Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-12 18:05 UTC

Lightning-Universe / stable-diffusion-deploy

Learn to serve Stable Diffusion models on cloud infrastructure at scale. This Lightning App shows load-balancing, orchestrating, pre-provisioning, dynamic batching, GPU-inference, micro-services working together via the Lightning Apps framework.

Python · TypeScriptApache-2.0★ 391 stars⑂ 38 forkssince Aug 2022archivedView on GitHub ↗
KindWeb interfacehow this is determined

Lightning-Universe/stable-diffusion-deploy holds a health index of 19 out of 100, placing it in the Critical band. It scores highest on Engineering Quality (80/100) and lowest on Vitality (25/100). The repository is archived, so no further maintenance is expected.

19
overall / 100
Critical

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

19
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 55 is calibrated to 57 on the published index scale (record calibration 2026-08-02).

Ownership

127 followers100 public repossince Dec 2022

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

25At Risk · 21% of overall
How it's scored
0/36Push recency — last push 1,075 days ago
0/36Commit cadence — 0/52 weeks with commits
0/18Commit volume — 0 commits in the last year
0/10OpenSSF Scorecard: Maintained — project is archived
Inputs used
commits_last_year0
human_commit_share0.61
days_since_last_push1,075
active_weeks_last_year0
How it's scored
27/27Ships releases — 4 releases published
0/36Release recency — latest release 1,387 days ago
27/27Release cadence — a release every ~14.4 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count4
latest_release_tagv0.3.0
releases_from_tagsno
days_since_latest_release1,387
mean_days_between_releases14.4
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

58Moderate · 17% of overall
How it's scored
42/60Stars — 391 stars
13.1/25Forks — 38 forks
4.3/15Watchers — 7 watchers
Inputs used
forks38
stars391
watchers7
growth_stateorganic
growth_factor_pct100
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges3
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesreadthedocs.org, shields.io
has_pull_request_templateyes

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

63Moderate · 23% of overall
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
13.1/22.5Commit distribution — top contributor authored 42% of commits
13.5/13.5Contributor breadth — 13 contributors
10/10OpenSSF Scorecard: Contributors — project has 21 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled13
top_contributor_share0.417
How it's scored
24.9/42Issue resolution — 59% of issues closed
25.7/30PR acceptance — 214/250 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
3/15OpenSSF Scorecard: Code-Review — Found 1/4 approved changesets -- score normalized to 2
Inputs used
merged_prs214
open_issues22
closed_issues32
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.593
closed_unmerged_prs36
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
15.1/25Owner reach — 127 followers of Lightning-Universe
20.5/25Track record — 100 public repos, account ~3 yr old
Inputs used
followers127
owner_typeOrganization
is_verifiedno
owner_loginLightning-Universe
public_repos100
account_age_days1,366

Engineering Quality

Are baseline engineering and documentation practices in place?

80Excellent · 19% of overall
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
16/16Linter config — muse/ui/package.json ("eslintConfig"), pyproject.toml ([tool.black])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — 0 out of 29 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://lightning.ai/muse
10/10Repository description
10/10Topics — 2 topics
0/10Wiki
Inputs used
topicsmodel-serving, stable-diffusion
has_wikino
homepagehttps://lightning.ai/muse
docs_sitehttps://lightning.ai/muse
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

50Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
0/2.5CI-Tests — 0 out of 29 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
1.5/7.5Code-Review — Found 1/4 approved changesets -- score normalized to 2
2.5/2.5Contributors — project has 21 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
2.5/2.5License — license file detected
0/7.5Maintained — project is archived
0/5Packaging — no data
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 — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 166 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate3.7
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories37
affected_packages4
assessed_packages13
unassessed_packages6
affected_by_severitycritical 1, high 1, moderate 2
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 13 resolved dependencies against OSV. 6 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

63Moderate · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://lightning.ai/llms.txt)
40/40Legible commit history — 47 of 61 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://lightning.ai/llms.txt
legible_history_share0.77
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — muse/ui/package.json ("eslintConfig"), pyproject.toml ([tool.black])
11/11Static type checking — muse/ui/tsconfig.json
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 35 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesyarn.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configsmuse/ui/tsconfig.json
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0.35
How it's scored
27/45Type-checkable code — Python with type-check config (muse/ui/tsconfig.json)
55/55Manageable file sizes — 0/46 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes11,944
source_files_sampled46
oversized_source_files0

Key facts

391GitHub stars
13contributors
0commits, last 12 months
1,075days since last push
4releases
2bus factor
22open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Star history carried forward from 2026-04-27: GitHub restricted the stargazers API to repository admins, so it can no longer be collected. The repository has 391 stars today.
  • Could not fetch pypi package 'lightning-muse' from its registry

More detail

Star and fork history 391 ★ / 38 ⇿
391Stars
38Forks
4Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

Star history is shown as collected on 2026-04-27. GitHub restricted the stargazers API to repository administrators in July 2026, so this series can no longer be extended; the current star total above remains live.

010020030040039138822022-082024-062026-04
Major 0Minor 3Patch 1

Each point covers 4 days.

OpenSSF Scorecard 3.7 / 10
3.7aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-09-12 18:04 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-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
0CI-Tests0 out of 29 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2Code-ReviewFound 1/4 approved changesets -- score normalized to 2
10Contributorsproject has 21 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintainedproject is archived
n/aPackagingpackaging workflow not 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
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities166 existing vulnerabilities detected
Direct dependencies 33
RegistryPackageVersion constraintManifest
npm@emotion/react^11.7.1muse/ui/package.json
npm@emotion/styled^11.6.0muse/ui/package.json
npm@mui/icons-material^5.6.2muse/ui/package.json
npm@mui/lab^5.0.0-alpha.64muse/ui/package.json
npm@mui/material^5.2.7muse/ui/package.json
npm@reduxjs/toolkit^1.8.0muse/ui/package.json
npm@stripe/stripe-js^1.29.0muse/ui/package.json
npmaxios^0.27.2muse/ui/package.json
npmboring-avatars^1.6.3muse/ui/package.json
npmcraco^0.0.3muse/ui/package.json
npmfilter-material-ui2.7.0muse/ui/package.json
npmfontfaceobserver^2.1.0muse/ui/package.json
npmlightning-uihttps://github.com/Lightning-AI/lightning-ui.git#1fff090ab288199ad3596381a49ce69d5160b5bcmuse/ui/package.json
npmlodash^4.17.21muse/ui/package.json
npmnotistack^2.0.4muse/ui/package.json
npmquery-string^7.1.0muse/ui/package.json
npmreact^17.0.2muse/ui/package.json
npmreact-dom^17.0.2muse/ui/package.json
npmreact-dropzone^14.2.1muse/ui/package.json
npmreact-github-btn^1.2.1muse/ui/package.json
npmreact-hook-form^7.27.1muse/ui/package.json
npmreact-query^3.34.7muse/ui/package.json
npmreact-router-dom^6.2.1muse/ui/package.json
npmreact-scripts5.0.0muse/ui/package.json
npmreact-spring^9.4.4muse/ui/package.json
npmreact-table^7.7.0muse/ui/package.json
npmrxjs^7.5.2muse/ui/package.json
npmtypescript^4.4.2muse/ui/package.json
npmuse-debounce^7.0.1muse/ui/package.json
npmweb-vitals^2.1.0muse/ui/package.json
npmxterm^4.18.0muse/ui/package.json
npmxterm-addon-fit^0.5.0muse/ui/package.json
npmxterm-addon-search^0.8.2muse/ui/package.json
All dependencies 19

Full resolved dependency set from the GitHub dependency graph: 0 direct and 19 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIasgi-ratelimit0.10.0indirect
PyPIasgiref3.7.2indirect
PyPIcoverage7.3.1indirect
PyPIfastapi0.103.2indirect
PyPIflask-cors—indirect
PyPIftfy6.1.1indirect
PyPIlightning2.0.*indirect
PyPIlocust—indirect
PyPIpillow10.0.1indirect
PyPIpytest7.4.2indirect
PyPIpytest-cov4.1.0indirect
PyPIpython-dotenv1.0.0indirect
PyPIscipy—indirect
PyPIsentry-sdk—indirect
PyPIslackclient2.9.4indirect
PyPIslackeventsapi3.0.1indirect
PyPIstarlette-exporter0.16.0indirect
PyPIuvicorn0.23.2indirect
PyPIuvloop—indirect
Dependency advisories 4

This repository publishes no package the index resolves, so its own dependency graph was assessed — 13 packages, which also include development and test pins that never ship: 4 carry known advisories, of which 0 are direct. 6 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
pillow10.0.1indirectcritical3212.3.0
fastapi0.103.2indirecthigh10.109.1
pytest7.4.2indirectmoderate29.0.3
python-dotenv1.0.0indirectmoderate21.2.2

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics.