPI	bitsandbytes	`>=0.44.0`	pyproject.toml
PyPI	xlwt	`—`	pyproject.toml
PyPI	xlrd	`—`	pyproject.toml
PyPI	openpyxl	`—`	pyproject.toml
PyPI	pyarrow	`>=14.0`	pyproject.toml
PyPI	lxml	`—`	pyproject.toml
PyPI	datasets	`—`	pyproject.toml
PyPI	safetensors	`>=0.4`	pyproject.toml

Усі залежності 32

Повний розв'язаний набір залежностей із графа залежностей GitHub: 22 прямих і 10 непрямих (транзитивних) пакетів. Транзитивне замикання є повним, коли в репозиторії закомічено lockfile.

Реєстр	Пакет	Версія	Зв'язок
PyPI	bitsandbytes	`—`	пряма
PyPI	jsonschema	`—`	пряма
PyPI	numpy	`—`	пряма
PyPI	pandas	`—`	пряма
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PyPI	pyyaml	`—`	пряма
PyPI	requests	`—`	пряма
PyPI	rich	`—`	пряма
PyPI	safetensors	`—`	пряма
PyPI	scikit-learn	`—`	пряма
PyPI	scipy	`—`	пряма
PyPI	sentencepiece	`—`	пряма
PyPI	spacy	`—`	пряма
PyPI	tabulate	`—`	пряма
PyPI	torch	`—`	пряма
PyPI	torchaudio	`—`	пряма
PyPI	torchcodec	`—`	пряма
PyPI	torchmetrics	`—`	пряма
PyPI	torchvision	`—`	пряма
PyPI	tqdm	`—`	пряма
PyPI	transformers	`—`	пряма
PyPI	configspace	`—`	непряма
PyPI	dask	`—`	непряма
PyPI	future	`—`	непряма
PyPI	matplotlib	`—`	непряма
PyPI	peft	`—`	непряма
PyPI	predibase	`—`	непряма
PyPI	ray	`—`	непряма
PyPI	ruff	`—`	непряма
PyPI	s3fs	`—`	непряма
PyPI	torchao	`—`	непряма

Сповіщення про залежності не оцінено

Звірка сповіщень не відбулася для цього звіту: No resolved dependencies carried a version and a supported ecosystem

Звіт у форматі JSON машиночитний

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          "is_bot": false,
          "headline": "fix(automl): dataset-aware sampling, transformer LR cap, SearchSpace …",
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          "is_bot": false,
          "headline": "feat(automl): dataset-size-aware epoch and batch_size caps in configs…",
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          "is_bot": false,
          "headline": "revert: remove tabpfn optional-dep workaround — tabpfn is now installed",
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          "is_bot": false,
          "headline": "feat: Mega-AutoML infrastructure — YAML search space, config pipeline…",
          "author_name": "Piero Molino",
          "author_login": "w4nderlust",
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          "is_bot": false,
          "headline": "refactor: remove stale duplicate text/encoders.py; flatten deep nesti…",
          "author_name": "Piero Molino",
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          "body": "…package (#4154)",
          "is_bot": false,
          "headline": "refactor: split 4144-line visualize.py into domain-scoped visualize/ …",
          "author_name": "Piero Molino",
          "author_login": "w4nderlust",
          "committed_at": "2026-05-11T03:25:18Z",
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          "headline": "Release v0.16.2",
          "author_name": "w4nderlust",
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          "headline": "fix: rewrite torch_utils tests to not fail in no-CUDA CI environments",
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          "committed_at": "2026-05-08T06:47:12Z",
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          "headline": "fix: update test_serve_v2 to use numpy_to_python (renamed from _numpy…",
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          "body": "…in__.py for python -m ludwig.visualize",
          "is_bot": false,
          "headline": "fix: remove redundant dtype check in text_feature; add visualize __ma…",
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          "body": "…tations, docstring fixes",
          "is_bot": false,
          "headline": "refactor: major api.py cleanup — guard clauses, extraction, type anno…",
          "author_name": "Piero Molino",
          "author_login": "w4nderlust",
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        {
          "oid": "686aa93225b3442215e4a2ad2b8bd81ac6eb578d",
          "body": "…st strategy\n\nTwo regression tests to prevent re-introduction of the bugs fixed in\nthe recent patch releases:\n\n1. tests/ludwig/utils/test_import_safety.py (#4142)\n   Simulates a broken torchao/PyTorch environment where transformers'\n   lazy loader raises ModuleNotFoundError for PreTrainedModel. Veri\n[…]\nr: Distributed strategy not\n   initialized. The existing category-output test missed this because\n   SoftmaxCrossEntropyMetric inherits MeanMetric and takes a shortcut\n   that bypasses sync_context().",
          "is_bot": false,
          "headline": "test: regression tests for transformers import safety and Ray tune di…",
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          "body": "…learning_rate_fn\n\nBoth Ray remote tuning functions run metric evaluation (train_step →\nupdate_metrics → eval_loss → TorchMetrics sync_context) without ever\ninitializing a distributed strategy. This caused:\n\n  RuntimeError: Distributed strategy not initialized\n\nin get_current_dist_strategy() inside \n[…]\nwhat train_fn and eval_fn already do: call\ninit_dist_strategy(\"local\") immediately after initialize_pytorch() so\nthe metric sync context is available for the duration of the tuning pass.\n\nFixes #4149.",
          "is_bot": false,
          "headline": "fix: call init_dist_strategy(\"local\") in tune_batch_size_fn and tune_…",
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          "headline": "Release v0.16.1",
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          "body": "…CKING in llm_utils and text_feature\n\nOn Python 3.12, function annotations are evaluated eagerly at module load\ntime. When torchao and PyTorch are version-mismatched (torchao calls\ntorch.utils._pytree.register_constant which doesn't exist in older PyTorch\nbuilds), transformers' lazy loader for class\n[…]\ne them to\n  TYPE_CHECKING and add `from __future__ import annotations`.\n- text_feature.py: PreTrainedTokenizer was imported at module level but only\n  used in type annotations. Same fix.\n\nFixes #4142.",
          "is_bot": false,
          "headline": "fix: defer PreTrainedModel/PreTrainedTokenizer/AutoConfig to TYPE_CHE…",
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          "is_bot": false,
          "headline": "refactor: migrate from black+isort+flake8 to unified ruff toolchain",
          "author_name": "Piero Molino",
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          "is_bot": false,
          "headline": "fix: replace assert with explicit exceptions; fix mutable default arg…",
          "author_name": "Piero Molino",
          "author_login": "w4nderlust",
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                "name": "Release cadence",
                "detail": "a release every ~9 days",
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                "details": [
                  {
                    "code": "release_cadence",
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                      "gap": 9
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                "max_points": 27
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              {
                "key": "openssf_scorecard_signed_releases",
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                "status": "excluded",
                "details": [
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                    "code": "no_data",
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                "max_points": 10
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          {
            "key": "abandonment",
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            "note": null,
            "notes": [],
            "value": 100,
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              "cap": null,
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        ],
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      },
      {
        "key": "community",
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        "name": "Community & Adoption",
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            "key": "popularity",
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            "note": null,
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              "forks": 1218,
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              "watchers": 183,
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            "components": [
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              {
                "key": "forks",
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                      "count": 1218
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              {
                "key": "watchers",
                "name": "Watchers",
                "detail": "183 watchers",
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                "status": "partial",
                "details": [
                  {
                    "code": "watchers",
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                      "count": 183
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                "max_points": 15
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            ]
          },
          {
            "key": "community_health",
            "band": "excellent",
            "name": "Community health",
            "note": null,
            "notes": [],
            "value": 92,
            "inputs": {
              "has_readme": true,
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              "readme_badges": null,
              "has_contributing": true,
              "has_issue_template": false,
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            "components": [
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                "key": "readme",
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                "status": "met",
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                "max_points": 22.5
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              {
                "key": "license",
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                "detail": "recognized license (Apache-2.0)",
                "points": 22.5,
                "status": "met",
                "details": [
                  {
                    "code": "license_standard",
                    "params": {}
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                  {
                    "code": "license_spdx",
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                "max_points": 22.5
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              {
                "key": "contributing_guide",
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              {
                "key": "code_of_conduct",
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                "key": "issue_template",
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                "key": "pr_template",
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          },
          {
            "key": "ecosystem_adoption",
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            "notes": [
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                "code": "excluded_no_data",
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              },
              {
                "code": "weights_renormalized",
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            "value": 59,
            "inputs": {
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              "dependents": null,
              "ecosystems": "pypi",
              "total_downloads": null,
              "monthly_downloads": 3413
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            "components": [
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                "key": "monthly_downloads",
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                    "code": "downloads_monthly",
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                  }
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                "max_points": 80
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              {
                "key": "registry_dependents",
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                "points": 0,
                "status": "excluded",
                "details": [
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                    "code": "not_reported_by_this_ecosystem",
                    "params": {}
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                "max_points": 20
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        ],
        "description": "Does the project have users, downloads, attention, and a welcoming setup for contributors?"
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      {
        "key": "governance",
        "band": "good",
        "name": "Sustainability & Governance",
        "value": 79,
        "weight": 0.23,
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            "key": "maintainer_resilience",
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            "note": null,
            "notes": [],
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                "key": "bus_factor",
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                "key": "commit_distribution",
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                    "code": "top_contributor_share",
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                "max_points": 22.5
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                "key": "contributor_breadth",
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                "status": "met",
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                      "count": 98
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                "max_points": 13.5
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              {
                "key": "openssf_scorecard_contributors",
                "name": "OpenSSF Scorecard: Contributors",
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                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
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            ]
          },
          {
            "key": "responsiveness",
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            "notes": [
              {
                "code": "excluded_no_data",
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              {
                "code": "weights_renormalized",
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            "value": 78,
            "inputs": {
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            "components": [
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                "key": "issue_resolution",
                "name": "Issue resolution",
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                "points": 42,
                "status": "partial",
                "details": [
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                    "code": "issues_closed_share",
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                      "share": 100
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                "max_points": 42
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              {
                "key": "pr_acceptance",
                "name": "PR acceptance",
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                "max_points": 30
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              {
                "key": "newcomer_pr_acceptance",
                "name": "Newcomer PR acceptance",
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                    "code": "no_newcomer_prs",
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                "key": "openssf_scorecard_code_review",
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          },
          {
            "key": "stewardship",
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            "inputs": {
              "followers": 176,
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                "key": "verified_domain",
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              {
                "key": "owner_reach",
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                "detail": "176 followers of ludwig-ai",
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                "key": "track_record",
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                    "code": "account_age_years",
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            "key": "package_maintenance",
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            "note": null,
            "notes": [],
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            "inputs": {
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              "ecosystems": "pypi",
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                "key": "published_resolvable",
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                "key": "publish_recency",
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                "max_points": 35
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                "key": "version_history",
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                "key": "not_deprecated",
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                "max_points": 20
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            ]
          }
        ],
        "description": "Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?"
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      {
        "key": "engineering",
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        "metrics": [
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                "key": "ci_workflows",
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              {
                "key": "linter_config",
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                "key": "pre_commit_hooks",
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                "key": "editorconfig",
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              },
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                "key": "openssf_scorecard_ci_tests",
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            "notes": [],
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            "components": [
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                "key": "readme",
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                "key": "documentation_directory",
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                "key": "documentation_homepage_site",
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                "key": "repository_description",
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                "key": "topics",
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              },
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                "key": "wiki",
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            ]
          }
        ],
        "description": "Are baseline engineering and documentation practices in place?"
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      {
        "key": "security",
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        "weight": 0.16,
        "metrics": [
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            "key": "security_posture",
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                "code": "excluded_no_data",
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                }
              },
              {
                "code": "weights_renormalized",
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            ],
            "value": 64,
            "inputs": {
              "source": "openssf_scorecard",
              "checks_evaluated": 16,
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            "components": [
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                "key": "binary_artifacts",
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                "key": "branch_protection",
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                "points": 0,
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                "key": "ci_tests",
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              {
                "key": "cii_best_practices",
                "name": "CII-Best-Practices",
                "detail": "no effort to earn an OpenSSF best practices badge detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "code_review",
                "name": "Code-Review",
                "detail": "Found 0/28 approved changesets -- score normalized to 0",
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              },
              {
                "key": "contributors",
                "name": "Contributors",
                "detail": "project has 17 contributing companies or organizations",
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                "details": [],
                "max_points": 2.5
              },
              {
                "key": "dangerous_workflow",
                "name": "Dangerous-Workflow",
                "detail": "no dangerous workflow patterns detected",
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
              },
              {
                "key": "dependency_update_tool",
                "name": "Dependency-Update-Tool",
                "detail": "update tool detected",
                "points": 7.5,
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                "details": [],
                "max_points": 7.5
              },
              {
                "key": "fuzzing",
                "name": "Fuzzing",
                "detail": "project is not fuzzed",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "license",
                "name": "License",
                "detail": "license file detected",
                "points": 2.5,
                "status": "met",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "maintained",
                "name": "Maintained",
                "detail": "30 commit(s) and 9 issue activity found in the last 90 days -- score normalized to 10",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "packaging",
                "name": "Packaging",
                "detail": "packaging workflow detected",
                "points": 5,
                "status": "met",
                "details": [],
                "max_points": 5
              },
              {
                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "sast",
                "name": "SAST",
                "detail": "SAST tool is not run on all commits -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "security_policy",
                "name": "Security-Policy",
                "detail": "security policy file detected",
                "points": 5,
                "status": "met",
                "details": [],
                "max_points": 5
              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
                "detail": "no releases found",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 7.5
              },
              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "detected GitHub workflow tokens with excessive permissions",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "0 existing vulnerabilities detected",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              }
            ]
          },
          {
            "key": "high_risk_jurisdiction_exposure",
            "band": "exceptional",
            "name": "High-Risk Jurisdiction Exposure",
            "note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
            "notes": [
              {
                "code": "jurisdiction_evidence_limits",
                "params": {}
              }
            ],
            "value": 100,
            "inputs": {
              "meaning": "self-published location evidence; not nationality or citizenship",
              "red_flag": false,
              "exposures": [],
              "policy_countries": [
                "Russia",
                "Iran",
                "North Korea"
              ],
              "commit_weight_rule": {
                "min_commits": 50,
                "min_commit_share": 0.1
              },
              "review_only_matches": 0,
              "below_threshold_exposures": [],
              "assessed_self_published_locations": 8
            },
            "components": [
              {
                "key": "policy_exposure_multiplier",
                "name": "Policy exposure multiplier",
                "detail": "no confirmed policy-scope location match",
                "points": 100,
                "status": "met",
                "details": [
                  {
                    "code": "jurisdiction_no_match",
                    "params": {}
                  }
                ],
                "max_points": 100
              }
            ]
          }
        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
      },
      {
        "key": "ai_readiness",
        "band": "moderate",
        "name": "AI Readiness",
        "value": 52,
        "weight": 0.04,
        "metrics": [
          {
            "key": "ai_agent_context",
            "band": "weak",
            "name": "Agent context & guidance",
            "note": null,
            "notes": [],
            "value": 40,
            "inputs": {
              "has_llms_txt": false,
              "legible_history_share": 0.918,
              "agent_instruction_files": [],
              "agent_instruction_max_bytes": null
            },
            "components": [
              {
                "key": "agent_instructions",
                "name": "Agent instructions",
                "detail": "no CLAUDE.md / AGENTS.md / editor rules",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_agent_instructions",
                    "params": {}
                  }
                ],
                "max_points": 45
              },
              {
                "key": "machine_readable_docs_llms_txt",
                "name": "Machine-readable docs (llms.txt)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 15
              },
              {
                "key": "legible_commit_history",
                "name": "Legible commit history",
                "detail": "90 of 98 human commits state their intent (structured subject or explanatory body)",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "legible_history",
                    "params": {
                      "legible": 90,
                      "sampled": 98
                    }
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
            "band": "moderate",
            "name": "Verify loop (build / test / typecheck)",
            "note": null,
            "notes": [],
            "value": 54,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [],
              "has_dockerfile": true,
              "typed_language": false,
              "bootstrap_files": [],
              "has_devcontainer": true,
              "has_linter_config": true,
              "typecheck_configs": [
                "ludwig/py.typed"
              ],
              "agent_commit_share": 0,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": 0
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 18
              },
              {
                "key": "automated_tests",
                "name": "Automated tests",
                "detail": null,
                "points": 22,
                "status": "met",
                "details": [],
                "max_points": 22
              },
              {
                "key": "lint_format_config",
                "name": "Lint / format config",
                "detail": ".flake8",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": ".flake8"
                    }
                  }
                ],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
                "name": "Static type checking",
                "detail": "ludwig/py.typed",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "ludwig/py.typed"
                    }
                  }
                ],
                "max_points": 11
              },
              {
                "key": "reproducible_environment",
                "name": "Reproducible environment",
                "detail": "devcontainer, Dockerfile",
                "points": 10,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "devcontainer, Dockerfile"
                    }
                  }
                ],
                "max_points": 10
              },
              {
                "key": "demonstrated_agent_practice",
                "name": "Demonstrated agent practice",
                "detail": "no agent-authored commits among the last 100",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_agent_authored_commits",
                    "params": {
                      "sampled": 100
                    }
                  }
                ],
                "max_points": 10
              },
              {
                "key": "automated_maintenance",
                "name": "Automated maintenance",
                "detail": "no automated dependency updates observed",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_dependency_automation",
                    "params": {}
                  }
                ],
                "max_points": 8
              },
              {
                "key": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 10
              }
            ]
          },
          {
            "key": "ai_code_legibility",
            "band": "excellent",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 82,
            "inputs": {
              "primary_language": "Python",
              "largest_source_bytes": 107706,
              "source_files_sampled": 805,
              "oversized_source_files": 7
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python with type-check config (ludwig/py.typed)",
                "points": 27,
                "status": "partial",
                "details": [
                  {
                    "code": "typecheck_config_language",
                    "params": {
                      "files": "ludwig/py.typed",
                      "language": "Python"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "7/805 source files over 60KB",
                "points": 54.5,
                "status": "partial",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 805,
                      "oversized": 7
                    }
                  }
                ],
                "max_points": 55
              }
            ]
          },
          {
            "key": "ai_interfaces",
            "band": "weak",
            "name": "Machine-readable interfaces",
            "note": null,
            "notes": [],
            "value": 40,
            "inputs": {
              "example_dirs": [
                "examples",
                "notebooks"
              ],
              "has_mcp_signal": false,
              "api_schema_files": []
            },
            "components": [
              {
                "key": "api_schema_openapi_graphql_proto",
                "name": "API schema (OpenAPI/GraphQL/proto)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 40
              },
              {
                "key": "mcp_server",
                "name": "MCP server",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 20
              },
              {
                "key": "runnable_examples",
                "name": "Runnable examples",
                "detail": "examples, notebooks",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "examples, notebooks"
                    }
                  }
                ],
                "max_points": 40
              }
            ]
          }
        ],
        "description": "How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight: agent tooling is a real maintenance signal, but its absence must never gate the top of the scale (calibration saturates at raw 91, so 100/100 remains reachable with AI Readiness at zero)."
      }
    ],
    "classification": {
      "top": [
        "library"
      ],
      "labels": [
        "library"
      ],
      "scores": {
        "library": 8
      },
      "primary": "library",
      "evidence": [
        {
          "tier": "distribution",
          "label": "library",
          "source": "registry:pypi",
          "weight": 6
        },
        {
          "tier": "description",
          "label": "library",
          "source": "description:library",
          "weight": 2
        }
      ],
      "artifacts": [],
      "confidence": "medium",
      "host_extension": false,
      "runs_as_process": false,
      "consumed_by_code": true
    },
    "metrics_version": "2.5.0"
  },
  "warnings": [
    "Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token",
    "deps.dev does not index pypi:ludwig@0.17.8; advisories assessed against the repository dependency graph instead",
    "No resolved dependencies carried a version and a supported ecosystem"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-27T00:43:05.617223Z",
  "schema_version": "0.27.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/l/ludwig-ai/ludwig.svg",
  "full_name": "ludwig-ai/ludwig",
  "license_state": "standard",
  "license_spdx": "Apache-2.0"
}

Оцінки — це сигнали, а не гарантії. Вони відображають публічно видимі практики на GitHub — це не аудит коду й не гарантія безпеки.

Відсутні дані виключаються, а ваги перенормовуються — нуль за відсутність ніколи не ставиться. Методологія версіонована й відкрита: метрики v2.5.0, схема v0.27.0 — повна методологія · вікі метрик.

Як окремий результат виглядає на тлі всього реєстру: сукупна статистика — PyPI.

60/60	Зірки — 11 746 зірок
25/25	Форки — 1 218 форків
12.6/15	Спостерігачі — 183 спостерігачів

forks	1 218
stars	11 746
watchers	183
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Індекс здоров'я програмного забезпечення

Профіль оцінок

Власність

Пакетні екосистеми

Метрики за категоріями

Ключові факти

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