Публічний реєстр
Звіт про здоров'я програмного забезпеченнясхема 0.16.0 · метрики 1.13.0 · 2026-07-21 02:45 UTC

mlc-ai / xgrammar

Fast, Flexible and Portable Structured Generation

C++ · PythonApache-2.0★ 1 792 зірки⑂ 172 форкиз черв. 2024 р.Переглянути на GitHub ↗
#large-language-models#structured-generation

mlc-ai/xgrammar має індекс здоров’я 82 зі 100, що відповідає смузі «Добрий». Найвищий показник — Vitality (99/100), найнижчий — AI Readiness (56/100). Останнє оновлення — сьогодні. Більшість нещодавньої роботи виконують 2 учасники.

82
загалом / 100
Добрий

Індекс здоров'я програмного забезпечення

Метрики згруповано у зважені категорії на шкалі 1–100. Загальна оцінка починається як їхнє середнє; коли публічні дані активують Політику юрисдикцій високого ризику, рейтинг коригується й отримує верхню межу 49 («Під ризиком»). Готовність до ШІ не входить до індексу.

82
Відмінний85-100Зразковий; відповідає практично всім перевіреним критеріям
Добрий70-84Здоровий; незначні прогалини
Помірний50-69Прийнятний, але з помітними прогалинами; рекомендовано перевірку
У зоні ризику30-49Суттєві слабкі місця; впровадження потребує обережності
Критичний1-29Серйозні проблеми (покинутий, єдиний мейнтейнер, без базової гігієни)
ЖиттєздатністьСпільнота тавпровадженняСталість таврядуванняІнженернаякістьБезпекаГотовність доШІ

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.

Власність

mlc-aiОрганізація
2 149 підписників39 публічних репозиторіївз трав. 2022 р.

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

Пакетні екосистеми

РеєстрПакетВерсіяЗавантажень / місВерсіїОстання публікаціяТеги
PyPIxgrammar0.2.46 561 105422 дні томуmachine-learninginference
npm@mlc-ai/web-xgrammar0.1.271 0472207 днів томуmachine-learningllmnlp

Метрики за категоріями

Життєздатність

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

99Відмінний · 22% загального індексу

Активність розробки

99Відмінний
Як обчислюється оцінка
36/36Свіжість push — останній push 0 дн. тому
34.6/36Ритм комітів — 50/52 тижнів із комітами
18/18Обсяг комітів — 222 комітів за останній рік
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 15 issue activity found in the last 90 days -- score normalized to 10
Використані вхідні дані
commits_last_year222
human_commit_share—
days_since_last_push0
active_weeks_last_year50

Дисципліна релізів

100Відмінний
Як обчислюється оцінка
27/27Випускає релізи — опубліковано 32 релізів
36/36Свіжість релізів — останній реліз 2 дн. тому
27/27Ритм релізів — реліз кожні ~20,2 дн.
0/10OpenSSF Scorecard: Signed-Releases — немає даних
Використані вхідні дані
releases_count32
latest_release_tagv0.2.4
releases_from_tagsні
days_since_latest_release2
mean_days_between_releases20,2
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?

81Добрий · 18% загального індексу

Популярність і впровадження

78Добрий
Як обчислюється оцінка
52.8/60Зірки — 1 792 зірок
18.6/25Форки — 172 форків
6.7/15Спостерігачі — 17 спостерігачів
Використані вхідні дані
forks172
stars1 792
watchers17
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Здоров'я спільноти

70Добрий
Як обчислюється оцінка
22.5/22.5README
22.5/22.5Ліцензія — визнана ліцензія (Apache-2.0)
18/18Настанови CONTRIBUTING
0/13.5Кодекс поведінки
0/7.2Шаблон issue
0/6.3Шаблон PR
Використані вхідні дані
has_readmeтак
has_licenseтак
has_contributingтак
has_issue_templateні
has_code_of_conductні
has_pull_request_templateні

Впровадження в екосистемі (завантаження)

100Відмінний
Як обчислюється оцінка
80/80Щомісячні завантаження — 6 562 152 завантажень/місяць у npm, pypi
0/20Залежні пакети в реєстрі — ця екосистема цього не повідомляє
Використані вхідні дані
packagesxgrammar, @mlc-ai/web-xgrammar
dependents—
ecosystemsnpm, pypi
total_downloads—
monthly_downloads6 562 152
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?

78Добрий · 24% загального індексу

Стійкість мейнтейнерів (бас-фактор)

62Помірний
Як обчислюється оцінка
25.2/54Бас-фактор — на 2 контриб’ютор(ів) припадає половина всіх комітів
13.5/22.5Розподіл комітів — головний контриб’ютор — автор 40% комітів
13.5/13.5Широта контриб’юторів — 58 контриб’юторів
10/10OpenSSF Scorecard: Contributors — project has 13 contributing companies or organizations
Використані вхідні дані
bus_factor2
contributors_sampled58
top_contributor_share0,398

Реактивність на issue та PR

82Добрий
Як обчислюється оцінка
39.4/46.8Вирішення issue — закрито 84% issue
33.1/38.3Прийняття PR — злито 467/540 вирішених PR
9/15OpenSSF Scorecard: Code-Review — Found 18/30 approved changesets -- score normalized to 6
Використані вхідні дані
merged_prs467
open_issues24
closed_issues128
issue_closed_ratio0,842
closed_unmerged_prs73

Власність та опіка

74Добрий
Як обчислюється оцінка
30/30Підтримка власника — у власності організації
0/20Верифікований домен
24/25Охоплення власника — 2 149 підписників у mlc-ai
20/25Послужний список — 39 публічних репозиторіїв, вік облікового запису ~4 р.
Використані вхідні дані
followers2 149
owner_typeOrganization
is_verified—
owner_loginmlc-ai
public_repos39
account_age_days1 518

Супровід пакетів

100Відмінний
Як обчислюється оцінка
25/25Опубліковано й доступно — 2 пакет(ів) у npm, pypi
35/35Свіжість публікацій — остання публікація 2 дн. тому
20/20Історія версій — 42 опублікованих версій
20/20Не застарілий — активний, не deprecated і не yanked
Використані вхідні дані
packagesxgrammar, @mlc-ai/web-xgrammar
ecosystemsnpm, pypi
any_deprecatedні
min_days_since_publish2

Інженерна якість

Чи наявні базові інженерні практики та документація?

92Відмінний · 20% загального індексу

Інженерні практики

94Відмінний
Як обчислюється оцінка
24/24Процеси CI — 8 процес(ів) CI
24/24Наявні тести
16/16Конфігурація лінтера
9.6/9.6Pre-commit-хуки
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Використані вхідні дані
has_ciтак
has_testsтак
has_editorconfigні
has_linter_configтак
has_precommit_configтак

Документація

90Відмінний
Як обчислюється оцінка
30/30README
25/25Каталог документації
15/15Сайт документації / домашня сторінка — https://xgrammar.mlc.ai/docs
10/10Опис репозиторію
10/10Теми — 2 тем
0/10Wiki
Використані вхідні дані
topicslarge-language-models, structured-generation
has_wikiні
homepagehttps://xgrammar.mlc.ai/docs
has_readmeтак
has_docs_dirтак
has_descriptionтак

Безпека

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

56Помірний · 16% загального індексу

Стан безпеки

45У зоні ризику
Як обчислюється оцінка
7.5/7.5Binary-Artifacts — no binaries found in the repo
2.2/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
4.5/7.5Code-Review — Found 18/30 approved changesets -- score normalized to 6
2.5/2.5Contributors — project has 13 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5Ліцензія — license file detected
7.5/7.5Maintained — 30 commit(s) and 15 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — немає даних
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 28 existing vulnerabilities detected
Використані вхідні дані
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate4,5
Виключено з оцінювання (немає даних або не застосовно): signed_releases. Залишкові ваги перенормовано.

Сповіщення про залежності

100Відмінний
Як обчислюється оцінка
35/35Прямі залежності без відомих сповіщень — жодна пряма залежність не має відомих сповіщень
0/25Непрямі залежності без відомих сповіщень — транзитивний набір не відокремлюється від залежностей розробки й тестування в цьому обсязі
0/40Немає задавнених сповіщень — жодне сповіщення не має дати публікації
Використані вхідні дані
sourceosv
advisories32
affected_packages14
assessed_packages439
unassessed_packages43
affected_by_severitycritical 3, high 8, moderate 2, low 1
direct_affected_packages0
Виключено з оцінювання (немає даних або не застосовно): Непрямі залежності без відомих сповіщень, Немає задавнених сповіщень. Залишкові ваги перенормовано. Звірено 439 резолвлених залежностей із OSV. 43 не вдалося оцінити — немає резолвленої версії, непідтримувана екосистема або поза межами звітованого переліку пакетів. Цей репозиторій не публікує пакета, який резолвить індекс, тож натомість оцінено граф залежностей репозиторію. Цей граф змішує закріплені версії для розробки й тестування зі справді постачаними залежностями, тож оцінюються лише задекларовані runtime-залежності; транзитивні знахідки подаються як контекст і в оцінку не входять. Досяжність не аналізується.

Готовність до ШІ

Наскільки репозиторій оснащений для розробки та супроводу за участі ШІ-агентів? Незалежний, експериментальний бейдж — вага 0.0, тож він подається окремо і не впливає на загальний індекс здоров'я.

56Помірний · 0% загального індексу

Контекст і настанови для агентів

1Критичний
Як обчислюється оцінка
0/45Інструкції для агентів — немає CLAUDE.md / AGENTS.md / правил редактора
0/15Машиночитана документація (llms.txt)
0/40Читабельна історія комітів — немає даних
Використані вхідні дані
has_llms_txtні
legible_history_share—
agent_instruction_files—
agent_instruction_max_bytes—
Виключено з оцінювання (немає даних або не застосовно): Читабельна історія комітів. Залишкові ваги перенормовано.

Цикл верифікації (збірка / тести / перевірка типів)

88Відмінний
Як обчислюється оцінка
18/18Розгортання однією командою — docs/Makefile
22/22Автоматизовані тести
11/11Конфігурація лінтера / форматера
11/11Статична перевірка типів — python/xgrammar/py.typed, web/example/tsconfig.json, web/tsconfig.json
10/10Відтворюване середовище — lockfile
0/10Підтверджена практика роботи з агентами — немає даних
0/8Автоматизоване супроводження — немає даних
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Використані вхідні дані
has_nixні
has_testsтак
lockfilespackage-lock.json
has_dockerfileні
typed_languageтак
bootstrap_filesdocs/Makefile
has_devcontainerні
has_linter_configтак
typecheck_configspython/xgrammar/py.typed, web/example/tsconfig.json, web/tsconfig.json
agent_commit_share—
toolchain_manifests—
dependency_bot_commit_share—
Виключено з оцінювання (немає даних або не застосовно): Підтверджена практика роботи з агентами, Автоматизоване супроводження. Залишкові ваги перенормовано.

Читабельність коду для моделей

96Відмінний
Як обчислюється оцінка
45/45Типізований код — C++ (статично типізована)
51.2/55Керовані розміри файлів — 10/143 файлів вихідного коду понад 60 КБ
Використані вхідні дані
primary_languageC++
largest_source_bytes152 695
source_files_sampled143
oversized_source_files10

Машиночитні інтерфейси

40У зоні ризику
Як обчислюється оцінка
0/40Схема API (OpenAPI/GraphQL/proto)
0/20Сервер MCP
40/40Придатні до запуску приклади — example, examples
Використані вхідні дані
example_dirsexample, examples
has_mcp_signalні
api_schema_files—

Ключові факти

1 792зірок GitHub
58контриб'юторів
222комітів за останні 12 місяців
0днів від останнього пушу
32релізів
2бас-фактор
24відкритих issue
npm, PyPI, RubyGemsпакетних екосистем

Попередження щодо збору даних

  • deps.dev does not index pypi:xgrammar@0.2.4; advisories assessed against the repository dependency graph instead

Докладніше

OpenSSF Scorecard 4.5 / 10
4.5сукупно

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 · 2026-07-21 02:44 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
6Code-ReviewFound 18/30 approved changesets -- score normalized to 6
10Contributorsproject has 13 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 15 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
н/дSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities28 existing vulnerabilities detected
Прямі залежності 9
РеєстрПакетОбмеження версіїМаніфест
PyPIapache-tvm-ffi>=0.1.9pyproject.toml
PyPIpydantic—pyproject.toml
PyPItorch>=1.10.0pyproject.toml
PyPItransformers>=4.38.0,<5pyproject.toml
PyPItriton—pyproject.toml
PyPInumpy—pyproject.toml
PyPItyping-extensions>=4.9.0pyproject.toml
RubyGemsjekyll-remote-theme—site/Gemfile
RubyGemsjekyll-sass-converter—site/Gemfile
Усі залежності 482

Повний розв'язаний набір залежностей із графа залежностей GitHub: 9 прямих і 473 непрямих (транзитивних) пакетів. Транзитивне замикання є повним, коли в репозиторії закомічено lockfile.

РеєстрПакетВерсіяЗв'язок
PyPIapache-tvm-ffi—пряма
PyPInumpy—пряма
PyPIpydantic—пряма
PyPItorch—пряма
PyPItransformers—пряма
PyPItriton—пряма
PyPItyping-extensions—пряма
RubyGemsjekyll-remote-theme—пряма
RubyGemsjekyll-sass-converter—пряма
npm@babel/code-frame7.27.1непряма
npm@babel/compat-data7.28.5непряма
npm@babel/core7.28.5непряма
npm@babel/generator7.28.5непряма
npm@babel/helper-compilation-targets7.27.2непряма
npm@babel/helper-globals7.28.0непряма
npm@babel/helper-module-imports7.27.1непряма
npm@babel/helper-module-transforms7.28.3непряма
npm@babel/helper-plugin-utils7.27.1непряма
npm@babel/helper-string-parser7.27.1непряма
npm@babel/helper-validator-identifier7.28.5непряма
npm@babel/helper-validator-option7.27.1непряма
npm@babel/helpers7.28.4непряма
npm@babel/parser7.28.5непряма
npm@babel/plugin-syntax-async-generators7.8.4непряма
npm@babel/plugin-syntax-bigint7.8.3непряма
npm@babel/plugin-syntax-class-properties7.12.13непряма
npm@babel/plugin-syntax-class-static-block7.14.5непряма
npm@babel/plugin-syntax-import-attributes7.27.1непряма
npm@babel/plugin-syntax-import-meta7.10.4непряма
npm@babel/plugin-syntax-json-strings7.8.3непряма
npm@babel/plugin-syntax-jsx7.27.1непряма
npm@babel/plugin-syntax-logical-assignment-operators7.10.4непряма
npm@babel/plugin-syntax-nullish-coalescing-operator7.8.3непряма
npm@babel/plugin-syntax-numeric-separator7.10.4непряма
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PyPIsphinx-toolbox3.4.0непряма
PyPIsphinxcontrib-httpdomain1.8.1непряма
PyPIsphinxcontrib-mermaid—непряма
PyPIsphinxcontrib-napoleon0.7непряма
PyPItiktoken—непряма
PyPItlcpack-sphinx-addon0.2.2непряма
PyPItomli—непряма
PyPIurllib3—непряма
Сповіщення про залежності 14

Цей репозиторій не публікує пакета, який розпізнає індекс, тож оцінено його власний граф залежностей — 439 пакетів, серед яких є й піниї розробки та тестування, що ніколи не постачаються: 14 мають відомі сповіщення, з них 0 прямі. 43 не вдалося оцінити — немає резолвленої версії, непідтримувана екосистема або поза наведеним переліком пакетів.

ПакетВерсіяЗв'язокКритичністьСповіщеньВиправлено в
flatted3.3.3непрямакритична23.4.2
handlebars4.7.8непрямакритична84.7.9
rollup4.53.3непрямакритична14.59.0
brace-expansion1.1.12непрямависока25.0.7
brace-expansion2.0.2непрямависока25.0.7
js-yaml3.14.2непрямависока24.3.0
js-yaml4.1.1непрямависока24.3.0
minimatch3.1.2непрямависока310.2.3
minimatch9.0.5непрямависока310.2.3
picomatch2.3.1непрямависока24.0.4
picomatch4.0.3непрямависока24.0.4
ajv6.12.6непрямапомірна18.18.0
setuptools81.0.0непрямапомірна183.0.0
@babel/core7.28.5непряманизька18.0.0-rc.6

Сповіщення означає, що версія, записана в графі залежностей, потрапляє в уражений діапазон. Досяжність не аналізується, а граф містить піниї розробки й тестування — знахідка може стосуватися інструментів, а не поставленого коду.

Звіт у форматі JSON машиночитний
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  "license_state": "standard",
  "license_spdx": "Apache-2.0"
}

Пов’язані записи

Перевірені репозиторії, що мають спільні каталожні теги або екосистеми з mlc-ai/xgrammar. Читати поруч →

93deepset-ai/haystackOpen-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.Відмінний88huggingface/transformers🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. Відмінний90ray-project/rayRay is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.Відмінний87Unstructured-IO/unstructuredConvert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.Відмінний88langchain-ai/langsmith-sdkLangSmith Client SDK ImplementationsВідмінний94run-llama/llama_indexLlamaIndex is the leading document agent and OCR platformВідмінний

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 v1.13.0, схема v0.16.0 — повна методологія · вікі метрик.

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