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Software-GesundheitsberichtSchema 0.27.0 · Metriken 1.13.0 · 2026-07-24 11:35 UTC

Lightning-AI / litgpt

20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.

PythonApache-2.0★ 13.496 Sterne⑂ 1.473 Forksseit Mai 2023Auf GitHub ansehen ↗

Lightning-AI/litgpt erreicht einen Gesundheitsindex von 82 von 100 und liegt damit im Bereich Gut. Am stärksten schneidet es bei Community & Adoption (91/100) ab, am schwächsten bei AI Readiness (52/100). Zuletzt vor 4 Tagen aktualisiert. 2 Mitwirkende tragen den Großteil der jüngsten Arbeit.

82
gesamt / 100
Gut

Software-Gesundheitsindex

Metriken werden auf einer Skala von 1–100 in gewichtete Kategorien gruppiert. Der Gesamtwert beginnt als ihr Mittel; sobald öffentliche Evidenz die Richtlinie für Hochrisikojurisdiktionen auslöst, wird die Bewertung angepasst und erhält die Obergrenze 49 (Gefährdet). AI Readiness liegt außerhalb.

82
Exzellent85-100Vorbildlich; erfüllt im Wesentlichen alle geprüften Kriterien
Gut70-84Gesund; geringfügige Lücken
Mittel50-69Akzeptabel mit deutlichen Lücken; Überprüfung empfohlen
Gefährdet30-49Erhebliche Schwächen; eine Übernahme erfordert Vorsicht
Kritisch1-29Schwerwiegende Probleme (aufgegeben, nur ein Maintainer, keine Hygiene)
VitalitätCommunity &VerbreitungNachhaltigkeit &GovernanceEngineering-QualitätSicherheitAI Readiness

Bewertungsprofil

Jede Achse ist eine Kategorie. Die Form zählt mehr als der Durchschnitt — ein gesundes Projekt füllt die gesamte Fläche, während ein Profil aus Spitzen und Kratern bedeutet, dass Stärke in einer Dimension Risiken in einer anderen verdeckt.

Eigentümerschaft

6.839 Follower29 öffentliche Reposseit Dez. 2019

Dieses Repository wird von einer Organisation getragen — geteilte, rechenschaftspflichtige Trägerschaft, die jeden einzelnen Maintainer überdauern kann.

Paket-Ökosysteme

RegistryPaketVersionDownloads / MonatVersionenZuletzt veröffentlicht
PyPIlitgpt0.5.13-34vor 21 Tagen

Metriken nach Kategorie

Vitalität

Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?

85Exzellent · 22 % des Gesamtindex
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 4 Tagen
22.2/36Commit-Rhythmus — 32/52 Wochen mit Commits
17.4/18Commit-Volumen — 86 Commits im letzten Jahr
10/10OpenSSF Scorecard: Maintained — 14 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Verwendete Eingangsdaten
commits_last_year86
human_commit_share0,81
days_since_last_push4
active_weeks_last_year32
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 29 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 24 Tagen
19.8/27Release-Rhythmus — ein Release etwa alle 61,5 Tage
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Verwendete Eingangsdaten
releases_count29
latest_release_tagv0.5.13
releases_from_tagsnein
days_since_latest_release24
mean_days_between_releases61,5

Community & Verbreitung

Hat das Projekt Nutzer, Downloads, Aufmerksamkeit und ein einladendes Umfeld für Beitragende?

91Exzellent · 18 % des Gesamtindex
Wie die Bewertung erfolgt
60/60Stars — 13.496 Stars
25/25Forks — 1.473 Forks
11.5/15Watcher — 118 Watcher
Verwendete Eingangsdaten
forks1.473
stars13.496
watchers118
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Wie die Bewertung erfolgt
22.5/22.5README
22.5/22.5Lizenz — anerkannte Lizenz (Apache-2.0)
18/18CONTRIBUTING-Leitfaden
13.5/13.5Verhaltenskodex
0/7.2Issue-Vorlage
0/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingja
has_issue_templatenein
has_code_of_conductja
has_pull_request_templatenein

Nachhaltigkeit & Governance

Überdauert das Projekt die Menschen, die es tragen — Bus-Faktor, Reaktionsfähigkeit, Trägerschaft und Paketpflege?

80Gut · 24 % des Gesamtindex
Wie die Bewertung erfolgt
25.2/54Bus-Faktor — 2 Beitragende decken die Hälfte aller Commits ab
16.1/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 28 % der Commits
13.5/13.5Breite der Beitragenden — 98 Beitragende
10/10OpenSSF Scorecard: Contributors — project has 27 contributing companies or organizations
Verwendete Eingangsdaten
bus_factor2
contributors_sampled98
top_contributor_share0,283
Wie die Bewertung erfolgt
34.7/46.8Issue-Lösungsquote — 74 % der Issues geschlossen
33.2/38.3PR-Annahme — 1.147/1.320 entschiedene PRs gemergt
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Verwendete Eingangsdaten
merged_prs1.147
open_issues235
closed_issues679
issue_closed_ratio0,743
closed_unmerged_prs173
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
25/25Reichweite des Inhabers — 6.839 Follower von Lightning-AI
22.8/25Kontohistorie — 29 öffentliche Repos, Kontoalter ca. 6 Jahre
Verwendete Eingangsdaten
followers6.839
owner_typeOrganization
is_verified
owner_loginLightning-AI
public_repos29
account_age_days2.427

Paketpflege

100Exzellent
Wie die Bewertung erfolgt
25/25Veröffentlicht & auflösbar — 1 Paket(e) auf pypi
35/35Veröffentlichungsaktualität — letzte Veröffentlichung vor 21 Tagen
20/20Versionshistorie — 34 veröffentlichte Versionen
20/20Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen
Verwendete Eingangsdaten
packageslitgpt
ecosystemspypi
any_deprecatednein
min_days_since_publish21

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

82Gut · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 4 Workflow(s)
24/24Tests vorhanden
16/16Linter-Konfiguration
9.6/9.6Pre-Commit-Hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Verwendete Eingangsdaten
has_cija
has_testsja
has_editorconfignein
has_linter_configja
has_precommit_configja
Wie die Bewertung erfolgt
30/30README
0/25Dokumentationsverzeichnis
15/15Dokumentations-/Homepage-Site — https://lightning.ai
10/10Repository-Beschreibung
10/10Topics — 7 Topics
0/10Wiki
Verwendete Eingangsdaten
topicsai, artificial-intelligence, deep-learning, large-language-models, llm, llm-inference, llms
has_wikinein
homepagehttps://lightning.ai
has_readmeja
has_docs_dirnein
has_descriptionja

Sicherheit

Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?

72Gut · 16 % des Gesamtindex
Wie die Bewertung erfolgt
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — keine Daten
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
7.5/7.5Code-Review — all changesets reviewed
2.5/2.5Contributors — project has 27 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5Lizenz — license file detected
7.5/7.5Maintained — 14 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
3/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 6
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 — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate6,5
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): branch_protection. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
35/35Direkte Abhängigkeiten ohne bekannte Advisories — keine direkte Abhängigkeit trägt ein bekanntes Advisory
25/25Indirekte Abhängigkeiten ohne bekannte Advisories — keine indirekte Abhängigkeit trägt ein bekanntes Advisory
0/40Keine offenen Advisories — kein Advisory trägt ein Veröffentlichungsdatum
Verwendete Eingangsdaten
sourceosv
advisories0
affected_packages0
assessed_packages43
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Keine offenen Advisories. Die verbleibenden Gewichte wurden renormalisiert. Abgeglichen wurde die Laufzeit-Abhängigkeitshülle von pypi:litgpt@0.5.13 — das, was die Installation des veröffentlichten Pakets nach sich zieht — mit 43 Paketen. Erreichbarkeit wird nicht analysiert.

AI Readiness

Wie gut ist das Repository dafür ausgestattet, mit KI-Coding-Agenten entwickelt und gepflegt zu werden? Ein unabhängiges, experimentelles Badge — Gewicht 0,0, es wird eigenständig ausgewiesen und verändert den Gesamt-Gesundheitswert nicht.

52Mittel · 0 % des Gesamtindex
Wie die Bewertung erfolgt
0/45Agentenanweisungen — keine CLAUDE.md / AGENTS.md / Editor-Regeln
0/15Maschinenlesbare Doku (llms.txt)
40/40Lesbare Commit-Historie — 80 von 81 menschlichen Commits benennen ihre Absicht (strukturierter Betreff oder erläuternder Text)
Verwendete Eingangsdaten
has_llms_txtnein
legible_history_share0,988
agent_instruction_files
agent_instruction_max_bytes
Wie die Bewertung erfolgt
0/18Bootstrap mit einem Befehl
22/22Automatisierte Tests
11/11Lint-/Format-Konfiguration
0/11Statische Typprüfung
10/10Reproduzierbare Umgebung — devcontainer, Dockerfile
8/10Belegte Agentenpraxis — 4 der letzten 100 Commits von Agenten verfasst oder ihnen zugeschrieben
8/8Automatisierte Wartung — 15 der letzten 100 Commits sind automatisierte Abhängigkeits-Updates
6/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 6
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfiles
has_dockerfileja
typed_languagenein
bootstrap_files
has_devcontainerja
has_linter_configja
typecheck_configs
agent_commit_share0,04
toolchain_manifests
dependency_bot_commit_share0,15
Wie die Bewertung erfolgt
0/45Typprüfbarer Code — Python ohne Typprüfungs-Konfiguration
53.8/55Handhabbare Dateigrößen — 3/137 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes99.516
source_files_sampled137
oversized_source_files3
Wie die Bewertung erfolgt
0/40API-Schema (OpenAPI/GraphQL/proto)
0/20MCP-Server
40/40Lauffähige Beispiele — examples
Verwendete Eingangsdaten
example_dirsexamples
has_mcp_signalnein
api_schema_files

Eckdaten

13.496GitHub-Sterne
98Mitwirkende
86Commits, letzte 12 Monate
4Tage seit letztem Push
29Releases
2Bus-Faktor
235offene Issues
PyPIPaket-Ökosysteme

Warnungen zur Datenerhebung

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

Weitere Details

Stern- und Fork-Verlauf 0 ★ / 1.473 ⇿
0Sterne
1.473Forks
29Releases

Wann jeder Stern und Fork hinzugefügt wurde, von GitHub erfasst und nach Tagen gruppiert. Das kumulierte Wachstum steht direkt über den täglichen Zugängen, aus denen es besteht, sodass beide gegeneinander lesbar sind: stetiger organischer Zuwachs sieht ganz anders aus als ein abrupter, kurzlebiger Ausschlag. Wo dieser Unterschied messbar ist, wird er als Wachstumsauthentizität ausgewiesen.

Es wird nur die jüngste Historie angezeigt — dieses Repository überschreitet das Erfassungsfenster, sodass die früheste Historie nicht erfasst wird.

05001.0001.5001.473432024-012025-042026-07
Major 0Minor 2Patch 26

Jeder Punkt umfasst 3 Tage.

OpenSSF Scorecard 6.5 / 10
6.5Gesamtwert

Unabhängige, werkzeugneutrale Sicherheitsbewertung durch das quelloffene OpenSSF Scorecard. Jede Prüfung honoriert eine Sicherheits-Praxis, nicht das Werkzeug eines bestimmten Anbieters. Prüfungen, die Scorecard nicht ermitteln konnte, sind mit k. A. markiert und vom Sicherheitswert ausgeschlossen (nie als null gezählt).Scorecard v5.5.0 · 2026-07-24 11:34 UTC

10Binary-Artifactsno binaries found in the repo
k. A.Branch-Protectioninternal 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
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
10Code-Reviewall changesets reviewed
10Contributorsproject has 27 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained14 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
6Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 6
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direkte Abhängigkeiten 8
RegistryPaketVersionsvorgabeManifest
PyPIhuggingface-hub>=0.30,<1.4pyproject.toml
PyPIjsonargparse>=4.37,<=4.41pyproject.toml
PyPIlightning>=2.6.1pyproject.toml
PyPIpsutil==7.2.2pyproject.toml
PyPIsafetensors>=0.4.3pyproject.toml
PyPItokenizers>=0.21pyproject.toml
PyPItorch>=2.7pyproject.toml
PyPItqdm>4.66pyproject.toml
Alle Abhängigkeiten 33

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 8 direkte und 25 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
PyPIhuggingface-hubdirekt
PyPIjsonargparsedirekt
PyPIlightningdirekt
PyPIpsutil7.2.2direkt
PyPIsafetensorsdirekt
PyPItokenizersdirekt
PyPItorchdirekt
PyPItqdmdirekt
PyPIbitsandbytesindirekt
PyPIdatasetsindirekt
PyPIeinopsindirekt
PyPIlightning-thunderindirekt
PyPIlitdata0.2.59indirekt
PyPIlitloggerindirekt
PyPIlitserveindirekt
PyPIlm-evalindirekt
PyPIpandasindirekt
PyPIprotobufindirekt
PyPIpyarrowindirekt
PyPIpytestindirekt
PyPIpytest-benchmarkindirekt
PyPIpytest-dependencyindirekt
PyPIpytest-rerunfailuresindirekt
PyPIpytest-timeoutindirekt
PyPIrequestsindirekt
PyPIsentencepieceindirekt
PyPIsetuptoolsindirekt
PyPItensorboardindirekt
PyPItorchmetricsindirekt
PyPItransformersindirekt
PyPIuvloopindirekt
PyPIwheelindirekt
PyPIzstandardindirekt
Abhängigkeits-Advisories 0

Die Installation von pypi:litgpt@0.5.13 zieht 43 Pakete nach sich, direkt und transitiv: 0 tragen bekannte Advisories, davon 0 direkte Abhängigkeiten.

Keine bekannten Advisories betreffen die bewerteten Abhängigkeiten.

Ein Advisory bedeutet, dass die im Abhängigkeitsgraphen erfasste Version in den betroffenen Bereich eines Advisories fällt. Erreichbarkeit wird nicht analysiert, und der Graph enthält Entwicklungs- und Test-Pins — ein Fund kann das Werkzeug betreffen und nicht die ausgelieferte Software.

JSON-Rohbericht maschinenlesbar
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                "detail": "34 published versions",
                "points": 20,
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                "details": [
                  {
                    "code": "published_versions",
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                ],
                "max_points": 20
              },
              {
                "key": "not_deprecated",
                "name": "Not deprecated",
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      {
        "key": "engineering",
        "band": "good",
        "name": "Engineering Quality",
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        "metrics": [
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                "key": "ci_workflows",
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                "detail": "4 workflow(s)",
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                "max_points": 24
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                "key": "tests_present",
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                "detail": null,
                "points": 24,
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              {
                "key": "linter_config",
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                "points": 16,
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              {
                "key": "pre_commit_hooks",
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                "points": 9.6,
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              {
                "key": "editorconfig",
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                "key": "openssf_scorecard_ci_tests",
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          {
            "key": "documentation",
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            "note": null,
            "notes": [],
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                "key": "maintained",
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                "key": "sast",
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                "key": "security_policy",
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                "max_points": 7.5
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                "status": "excluded",
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            "note": null,
            "notes": [],
            "value": 100,
            "inputs": {
              "source": "osv",
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  "warnings": [
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}

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