Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-20 09:36 UTC

abetlen / llama-cpp-python

Python bindings for llama.cpp

PythonMIT★ 10,652 stars⑂ 1,472 forkssince Mar 2023View on GitHub ↗

abetlen/llama-cpp-python holds a health index of 86 out of 100, placing it in the Excellent band. It scores highest on Community & Adoption (87/100) and lowest on Security (44/100). It was last updated 19 days ago. A single contributor accounts for most of its recent work.

86
overall / 100
Excellent

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.

86
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 72 is calibrated to 86 on the published index scale (record calibration 2026-08-02).

Ownership

AndreiPersonal account
682 followers53 public repossince Mar 2014

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIllama_cpp_python0.3.36519,08520919 days ago

Metrics by category

Vitality

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

81Excellent · 21% of overall
How it's scored
28.8/36Push recency — last push 19 days ago
14.5/36Commit cadence — 21/52 weeks with commits
18/18Commit volume — 158 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year158
human_commit_share0.85
days_since_last_push19
active_weeks_last_year21

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 100 releases published
36/36Release recency — latest release 19 days ago
27/27Release cadence — a release every ~0 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count100
latest_release_tagv0.3.36-hip-radeon
releases_from_tagsno
days_since_latest_release19
mean_days_between_releases0

Community & Adoption

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

87Excellent · 17% of overall
How it's scored
60/60Stars — 10,652 stars
25/25Forks — 1,472 forks
10.7/15Watchers — 85 watchers
Inputs used
forks1,472
stars10,652
watchers85
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges6
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesgithub.com, readthedocs.org, shields.io
has_pull_request_templateno
How it's scored
76.2/80Monthly downloads — 519,085 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesllama_cpp_python
dependents—
ecosystemspypi
total_downloads—
monthly_downloads519,085
unverified_packages_excluded—
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

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

62Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
2.8/22.5Commit distribution — top contributor authored 88% of commits
13.5/13.5Contributor breadth — 99 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor1
contributors_sampled99
top_contributor_share0.876
How it's scored
23.5/42Issue resolution — 56% of issues closed
23.3/30PR acceptance — 510/658 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs510
open_issues597
closed_issues757
prs_merged_7d0
prs_decided_7d0
prs_merged_30d3
prs_decided_30d3
issue_closed_ratio0.559
closed_unmerged_prs148
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
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
20.4/25Owner reach — 682 followers of abetlen
24.6/25Track record — 53 public repos, account ~12 yr old
Inputs used
followers682
owner_typeUser
is_verified—
owner_loginabetlen
public_repos53
account_age_days4,615
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 19 days ago
20/20Version history — 209 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesllama_cpp_python
ecosystemspypi
any_deprecatedno
min_days_since_publish19

Engineering Quality

Are baseline engineering and documentation practices in place?

84Excellent · 19% of overall
How it's scored
24/24CI workflows — 12 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://llama-cpp-python.readthedocs.io
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepagehttps://llama-cpp-python.readthedocs.io
docs_sitehttps://llama-cpp-python.readthedocs.io
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

44Weak · 16% of overall
How it's scored
0/30Security policy (SECURITY.md)
25/25Dependabot config
0/25Dependency lockfiles — published library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles—
manifestsdocs/requirements.txt, pyproject.toml
has_codeql_workflowno
has_security_policyno
has_dependabot_configyes
Excluded from scoring (no data or not applicable): Dependency lockfiles. Remaining weights renormalized.
How it's scored
26.6/35Direct dependencies free of known advisories — 1 affected: diskcache 5.6.3 (moderate)
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
37.2/40No advisories left outstanding — 1 advisory-carrying package(s) unaddressed past 90 days; oldest published 250 days ago
Inputs used
sourceosv
advisories2
affected_packages1
assessed_packages5
unassessed_packages0
affected_by_severitymoderate 1
direct_affected_packages1
Matched the pypi:llama_cpp_python@0.3.36 runtime dependency closure — what installing the published package pulls in — 5 packages. 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.

79Good · 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://python.langchain.com/llms.txt)
40/40Legible commit history — 85 of 85 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://python.langchain.com/llms.txt
legible_history_share1
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — llama_cpp/py.typed
10/10Reproducible environment — Dockerfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 15 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configsllama_cpp/py.typed
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0.15
How it's scored
27/45Type-checkable code — Python with type-check config (llama_cpp/py.typed)
50.6/55Manageable file sizes — 4/50 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes653,598
source_files_sampled50
oversized_source_files4
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — examples, notebooks
Inputs used
example_dirsexamples, notebooks
has_mcp_signalno
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

10,652GitHub stars
99contributors
158commits, last 12 months
19days since last push
100releases
1bus factor
597open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • OpenSSF Scorecard did not return a usable result (killed by SIGKILL — most likely the container's memory limit; 2026/10/20 09:34:47 Warning: PATs stored in env variables GITHUB_AUTH_TOKEN and GITHUB_TOKEN differ. Scorecard will use the former.); skipping Scorecard checks

More detail

Star and fork history 0 ★ / 1,472 ⇿
0Stars
1,472Forks
100Releases

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.

Only the most recent history is shown — this repository exceeds the collection window, so the earliest history is not captured.

05001,0001,5001,472142023-102025-042026-10
Major 0Minor 0Patch 6

Each point covers 3 days.

Direct dependencies 4
RegistryPackageVersion constraintManifest
PyPItyping-extensions>=4.5.0pyproject.toml
PyPInumpy>=1.20.0pyproject.toml
PyPIdiskcache>=5.6.1pyproject.toml
PyPIjinja2>=2.11.3pyproject.toml
All dependencies 22

Full resolved dependency set from the GitHub dependency graph: 4 direct and 18 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIdiskcache—direct
PyPIjinja2—direct
PyPInumpy—direct
PyPItyping-extensions—direct
PyPIfastapi—indirect
PyPIhttpx—indirect
PyPIhuggingface-hub—indirect
PyPIllama-cpp-python—indirect
PyPImkdocs—indirect
PyPImkdocs-material—indirect
PyPImkdocstrings—indirect
PyPIpydantic-settings—indirect
PyPIpytest—indirect
PyPIpyyaml—indirect
PyPIray—indirect
PyPIruff—indirect
PyPIscikit-build-core—indirect
PyPIscipy—indirect
PyPIsse-starlette—indirect
PyPIstarlette-context—indirect
PyPItwine—indirect
PyPIuvicorn—indirect
Dependency advisories 1

Installing pypi:llama_cpp_python@0.3.36 pulls in 5 packages, direct and transitive: 1 carry known advisories, of which 1 are direct dependencies.

PackageVersionRelationSeverityAdvisoriesFixed in
diskcache5.6.3directmoderate2—

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 — PyPI.